Category: Bob&Les

Fictional conversations between Bob, an ISP coach, and Lesley/Leslie an ISP coachee.

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The Strangeness of LoS

It had been some time since Bob and Leslie had chatted so an email from the blue was a welcome distraction from a complex data analysis task.

<Bob> Hi Leslie, great to hear from you. I was beginning to think you had lost interest in health care improvement-by-design.

<Leslie> Hi Bob, not at all.  Rather the opposite.  I’ve been very busy using everything that I’ve learned so far.  It’s applications are endless, but I have hit a problem that I have been unable to solve, and it is driving me nuts!

<Bob> OK. That sounds encouraging and interesting.  Would you be able to outline this thorny problem and I will help if I can.

<Leslie> Thanks Bob.  It relates to a big issue that my organisation is stuck with – managing urgent admissions.  The problem is that very often there is no bed available, but there is no predictability to that.  It feels like a lottery; a quality and safety lottery.  The clinicians are clamoring for “more beds” but the commissioners are saying “there is no more money“.  So the focus has turned to reducing length of stay.

<Bob> OK.  A focus on length of stay sounds reasonable.  Reducing that can free up enough beds to provide the necessary space-capacity resilience to dramatically improve the service quality.  So long as you don’t then close all the “empty” beds to save money, or fall into the trap of believing that 85% average bed occupancy is the “optimum”.

<Leslie> Yes, I know.  We have explored all of these topics before.  That is not the problem.

<Bob> OK. What is the problem?

<Leslie> The problem is demonstrating objectively that the length-of-stay reduction experiments are having a beneficial impact.  The data seems to say they they are, and the senior managers are trumpeting the success, but the people on the ground say they are not. We have hit a stalemate.

<Bob> Ah ha!  That old chestnut.  So, can I first ask what happens to the patients who cannot get a bed urgently?

<Leslie> Good question.  We have mapped and measured that.  What happens is the most urgent admission failures spill over to commercial service providers, who charge a fee-per-case and we have no choice but to pay it.  The Director of Finance is going mental!  The less urgent admission failures just wait on queue-in-the-community until a bed becomes available.  They are the ones who are complaining the most, so the Director of Governance is also going mental.  The Director of Operations is caught in the cross-fire and the Chief Executive and Chair are doing their best to calm frayed tempers and to referee the increasingly toxic arguments.

<Bob> OK.  I can see why a “Reduce Length of Stay Initiative” would tick everyone’s Nice If box.  So, the data analysts are saying “the length of stay has come down since the Initiative was launched” but the teams on the ground are saying “it feels the same to us … the beds are still full and we still cannot admit patients“.

<Leslie> Yes, that is exactly it.  And everyone has come to the conclusion that demand must have increased so it is pointless to attempt to reduce length of stay because when we do that it just sucks in more work.  They are feeling increasingly helpless and hopeless.

<Bob> OK.  Well, the “chronic backlog of unmet need” issue is certainly possible, but your data will show if admissions have gone up.

<Leslie> I know, and as far as I can see they have not.

<Bob> OK.  So I’m guessing that the next explanation is that “the data is wonky“.

<Leslie> Yup.  Spot on.  So, to counter that the Information Department has embarked on a massive push on data collection and quality control and they are adamant that the data is complete and clean.

<Bob> OK.  So what is your diagnosis?

<Leslie> I don’t have one, that’s why I emailed you.  I’m stuck.

<Bob> OK.  We need a diagnosis, and that means we need to take a “history” and “examine” the process.  Can you tell me the outline of the RLoS Initiative.

<Leslie> We knew that we would need a baseline to measure from so we got the historical admission and discharge data and plotted a Diagnostic Vitals Chart®.  I have learned something from my HCSE training!  Then we planned the implementation of a visual feedback tool that would show ward staff which patients were delayed so that they could focus on “unblocking” the bottlenecks.  We then planned to measure the impact of the intervention for three months, and then we planned to compare the average length of stay before and after the RLoS Intervention with a big enough data set to give us an accurate estimate of the averages.  The data showed a very obvious improvement, a highly statistically significant one.

<Bob> OK.  It sounds like you have avoided the usual trap of just relying on subjective feedback, and now have a different problem because your objective and subjective feedback are in disagreement.

<Leslie> Yes.  And I have to say, getting stuck like this has rather dented my confidence.

<Bob> Fear not Leslie.  I said this is an “old chestnut” and I can say with 100% confidence that you already have what you need in your T4 kit bag?

<Leslie>Tee-Four?

<Bob> Sorry, a new abbreviation. It stands for “theory, techniques, tools and training“.

<Leslie> Phew!  That is very reassuring to hear, but it does not tell me what to do next.

<Bob> You are an engineer now Leslie, so you need to don the hard-hat of Improvement-by-Design.  Start with your Needs Analysis.

<Leslie> OK.  I need a trustworthy tool that will tell me if the planned intervention has has a significant impact on length of stay, for better or worse or not at all.  And I need it to tell me that quickly so I can decide what to do next.

<Bob> Good.  Now list all the things that you currently have that you feel you can trust.

<Leslie> I do actually trust that the Information team collect, store, verify and clean the raw data – they are really passionate about it.  And I do trust that the front line teams are giving accurate subjective feedback – I work with them and they are just as passionate.  And I do trust the systems engineering “T4” kit bag – it has proven itself again-and-again.

<Bob> Good, and I say that because you have everything you need to solve this, and it sounds like the data analysis part of the process is a good place to focus.

<Leslie> That was my conclusion too.  And I have looked at the process, and I can’t see a flaw. It is driving me nuts!

<Bob> OK.  Let us take a different tack.  Have you thought about designing the tool you need from scratch?

<Leslie> No. I’ve been using the ones I already have, and assume that I must be using them incorrectly, but I can’t see where I’m going wrong.

<Bob> Ah!  Then, I think it would be a good idea to run each of your tools through a verification test and check that they are fit-4-purpose in this specific context.

<Leslie> OK. That sounds like something I haven’t covered before.

<Bob> I know.  Designing verification test-rigs is part of the Level 2 training.  I think you have demonstrated that you are ready to take the next step up the HCSE learning curve.

<Leslie> Do you mean I can learn how to design and build my own tools?  Special tools for specific tasks?

<Bob> Yup.  All the techniques and tools that you are using now had to be specified, designed, built, verified, and validated. That is why you can trust them to be fit-4-purpose.

<Leslie> Wooohooo! I knew it was a good idea to give you a call.  Let’s get started.

[Postscript] And Leslie, together with the other stakeholders, went on to design the tool that they needed and to use the available data to dissolve the stalemate.  And once everyone was on the same page again they were able to work collaboratively to resolve the flow problems, and to improve the safety, flow, quality and affordability of their service.  Oh, and to know for sure that they had improved it.

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The Lost Tribe

figures_lost_looking_at_map_anim_150_wht_15601

“Jingle Bells, Jingle Bells” announced Bob’s computer as he logged into the Webex meeting with Lesley.

<Bob> Hi Lesley, in case I forget later I’d like to wish you a Happy Christmas and hope that 2017 brings you new opportunity for learning and fun.

<Lesley> Thanks Bob, and I wish you the same. And I believe the blog last week pointed to some.

<Bob> Thank you and I agree;  every niggle is an opportunity for improvement and the “Houston we have a problem!” one is a biggie.

<Lesley> So how do we start on this one? It is massive!

<Bob> The same way we do on all niggles; we diagnose the root cause first. What do you feel they might be?

<Lesley> Well, following it backwards from your niggle, the board reports are created by the data analysts, and they will produce whatever they are asked to. It must be really irritating for them to have their work rubbished!

<Bob> Are you suggesting that they understand the flaws in what they are asked to do but keep quiet?

<Lesley> I am not sure they do, but there is clearly a gap between their intent and their impact. Where would they gain the insight? Do they have access to the sort of training I have am getting?

<Bob> That is a very good question, and until this week I would not have been able to answer, but an interesting report by the Health Foundation was recently published on that very topic. It is entitled “Understanding Analytical Capability In Health Care” and what it says is that there is a lost tribe of data analysts in the NHS.

<Lesley> How interesting! That certainly resonates with my experience.  All the data analysts I know seem to be hidden away behind their computers, caught in the cross-fire between between the boards and the wards, and very sensibly keeping their heads down and doing what they are asked to.

<Bob> That would certainly help to explain what we are seeing! And the good news is that Martin Bardsley, the author of the paper, has interviewed many people across the system, gathered their feedback, and offered some helpful recommendations.  Here is a snippet.

analysiscapability

<Lesley> I like these recommendations, especially the “in-work training programmes” and inclusion “in general management and leadership training“. But isn’t that one of the purposes of the CHIPs training?

<Bob> It is indeed, which is why it is good to see that Martin has specifically recommended it.

saasoftrecommended

<Lesley> Excellent! That means that my own investment in the CHIPs training has just gained in street value and that’s good for my CV. An unexpected early Xmas present. Thank you!

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Patient Traffic Engineering

motorway[Beep] Bob’s computer alerted him to Leslie signing on to the Webex session.

<Bob> Good afternoon Leslie, how are you? It seems a long time since we last chatted.

<Leslie> Hi Bob. I am well and it has been a long time. If you remember, I had to loop out of the Health Care Systems Engineering training because I changed job, and it has taken me a while to bring a lot of fresh skeptics around to the idea of improvement-by-design.

<Bob> Good to hear, and I assume you did that by demonstrating what was possible by doing it, delivering results, and describing the approach.

<Leslie> Yup. And as you know, even with objective evidence of improvement it can take a while because that exposes another gap, the one between intent and impact.  Many people get rather defensive at that point, so I have had to take it slowly. Some people get really fired up though.

 <Bob> Yes. Respect, challenge, patience and persistence are all needed. So, where shall we pick up?

<Leslie> The old chestnut of winter pressures and A&E targets.  Except that it is an all-year problem now and according to what I read in the news, everyone is predicting a ‘melt-down’.

<Bob> Did you see last week’s IS blog on that very topic?

<Leslie> Yes, I did!  And that is what prompted me to contact you and to re-start my CHIPs coaching.  It was a real eye opener.  I liked the black swan code-named “RC9” story, it makes it sound like a James Bond film!

<Bob> I wonder how many people dug deeper into how “RC9” achieved that rock-steady A&E performance despite a rising tide of arrivals and admissions?

<Leslie> I did, and I saw several examples of anti-carve-out design.  I have read though my notes and we have talked about carve out many times.

<Bob> Excellent. Being able to see the signs of competent design is just as important as the symptoms of inept design. So, what shall we talk about?

<Leslie> Well, by co-incidence I was sent a copy of of a report entitled “Understanding patient flow in hospitals” published by one of the leading Think Tanks and I confess it made no sense to me.  Can we talk about that?

<Bob> OK. Can you describe the essence of the report for me?

<Leslie> Well, in a nutshell it said that flow needs space so if we want hospitals to flow better we need more space, in other words more beds.

<Bob> And what evidence was presented to support that hypothesis?

<Leslie> The authors equated the flow of patients through a hospital to the flow of traffic on a motorway. They presented a table of numbers that made no sense to me, I think partly because there are no units stated for some of the numbers … I’ll email you a picture.

traffic_flow_dynamics

<Bob> I agree this is not a very informative table.  I am not sure what the definition of “capacity” is here and it may be that the authors may be equating “hospital bed” to “area of tarmac”.  Anyway, the assertion that hospital flow is equivalent to motorway flow is inaccurate.  There are some similarities and traffic engineering is an interesting subject, but they are not equivalent.  A hospital is more like a busy city with junctions, cross-roads, traffic lights, roundabouts, zebra crossings, pelican crossings and all manner of unpredictable factors such as cyclists and pedestrians. Motorways are intentionally designed without these “impediments”, for obvious reasons! A complex adaptive flow system like a hospital cannot be equated to a motorway. It is a dangerous over-simplification.

<Leslie> So, if the hospital-motorway analogy is invalid then the conclusions are also invalid?

<Bob> Sometimes, by accident, we get a valid conclusion from an invalid method. What were the conclusions?

<Leslie> That the solution to improving A&E performance is more space (i.e. hospital beds) but there is no more money to build them or people to staff them.  So the recommendations are to reduce volume, redesign rehabilitation and discharge processes, and improve IT systems.

<Bob> So just re-iterating the habitual exhortations and nothing about using well-understood systems engineering methods to accurately diagnose the actual root cause of the ‘symptoms’, which is likely to be the endemic carveoutosis multiforme, and then treat accordingly?

<Leslie> No. I could not find the term “carve out” anywhere in the document.

<Bob> Oh dear.  Based on that observation, I do not believe this latest Think Tank report is going to be any more effective than the previous ones.  Perhaps asking “RC9” to write an account of what they did and how they learned to do it would be more informative?  They did not reduce volume, and I doubt they opened more beds, and their annual report suggests they identified some space and flow carveoutosis and treated it. That is what a competent systems engineer would do.

<Leslie> Thanks Bob. Very helpful as always. What is my next step?

<Bob> Some ISP-2 brain-teasers, a juicy ISP-2 project, and some one day training workshops for your all-fired-up CHIPs.

<Leslie> Bring it on!

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Posted on

Type II Error

figure_pointing_out_chart_data_150_clr_8005It was the time for Bob and Leslie’s regular Improvement Science coaching session.

<Leslie> Hi Bob, how are you today?

<Bob> I am getting over a winter cold but otherwise I am good.  And you?

<Leslie> I am OK and I need to talk something through with you because I suspect you will be able to help.

<Bob> OK. What is the context?

<Leslie> Well, one of the projects that I am involved with is looking at the elderly unplanned admission stream which accounts for less than half of our unplanned admissions but more than half of our bed days.

<Bob> OK. So what were you looking to improve?

<Leslie> We want to reduce the average length of stay so that we free up beds to provide resilient space-capacity to ease the 4-hour A&E admission delay niggle.

<Bob> That sounds like a very reasonable strategy.  So have you made any changes and measured any improvements?

<Leslie> We worked through the 6M Design® sequence. We studied the current system, diagnosed some time traps and bottlenecks, redesigned the ones we could influence, modified the system, and continued to measure to monitor the effect.

<Bob> And?

<Leslie> It feels better but the system behaviour charts do not show an improvement.

<Bob> Which charts, specifically?

<Leslie> The BaseLine XmR charts of average length of stay for each week of activity.

<Bob> And you locked the limits when you made the changes?

<Leslie> Yes. And there still were no red flags. So that means our changes have not had a significant effect. But it definitely feels better. Am I deluding myself?

<Bob> I do not believe so. Your subjective assessment is very likely to be accurate. Our Chimp OS 1.0 is very good at some things! I think the issue is with the tool you are using to measure the change.

<Leslie> The XmR chart?  But I thought that was THE tool to use?

<Bob> Like all tools it is designed for a specific purpose.  Are you familiar with the term Type II Error.

<Leslie> Doesn’t that come from research? I seem to remember that is the error we make when we have an under-powered study.  When our sample size is too small to confidently detect the change in the mean that we are looking for.

<Bob> A perfect definition!  The same error can happen when we are doing before and after studies too.  And when it does, we see the pattern you have just described: the process feels better but we do not see any red flags on our BaseLine© chart.

<Leslie> But if our changes only have a small effect how can it feel better?

<Bob> Because some changes have cumulative effects and we omit to measure them.

<Leslie> OMG!  That makes complete sense!  For example, if my bank balance is stable my average income and average expenses are balanced over time. So if I make a small-but-sustained improvement to my expenses, like using lower cost generic label products, then I will see a cumulative benefit over time to the balance, but not the monthly expenses; because the noise swamps the signal on that chart!

<Bob> An excellent analogy!

<Leslie> So the XmR chart is not the tool for this job. And if this is the only tool we have then we risk making a Type II error. Is that correct?

<Bob> Yes. We do still use an XmR chart first though, because if there is a big enough and fast enough shift then the XmR chart will reveal it.  If there is not then we do not give up just yet; we reach for our more sensitive shift detector tool.

<Leslie> Which is?

<Bob> I will leave you to ponder on that question.  You are a trained designer now so it is time to put your designer hat on and first consider the purpose of this new tool, and then create the outline a fit-for-purpose design.

<Leslie> OK, I am on the case!

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Melting the Queue

custom_meter_15256[Drrrrrrring]

<Leslie> Hi Bob, I hope I am not interrupting you.  Do you have five minutes?

<Bob> Hi Leslie. I have just finished what I was working on and a chat would be a very welcome break.  Fire away.

<Leslie> I really just wanted to say how much I enjoyed the workshop this week, and so did all the delegates.  They have been emailing me to say how much they learned and thanking me for organising it.

<Bob> Thank you Leslie. I really enjoyed it too … and I learned lots … I always do.

<Leslie> As you know I have been doing the ISP programme for some time, and I have come to believe that you could not surprise me any more … but you did!  I never thought that we could make such a dramatic improvement in waiting times.  The queue just melted away and I still cannot really believe it.  Was it a trick?

<Bob> Ahhhh, the siren-call of the battle-hardened sceptic! It was no trick. What you all saw was real enough. There were no computers, statistics or smoke-and-mirrors used … just squared paper and a few coloured pens. You saw it with your own eyes; you drew the charts; you made the diagnosis; and you re-designed the policy.  All I did was provide the context and a few nudges.

<Leslie> I know, and that is why I think seeing the before and after data would help me. The process felt so much better, but I know I will need to show the hard evidence to convince others, and to convince myself as well, to be brutally honest.  I have the before data … do you have the after data?

<Bob> I do. And I was just plotting it as BaseLine charts to send to you.  So you have pre-empted me.  Here you are.

StE_OSC_Before_and_After
This is the waiting time run chart for the one stop clinic improvement exercise that you all did.  The leftmost segment is the before, and the rightmost are the after … your two ‘new’ designs.

As you say, the queue and the waiting has melted away despite doing exactly the same work with exactly the same resources.  Surprising and counter-intuitive but there is the evidence.

<Leslie> Wow! That fits exactly with how it felt.  Quick and calm! But I seem to remember that the waiting room was empty, particularly in the case of the design that Team 1 created. How come the waiting is not closer to zero on the chart?

<Bob> You are correct.  This is not just the time in the waiting room, it also includes the time needed to move between the rooms and the changeover time within the rooms.  It is what I call the ‘tween-time.

<Leslie> OK, that makes sense now.  And what also jumps out of the picture for me is the proof that we converted an unstable process into a stable one.  The chaos was calmed.  So what is the root cause of the difference between the two ‘after’ designs?

<Bob> The middle one, the slightly better of the two, is the one where all patients followed the newly designed process.  The rightmost one was where we deliberately threw a spanner in the works by assuming an unpredictable case mix.

<Leslie> Which made very little difference!  The new design was still much, much better than before.

<Bob> Yes. What you are seeing here is the footprint of resilient design. Do you believe it is possible now?

<Leslie> You bet I do!

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The Magic Black Box

stick_figure_magic_carpet_150_wht_5040It was the appointed time for Bob and Leslie’s regular coaching session as part of the improvement science practitioner programme.

<Leslie> Hi Bob, I am feeling rather despondent today so please excuse me in advance if you hear a lot of “Yes, but …” language.

<Bob> I am sorry to hear that Leslie. Do you want to talk about it?

<Leslie> Yes, please.  The trigger for my gloom was being sent on a mandatory training workshop.

<Bob> OK. Training to do what?

<Leslie> Outpatient demand and capacity planning!

<Bob> But you know how to do that already, so what is the reason you were “sent”?

<Leslie> Well, I am no longer sure I know how to it.  That is why I am feeling so blue.  I went more out of curiosity and I came away utterly confused and with my confidence shattered.

<Bob> Oh dear! We had better start at the beginning.  What was the purpose of the workshop?

<Leslie> To train everyone in how to use an Outpatient Demand and Capacity planning model, an Excel one that we were told to download along with the User Guide.  I think it is part of a national push to improve waiting times for outpatients.

<Bob> OK. On the surface that sounds reasonable. You have designed and built your own Excel flow-models already; so where did the trouble start?

<Leslie> I will attempt to explain.  This was a paragraph in the instructions. I felt OK with this because my Improvement Science training has given me a very good understanding of basic demand and capacity theory.

IST_DandC_Model_01<Bob> OK.  I am guessing that other delegates may have felt less comfortable with this. Was that the case?

<Leslie> The training workshops are targeted at Operational Managers and the ones I spoke to actually felt that they had a good grasp of the basics.

<Bob> OK. That is encouraging, but a warning bell is ringing for me. So where did the trouble start?

<Leslie> Well, before going to the workshop I decided to read the User Guide so that I had some idea of how this magic tool worked.  This is where I started to wobble – this paragraph specifically …

IST_DandC_Model_02

<Bob> H’mm. What did you make of that?

<Leslie> It was complete gibberish to me and I felt like an idiot for not understanding it.  I went to the workshop in a bit of a panic and hoped that all would become clear. It didn’t.

<Bob> Did the User Guide explain what ‘percentile’ means in this context, ideally with some visual charts to assist?

<Leslie> No and the use of ‘th’ and ‘%’ was really confusing too.  After that I sort of went into a mental fog and none of the workshop made much sense.  It was all about practising using the tool without any understanding of how it worked. Like a black magic box.

<Bob> OK.  I can see why you were confused, and do not worry, you are not an idiot.  It looks like the author of the User Guide has unwittingly used some very confusing and ambiguous terminology here.  So can you talk me through what you have to do to use this magic box?

<Leslie> First we have to enter some of our historical data; the number of new referrals per week for a year; and the referral and appointment dates for all patients for the most recent three months.

<Bob> OK. That sounds very reasonable.  A run chart of historical demand and the raw event data for a Vitals Chart® is where I would start the measurement phase too – so long as the data creates a valid 3 month reporting window.

<Leslie> Yes, I though so too … but that is not how the black box model seems to work. The weekly demand is used to draw an SPC chart, but the event data seems to disappear into the innards of the black box, and recommendations pop out of it.

<Bob> Ah ha!  And let me guess the relationship between the term ‘percentile’ and the SPC chart of weekly new demand was not explained?

<Leslie> Spot on.  What does percentile mean?

<Bob> It is statistics jargon. Remember that we have talked about the distribution of the data around the average on a BaseLine chart; and how we use the histogram feature of BaseLine to show it visually.  Like this example.

IST_DandC_Model_03<Leslie> Yes. I recognise that. This chart shows a stable system of demand with an average of around 150 new referrals per week and the variation distributed above and below the average in a symmetrical pattern, falling off to zero around the upper and lower process limits.  I believe that you said that over 99% will fall within the limits.

<Bob> Good.  The blue histogram on this chart is called a probability distribution function, to use the terminology of a statistician.

<Leslie> OK.

<Bob> So, what would happen if we created a Pareto chart of demand using the number of patients per week as the categories and ignoring the time aspect? We are allowed to do that if the behaviour is stable, as this chart suggests.

<Leslie> Give me a minute, I will need to do a rough sketch. Does this look right?

IST_DandC_Model_04

<Bob> Perfect!  So if you now convert the Y-axis to a percentage scale so that 52 weeks is 100% then where does the average weekly demand of about 150 fall? Read up from the X-axis to the line then across to the Y-axis.

<Leslie> At about 26 weeks or 50% of 52 weeks.  Ah ha!  So that is what a percentile means!  The 50th percentile is the average, the zeroth percentile is around the lower process limit and the 100th percentile is around the upper process limit!

<Bob> In this case the 50th percentile is the average, it is not always the case though.  So where is the 85th percentile line?

<Leslie> Um, 52 times 0.85 is 44.2 which, reading across from the Y-axis then down to the X-axis gives a weekly demand of about 170 per week.  That is about the same as the average plus one sigma according to the run chart.

<Bob> Excellent. The Pareto chart that you have drawn is called a cumulative probability distribution function … and that is usually what percentiles refer to. Comparative Statisticians love these but often omit to explain their rationale to non-statisticians!

<Leslie> Phew!  So, now I can see that the 65th percentile is just above average demand, and 85th percentile is above that.  But in the confusing paragraph how does that relate to the phrase “65% and 85% of the time”?

<Bob> It doesn’t. That is the really, really confusing part of  that paragraph. I am not surprised that you looped out at that point!

<Leslie> OK. Let us leave that for another conversation.  If I ignore that bit then does the rest of it make sense?

<Bob> Not yet alas. We need to dig a bit deeper. What would you say are the implications of this message?

<Leslie> Well.  I know that if our flow-capacity is less than our average demand then we will guarantee to create an unstable queue and chaos. That is the Flaw of Averages trap.

<Bob> OK.  The creator of this tool seems to know that.

<Leslie> And my outpatient manager colleagues are always complaining that they do not have enough slots to book into, so I conclude that our current flow-capacity is just above the 50th percentile.

<Bob> A reasonable hypothesis.

<Leslie> So to calm the chaos the message is saying I will need to increase my flow capacity up to the 85th percentile of demand which is from about 150 slots per week to 170 slots per week. An increase of 7% which implies a 7% increase in costs.

<Bob> Good.  I am pleased that you did not fall into the intuitive trap that a increase from the 50th to the 85th percentile implies a 35/50 or 70% increase! Your estimate of 7% is a reasonable one.

<Leslie> Well it may be theoretically reasonable but it is not practically possible. We are exhorted to reduce costs by at least that amount.

<Bob> So we have a finance versus governance bun-fight with the operational managers caught in the middle: FOG. That is not the end of the litany of woes … is there anything about Did Not Attends in the model?

<Leslie> Yes indeed! We are required to enter the percentage of DNAs and what we do with them. Do we discharge them or re-book them.

<Bob> OK. Pragmatic reality is always much more interesting than academic rhetoric and this aspect of the real system rather complicates things, at least for a comparative statistician. This is where the smoke and mirrors will appear and they will be hidden inside the black magic box.  To solve this conundrum we need to understand the relationship between demand, capacity, variation and yield … and it is rather counter-intuitive.  So, how would you approach this problem?

<Leslie> I would use the 6M Design® framework and I would start with a map and not with a model; least of all a magic black box one that I did not design, build and verify myself.

<Bob> And how do you know that will work any better?

<Leslie> Because at the One Day ISP Workshop I saw it work with my own eyes. The queues, waits and chaos just evaporated.  And it cost nothing.  We already had more than enough “capacity”.

<Bob> Indeed you did.  So shall we do this one as an ISP-2 project?

<Leslie> An excellent suggestion.  I already feel my confidence flowing back and I am looking forward to this new challenge. Thank you again Bob.

Posted on

Hot and Cold

stick_figure_on_cloud_150_wht_9604Last week Bob and Leslie were exploring the data analysis trap called a two-points-in-time comparison: as illustrated by the headline “This winter has not been as bad as last … which proves that our winter action plan has worked.”

Actually it doesn’t.

But just saying that is not very helpful. We need to explain the reason why this conclusion is invalid and therefore potentially dangerous.

So here is the continuation of Bob and Leslie’s conversation.

<Bob> Hi Leslie, have you been reflecting on the two-points-in-time challenge?

<Leslie> Yes indeed, and you were correct, I did know the answer … I just didn’t know I knew if you get my drift.

<Bob> Yes, I do. So, are you willing to share your story?

<Leslie> OK, but before I do that I would like to share what happened when I described what we talked about to some colleagues.  They sort of got the idea but got lost in the unfamiliar language of ‘variance’ and I realized that I needed an example to illustrate.

<Bob> Excellent … what example did you choose?

<Leslie> The UK weather – or more specifically the temperature.  My reasons for choosing this were many: first it is something that everyone can relate to; secondly it has strong seasonal cycle; and thirdly because the data is readily available on the Internet.

<Bob> OK, so what specific question were you trying to answer and what data did you use?

<Leslie> The question was “Are our winters getting warmer?” and my interest in that is because many people assume that the colder the winter the more people suffer from respiratory illness and the more that go to hospital … contributing to the winter A&E and hospital pressures.  The data that I used was the maximum monthly temperature from 1960 to the present recorded at our closest weather station.

<Bob> OK, and what did you do with that data?

<Leslie> Well, what I did not do was to compare this winter with last winter and draw my conclusion from that!  What I did first was just to plot-the-dots … I created a time-series chart … using the BaseLine© software.

MaxMonthTemp1960-2015

And it shows what I expected to see, a strong, regular, 12-month cycle, with peaks in the summer and troughs in the winter.

<Bob> Can you explain what the green and red lines are and why some dots are red?

<Leslie> Sure. The green line is the average for all the data. The red lines are called the upper and lower process limits.  They are calculated from the data and what they say is “if the variation in this data is random then we will expect more than 99% of the points to fall between these two red lines“.

<Bob> So, we have 55 years of monthly data which is nearly 700 points which means we would expect fewer than seven to fall outside these lines … and we clearly have many more than that.  For example, the winter of 1962-63 and the summer of 1976 look exceptional – a run of three consecutive dots outside the red lines. So can we conclude the variation we are seeing is not random?

<Leslie> Yes, and there is more evidence to support that conclusion. First is the reality check … I do not remember either of those exceptionally cold or hot years personally, so I asked Dr Google.

BigFreeze_1963This picture from January 1963 shows copper telephone lines that are so weighed down with ice, and for so long, that they have stretched down to the ground.  In this era of mobile phones we forget this was what telecommunication was like!

 

 

HeatWave_1976

And just look at the young Michal Fish in the Summer of ’76! Did people really wear clothes like that?

And there is more evidence on the chart. The red dots that you mentioned are indicators that BaseLine© has detected other non-random patterns.

So the large number of red dots confirms our Mark I Eyeball conclusion … that there are signals mixed up with the noise.

<Bob> Actually, I do remember the Summer of ’76 – it was the year I did my O Levels!  And your signals-in-the-noise phrase reminds me of SETI – the search for extra-terrestrial intelligence!  I really enjoyed the 1997 film of Carl Sagan’s book Contact with Jodi Foster playing the role of the determined scientist who ends up taking a faster-than-light trip through space in a machine designed by ET and built by humans. And especially the line about 10 minutes from the end when those-in-high-places who had discounted her story as “unbelievable” realized they may have made an error … the line ‘Yes, that is interesting isn’t it’.

<Leslie> Ha ha! Yes. I enjoyed that film too. It had lots of great characters – her glory seeking boss; the hyper-suspicious head of national security who militarized the project; the charismatic anti-hero; the ranting radical who blew up the first alien machine; and John Hurt as her guardian angel. I must watch it again.

Anyway, back to the story. The problem we have here is that this type of time-series chart is not designed to extract the overwhelming cyclical, annual pattern so that we can search for any weaker signals … such as a smaller change in winter temperature over a longer period of time.

<Bob>Yes, that is indeed the problem with these statistical process control charts.  SPC charts were designed over 60 years ago for process quality assurance in manufacturing not as a diagnostic tool in a complex adaptive system such a healthcare. So how did you solve the problem?

<Leslie> I realized that it was the regularity of  the cyclical pattern that was the key.  I realized that I could use that to separate out the annual cycle and to expose the weaker signals.  I did that using the rational grouping feature of BaseLine© with the month-of-the-year as the group.

MaxMonthTemp1960-2015_ByMonth

Now I realize why the designers of the software put this feature in! With just one mouse click the story jumped out of the screen!

<Bob> OK. So can you explain what we are looking at here?

<Leslie> Sure. This chart shows the same data as before except that I asked BaseLine© first to group the data by month and then to create a mini-chart for each month-group independently.  Each group has its own average and process limits.  So if we look at the pattern of the averages, the green lines, we can clearly see the annual cycle.  What is very obvious now is that the process limits for each sub-group are much narrower, and that there are now very few red points  … other than in the groups that are coloured red anyway … a niggle that the designers need to nail in my opinion!

<Bob> I will pass on your improvement suggestion! So are you saying that the regular annual cycle has accounted for the majority of the signal in the previous chart and that now we have extracted that signal we can look for weaker signals by looking for red flags in each monthly group?

<Leslie> Exactly so.  And the groups I am most interested in are the November to March ones.  So, next I filtered out the November data and plotted it as a separate chart; and I then used another cool feature of BaseLine© called limit locking.

MaxTempNov1960-2015_LockedLimits

What that means is that I have used the November maximum temperature data for the first 30 years to get the baseline average and natural process limits … and we can see that there are no red flags in that section, no obvious signals.  Then I locked these limits at 1990 and this tells BaseLine© to compare the subsequent 25 years of data against these projected limits.  That exposed a lot of signal flags, and we can clearly see that most of the points in the later section are above the projected average from the earlier one.  This confirms that there has been a significant increase in November maximum temperature over this 55 year period.

<Bob> Excellent! You have answered part of your question. So what about December onwards?

<Leslie> I was on a roll now! I also noticed from my second chart that the December, January and February groups looked rather similar so I filtered that data out and plotted them as a separate chart.

MaxTempDecJanFeb1960-2015_GroupedThese were indeed almost identical so I lumped them together as a ‘winter’ group and compared the earlier half with the later half using another BaseLine© feature called segmentation.

MaxTempDecJanFeb1960-2015-SplitThis showed that the more recent winter months have a higher maximum temperature … on average. The difference is just over one degree Celsius. But it also shows that that the month-to-month and year-to-year variation still dominates the picture.

<Bob> Which implies?

<Leslie> That, with data like this, a two-points-in-time comparison is meaningless.  If we do that we are just sampling random noise and there is no useful information in noise. Nothing that we can  learn from. Nothing that we can justify a decision with.  This is the reason the ‘this year was better than last year’ statement is meaningless at best; and dangerous at worst.  Dangerous because if we draw an invalid conclusion, then it can lead us to make an unwise decision, then decide a counter-productive action, and then deliver an unintended outcome.

By doing invalid two-point comparisons we can too easily make the problem worse … not better.

<Bob> Yes. This is what W. Edwards Deming, an early guru of improvement science, referred to as ‘tampering‘.  He was a student of Walter A. Shewhart who recognized this problem in manufacturing and, in 1924, invented the first control chart to highlight it, and so prevent it.  My grandmother used the term meddling to describe this same behavior … and I now use that term as one of the eight sources of variation. Well done Leslie!

Posted on

The Two-Points-In-Time Comparison Trap

comparing_information_anim_5545[Bzzzzzz] Bob’s phone vibrated to remind him it was time for the regular ISP remote coaching session with Leslie. He flipped the lid of his laptop just as Leslie joined the virtual meeting.

<Leslie> Hi Bob, and Happy New Year!

<Bob> Hello Leslie and I wish you well in 2016 too.  So, what shall we talk about today?

<Leslie> Well, given the time of year I suppose it should be the Winter Crisis.  The regularly repeating annual winter crisis. The one that feels more like the perpetual winter crisis.

<Bob> OK. What specifically would you like to explore?

<Leslie> Specifically? The habit of comparing of this year with last year to answer the burning question “Are we doing better, the same or worse?”  Especially given the enormous effort and political attention that has been focused on the hot potato of A&E 4-hour performance.

<Bob> Aaaaah! That old chestnut! Two-Points-In-Time comparison.

<Leslie> Yes. I seem to recall you usually add the word ‘meaningless’ to that phrase.

<Bob> H’mm.  Yes.  It can certainly become that, but there is a perfectly good reason why we do this.

<Leslie> Indeed, it is because we see seasonal cycles in the data so we only want to compare the same parts of the seasonal cycle with each other. The apples and oranges thing.

<Bob> Yes, that is part of it. So what do you feel is the problem?

<Leslie> It feels like a lottery!  It feels like whether we appear to be better or worse is just the outcome of a random toss.

<Bob> Ah!  So we are back to the question “Is the variation I am looking at signal or noise?” 

<Leslie> Yes, exactly.

<Bob> And we need a scientifically robust way to answer it. One that we can all trust.

<Leslie> Yes.

<Bob> So how do you decide that now in your improvement work?  How do you do it when you have data that does not show a seasonal cycle?

<Leslie> I plot-the-dots and use an XmR chart to alert me to the presence of the signals I am interested in – especially a change of the mean.

<Bob> Good.  So why can we not use that approach here?

<Leslie> Because the seasonal cycle is usually a big signal and it can swamp the smaller change I am looking for.

<Bob> Exactly so. Which is why we have to abandon the XmR chart and fall back the two points in time comparison?

<Leslie> That is what I see. That is the argument I am presented with and I have no answer.

<Bob> OK. It is important to appreciate that the XmR chart was not designed for doing this.  It was designed for monitoring the output quality of a stable and capable process. It was designed to look for early warning signs; small but significant signals that suggest future problems. The purpose is to alert us so that we can identify the root causes, correct them and the avoid a future problem.

<Leslie> So we are using the wrong tool for the job. I sort of knew that. But surely there must be a better way than a two-points-in-time comparison!

<Bob> There is, but first we need to understand why a TPIT is a poor design.

<Leslie> Excellent. I’m all ears.

<Bob> A two point comparison is looking at the difference between two values, and that difference can be positive, zero or negative.  In fact, it is very unlikely to be zero because noise is always present.

<Leslie> OK.

<Bob> Now, both of the values we are comparing are single samples from two bigger pools of data.  It is the difference between the pools that we are interested in but we only have single samples of each one … so they are not measurements … they are estimates.

<Leslie> So, when we do a TPIT comparison we are looking at the difference between two samples that come from two pools that have inherent variation and may or may not actually be different.

<Bob> Well put.  We give that inherent variation a name … we call it variance … and we can quantify it.

<Leslie> So if we do many TPIT comparisons then they will show variation as well … for two reasons; first because the pools we are sampling have inherent variation; and second just from the process of sampling itself.  It was the first lesson in the ISP-1 course.

<Bob> Well done!  So the question is: “How does the variance of the TPIT sample compare with the variance of the pools that the samples are taken from?”

<Leslie> My intuition tells me that it will be less because we are subtracting.

<Bob> Your intuition is half-right.  The effect of the variation caused by the signal will be less … that is the rationale for the TPIT after all … but the same does not hold for the noise.

<Leslie> So the noise variation in the TPIT is the same?

<Bob> No. It is increased.

<Leslie> What! But that would imply that when we do this we are less likely to be able to detect a change because a small shift in signal will be swamped by the increase in the noise!

<Bob> Precisely.  And the degree that the variance increases by is mathematically predictable … it is increased by a factor of two.

<Leslie> So as we usually present variation as the square root of the variance, to get it into the same units as the metric, then that will be increased by the square root of two … 1.414

<Bob> Yes.

<Leslie> I need to put this counter-intuitive theory to the test!

<Bob> Excellent. Accept nothing on faith. Always test assumptions. And how will you do that?

<Leslie> I will use Excel to generate a big series of normally distributed random numbers; then I will calculate a series of TPIT differences using a fixed time interval; then I will calculate the means and variations of the two sets of data; and then I will compare them.

<Bob> Excellent.  Let us reconvene in ten minutes when you have done that.

10 minutes later …

<Leslie> Hi Bob, OK I am ready and I would like to present the results as charts. Is that OK?

<Bob> Perfect!

<Leslie> Here is the first one.  I used our A&E performance data to give me some context. We know that on Mondays we have an average of 210 arrivals with an approximately normal distribution and a standard deviation of 44; so I used these values to generate the random numbers. Here is the simulated Monday Arrivals chart for two years.

TPIT_SourceData

<Bob> OK. It looks stable as we would expect and I see that you have plotted the sigma levels which look to be just under 50 wide.

<Leslie> Yes, it shows that my simulation is working. So next is the chart of the comparison of arrivals for each Monday in Year 2 compared with the corresponding week in Year 1.

TPIT_DifferenceData <Bob> Oooookaaaaay. What have we here?  Another stable chart with a mean of about zero. That is what we would expect given that there has not been a change in the average from Year 1 to Year 2. And the variation has increased … sigma looks to be just over 60.

<Leslie> Yes!  Just as the theory predicted.  And this is not a spurious answer. I ran the simulation dozens of times and the effect is consistent!  So, I am forced by reality to accept the conclusion that when we do two-point-in-time comparisons to eliminate a cyclical signal we will reduce the sensitivity of our test and make it harder to detect other signals.

<Bob> Good work Leslie!  Now that you have demonstrated this to yourself using a carefully designed and conducted simulation experiment, you will be better able to explain it to others.

<Leslie> So how do we avoid this problem?

<Bob> An excellent question and one that I will ask you to ponder on until our next chat.  You know the answer to this … you just need to bring it to conscious awareness.

 

Posted on

A Case of Chronic A&E Pain: Part 6

Dr_Bob_ThumbnailDr Bob runs a Clinic for Sick Systems and is sharing the Case of St Elsewhere’s® Hospital which is suffering from chronic pain in their A&E department.

The story so far: The history and examination of St.Elsewhere’s® Emergency Flow System have revealed that the underlying disease includes carveoutosis multiforme.  StE has consented to a knowledge transplant but is suffering symptoms of disbelief – the emotional rejection of the new reality. Dr Bob prescribed some loosening up exercises using the Carveoutosis Game.  This is the appointment to review the progress.

<Dr Bob> Hello again. I hope you have done the exercises as we agreed.

<StE> Indeed we have.  Many times in fact because at first we could not believe what we were seeing. We even modified the game to explore the ramifications.  And we have an apology to make. We discounted what you said last week but you were absolutely correct.

<Dr Bob> I am delighted to hear that you have explored further and I applaud you for the curiosity and courage in doing that.  There is no need to apologize. If this flow science was intuitively obvious then we we would not be having this conversation. So, how have you used the new understanding?

<StE> Before we tell the story of what happened next we are curious to know where you learned about this?

<Dr Bob> The pathogenesis of carveoutosis spatialis has been known for about 100 years but in a different context.  The story goes back to the 1870s when Alexander Graham Bell invented the telephone.  He was not an engineer or mathematician by background; he was interested in phonetics and he was a pragmatist and experimented by making things. He invented the telephone and the Bell Telephone Co. was born.  This innovation spread like wildfire, as you can imagine, and by the early 1900’s there were many telephone companies all over the world.  At that time the connections were made manually by telephone operators using patch boards and the growing demand created a new problem.  How many lines and operators were needed to provide a high quality service to bill paying customers? In other words … to achieve an acceptably low chance of hearing the reply “I’m sorry but all lines are busy, please try again later“.  Adding new lines and more operators was a slow and expensive business so they needed a way to predict how many would be needed – and how to do that was not obvious!  In 1917, a Danish mathematician, statistician and engineer called Agner Krarup Erlang published a paper with the solution.  A complicated formula that described the relationship and his Erlang B equation allowed telephone exchanges to be designed, built and staffed and to provide a high quality service at an acceptably low cost.  Mass real-time voice communication by telephone became affordable and has transformed the world.

<StE> Fascinating! We sort of sense there is a link here and certainly the “high quality and low cost” message resonates for us. But how does designing telephone exchanges relate to hospital beds?

<Dr Bob> If we equate an emergency admission needing a bed to a customer making a phone call, and we equate the number of telephone lines to the number of beds, then the two systems are very similar from the flow physics perspective. Erlang’s scary-looking equation can be used to estimate the minimum number of beds needed to achieve any specified level of admission service quality if you know the average rate of demand and average the length of stay.  That is how I made the estimate last week. It is this predictable-within-limits behaviour that you demonstrated to yourself with the Carveoutosis Game.

<StE> And this has been known for nearly 100 years but we have only just learned about it!

<Dr Bob> Yes. That is a bit annoying isn’t it?

<StE> And that explains why when we ‘ring-fence’ our fixed stock of beds the 4-hour performance falls!

<Dr Bob> Yes, that is a valid assertion. By doing that you are reducing your space-capacity resilience and the resulting danger, chaos, disappointment and escalating cost is completely predictable.

<StE> So our pain is iatrogenic as you said! We have unwittingly caused this. That is uncomfortable news to hear.

<Dr Bob> The root cause is actually not what you have done wrong, it is what you have not done right. It is an error of omission. You have not learned to listen to what your system is telling you. You have not learned how that can help you to deepen your understanding of how your system works. It is that information, knowledge, understanding and wisdom that you need to design a safer, calmer, higher quality and more affordable healthcare system.

<StE> And now we can see our omission … before it was like a blind spot … and now we can see the fallacy of our previously deeply held belief: that it was impossible to solve this without more beds, more staff and more money.  The gap is now obvious where before it was invisible. It is like a light has been turned on.  Now we know what to do and we are on the road to recovery. We need to learn how to do this ourselves … but not by guessing and meddling … we need to learn to diagnose and then to design and then to deliver safety, flow, quality and productivity.  All at the same time.

<Dr Bob> Welcome to the world of Improvement Science. And here I must sound a note of caution … there is a lot more to it than just blindly applying Erlang’s B equation. That will get us into the ball-park, which is a big leap forward, but real systems are not just simple, passive games of chance; they are complicated, active and adaptive.  Applying the principles of flow design in that context requires more than just mathematics, statistics and computer models.  But that know-how is available and accessible too … and waiting for when you are ready to take that leap of learning.

OK. I do not think you require any more help from me at this stage. You have what you need and I wish you well.  And please let me know the outcome.

<StE> Thank you and rest assured we will. We have already started writing our story … and we wanted to share the that with you today … but with this new insight we will need to write a few more chapters first.  This is really exciting … thank you so much.

St.Elsewhere’s® is a registered trademark of Kate Silvester Ltd,  and to read more real cases of 4-hour A&E pain download Kate’s: The Christmas Crisis

Part 1 is here. Part 2 is here. Part 3 is here. Part 4 is here. Part 5 is here.

Posted on

A Case of Chronic A&E Pain: Part 5

Dr_Bob_ThumbnailDr Bob runs a Clinic for Sick Systems and is sharing the Case of St Elsewhere’s® Hospital which is suffering from chronic pain in their A&E department.

The story so far: The history and examination of St.Elsewhere’s® Emergency Flow System have revealed the footprint of a Horned Gaussian in their raw A&E data. This characteristic sign suggests that the underlying disease includes carveoutosis.  StE has signed up for treatment and has started by installing learning loops. This is the one week follow up appointment.

<Dr Bob> Hi there. How are things? What has changed this week?

<StE> Lots! We shared the eureka moment we had when you described the symptoms, signs and pathogenesis of carvoutosis temporalis using the Friday Afternoon Snail Mail story.  That resonated strongly with lots of people. And as a result that symptom has almost gone – as if by magic!  We are now keeping on top of our emails by doing a few each day and we are seeing decisions and actions happening much more quickly.

<Dr Bob> Excellent. Many find it surprising to see such a large beneficial impact from such an apparently small change. And how are you feeling overall? How is the other pain?

<StE> Still there unfortunately. Our A&E performance has not really improved but we do feel a new sense of purpose, determination and almost optimism.  It is hard to put a finger on it.

<Dr Bob> Does it feel like a paradoxical combination of “feels subjectively better but looks objectively the same”?

<StE> Yes, that’s exactly it. And it is really confusing. Are we just fire-fighting more quickly but still not putting out the fire?

<Dr Bob> Possibly. It depends on your decisions and actions … you may be unwittingly both fighting and fanning the fire at the same time.  It may be that you are suffering from carveoutosis multiforme.

<StE> Is that bad?

<Dr Bob> No. Just trickier to diagnose and treat. It implies that there is more than one type of carveoutosis active at the same time and they tend to amplify each other. The other common type is called carveoutosis spatialis. Shall we explore that hypothesis?

<StE> Um, OK. Does it require more painful poking?

<Dr Bob> A bit. Do you want to proceed? I cannot do so without your consent.

<StE> I suppose so.

<Dr Bob> OK. Can you describe for me what happens to emergency patients after they are admitted. Where do they go to?

<StE> That’s easy.  The medical emergencies go to the medical wards and the others go to the surgical wards. Or rather they should. Very often there is spillover from one to the other because the specialty wards are full. That generates a lot of grumbling from everyone … doctors, nurses and patients. We call them outliers.

<Dr Bob> And when a patient gets to a ward where do they go? Into any available empty bed?

<StE> No.  We have to keep males and females separate, to maintain privacy and dignity.  We get really badly beaten up if we mix them.  Our wards are split up into six-bedded bays and a few single side-rooms, and we are constantly juggling bays and swapping them from male to female and back. Often moving patients around in the process, and often late at night. The patients do not like it and it creates lots of extra work for the nurses.

<Dr Bob> And when did these specialty and gender segregation policies come into force?

<StE> The specialty split goes back decades, the gender split was introduced after StE was built. We were told that it wouldn’t make any difference because we are still admitting the same proportion of males and females so it would average out, but it causes us a lot of headaches!  Maybe we are now having to admit more patients than the hospital was designed to hold!

<Dr Bob> That is possible, but even if you were admitting the same number for the same length of time the symptoms of carveoutosis spatialis are quite predictable. When there is any form of variation in demand, casemix, or gender then if you split your space-capacity into ‘ring-fenced’ areas you will always need more total space-capacity to achieve the same waiting time performance. Always. It is mandated by the Laws of Physics. It is not negotiable. And it does not average out.

<StE> What! So we were mis-informed?  The chaos we are seeing was predictable?

<Dr Bob> The effect of carveoutosis spatialis is predictable. But knowing that does not prove it is the sole cause of the chaos you are experiencing. It may well be a contributory factor though.

<StE> So how big an effect are we talking about here? A few percent?

<Dr Bob> I can estimate it for you.  What are your average number of emergency admissions per day, the split between medical and surgical, the split between gender, and the average length of stay in each group?

<StE> We have an average of sixty emergency admissions per day, the split between medicine and surgery is 50:50 on average;  the gender split is 50:50 on average and the average LoS in each of those 4 groups is 8 days.  We worked out using these number that we should need 480 beds but even now we have about 540 and even that doesn’t seem to be enough!

<Dr Bob> OK, let me work this out … with those parameters and assuming that the LoS does not change then the Laws of Flow Physics predict that you would need about 25% more beds than 480 – nearer six hundred – to be confident that there will always be a free bed for the next emergency admission in all four categories of  patient.

<StE> What! Our Director of Finance has just fallen off his chair! That can’t be correct!

[pause]

But that is exactly what we are seeing.

[pause]

If we we were able to treated this carvoutosis spatialis … if, just for the sake of argument, we could put any patient into any available bed … what effect would that have?  Would we then only need 480 beds?

<Dr Bob> You would if there was absolutely zero variation of any sort … but that is impossible. If nothing else changed the Laws of Physics predict that you would need about 520 beds.

<StE> What! But we have 540 beds now. Are you saying our whole A&E headache would evaporate just by doing that … and we would still have beds to spare?

<Dr Bob> That would be my prognosis, assuming there are no other factors at play that we have not explored yet.

<StE> Now the Head of Governance has just exploded! This is getting messy! We cannot just abandon the privacy and dignity policy.  But there isn’t much privacy or dignity lying on a trolley in the A&E corridor for hours!  We’re really sorry Dr Bob but we cannot believe you. We need proof.

<Dr Bob> And so would I were I in your position. Would you like to prove it to yourselves?  I have a game you can play that will demonstrate this unavoidable consequence of the Laws of Physics. Would you like to play it?

<StE> We would indeed!

<Dr Bob> OK. Here are the instructions for the game. This is your homework for this week.  See you next week.

St.Elsewhere’s® is a registered trademark of Kate Silvester Ltd,  and to read more real cases of 4-hour A&E pain download Kate’s: The Christmas Crisis

Part 1 is here. Part 2 is here. Part 3 is here. Part 4 is here.

Posted on

A Case of Chronic A&E Pain: Part 4

Dr_Bob_ThumbnailDr Bob runs a Clinic for Sick Systems and is sharing the Case of St Elsewhere’s ® Hospital which is suffering from chronic pain in the A&E department.

Dr Bob is presenting the case study in weekly bite-sized bits that are ample food for thought.

Part 1 is here. Part 2 is here. Part 3 is here.

The story so far:

The history and initial examination of St.Elsewhere’s® Emergency Flow System have revealed the footprint of a Horned Gaussian in their raw A&E data.  That characteristic sign suggests that the underlying disease complex includes one or more forms of carveoutosis.  So that is what Dr Bob and StE will need to explore together.

<Dr Bob> Hello again and how are you feeling since our last conversation?

<StE> Actually, although the A&E pain continues unabated, we feel better. More optimistic. We have followed your advice and have been plotting our daily A&E time-series charts and sharing those with the front-line staff.  And what is interesting to observe is the effect of just doing that.  There are fewer “What you should do!” statements and more “What we could do …” conversations starting to happen – right at the front line.

<Dr Bob> Excellent. That is what usually happens when we switch on the fast feedback loop. I detect that you are already feeling the emotional benefit.  So now we need to explore carveoutosis.  Are you up for that?

<StE> You betcha! 

<Dr Bob> OK. The common pathology in carveoutosis is that we have some form of resource that we, literally, carve up into a larger number of smaller pieces.  It does not matter what the resource is.  It can be time, space, knowledge, skill, cash.  Anything.

<StE> Um, that is a bit abstract.  Can you explain with a real example?

<Dr Bob> OK. I will use the example of temporal carveoutosis.  Do you use email?  And if so what are your frustrations with it … your Niggles?

<StE> Ouch! You poked a tender spot with that question!  Email is one of our biggest sources of frustration.  A relentless influx of dross that needs careful scanning to filter out the important stuff. We waste hours every week on this hamster wheel.  And if we do not clear our Inboxes by close of play on Friday then the following week is even worse!

<Dr Bob> And how many of you put time aside on Friday afternoon to ‘Clear-the-Inbox’?

<StE> We all do. It does at least give us some sense of control amidst the chaos. 

<Dr Bob> OK. This is a perfect example of temporal carveoutosis.  Suppose we consider the extreme case where we only process our emails on a Friday afternoon in a chunk of protected time carved out of our diary.  Now consider the effect of our carved-out-time-policy on the flow of emails. What happens?

<StE> Well, if we all do this then we will only send emails on a Friday afternoon and the person we are sending them to will only read them the following Friday afternoon and if we need a reply we will read that the Friday after.  So the time from sending an email to getting a reply will be two weeks. And it does not make any difference how many emails we send!

<Dr Bob> Yes. That is the effect on the lead-time … but I asked what the effect was on flow?

<StE> Oops! So our answer was correct but that was not the question you asked.  Um, the effect on flow is that it will be very jerky.  Emails will only flow on Friday afternoons … so all the emails for the week will try to flow around in a few hours or minutes.  Ah! That may explain why the email system seems to slow down on Friday afternoons and that only delays the work and adds to our frustration! We naturally assumed it was because the IT department have not invested enough in hardware! Faster computers and bigger mailboxes!

<Dr Bob> What you are seeing is the inevitable and predictable effect of one form of temporal carveoutosis.  The technical name for this is a QBQ time trap and it is an iatrogenic disease. Self-inflicted. (QBQ=queue-batch-queue).

<StE> So if the IT Department actually had the budget, and if they had actually treated the ear-ache we were giving them, and if they had actually invested in faster and bigger computers then the symptom of Friday Snail Mail would go away – but the time trap would remain.  And it might actually reinforce our emails-only-on-a-Friday-afternoon behaviour! Wow! That was not obvious until you forced us to think it through logically.

<Dr Bob> Well. I think that insight is enough to chew over for now. One eureka reaction at a time is enough in my experience. Food for thought requires time to digest.  This week your treatment plan is to share your new insight with the front-line teams.  You can use this example because email Niggles are very common.  And remember … Focus on the Flow.  Repeat that mantra to yourselves until it becomes a little voice in your head that reminds you what to do when you are pricked by the feelings of disappointment, frustration and fear.  Next week …

St.Elsewhere’s® is a registered trademark of Kate Silvester Ltd. And to read more real cases of 4-hour A&E pain download Kate’s: The Christmas Crisis

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A Case of Chronic A&E Pain: Part 3

Dr_Bob_ThumbnailDr Bob runs a Clinic for Sick Systems and is sharing the story of a recent case – a hospital that has presented with chronic pain in their A&E department.

It is a complicated story so Dr Bob is presenting it in bite-sized bits that only require a few minutes to read. Part 1 is here. Part 2 is here.

To summarise the case history so far:

The patient is St.Elsewhere’s® Hospital, a medium sized district general hospital situated in mid-England. StE has a type-1 A&E Department that receives about 200 A&E arrivals per day which is rather average. StE is suffering with chronic pain – specifically the emotional, operational, cultural and financial pain caused by failing their 4-hour A&E target. Their Paymasters and Inspectors have the thumbscrews on, and each quarter … when StE publish their performance report that shows they have failed their A&E target (again) … the thumbscrews are tightened a few more clicks. Arrrrrrrrrrrrgh.

Dr Bob has discovered that StE routinely collect data on when individual patients arrive in A&E and when they depart, and that they use this information for three purposes:
1) To calculate their daily and quarterly 4-hour target failure rate.
2) To create action plans that they believe will eliminate their pain-of-failure.
3) To expedite patients who are approaching the 4-hour target – because that eases the pain.

But the action plans do not appear to have worked and, despite their heroic expeditionary effort, the chronic pain is getting worse. StE is desperate and has finally accepted that it needs help. The Board are worried that they might not survive the coming winter storm and when they hear whispers of P45s being armed and aimed by the P&I then they are finally scared enough to seek professional advice. So they Choose&Book an urgent appointment at Dr Bob’s clinic … and they want a solution yesterday … but they fear the worst. They fear discovering that there is no solution!

The Board, the operational managers and the senior clinicians feel like they are between a rock and a hard place.  If Dr Bob’s diagnosis is ‘terminal’ then they cannot avert the launch of the P45’s and it is Game Over for the Board and probably for StE as well.  And if Dr Bob’s diagnosis is ‘treatable’ then they cannot avert accepting the painful exposure of their past and present ineptitude – particularly if the prescribed humble pie is swallowed and has the desired effect of curing the A&E pain.

So whatever the diagnosis they appear to have an uncomfortable choice: leave or learn?

Dr Bob has been looking at the A&E data for one typical week that StE have shared.

And Dr Bob knows what to look for … the footprint of a dangerous yet elusive disease. A characteristic sign that doctors have a name for … a pathognomic sign.

Dr Bob is looking for the Horned Gaussian … and has found it!

So now Dr Bob has to deliver the bittersweet news to the patient.

<Dr Bob> Hello again. Please sit down and make yourselves comfortable. As you know I have been doing some tests on the A&E data that you shared.  I have the results of those tests and I need to be completely candid with you. There is good news and there is not-so-good news.

[pause]

Would you like to hear this news and if so … in what order?

<StE> Oh dear. We were hoping there was only good news so perhaps we should start there.

<Dr Bob> OK.  The good news is that you appear to be suffering from a treatable disease. The data shows the unmistakable footprint of a Horned Gaussian.

<StE> Phew! Thank the Stars! That is what we had hoped and prayed for! Thank you so much. You cannot imagine how much better we feel already.  But what is the not-so-good news?

<Dr Bob> The not-so-good news is that the disease is iatrogenic which is medical jargon for self-inflicted.  And I appreciate that you did not do this knowingly so you should not feel guilt or blame for doing things that you did not know are self-defeating.

[pause]

And in order to treat this disease we have to treat the root cause and that implies you have a simple choice to make.

<StE> Actually, what you are saying does not come as a surprise. We have sensed for some time that there was something that we did not really understand but we have been so consumed by fighting-the-fire that we have prevaricated in grasping that nettle.  And we think we know what the choice is: to leave or to learn. Continuing as we are is no longer an option.

<Dr Bob> You are correct.  That is the choice.

StE confers and unanimously choose to take the more courageous path … they choose to learn.

<StE> We choose to learn. Can we start immediately? Can you teach us about the Horned Gaussian?

<Dr Bob> Of course, but before that we need to understand what a Gaussian is.

Suppose we have some very special sixty-sided dice with faces numbered 1 to 59, and suppose we toss six of them and wait until they come to rest. Then suppose we count up the total score on the topmost facet of each die … and then suppose we write that total down. And suppose we do this 1500 times and then calculate the average total score. What do you suppose the average would be … approximately?

<StE> Well … the score on each die can be between 1 and 59 and each number is equally likely to happen … so the average score for 1500 throws of one die will be about 30 … so the average score for six of these mega-dice will be about 180.

<Dr Bob> Excellent. And how will the total score vary from throw to throw?

<StE> H’mm … tricky.  We know that it will vary but our intuition does not tell us by how much.

<Dr Bob> I agree. It is not intuitively obvious at all. We sense that the further away from 180 we look the less likely we are to find that score in our set of 1500 totals but that is about as close as our intuition can take us.  So we need to do an empirical experiment and we can do that easily with a spreadsheet. I have run this experiment and this is what I found …

Sixty_Sided_Dice_GameNotice that there is rather a wide spread around our expected average of 180 and remember that this is just tossing a handful of sixty-sided dice … so this variation is random … it is inherent and expected and we have no influence over it. Notice too that on the left the distribution of the scores is plotted as a histogram … the blue line. Notice the symmetrical hump-like shape … this is the footprint of a Gaussian.

<StE> So what? This is a bit abstract and theoretical for us. How does it help us?

<Dr Bob> Please bear with me a little longer. I have also plotted the time that each of your patients were in A&E last week on the same sort of chart. What do you notice?

StE_A&E_Actual

<StE> H’mm. This is very odd. It looks like someone has taken a blunt razor to the data … they fluffed the first bit but sharpened up their act for the rest of it. And the histogram looks a bit like the one on your chart, well the lower half does, then there is a big spike. Is that the Horned thingamy?

<Dr Bob> Yes. This is the footprint of a Horned Gaussian. What this picture of your data says is that something is distorting the natural behaviour of your A&E system and that something is cutting in at 240 minutes. Four hours.

<StE> Wait a minute! That is exactly what we do. We admit patients who are getting close to the 4-hour target to stop the A&E clock and reduce the pain of 4-hour failure.  But we can only admit as many as we have space for … and sometimes we run out of space.  That happened last Monday evening. The whole of StE hospital was gridlocked and we had no option but to store the A&E patients in the corridors – some for more than 12 hours! Just as the chart shows.

<Dr Bob> And by distorting your natural system behaviour in this way you are also distorting the data.  Your 4-hour breach rate is actually a lot lower that it would otherwise be … until the system gridlocks then it goes through the roof.  This design is unstable and unsafe.

[pause]

Are Mondays always like this?

<StE> Usually, yes. Tuesday feels less painful and the agony eases up to Friday then it builds up again.  It is worse than Groundhog Day … it is more like Groundhog Week!  The chaos and firefighting is continuous though, particularly in the late afternoon and evenings.      

<Dr Bob> So now we are gaining some understanding.  The uncomfortable discovery when we look in the mirror is that: part of the cause is our own policies that create the symptoms and obscure the disease. We have looked in the mirror and “we have seen the enemy and the enemy is us“. This is an iatrogenic disease and in my experience a common root cause is something called carveoutosis.  Understanding the pathogenesis of carveoutosis is the path to understanding what is needed to treat it.  Are you up for that?

<StE> You bet we are!

<Dr Bob> OK. First we need to establish a new habit. You need to start plotting your A&E data just like this. Every day. Every week. Forever. This is your primary feedback loop. This chart will tell you when real improvement is happening. Your quarterly average 4-hour breach percentage will not. The Paymasters, Inspectors and Government will still ask for that quarterly aggregated target failure data but you will use these diagnostic and prognostic system behaviour charts for all your internal diagnosis, decisions and actions.  And next week we will explore carveoutosis … 

St.Elsewhere’s® is a registered trademark of Kate Silvester Ltd.
And to read more real cases of 4-hour pain download Kate’s: The Christmas Crisis

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A Case of Chronic A&E Pain: Part 2

Dr_Bob_ThumbnailHello, Dr Bob here.

This week we will continue to explore the Case of Chronic Pain in the A&E Department of St.Elsewhere’s Hospital.

Last week we started by ‘taking a history’.  We asked about symptoms and we asked about the time patterns and associations of those symptoms. The subjective stuff.

And as we studied the pattern of symptoms a list of plausible diagnoses started to form … with chronic carveoutosis as a hot contender.

Carveoutosis is a group of related system diseases that have a common theme. So if we find objective evidence of carveoutosis then we will talk about it … but for now we need to keep an open mind.

The next step is to ‘examine the patient’ – which means that we use the pattern of symptoms to focus our attention on seeking objective signs that will help us to prune our differential diagnosis.

But first we need to be clear what the pain actually is. We need a more detailed description.

<Dr Bob> Can you explain to me what the ‘4-hour target’ is?

<StE> Of course. When a new patient arrives at our A&E Department we start a clock for that patient, and when the patient leaves we stop their clock.  Then we work out how long they were in the A&E Department and we count the number that were longer than 4-hours for each day.  Then we divide this number by the number of patients who arrived that day to give us a percentage: a 4-hour target failure rate. Then we average those daily rates over three months to give us our Quarterly 4-hour A&E Target Performance; one of the Key Performance Indicators (KPIs) that are written into our contract and which we are required to send to our Paymasters and Inspectors.  If that is more than 5% we are in breach of our contract and we get into big trouble, if it is less than 5% we get left alone. Or to be more precise the Board get into big trouble and they share the pain with us.

<Dr Bob> That is much clearer now.  Do you know how many new patients arrive in A&E each day, on average.

<StE> About two hundred, but it varies quite a lot from day-to-day.

Dr Bob does a quick calculation … about 200 patients for 3 months is about 18,000 pieces of data on how long the patients were in the A&E Department …  a treasure trove of information that could help to diagnose the root cause of the chronic 4-hour target pain.  And all this data is boiled down into a binary answer to the one question in their quarterly KPI report:

Q: Did you fail the 4-hour A&E target this quarter? [Yes] [No]       

That implies that more than 99.99% of the available information is not used.

Which is like driving on a mountain road at night with your lights on but your eyes closed! Dangerous and scary!

Dr Bob now has a further addition to his list of diagnoses: amaurosis agnosias which roughly translated means ‘turning a blind eye’.

<Dr Bob> Can I ask how you use this clock information in your minute-to-minute management of patients?

<StE> Well for the first three hours we do not use it … we just get on with managing the patients.  Some are higher priority and more complicated than others, we call them Majors and we put them in the Majors Area. Some are lower priority and easier so we call them Minors and we put them in the Minors Area. Our doctors and nurses then run around looking after the highest clinical priority patients first … for obvious reasons. However, as a patient’s clock starts to get closer to 4-hours then that takes priority and those patients start to leapfrog up the queue of who to see next.  We have found that this is an easy and effective way to improve our 4-hour performance. It can make the difference between passing or failing a quarter and reducing our referred pain! To assist us implement the Leapfrog Policy our Board have invested in some impressive digital technology … a huge computer monitor on the wall that shows exactly who is closest to the 4-hour target.  This makes it much easier for us to see which patients needs to be leapfrogged for decision and action.

<Dr Bob>  Do you, by any chance, keep any of the individual patient clock data?

<StE> Yes, we have to do that because we are required to complete a report each week for the causes of 4-hour failures and we also have to submit an Action Plan for how we will eliminate them.  So we keep the data and then spend hours going back through the thousands of A&E cards to identify what we think are the causes of the delays. There are lots of causes and many patients are affected by more than one; and there does not appear to be any clear pattern … other than ‘too busy’. So our action plan is the same each week … write yet another business case asking for more staff and for more space. 

<Dr Bob> Could you send me some of that raw clock data?  Anonymous of course. I just need the arrival date and time and the departure date and time for an average week.

<StE> Yes of course – we will send the data from last week – there were about 1500 patients.

Dr Bob now has all the information needed to explore the hunch that the A&E Department is being regularly mauled by a data mower … one that makes the A&E performance look better … on paper … and that obscures the actual problem.

Just like treating a patient’s symptoms and making their underlying disease harder to diagnose and therefore harder to cure.

To be continued … here

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A Case of Chronic A&E Pain: Part 1

 

Dr_Bob_Thumbnail

The blog last week seems to have caused a bit of a stir … so this week we will continue on the same theme.

I’m Dr Bob and I am a hospital doctor: I help to improve the health of poorly hospitals.

And I do that using the Science of Improvement – which is the same as all sciences, there is a method to it.

Over the next few weeks I will outline, in broad terms, how this is done in practice.

And I will use the example of a hospital presenting with pain in their A&E department.  We will call it St.Elsewhere’s ® Hospital … a fictional name for a real patient.

It is a while since I learned science at school … so I thought a bit of a self-refresher would be in order … just to check that nothing fundamental has changed.

Science_Sequence

This is what I found on page 2 of a current GCSE chemistry textbook.

Note carefully that the process starts with observations; hypotheses come after that; then predictions and finally designing experiments to test them.

The scientific process starts with study.

Which is reassuring because when helping a poorly patient or a poorly hospital that is exactly where we start.

So, first we need to know the symptoms; only then can we start to suggest some hypotheses for what might be causing those symptoms – a differential diagnosis; and then we look for more specific and objective symptoms and signs of those hypothetical causes.

<Dr Bob> What is the presenting symptom?

<StE> “Pain in the A&E Department … or more specifically the pain is being felt by the Executive Department who attribute the source to the A&E Department.  Their pain is that of 4-hour target failure.“

<Dr Bob> Are there any other associated symptoms?

<StE> “Yes, a whole constellation.  Complaints from patients and relatives; low staff morale, high staff turnover, high staff sickness, difficulty recruiting new staff, and escalating locum and agency costs. The list is endless.”

<Dr Bob> How long have these symptoms been present?

<StE> “As long as we can remember.”

<Dr Bob> Are the symptoms staying the same, getting worse or getting better?

<StE> “Getting worse. It is worse in the winter and each winter is worse than the last.”

<Dr Bob> And what have you tried to relieve the pain?

<StE> “We have tried everything and anything – business process re-engineering, balanced scorecards, Lean, Six Sigma, True North, Blue Oceans, Golden Hours, Perfect Weeks, Quality Champions, performance management, pleading, podcasts, huddles, cuddles, sticks, carrots, blogs  and even begging. You name it we’ve tried it! The current recommended treatment is to create a swarm of specialist short-stay assessment units – medical, surgical, trauma, elderly, frail elderly just to name a few.” 

<Dr Bob> And how effective have these been?

<StE> “Well some seemed to have limited and temporary success but nothing very spectacular or sustained … and the complexity and cost of our processes just seem to go up and up with each new initiative. It is no surprise that everyone is change weary and cynical.”

The pattern of symptoms is that of a chronic (longstanding) illness that has seasonal variation, which is getting worse over time and the usual remedies are not working.

And it is obvious that we do not have a clear diagnosis; or know if our unclear diagnosis is incorrect; or know if we are actually dealing with an incurable disease.

So first we need to focus on establishing the diagnosis.

And Dr Bob is already drawing up a list of likely candidates … with carveoutosis at the top.

<Dr Bob> Do you have any data on the 4-hour target pain?  Do you measure it?

<StE> “We are awash with data! I can send the quarterly breach performance data for the last ten years!”

<Dr Bob> Excellent, that will be useful as it should confirm that this is a chronic and worsening problem but it does not help establish a diagnosis.  What we need is more recent, daily data. Just the last six months should be enough. Do you have that?

<StE> “Yes, that is how we calculate the quarterly average that we are performance managed on. Here is the spreadsheet. We are ‘required’ to have fewer than 5% 4-hour breaches on average. Or else.”

This is where Dr Bob needs some diagnostic tools.  He needs to see the pain scores presented as  picture … so he can see the pattern over time … because it is a very effective way to generate plausible causal hypotheses.

Dr Bob can do this on paper, or with an Excel spreadsheet, or use a tool specifically designed for the job. He selects his trusted visualisation tool : BaseLine©.

StE_4hr_Pain_Chart

<Dr Bob> This is your A&E pain data plotted as a time-series chart.  At first glance it looks very chaotic … that is shown by the wide and flat histogram. Is that how it feels?

<StE> “That is exactly how it feels … earlier in the year it was unremitting pain and now we have a constant background ache with sharp, severe, unpredictable stabbing pains on top. I’m not sure what is worse!

<Dr Bob> We will need to dig a bit deeper to find the root cause of this chronic pain … we need to identify the diagnosis or diagnoses … and your daily pain data should offer us some clues.

StE_4hr_Pain_Chart_RG_DoWSo I have plotted your data in a different way … grouping by day of the week … and this shows there is a weekly pattern to your pain. It looks worse on Mondays and least bad on Fridays.  Is that your experience?

<StE> “Yes, the beginning of the week is definitely worse … because it is like a perfect storm … more people referred by their GPs on Mondays and the hospital is already full with the weekend backlog of delayed discharges so there are rarely beds to admit new patients into until late in the day. So they wait in A&E.  

Dr Bob’s differential diagnosis is firming up … he still suspects acute-on-chronic carveoutosis as the primary cause but he now has identified an additional complication … Forrester’s Syndrome.

And Dr Bob suspects an unmentioned problem … that the patient has been traumatised by a blunt datamower!

So that is the evidence we will look for next … here

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The Five-day versus Seven-day Bun-Fight

Dr_Bob_ThumbnailThere is a big bun-fight kicking off on the topic of 7-day working in the NHS.

The evidence is that there is a statistical association between mortality in hospital of emergency admissions and day of the week: and weekends are more dangerous.

There are fewer staff working at weekends in hospitals than during the week … and delays and avoidable errors increase … so risk of harm increases.

The evidence also shows that significantly fewer patients are discharged at weekends.

So the ‘obvious’ solution is to have more staff on duty at weekends … which will cost more money.

Simple, obvious, linear and wrong.  Our intuition has tricked us … again!

Let us unravel this Gordian Knot with a bit of flow science and a thought experiment.

1. The evidence shows that there are fewer discharges at weekends … and so demonstrates lack of discharge flow-capacity. A discharge process is not a single step, there are many things that must flow in sync for a discharge to happen … and if any one of them is missing or delayed then the discharge does not happen or is delayed.  The weakest link effect.

2. The evidence shows that the number of unplanned admissions varies rather less across the week; which makes sense because they are unplanned.

3. So add those two together and at weekends we see hospitals filling up with unplanned admissions – not because the sick ones are arriving faster – but because the well ones are leaving slower.

4. The effect of this is that at weekends the queue of people in beds gets bigger … and they need looking after … which requires people and time and money.

5. So the number of staffed beds in a hospital must be enough to hold the biggest queue – not the average or some fudged version of the average like a 95th percentile.

6. So a hospital running a 5-day model needs more beds because there will be more variation in bed use and we do not want to run out of beds and delay the admission of the newest and sickest patients. The ones at most risk.

7. People do not get sicker because there is better availability of healthcare services – but saying we need to add more unplanned care flow capacity at weekends implies that it does.  What is actually required is that the same amount of flow-resource that is currently available Mon-Fri is spread out Mon-Sun. The flow-capacity is designed to match the customer demand – not the convenience of the supplier.  And that means for all parts of the system required for unplanned patients to flow.  What, where and when. It costs the same.

8. Then what happens is that the variation in the maximum size of the queue of patients in the hospital will fall and empty beds will appear – as if by magic.  Empty beds that ensure there is always one for a new, sick, unplanned admission on any day of the week.

9. And empty beds that are never used … do not need to be staffed … so there is a quick way to reduce expensive agency staff costs.

So with a comprehensive 7-day flow-capacity model the system actually gets safer, less chaotic, higher quality and less expensive. All at the same time. Safety-Flow-Quality-Productivity.

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What is Productivity?

It was the time for Bob and Leslie’s regular coaching session. Dr_Bob_ThumbnailBob was already on line when Leslie dialed in to the teleconference.

<Leslie> Hi Bob, sorry I am a bit late.

<Bob> No problem Leslie. What aspect of improvement science shall we explore today?

<Leslie> Well, I’ve been working through the Safety-Flow-Quality-Productivity cycle in my project and everything is going really well.  The team are really starting to put the bits of the jigsaw together and can see how the synergy works.

<Bob> Excellent. And I assume they can see the sources of antagonism too.

<Leslie> Yes, indeed! I am now up to the point of considering productivity and I know it was introduced at the end of the Foundation course but only very briefly.

<Bob> Yes,  productivity was described as a system metric. A ratio of a steam metric and a stage metric … what we get out of the streams divided by what we put into the stages.  That is a very generic definition.

<Leslie> Yes, and that I think is my problem. It is too generic and I get it confused with concepts like efficiency.  Are they the same thing?

<Bob> A very good question and the short answer is “No”, but we need to explore that in more depth.  Many people confuse efficiency and productivity and I believe that is because we learn the meaning of words from the context that we see them used in. If  others use the words imprecisely then it generates discussion, antagonism and confusion and we are left with the impression of that it is a ‘difficult’ subject.  The reality is that it is not difficult when we use the words in a valid way.

<Leslie> OK. That reassures me a bit … so what is the definition of efficiency?

<Bob> Efficiency is measure of wasted resource – it is the ratio of the minimum cost of the resources required to complete one task divided by the actual cost of the resources used to complete one task.

<Leslie> Um.  OK … so how does time come into that?

<Bob> Cost is a generic concept … it can refer to time, money and lots of other things.  If we stick to time and money then we know that if we have to employ ‘people’ then time will cost money because people need money to buy essential stuff that the need for survival. Water, food, clothes, shelter and so on.

<Leslie> So, we could use efficiency in terms of resource-time required to complete a task?

<Bob> Yes. That is a very useful way of looking at it.

<Leslie> So, how is productivity different? Completed tasks out divided by the cash in to pay for resource time would be a productivity metric. It looks the same.

<Bob> Does it?  The definition of efficiency is possible cost divided by actual cost. It is not the same as our definition of system productivity.

<Leslie> Ah yes, I see. So do others define productivity the same way?

<Bob> Let us try looking it up on Wikipedia …

<Leslie> OK … here we go …

“Productivity is an average measure of the efficiency of production. It can be expressed as the ratio of output to inputs used in the production process, i.e. output per unit of input”.

Now that is really confusing!  It looks like efficiency and productivity are the same. Let me see what the Wikipedia definition of efficiency is …

“Efficiency is the (often measurable) ability to avoid wasting materials, energy, efforts, money, and time in doing something or in producing a desired result”.

But that is closer to your definition of efficiency – the actual cost is the minimum cost plus the cost of waste.

<Bob> Yes.  I think you are starting to see where the confusion arises.  And this is because there is a critical piece of the jigsaw missing.

<Leslie> Oh …. and what is that?

<Bob> Worth.

<Leslie> Eh?

<Bob> Efficiency has nothing to do with whether the output of the stream has any worth.  I can produce a worthless product very efficiently.  And what if we have the situation where the output of my process is actually harmful.  The more efficiently I use my resources the more harm I will cause from a fixed amount of resource … and in that situation it is actually safer to have an inefficient process!

<Leslie> Wow!  That really hits the nail on the head … and the implications are … um … profound.  Efficiency is objective and relates only to flow … and between flow and productivity we have to cross the Safety-Quality line.  Productivity also includes the subjective concept of worth or value. That all makes complete sense now. A productive system is a subjectively and objectively win-win-win design.

<Bob> Yup.  Get the safety, flow and quality perspectives of the design in synergy and productivity will sky-rocket. It is called a Fit-4-Purpose design that creates a Value-4-Money product or service

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V.U.T.

figure_pointing_out_chart_data_150_wht_8005It was the appointed time for the ISP coaching session and both Bob and Leslie were logged on and chatting about their Easter breaks.

<Bob> OK Leslie, I suppose we had better do some actual work, which seems a shame on such a wonderful spring day.

<Leslie> Yes, I suppose so. There is actually something I would like to ask you about because I came across it by accident and it looked very pertinent to flow design … but you have never mentioned it.

<Bob> That sounds interesting. What is it?

<Leslie> V.U.T.

<Bob> Ah ha!  You have stumbled across the Queue Theorists and the Factory Physicists.  So, what was your take on it?

<Leslie> Well it all sounded very impressive. The context is I was having a chat with a colleague who is also getting into the improvement stuff and who had been to a course called “Factory Physics for Managers” – and he came away buzzing about the VUT equation … and claimed that it explained everything!

<Bob> OK. So what did you do next?

<Leslie> I looked it up of course and I have to say the more I read the more confused I got. Maybe I am just a bid dim and not up to understanding this stuff.

<Bob> Well you are certainly not dim so your confusion must be caused by something else. Did your colleague describe how the VUT equation is applied in practice?

<Leslie> Um. No, I do not remember him describing an example – just that it explained why we cannot expect to run resources at 100% utilisation.

<Bob> Well he is correct on that point … though there is a bit more to it than that.  A more accurate statement is “We cannot expect our system to be stable if there is variation and we run flow-resources at 100% utilisation”.

<Leslie> Well that sounds just like the sort of thing we have been talking about, what you call “resilient design”, so what is the problem with the VUT equation?

<Bob> The problem is that it gives an estimate of the average waiting time in a very simple system called a G/G/1 system.

<Leslie> Eh? What is a G/G/1 system?

<Bob> Arrgh … this is the can of queue theory worms that I was hoping to avoid … but as you brought it up let us grasp the nettle.  This is called Kendall’s Notation and it is a short cut notation for describing the system design. The first letter refers to the arrivals or demand and G means a general distribution of arrival times; the second G refers to the size of the jobs or the cycle time and again the distribution is general; and the last number refers to the number of parallel resources pulling from the queue.

<Leslie> OK, so that is a single queue feeding into a single resource … the simplest possible flow system.

<Bob> Yes. But that isn’t the problem.  The problem is that the VUT equation gives an approximation to the average waiting time. It tells us nothing about the variation in the waiting time.

<Leslie> Ah I see. So it tells us nothing about the variation in the size of the queue either … so does not help us plan the required space-capacity to hold the varying queue.

<Bob> Precisely.  There is another problem too.  The ‘U’ term in the VUT equation refers to utilisation of the resource … denoted by the symbol ? or rho.  The actual term is ? / (1-?) … so what happens when rho approaches one … or in practical terms the average utilisation of the resource approaches 100%?

<Leslie> Um … 1 divided by (1-1) is 1 divided by zero which is … infinity!  The average waiting time becomes infinitely long!

<Bob> Yes, but only if we wait forever – in reality we cannot and anyway – reality is always changing … we live in a dynamic, ever-changing, unstable system called Reality. The VUT equation may be academically appealing but in practice it is almost useless.

<Leslie> Ah ha! Now I see why you never mentioned it. So how do we design for resilience in practice? How do we get a handle on the behaviour of even the G/G/1 system over time?

<Bob> We use an Excel spreadsheet to simulate our G/G/1 system and we find a fit-for-purpose design using an empirical, experimental approach. It is actually quite straightforward and does not require any Queue Theory or VUT equations … just a bit of basic Excel know-how.

<Leslie> Phew!  That sounds more up my street. I would like to see an example.

<Bob> Welcome to the first exercise in ISP-2 (Flow).

Posted on

Co-Labor-Ation

Dr_Bob_ThumbnailBob and Leslie were already into the dialogue of their regular ISP coaching session when Bob saw an incoming text from one of his other ISPees. It was simply marked: “Very Urgent”.

<Bob> Leslie, I have just received an urgent SMS that I think I need to investigate immediately. Could we put this conversation on ice for 10 minutes and I will call you back?

<Leslie> Of course. I have lots to do. Please do not rush back if it requires more time.

<Bob> Thank you.

Ten minutes later Leslie saw that Bob was phoning and picked up.

<Leslie> Hi Bob.  I hope you were able to sort out the urgent problem. The fact that you are back suggests you did.

<Bob> Hi Leslie.  Thank you for your understanding and patience. The issue was urgent and the root cause is not yet solved, but lessons are being learned.  And this is one you are going to come up against too so it may be an opportune time to explore it.

<Leslie> H’mm. Now you have pricked my curiosity. But you can’t discuss someone else’s problem with me surely!

<Bob> No indeed.  Strict confidentiality is essential.  We can talk about the generic issue though, without disclosing any details.  Do you remember that project you were doing last year where you achieved an initial success and then it all seemed to go wobbly?

<Leslie> Yes. At the time you said that I needed to put that one on the shelf and to press on with other projects. I think the phrase you used was “it needs to stew for a while“.

<Bob> And what happened?

<Leslie> The hard won improvement in performance slipped back and I felt like a failure and started to lose confidence. You said not to blame myself but to learn and  move on.  The lesson was I did not appreciate the difference between circles of control and circles of influence. I was trying to influence others before I had mastered self-control.

<Bob> Yes. There was another factor too but I did not feel it was the time to explore it. Now feels like a better time.

<Leslie> OK … now my curiosity is really fired up.

<Bob> Do you remember last week’s blog about the Improvement Gearbox?

<Leslie> Yes. I really liked the mechanical metaphor.  It resonated with so many things. I have used it several times this week in conversations.

<Bob> Well, there is a close relationship between the level of challenge and the gearbox.  As complexity increases we need to be able to use more of the gears, and to change up and down with ease and according to need.

<Leslie> Change down? I sort of assumed that once you got to fourth gear you stay there.

<Bob> That is true if the terrain is level and everyone is on board the bus with the same destination in mind.  In reality the terrain goes up and down and as we learn we need to stop and let some people get off and take others on board.

<Leslie> So we need to change down gears on the uphill bits, change up gears on the downhill, and go through the whole gear sequence when we deliberately slow to a halt, and then get on our way again.

<Bob> Yes. Well put. The world is changing all the time and the team on board is in dynamic flux. Some arrive, some leave and others stay on the bus but change seats as we move along.  Not all seats suit all people. What is comfortable for one may be painful for another.

<Leslie> So how come the urgent call?

<Bob> A fight had broken out on their bus, the tribes were arguing because the improvements they have made have blown away some of the fog and exposed some deeper cultural cracks. Cracks that had been there all the time but were concealed by the fog of the daily chaos and the smoke of the burning martyrs. They had taken their eye off the road and were heading for a blind bend unaware of what was around the corner.

<Leslie> So your intervention was to shout “Pay attention to the road and make a decision … steer or stop!“

<Bob> Yes, that about sums it up.  A co-labor-ation call.

<Leslie> Eh? Dis you just say collaboration in a weird way?

<Bob> Yes. I chopped it up into concepts … “co” means together, “labor” means work and “ation” means action or process.  If they do not learn to co-labor-ate then they will come off the road, crash, and burn. And join the graveyard of improvement train wrecks that litter the verges of the rocky road of change.

<Leslie> Fourth gear stuff?

<Bob> Whole gearbox stuff. All gears between first and fourth because they are all necessary at different times.  Each gear builds on those which go before. There are no good or bad gears just fit-for-current-purpose or not.  Bad driving is ineptitude. Not using the vehicle’s gearbox effectively and efficiently and risking the safety and comfort of the passengers and other road users. Poor leadership is analogous to poor driving. Dangerous.

<Leslie> So an effective leader of change needs to be able to use all the gears competently and to know when to use which and when to change. And in doing so demonstrate what a safe pair of leadership hands looks like and what it can achieve … through collaborative effort.

<Bob> Perfect!  It is time for you to tear up your L plates.

Posted on

Cumulative Sum

Dr_Bob_Thumbnail[Bing] Bob logged in for the weekly Webex coaching session. Leslie was not yet on line, but joined a few minutes later.

<Leslie> Hi Bob, sorry I am a bit late, I have been grappling with a data analysis problem and did not notice the time.

<Bob> Hi Leslie. Sounds interesting. Would you like to talk about that?

<Leslie> Yes please! It has been driving me nuts!

<Bob> OK. Some context first please.

<Leslie> Right, yes. The context is an improvement-by-design assignment with a primary care team who are looking at ways to reduce the unplanned admissions for elderly patients by 10%.

<Bob> OK. Why 10%?

<Leslie> Because they said that would be an operationally very significant reduction.  Most of their unplanned admissions, and therefore costs for admissions, are in that age group.  They feel that some admissions are avoidable with better primary care support and a 10% reduction would make their investment of time and effort worthwhile.

<Bob> OK. That makes complete sense. Setting a new design specification is OK.  I assume they have some baseline flow data.

<Leslie> Yes. We have historical weekly unplanned admissions data for two years. It looks stable, though rather variable on a week-by-week basis.

<Bob> So has the design change been made?

<Leslie> Yes, over three months ago – so I expected to be able to see something by now but there are no red flags on the XmR chart of weekly admissions. No change.  They are adamant that they are making a difference, particularly in reducing re-admissions.  I do not want to disappoint them by saying that all their hard work has made no difference!

<Bob> OK Leslie. Let us approach this rationally.  What are the possible causes that the weekly admissions chart is not signalling a change?

<Leslie> If there has not been a change in admissions. This could be because they have indeed reduced readmissions but new admissions have gone up and is masking the effect.

<Bob> Yes. That is possible. Any other ideas?

<Leslie> That their intervention has made no difference to re-admissions and their data is erroneous … or worse still … fabricated!

<Bob> Yes. That is possible too. Any other ideas?

<Leslie> Um. No. I cannot think of any.

<Bob> What about the idea that the XmR chart is not showing a change that is actually there?

<Leslie> You mean a false negative? That the sensitivity of the XmR chart is limited? How can that be? I thought these charts will always signal a significant shift.

<Bob> It depends on the degree of shift and the amount of variation. The more variation there is the harder it is to detect a small shift.  In a conventional statistical test we would just use bigger samples, but that does not work with an XmR chart because the run tests are all fixed length. Pre-defined sample sizes.

<Leslie> So that means we can miss small but significant changes and come to the wrong conclusion that our change has had no effect! Isn’t that called a Type 2 error?

<Bob> Yes, it is. And we need to be aware of the limitations of the analysis tool we are using. So, now you know that how might you get around the problem?

<Leslie> One way would be to aggregate the data over a longer time period before plotting on the chart … we know that will reduce the sample variation.

<Bob> Yes. That would work … but what is the downside?

<Leslie> That we have to wait a lot longer to show a change, or not. We do not want that.

<Bob> I agree. So what we do is we use a chart that is much more sensitive to small shifts of the mean.  And that is called a cusum chart. These were not invented until 30 years after Shewhart first described his time-series chart.  To give you an example, do you recall that the work-in-progress chart is much more sensitive to changes in flow than either demand or activity charts?

<Leslie> Yes, and the WIP chart also reacts immediately if either demand or activity change. It is the one I always look at first.

<Bob> That is because a WIP chart is actually a cusum chart. It is the cumulative sum of the difference between demand and activity.

<Leslie> OK! That makes sense. So how do I create and use a cusum chart?

<Bob> I have just emailed you some instructions and a few examples. You can try with your unplanned admissions data. It should only take a few minutes. I will get a cup of tea and a chocolate Hobnob while I wait.

[Five minutes later]

<Leslie> Wow! That is just brilliant!  I can see clearly on the cusum chart when the shifts happened and when I split the XmR chart at those points the underlying changes become clear and measurable. The team did indeed achieve a 10% reduction in admissions just as they claimed they had.  And I checked with a statistical test which confirmed that it is statistically significant.

<Bob> Good work.  Cusum charts take a bit of getting used to and we have be careful about the metric we are plotting and a few other things but it is a useful trick to have up our sleeves for situations like this.

<Leslie> Thanks Bob. I will bear that in mind.  Now I just need to work out how to explain cusum charts to others! I do not want to be accused of using statistical smoke-and-mirrors! I think a golf metaphor may work with the GPs.

Posted on

Learning Loops

campfire_burning_150_wht_174[Beep Beep] Bob’s phone reminded him that it was time for the remote coaching session with Leslie, one of the CHIPs (community of healthcare improvement science practitioners). He flipped open his laptop and logged in. Leslie was already there.

<Leslie> Hi Bob.  I hope you had a good Xmas.

<Bob> Thank you Leslie. Yes, I did. I was about to ask the same question.

<Leslie> Not so good here I am afraid to say. The whole urgent care system is in meltdown. The hospital is gridlocked, the 4-hour target performance has crashed like the Stock Market on Black Wednesday, emergency admissions have spilled over into the Day Surgery Unit, hundreds of operations have been cancelled, waiting lists are spiralling upwards and the fragile 18-week performance ceiling has been smashed. It is chaos. Dangerous chaos.

<Bob> Oh dear. It sounds as if the butterfly has flapped its wings. Do you remember seeing this pattern of behaviour before?

<Leslie> Sadly yes. When I saw you demonstrate the Save the NHS Game.  This is exactly the chaos I created when I attempted to solve the 4-hour target problem, and the chaos I have seen every doctor, manager and executive create when they do too. We seem to be the root cause!

<Bob> Please do not be too hard on yourself Leslie. I am no different. I had to realise that I was contributing to the chaos I was complaining about, by complaining about it. Paradoxically not complaining about it made no difference. My error was one of omission. I was not learning. I was stuck in a self-justifying delusional blame-bubble of my own making. My humility and curiosity disabled by my disappointment, frustration and anxiety. My inner chimp was running the show!

<Leslie> Wow! That is just how everyone is feeling and behaving. Including me. So how did you escape from the blame-bubble?

<Bob> Well first of all I haven’t completely escaped. I just spend less time there. It is always possible to get sucked back in. The way out started to appear when I installed a “learning loop”.

<Leslie> A what? Is that  like a hearing loop for the partially deaf?

<Bob> Ha! Yes! A very apt metaphor.  Yes, just like that. Very good. I will borrow that if I may.

<Leslie> So what did your learning loop consist of?

<Bob> A journal.  I started a journal. I invested a few minutes each day reflecting and writing it down. The first entries were short and rather “ranty”. I cannot possibly share them in public. It is too embarrassing. But it was therapeutic and over time the anger subsided and a quieter, calmer inner voice could be heard. The voice of curiosity. It was asking one question over and over again. “How?” … not “Why?”.

<Leslie> Like “How did I get myself into this state?“

<Bob> Exactly so.  And also “How come I cannot get myself out of this mess?“

<Leslie> And what happened next?

<Bob> I started to take more notice of things that I had discounted before. Apparently insignificant things that I discovered had profound implications. Like the “butterflies wing” effect … I discovered that small changes can have big effects.  I also learned to tune in to specific feelings because they were my warning signals.

<Leslie> Niggles you mean?

<Bob> Yes. Niggles are flashes of negative emotion that signal a design flaw. They are usually followed by an untested assumption, an invalid conclusion, an unwise decision and a counter-productive action. It all happens unconsciously and very fast so we are only aware of the final action – the MR ANGRY reply to the email that we stupidly broadcast via the Reply All button!

<Leslie> So you learned to tune into the niggle to avoid the chain reaction that led to hitting the Red Button.

<Bob> Sort of. What actually happened is that the passion unleashed by the niggle got redirected into a more constructive channel – via my Curiosity Centre to power up the Improvement Engine. It was a bit rusty! It had not been used for a long while.

<Leslie> And once the “engine” was running it sucked in niggles that were now a source of fuel! You started harvesting them using the 4N Chart! So what was the output?

<Bob> Purposeful, focused, constructive, rational actions. Not random, destructive, emotional explosions.

<Leslie> Constructive actions such as?

<Bob> Well designing and building the FISH course is one, and this ISP programme is another.

<Leslie> More learning loops!

<Bob> Yup.

<Leslie> OK. So I can see that a private journal can help an individual to build their own learning loop. How does that work with groups? We do not all need to design and build a FISH-equivalent surely!

<Bob> No indeed. What we do is we share stories. We gather together in small groups around camp fires and we share what we are learning … as we are learning it. We contribute our perspective to the collective awareness … and we all gain from everyone’s learning. We learn and teach together.

<Leslie> So the stories are about what we are learning, not what we achieved with that learning.

<Bob> Well put! The “how” we achieved it is more valuable knowledge than “what” we achieved. The “how” is the process, the “what” is just the product. And the “how” we failed to achieve is even more valuable.

<Leslie> Wow! So are you saying that the chaos we are experiencing is the expected effect of not installing enough learning loops! A system-wide error of omission.

<Bob> I would say that is a reasonable diagnosis.

<Leslie> So a rational and reasonable course of treatment becomes clear.  I am on the case!

Posted on

Catalyst

everyone_has_an_idea_300_wht_12709[Bing Bong] Bob was already logged into the weekly coaching Webex when Leslie arrived: a little late.

<Bob> Hi Leslie, how has your week been?

<Leslie> Hi Bob, sorry I am a bit late. It has been a very interesting week.

<Bob> My curiosity is pricked … are you willing to share?

<Leslie> Yes indeed! First an update on the improvement project was talked about a few weeks ago.

<Bob> The call centre one?

<Leslie> Yes.  The good news is that the improvement has been sustained. It was not a flash in the pan. The chaos is gone and the calm has continued.

<Bob> That is very good to hear. And how did the team react?

<Leslie> That is one of the interesting things. They went really quiet.  There was no celebration, no cheering, no sounds of champagne corks popping.  It was almost as if they did not believe what they were seeing and they feared that if they celebrated too early they would somehow trigger a failure … or wake up from a dream.

<Bob> That is a very common reaction.  It takes a while for reality to sink in – the reality that they have changed something, that the world did not end, and that their chronic chaos has evaporated.  It is like a grief reaction … they have to mourn the loss of their disbelief. That takes time. About six weeks usually.

<Leslie> Yes, that is exactly what has happened – and I know they have now got over the surprise because the message I got this week was simply “OK, that appears to have worked exactly as you predicted it would. Will you help us solve the next impossible problem?“

<Bob> Well done Leslie!  You have helped them break through the “Impossibility Barrier”.  So what was your answer?

<Leslie> Well I was really tempted to say “Of course, let me at it!” but I did not. Instead I asked a question “What specifically do you need my help to do?“

<Bob> OK.  And how was that reply received?

<Leslie> They were surprised, and they said “But we could not have done this on our own. You know what to do right at the start and even with your help it took us months to get to the point where we were ready to make the change. So you can do this stuff much more quickly than we can.“

<Bob> Well they are factually correct.

<Leslie> Yes I know, so I pointed out that although the technical part of the design does not take very long … that was not the problem … what slowed us down was the cultural part of the change.  And that is done now so does not need to be repeated. The next study-plan-do cycle will be much quicker and they only need me for the technical bits they have not seen before.

<Bob> Excellent. So how would you now describe your role?

<Leslie> More of a facilitator and coach with a bit of only-when-needed training thrown in.

<Bob> Exactly … and I have a label for this role … I call it a Catalyst.

<Leslie> That is interesting, why so?

<Bob> Because the definition of a catalyst fits rather well. Using the usual scientific definition, a catalyst increases the yield and rate of a chemical reaction. With a catalyst, reactions occur faster and with less energy and catalysts are not consumed, they are recycled, so only tiny amounts are required.

<Leslie> Ah yes, that feels about right.  But I am not just catalysing the reaction that produced the desired result am I?

<Bob> No. What else are you doing?

<Leslie> I am also converting some of the substrate into potential future catalysts too.

<Bob> Yes, you are. And that is what is needed for the current paradigm to shift.

<Leslie> Wow! I see that. This is powerful stuff!

<Bob> It is indeed. And the reaction you are catalysing is the combination of wisdom with ineptitude.

<Leslie> Eh? Can you repeat that again. Wisdom and ineptitude? Those are not words that I hear very often. I hear words like dumb, stupid, ignorant, incompetent and incapable. What is the reason you use those words?

<Bob> Simply because the dictionary definitions fit. Ineptitude means not knowing what to do to get the result we want, which is not the same as just not knowing stuff or not having the necessary skills.  What we need are decisions which lead to effective actions and to intended outcomes. Wise decisions. If we demonstrate ineptitude we reveal that we lack the wisdom to make those effective decisions.  So we need to combine ineptitude with wisdom to get the capability to achieve our purpose.

<Leslie> But why use the word “wisdom”? Why not just “knowledge”?

<Bob> Because knowledge is not enough.  Knowledge just implies that I recognise what I am seeing. “I know this. I have seen it before“.  Appreciating the implication of what I recognise is something more … it is called “understanding”.

<Leslie> Ah! I know this. I have seen this before. I know what a time-series chart is and I know how to create one but it takes guidance, time and practice to understand the implications of what the chart is saying about the system.  But where does wisdom fit?

<Bob>Understanding is past-focussed. We understand how we got to where we are in the present. We cannot change the past so understanding has nothing to do with wise decisions or effective actions or intended outcomes. It is retrospection.

<Leslie> So wisdom is future-focussed. It is prospective. It is the ability to predict the outcome of an action and that ability is necessary to make wise decisions. That is why wisdom is the antidote to ineptitude!

<Bob> Well put! And that is what you did long before you made the change in the call centre … you learned how to make reliable predictions … and the results have confirmed yours was a wise decision.  They got their intended outcome. You are not inept.

<Leslie> Ah! Now I understand the difference. I am a catalyst for improvement because I am able to diagnose and treat ineptitude. That is what you did for me. You are a catalyst.

<Bob> Welcome to the world of the Improvement Science Practitioner.  You have earned your place.

Atul_GawandeThe word “ineptitude” is coined by Dr Atul Gawande in the first of the 2014 Reith Lectures entitled “Why Do Doctors Fail?“.

Click HERE to listen to his first lecture (30 minutes).

In his second lecture he describes how it is the design of the system that delivers apparently miraculous outcomes.  It is the way that the parts work together and the attention to context and to detail that counts.

Click HERE to hear his second lecture  “The Century of the System” (30 minutes).

And Atul has a proven track record in system improvement … he is the doctor-surgeon-instigator of the WHO Safer Surgery Check List – a simple idea borrowed from aviation that is now used worldwide and is preventing 1000’s of easily avoidable deaths during and after surgery.

Click HERE to hear his third lecture  “The Problem of Hubris” (30 minutes).

Click HERE to hear his fourth lecture  “The Idea of Wellbeing” (30 minutes).

Posted on

Counter-Productivity

coffee_table_talk_PA_150_wht_6082The Webex icon bounced up and down on Bob’s task bar signalling that Leslie had just joined the weekly ISP coaching session.

<Leslie> Hi Bob. I have been so busy this week that I have not had time to consider a topic to explore.

<Bob> No problem Leslie, I have shelf full of topics we have not touched yet.  So shall we talk about counter-productivity?

<Leslie> Don’t you mean productivity … the fourth dimension of system improvement.

<Bob>They are related of course but we will approach the issue of productivity from a different angle. Rather like we did with safety. To improve safety we considered at the causes of un-safety and focussed our efforts there.

<Leslie> Ah yes, I see.  So to improve productivity we look at the causes of un-productivity … in other words counter-productive beliefs and behaviours that are manifest as system design flaws.

<Bob> Exactly. So remind me what the definition of a productivity metric is from your FISH course.

<Leslie> Productivity is the ratio of a stream metric and a stage metric.  Value-for-Money for example.

<Bob> Good.  So counter-productivity is also a ratio of a stream and a stage metric.

<Leslie> Um, I’m not sure I quite get that. Can you explain a bit more.

<Bob> OK. To explore deeper we need to be clear about how each metric relates to our intended outcome.  Remember in safety-by-design we count the number and severity of risks and harm because  as harm is going up then safety is going down.  So harm is an un-safety stream metric.

<Leslie> Ah! Yes I see.  So if we look at cycle-time, which is a stage metric; as cycle-time increases, the activity falls and productivity falls. So cycle-time is actually a counter-productivity metric.

<Bob>Excellent. You are getting the hang of the concept of counter-productivity.

<Leslie> And we need to be careful because productivity is a ratio so the numerator and denominator metrics work in opposite ways: increasing the magnitude of the numerator is equivalent to decreasing the magnitude of the denominator – the ratio increases.

<Bob> Indeed, there are many hazards with ratios as we have explored before. So let is consider a real and rather useful example.  Let us look at Little’s Law from the perspective of counter-productivity. Remind me of the definition of Little’s Law for a single step system.

<Leslie> Little’s Law is a mathematically proven law of flow physics which states that the average lead-time is the product of the average work-in-progress and the average cycle-time.

LT = WIP * CT

<Bob> Good and I am pleased to see that you have used cycle-time. We are considering a single stream, single stage, single step system.

<Leslie> Yes, I avoided using the unqualified term ‘activity’. I have learned that lesson the hard way too!

<Bob> So how do the terms in Little’s Law relate to streams, stages and systems?

<Leslie> Lead-time is a stream metric, cycle-time is a stage metric and work-in-progress is a …. h’mm. What it is? A stream metric or a stage metric?

<Bob>Or?

<Leslie>A system metric?  WIP is a system metric!

<Bob> Good. So now re-arrange Little’s Law as a productivity formula.

<Leslie> Work-in-Progress equals lead-time divided by cycle-time

WIP = LT / CT

<Bob> So is WIP a productivity or a counter-productivity metric?

<Leslie> H’mmm …. I will need to work this through logically and step-by-step. I do not trust my intuition on this flow stuff.

Increasing cycle-time is counter-productive because it implies activity is falling while costs are not.

But cycle-time is on the bottom of the ratio so it’s effect reverses.

So if lead-time stays the same and cycle-time increases then because it is on the bottom of the ratio that implies a more productive design. And at the same time work in progress must be falling. Urrgh! This is hurting my head.

<Bob> Good, keep going … you are nearly there.

<Leslie> So a falling WIP is a sign of increasing productivity.

<Bob> Good … and that implies?

<Leslie> WIP is a counter-productivity system metric!

<Bob> Well done. Your logic is flawless.

<Leslie> So that  is why we focus on WIP so much!  Whatever causes WIP to increase is counter-productive!

Ahhhh …. that makes complete sense.

Lo-WIP  designs are more productive than Hi-WIP designs.

<Bob> Bravo!  And translating this into financial metrics … it is because a big queue of waiting work incurs costs. Storage cost, maintenance cost, processing cost and so on. So WIP is a liability. It is not an asset!

<Leslie> But doesn’t that imply treating work-in-progress as an asset on the financial balance sheet is counter-productive?

<Bob> It does indeed.

<Leslie> Oh dear! That revelation is going to upset a lot of people in the accounting department!

<Bob> The painful reality is that  the Laws of Flow Physics are completely indifferent to what any of us believe or do not believe.

<Leslie> Wow!  I like this concept of counter-productivity … it really helps to expose some of our invalid assumptions that invisibly block improvement!

<Bob> So here is a question to ponder.  Is zero WIP desirable or even possible?

<Leslie> H’mmm.  I will have to think about that.  I know you would not have asked the question for no reason.

Posted on

Seeing and Believing

Flow_Science_Works[Beep] It was time again for the weekly Webex coaching session. Bob dialled into the teleconference to find Leslie already there … and very excited.

<Leslie> Hi Bob, I am so excited. I cannot wait to tell you about what has happened this week.

<Bob> Hi Leslie. You really do sound excited. I cannot wait to hear.

<Leslie> Well, let us go back a bit in the story.  You remember that I was really struggling to convince the teams I am working with to actually make changes.  I kept getting the ‘Yes … but‘ reaction from the sceptics.  It was as if they were more comfortable with complaining.

<Bob> That is the normal situation. We are all very able to delude ourselves that what we have is all we can expect.

<Leslie> Well, I listened to what you said and I asked them to work through what they predicted could happen if they did nothing.  Their healthy scepticism then worked to build their conviction that doing nothing was a very dangerous choice.

<Bob> OK. And I am guessing that insight was not enough.

<Leslie> Correct.  So then I shared some examples of what others had achieved and how they had done it, and I started to see some curiosity building, but no engagement still.  So I kept going, sharing stories of ‘what’, and ‘how’.  And eventually I got an email saying “We have thought about what you said about a one day experiment and we are prepared to give that a try“.

<Bob> Excellent. How long ago was that?

<Leslie> Three months. And I confess that I was part of the delay.  I was so surprised that they said ‘OK‘ that I was not ready to follow on.

<Bob> OK. It sounds like you did not really believe it was possible either. So what did you do next?

<Leslie> Well I knew for sure that we would only get one chance.  If the experiment failed then it would be Game Over. So I needed to know before the change what the effect would be.  I needed to be able to predict it accurately. I also needed to feel reassured enough to take the leap of faith.

<Bob> Very good, so did you use some of your ISP-2 skills?

<Leslie> Yes! And it was a bit of a struggle because doing it in theory is one thing; doing it in reality is a lot messier.

<Bob> So what did you focus on?

<Leslie> The top niggle of course!  At St Elsewhere® we have a call-centre that provides out-of-office-hours telephone advice and guidance – and it is especially busy at weekends.  We are required to answer all calls quickly, which we do, and then we categorise them into ‘urgent’  and ‘non-urgent’ and pass them on to the specialists.  They call the clients back and provide expert advice and guidance for their specific problem.

<Bob>So you do not use standard scripts?

<Leslie> No, that does not work. The variety of the problems we have to solve is too wide. And the specialist has to come to a decision quite quickly … solve the problem over the phone, arrange a visit to an out of hours clinic, or to dispatch a mobile specialist to the client immediately.

<Bob> OK. So what was the top niggle?

<Leslie> We have contractual performance specifications we have to meet for the maximum waiting time for our specialists to call clients back; and we were not meeting them.  That implied that we were at risk of losing the contract and that meant loss of revenue and jobs.

<Bob> So doing nothing was not an option.

<Leslie> Correct. And asking for more resources was not either … the contract was a fixed price one. We got it because we offered the lowest price. If we employed more staff we would go out of business.  It was a rock-and-a-hard-place problem.

<Bob> OK.  So if this was ranked as your top niggle then you must have had a solution in mind.

<Leslie> I had a diagnosis.  The Vitals Chart© showed that we already had enough resources to do the work. The performance failure was caused by a scheduling policy – one that we created – our intuitively-obvious policy.

<Bob> Ah ha! So you suggested doing something that felt counter-intuitive.

<Leslie> Yes. And that generated all the ‘Yes .. but‘  discussion.

<Bob> OK. Do you have the Vitals Chart© to hand? Can you send me the Wait-Time run chart?

<Leslie> Yes, I expected you would ask for that … here it is.

StE_CallCentre_Before<Bob> OK. So I am looking at the run chart of waiting time for the call backs for one Saturday, and it is in call arrival order, and the blue line is the maximum allowed waiting time is that correct?

<Leslie>Yup. Can you see the diagnosis?

<Bob> Yes. This chart shows the classic pattern of ‘prioritycarveoutosis’.  The upper border is the ‘non-urgents’ and the lower group are the ‘urgents’ … the queue jumpers.

<Leslie> Spot on.  It is the rising tide of non-urgent calls that spill over the specification limit.  And when I shared this chart the immediate reaction was ‘Well that proves we need more capacity!‘

<Bob> And the WIP chart did not support that assertion.

<Leslie> Correct. It showed we had enough total flow-capacity already.

<Bob> So you suggested a change in the scheduling policy would solve the problem without costing any money.

<Leslie> Yes. And the reaction to that was ‘That is impossible. We are already working flat out. We need more capacity because to work quicker will mean cutting corners and it is unsafe to cut-corners‘.

<Bob> So how did you get around that invalid but widely held belief?

<Leslie> I used one of the FISH techniques. I got a few of them to play a table top game where we simulated a much simpler process and demonstrated the same waiting time pattern on a hand-drawn run chart.

<Bob> Excellent.  Did that get you to the ‘OK, we will give it a go for one day‘ decision.

<Leslie>Yes. But then I had to come up with a new design and I had test it so I know it would work.

<Bob> Because that was a step too far for them. And It sounds like you achieved that.

<Leslie> Yes.  It was tough though because I knew I had to prove to myself I could do it. If I had asked you I know what you would have said – ‘I know you can do this‘.  And last Saturday we ran the ‘experiment’. I was pacing up and down like an expectant parent!

<Bob> I expect rather like the ESA team who have just landed Rosetta’s little probe-child on an asteroid travelling at 38,000 miles per hour, billions of miles from Earth after a 10 year journey through deep space!  Totally inspiring stuff!

<Leslie> Yes. And that is why I am so excited because OUR DESIGN WORKED!  Exactly as predicted.

<Bob> Three cheers for you!  You have experienced that wonderful feeling when you see the effect of improvement-by-design with your own eyes. When that happens then you really believe what opportunities become possible.

<Leslie> So I want to show you the ‘after’ chart …

StE_CallCentre_After

<Bob> Wow!  That is a spectacular result! The activity looks very similar, and other than a ‘blip’ between 15:00 and 19:00 the prioritycarveoutosis has gone. The spikes have assignable causes I assume?

<Leslie> Spot on again!  The activity was actually well above average for a Saturday.  The subjective feedback was that the new design felt calm and under-control. The chaos had evaporated.  The performance was easily achieved and everyone was very positive about the whole experience.  The sceptics were generous enough to say it had gone better than they expected.  And yes, I am now working through the ‘spikes’ and excluding them … but only once I have a root cause that explains them.

<Bob> Well done Leslie! I sense that you now believe what is possible whereas before you just hoped it would be.

<Leslie> Yes! And the most important thing to me is that we did it ourselves. Which means improvement-by-design can be learned. It is not obvious, it feels counter-intuitive, so it is not easy … but it works.

<Bob> Yes. That is the most important message. And you have now earned your ISP Certificate of Competency.

Posted on

Spring the Trap

trapped_in_question_PA_300_wht_3174[Beeeeeep] It was time for the weekly coaching chat.  Bob, a seasoned practitioner of flow science, dialled into the teleconference with Lesley.

<Bob> Good afternoon Lesley, can I suggest a topic today?

<Lesley> Hi Bob. That would be great, and I am sure you have a good reason for suggesting it.

<Bob> I would like to explore the concept of time-traps again because it something that many find confusing. Which is a shame because it is often the key to delivering surprisingly dramatic and rapid improvements; at no cost.

<Lesley> Well doing exactly that is what everyone seems to be clamouring for so it sounds like a good topic to me.  I confess that I am still not confident to teach others about time-traps.

<Bob> OK. Let us start there. Can you describe what happens when you try to teach it?

<Lesley> Well, it seems to be when I say that the essence of a time-trap is that the lead time and the flow are independent.  For example, the lead time stays the same even though the flow is changing.  That really seems to confuse people; and me too if I am brutally honest.

<Bob> OK.  Can you share the example that you use?

<Lesley> Well it depends on who I am talking to.  I prefer to use an example that they are familiar with.  If it is a doctor I might use the example of the ward round.  If it is a manager I might use the example of emails or meetings.

<Bob> Assume I am a doctor then – an urgent care physician.

<Lesley> OK.  Let us take it that I have done the 4N Chart and the  top niggle is ‘Frustration because the post-take ward round takes so long that it delays the discharge of patients who then often have to stay an extra night which then fills up the unit with waiting patients and we get blamed for blocking flow from A&E and causing A&E breaches‘.

<Bob> That sounds like a good example. What is the time-trap in that design?

<Lesley> The  post-take ward round.

<Bob> And what justification is usually offered for using that design?

<Lesley> That it is a more efficient use of the expensive doctor’s time if the whole team congregate once a day and work through all the patients admitted over the previous 24 hours.  They review the presentation, results of tests, diagnosis, management plans, response to treatment, decide the next steps and do the paperwork.

<Bob> And why is that a time-trap design?

<Lesley> Because  it does not matter if one patient is admitted or ten, the average lead time from the perspective of the patient is the same – about one day.

<Bob> Correct. So why is the doctor complaining that there are always lots of patients to see?

<Lesley> Because there are. The emergency short stay ward is usually full by the time the post take ward round happens.

<Bob> And how do you present the data that shows the lead time is independent of the flow?

<Lesley> I use a Gantt chart, but the problem I find is that there is so much variation and queue jumping it is not blindingly obvious from the Gantt chart that there is a time-trap. There is so much else clouding the picture.

<Bob>Is that where the ‘but I do not understand‘ conversation starts?

<Lesley> Yes. And that is where I get stuck too.

<Bob> OK.  The issue here is that a Gantt chart is not the ideal visualisation tool when there are lots of crossed-streams, frequently changing priorities, and many other sources of variation.  The Gantt chart gets ‘messy’.   The trick here is to use a Vitals Chart – and you can derive that from the same data you used for the Gantt chart.

<Lesley> You are right about the Gantt chart getting messy. I have seen massive wall-sized Gantt charts that are veritable works-of-art and that have taken hours to create; and everyone standing looking at it and saying ‘Wow! That is an impressive piece of work.  So what does it tell us? How does it help?‘

<Bob> Yes, I have experienced that too. I think what happens is that those who do the foundation training and discover the Gantt chart then try to use it to solve every flow problem – and in their enthusiasm they discount any warning advice.  Desperation drives over-inflated expectation which is often the pre-cursor to disappointment, and then disillusionment.  The Nerve Curve again.

<Lesley> But a Vitals Chart is an HCSE level technique and you said that we do not need to put everyone through HCSE training.

<Bob>That is correct. I am advocating an HCSE-in-training using a Vitals Chart to explain the concept of a time-trap so that everyone understands it well enough to see the flaw in the design.

<Lesley> Ah ha!  Yes, I see.  So what is my next step?

<Bob> I will let you answer that.

<Lesley> Um, let me think.

The outcome I want is everyone understands the concept of a time-trap well enough to feel comfortable with trying a time-trap-free design because they can see the benefits for them.

And to get that depth of understanding I need to design a table top exercise that starts with a time-trap design and generates raw data that we can use to build both a Gantt chart and the Vitals Chart; so I can point out and explain the characteristic finger-print of a time trap.

And then we can ‘test’ an alternative time-trap-free design and generate the prognostic Gantt and Vitals Chart and compare with the baseline diagnostic charts to reveal the improvement.

<Bob> That sounds like a good plan to me.  And if you do that, and your team apply it to a real improvement exercise, and you see the improvement and you share the story, then that will earn you a coveted HCSE Certificate of Competency.

<Lesley>Ah ha! Now I understand the reason you suggested this topic!  I am on the case!

Posted on

A Little Law and Order

teamwork_puzzle_build_PA_150_wht_2341[Bing bong]. The sound heralded Lesley logging on to the weekly Webex coaching session with Bob, an experienced Improvement Science Practitioner.

<Bob> Good afternoon Lesley.  How has your week been and what topic shall we explore today?

<Lesley> Hi Bob. Well in a nutshell, the bit of the system that I have control over feels like a fragile oasis of calm in a perpetual desert of chaos.  It is hard work keeping the oasis clear of the toxic sand that blows in!

<Bob> A compelling metaphor. I can just picture it.  Maintaining order amidst chaos requires energy. So what would you like to talk about?

<Lesley> Well, I have a small shoal of FISHees who I am guiding  through the foundation shallows and they are getting stuck on Little’s Law.  I confess I am not very good at explaining it and that suggests to me that I do not really understand it well enough either.

<Bob> OK. So shall we link those two theme – chaos and Little’s Law?

<Lesley> That sounds like an excellent plan!

<Bob> OK. So let us refresh the foundation knowledge. What is Little’s Law?

<Lesley>It is a fundamental Law of process physics that relates flow, with lead time and work in progress.

<Bob> Good. And specifically?

<Lesley> Average lead time is equal to the average flow multiplied by the average work in progress.

<Bob>Yes. And what are the units of flow in your equation?

<Lesley> Ah yes! That is  a trap for the unwary. We need to be clear how we express flow. The usual way is to state it as number of tasks in a defined period of time, such as patients admitted per day.  In Little’s Law the convention is to use the inverse of that which is the average interval between consecutive flow events. This is an unfamiliar way to present flow to most people.

<Bob> Good. And what is the reason that we use the ‘interval between events’ form?

<Leslie> Because it is easier to compare it with two critically important  flow metrics … the takt time and the cycle time.

<Bob> And what is the takt time?

<Leslie> It is the average interval between new tasks arriving … the average demand interval.

<Bob> And the cycle time?

<Leslie> It is the shortest average interval between tasks departing …. and is determined by the design of the flow constraint step.

<Bob> Excellent. And what is the essence of a stable flow design?

<Lesley> That the cycle time is less than the takt time.

<Bob>Why less than? Why not equal to?

<Leslie> Because all realistic systems need some flow resilience to exhibit stable and predictable-within-limits behaviour.

<Bob> Excellent. Now describe the design requirements for creating chronically chaotic system behaviour?

<Leslie> This is a bit trickier to explain. The essence is that for chronically chaotic behaviour to happen then there must be two feedback loops – a destabilising loop and a stabilising loop.  The destabilising loop creates the chaos, the stabilising loop ensures it is chronic.

<Bob> Good … so can you give me an example of a destabilising feedback loop?

<Leslie> A common one that I see is when there is a long delay between detecting a safety risk and the diagnosis, decision and corrective action.  The risks are often transitory so if the corrective action arrives long after the root cause has gone away then it can actually destabilise the process and paradoxically increase the risk of harm.

<Bob> Can you give me an example?

<Leslie>Yes. Suppose a safety risk is exposed by a near miss.  A delay in communicating the niggle and a root cause analysis means that the specific combination of factors that led to the near miss has gone. The holes in the Swiss cheese are not static … they move about in the chaos.  So the action that follows the accumulation of many undiagnosed near misses is usually the non-specific mantra of adding yet another safety-check to the already burgeoning check-list. The longer check-list takes more time to do, and is often repeated many times, so the whole flow slows down, queues grow bigger, waiting times get longer and as pressure comes from the delivery targets corners start being cut, and new near misses start to occur; on top of the other ones. So more checks are added and so on.

<Bob> An excellent example! And what is the outcome?

<Leslie> Chronic chaos which is more dangerous, more disordered and more expensive. Lose lose lose.

<Bob> And how do the people feel who work in the system?

<Leslie> Chronically naffed off! Angry. Demotivated. Cynical.

<Bob>And those feelings are the key symptoms.  Niggles are not only symptoms of poor process design, they are also symptoms of a much deeper problem: a violation of values.

<Leslie> I get the first bit about poor design; but what is that second bit about values?

<Bob>  We all have a set of values that we learned when we were very young and that have bee shaped by life experience.  They are our source of emotional energy, and our guiding lights in an uncertain world. Our internal unconscious check-list.  So when one of our values is violated we know because we feel angry. How that anger is directed varies from person to person … some internalise it and some externalise it.

<Leslie> OK. That explains the commonest emotion that people report when they feel a niggle … frustration which is the same as anger.

<Bob>Yes.  And we reveal our values by uncovering the specific root causes of our niggles.  For example if I value ‘Hard Work’ then I will be niggled by laziness. If you value ‘Experimentation’ then you may be niggled by ‘Rigid Rules’.  If someone else values ‘Safety’ then they may value ‘Rigid Rules’ and be niggled by ‘Innovation’ which they interpret as risky.

<Leslie> Ahhhh! Yes, I see.  This explains why there is so much impassioned discussion when we do a 4N Chart! But if this behaviour is so innate then it must be impossible to resolve!

<Bob> Understanding  how our values motivate us actually helps a lot because we are naturally attracted to others who share the same values – because we have learned that it reduces conflict and stress and improves our chance of survival. We are tribal and tribes share the same values.

<Leslie> Is that why different  departments appear to have different cultures and behaviours and why they fight each other?

<Bob> It is one factor in the Silo Wars that are a characteristic of some large organisations.  But Silo Wars are not inevitable.

<Leslie> So how are they avoided?

<Bob> By everyone knowing what common purpose of the organisation is and by being clear about what values are aligned with that purpose.

<Leslie> So in the healthcare context one purpose is avoidance of harm … primum non nocere … so ‘safety’ is a core value.  Which implies anything that is felt to be unsafe generates niggles and well-intended but potentially self-destructive negative behaviour.

<Bob> Indeed so, as you described very well.

<Leslie> So how does all this link to Little’s Law?

<Bob>Let us go back to the foundation knowledge. What are the four interdependent dimensions of system improvement?

<Leslie> Safety, Flow, Quality and Productivity.

<Bob> And one measure of  productivity is profit.  So organisations that have only short term profit as their primary goal are at risk of making poor long term safety, flow and quality decisions.

<Leslie> And flow is the key dimension – because profit is just  the difference between two cash flows: income and expenses.

<Bob> Exactly. One way or another it all comes down to flow … and Little’s Law is a fundamental Law of flow physics. So if you want all the other outcomes … without the emotionally painful disorder and chaos … then you cannot avoid learning to use Little’s Law.

<Leslie> Wow!  That is a profound insight.  I will need to lie down in a darkened room and meditate on that!

<Bob> An oasis of calm is the perfect place to pause, rest and reflect.

Posted on

A Sisyphean Nightmare

cardiogram_heart_signal_150_wht_5748[Beep] It was time for the weekly e-mentoring session so Bob switched on his laptop, logged in to the virtual meeting site and found that Lesley was already there.

<Bob> Hi Lesley. What shall we talk about today?

<Lesley> Hello Bob. Another old chestnut I am afraid. Queues.  I keep hitting the same barrier where people who are fed up with the perpetual queue chaos have only one mantra “If you want to avoid long waiting times then we need more capacity.“

<Bob> So what is the problem? You know that is not the cause of chronic queues.

<Lesley> Yes, I know that mantra is incorrect – but I do not yet understand how to respectfully challenge it and how to demonstrate why it is incorrect and what the alternative is.

<Bob> OK. I understand. So could you outline a real example that we can work with.

<Lesley> Yes. Another old chestnut: the Emergency Department 4-hour breaches.

<Bob> Do you remember the Myth of Sisyphus?

<Leslie> No, I do not remember that being mentioned in the FISH course.

<Bob> Ho ho! No indeed,  it is much older. In Greek mythology Sisyphus was a king of Ephyra who was punished by the Gods for chronic deceitfulness by being compelled to roll an immense boulder up a hill, only to watch it roll back down, and then to repeat this action forever.

Sisyphus_Cartoon

<Lesley> Ah! I see the link. Yes, that is exactly how people in the ED feel.  Everyday it feels like they are pushing a heavy boulder uphill – only to have to repeat the same labour the next day. And they do not believe it can ever be any better with the resources they have.

<Bob> A rather depressing conclusion! Perhaps a better metaphor is the story in the film  “Ground Hog Day” where Bill Murray plays the part of a rather arrogant newsreader who enters a recurring nightmare where the same day is repeated, over and over. He seems powerless to prevent it.  He does eventually escape when he learns the power of humility and learns how to behave differently.

<Lesley> So the message is that there is a way out of this daily torture – if we are humble enough to learn the ‘how’.

<Bob> Well put. So shall we start?

<Lesley> Yes please!

<Bob> OK. As you know very well it is important not to use the unqualified term ‘capacity’.  We must always state if we are referring to flow-capacity or space-capacity.

<Lesley> Because they have different units and because they are intimately related to lead time by Little’s Law.

<Bob> Yes.  Little’s Law is mathematically proven Law of flow physics – it is not negotiable.

<Lesley> OK. I know that but how does it solve problem we started with?

<Bob> Little’s Law is necessary but it is not sufficient. Little’s Law relates to averages – and is therefore just the foundation. We now need to build the next level of understanding.

<Lesley> So you mean we need to introduce variation?

<Bob> Yes. And the tool we need for this is a particular form of time-series chart called a Vitals Chart.

<Lesley> And I am assuming that will show the relationship between flow, lead time and work in progress … over time ?

<Bob> Exactly. It is the temporal patterns on the Vitals Chart that point to the root causes of the Sisyphean Chaos. The flow design flaws.

<Lesley> Which are not lack of flow-capacity or space-capacity.

<Bob> Correct. If the chaos is chronic then there must already be enough space-capacity and flow-capacity. Little’s Law shows that, because if there were not the system would have failed completely a long time ago. The usual design flaw in a chronically chaotic system is one or more misaligned policies.  It is as if the system hardware is OK but the operating software is not.

<Lesley> So to escape from the Sisyphean Recurring ED 4-Hour Breach Nightmare we just need enough humility and enough time to learn how to diagnose and redesign some of our ED system operating software? Some of our own policies? Some of our own mantras?

<Bob> Yup.  And not very much actually. Most of the software is OK. We need to focus on the flaws.

<Lesley> So where do I start?

<Bob> You need to do the ISP-1 challenge that is called Brainteaser 104.  That is where you learn how to create a Vitals Chart.

<Lesley> OK. Now I see what I need to do and the reason:  understanding how to do that will help me explain it to others. And you are not going to just give me the answer.

<Bob> Correct. I am not going to just give you the answer. You will not fully understand unless you are able to build your own Vitals Chart generator. You will not be able to explain the how to others unless you demonstrate it to yourself first.

<Lesley> And what else do I need to do that?

<Bob> A spreadsheet and your raw start and finish event data.

<Lesley> But we have tried that before and neither I nor the database experts in our Performance Department could work out how to get the real time work in progress from the events – so we assumed we would have to do a head count or a bed count every hour which is impractical.

<Bob> It is indeed possible as you are about to discover for yourself. The fact that we do not know how to do something does not prove that it is impossible … humility means accepting our inevitable ignorance and being open to learning. Those who lack humility will continue to live the Sisyphean Nightmare of ED Ground Hog Day. The choice to escape is ours.

<Lesley> I choose to learn. Please send me BT104.

<Bob> It is on its way …

Posted on

Perfect Storm

lightning_strike_150_wht_5809[Drrrrring Drrrrring]

<Bob> Hi Lesley! How are you today?

<Leslie> Hi Bob.  Really good.  I have just got back from a well earned holiday so I am feeling refreshed and re-energised.

<Bob> That is good to hear.  It has been a bit stormy here over the past few weeks.  Apparently lots of  hot air hitting cold reality and forming a fog of disillusionment and storms of protest.

<Leslie> Is that a metaphor?

<Bob> Yes!  A good one do you think? And it leads us into our topic for this week. Perfect storms.

<Leslie> I am looking forward to it.  Can you be a bit more specific?

<Bob> Sure.  Remember the ISP exercise where I asked you to build a ‘chaos generator’?

<Leslie> I sure do. That was an eye-opener!  I had no idea how easy it is to create chaotic performance in a system – just by making the Flaw of Averages error and adding a pinch of variation. Booom!

<Bob> Good. We are going to use that model to demonstrate another facet of system design.  How to steer out of chaos.

<Leslie> OK – what do I need to do.

<Bob> Start up that model and set the cycle time to 10 minutes with a sigma of 1.5 minutes.

<Leslie> OK.

<Bob> Now set the demand interval to 10 minutes and the sigma of that to 2.0 minutes.

<Leslie> OK. That is what I had before.

<Bob> Set the lead time upper specification limit to 30 minutes. Run that 12 times and record the failure rate.

<Leslie> OK.  That gives a chaotic picture!  All over the place.

<Bob> OK now change just the average of the demand interval.  Start with a value of 8 minutes, run 12 times, and then increase to 8.5 minutes and repeat that up to 12 minutes.

<Leslie> OK. That will repeat the run for 10 minutes. Is that OK.

<Bob> Yes.

<Leslie> OK … it will take me a few minutes to run all these.  Do you want to get a cup of tea while I do that?

<Bob> Good idea.

[5 minutes later]

<Leslie> OK I have done all that – 108 data points. Do I plot that as a run chart?

<Bob> You could.  I suggest plotting as a scattergram.

<Leslie> With the average demand interval on the X axis and the Failure % on the  Y axis?

<Bob> Yes. Exactly so. And just the dots, no lines.

<Leslie> OK. Wow! That is amazing!  Now I see why you get so worked up about the Flaw of Averages!

<Bob> What you are looking at is called a performance curve.  Notice how steep and fuzzy it is. That is called a chaotic transition. The perfect storm.  And when fall into the Flaw of Averages trap we design our systems to be smack in the middle of it.

<Leslie> Yes I see what you are getting at.  And that implies that to calm the chaos we do not need very much resilient flow capacity … and we could probably release that just from a few minor design tweaks.

<Bob> Yup.

<Leslie> That is so cool. I cannot wait to share this with the team. Thanks again Bob.

Posted on

A Stab At The Vitals

pirate_flag_anim_150_wht_12881[Drrring Drrring] The phone heralded the start of the weekly ISP mentoring session.

<Bob> Hi Leslie, how are you today?

<Leslie> Hi Bob. To be honest I am not good. I am drowning. Drowning in data!

<Bob> Oh dear! I am sorry to hear that. Can I help? What led up to this?

<Leslie> Well, it was sort of triggered by our last chat and after you opened my eyes to the fact that we habitually throw most of our valuable information away by thresholding, aggregating and normalising.  Then we wonder why we make poor decisions … and then we get frustrated because nothing seems to improve.

<Bob> OK. What happened next?

<Leslie> I phoned our Performance Team and asked for some raw data. Three months worth.

<Bob> And what was their reaction?

<Leslie> They said “OK, here you go!” and sent me a twenty megabyte Excel spreadsheet that clogged my email inbox!  I did manage to unclog it eventually by deleting loads of old junk.  But I could swear that I heard the whole office laughing as they hung up the phone! Maybe I am paranoid?

<Bob> OK. And what happened next?

<Leslie> I started drowning!  The mega-file had a row of data for every patient that has attended A&E for the last three months as I had requested, but there were dozens of columns!  Trying to slice-and-dice it was a nightmare! My computer was smoking and each step took ages for it to complete.  In the end I gave up in frustration.  I now have a lot more respect for the Performance Team I can tell you! They do this for a living?

<Bob> OK.  It sounds like you are ready for a Stab At the Vitals.

<Leslie> What?  That sounds rather piratical!  Are you making fun of my slicing-and-dicing metaphor?

<Bob> No indeed.  I am deadly serious!  Before we leap into the data ocean we need to be able to swim; and we also need a raft that will keep us afloat;  and we need a sail to power our raft; and we need a way to navigate our raft to our desired destination.

<Leslie> OK. I like the nautical metaphor but how does it help?

<Bob> Let me translate. Learning to use system behaviour charts is equivalent to learning the skill of swimming. We have to do that first and practice until we are competent and confident.  Let us call our raft “ISP” – you are already aboard.  The sail you also have already – your Excel software.  The navigation aid is what I refer to as Vitals. So we need to have a “stab at the vitals”.

<Leslie> Do you mean we use a combination of time-series charts, ISP and Excel to create a navigation aid that helps avoid the Depths of Data and the Rocks of DRAT?

<Bob> Exactly.

<Leslie> Can you demonstrate with an example?

<Bob> Sure. Send me some of your data … just the arrival and departure events for one day – a typical one.

<Leslie> OK … give me a minute!  …  It is on its way.  How long will it take for you to analyse it?

<Bob> About 2 seconds. OK, here is your email … um … copy … paste … copy … reply

Vitals_Charts<Leslie> What the ****? That was quick! Let me see what this is … the top left chart is the demand, activity and work-in-progress for each hour; the top right chart is the lead time by patient plotted in discharge order; the table bottom left includes the 4 hour breach rate.  Those I do recognise. What is the chart on the bottom right?

<Bob> It is a histogram of the lead times … and it shows a problem.  Can you see the spike at 225 to 240 minutes?

<Leslie> Is that the fabled Horned Gaussian?

<Bob> Yes.  That is the sign that the 4-hour performance target is distorting the behaviour of the system.  And this is yet another reason why the  Breach Rate is a dangerous management metric. The adaptive reaction it triggers amplifies the variation and fuels the chaos.

<Leslie> Wow! And you did all that in Excel using my data in two seconds?  That must need a whole host of clever macros and code!

<Bob> “Yes” it was done in Excel and “No” it does not need any macros or code.  It is all done using simple formulae.

<Leslie> That is fantastic! Can you send me a copy of your Excel file?

<Bob> Nope.

<Leslie>Whaaaat? Why not? Is this some sort of evil piratical game?

<Bob> Nope. You are going to learn how to do this yourself – you are going to build your own Vitals Chart Generator – because that is the only way to really understand how it works.

<Leslie> Phew! You had me going for a second there! Bring it on! What do I do next?

<Bob> I will send you the step-by-step instructions of how to build, test and use a Vitals Chart Generator.

<Leslie> Thanks Bob. I cannot wait to get started! Weigh anchor and set the sails! Ha’ harrrr me hearties.

Posted on

Ratio Hazards

waste_paper_shot_miss_150_wht_11853[Bzzzzz Bzzzzz] Bob’s phone was on silent but the desktop amplified the vibration and heralded the arrival of Leslie’s weekly ISP coaching call.

<Bob> Hi Leslie.  How are you today and what would you like to talk about?

<Leslie> Hi Bob.  I am well and I have an old chestnut to roast today … target-driven-behaviour!

<Bob> Excellent. That is one of my favorite topics. Is there a specific context?

<Leslie> Yes.  The usual desperate directive from on-high exhorting everyone to “work harder to hit the target” and usually accompanied by a RAG table of percentages that show just who is failing and how badly they are doing.

<Bob> OK. Red RAGs irritating the Bulls eh? Percentages eh? Have we talked about Ratio Hazards?

<Leslie> We have talked about DRATs … Delusional Ratios and Arbitrary Targets as you call them. Is that the same thing?

<Bob> Sort of. What happened when you tried to explain DRATs to those who are reacting to these ‘desperate directives’?

<Leslie> The usual reply is ‘Yes, but that is how we are required to report our performance to our Commissioners and Regulatory Bodies.’

<Bob> And are the key performance indicators that are reported upwards and outwards also being used to manage downwards and inwards?  If so, then that is poor design and is very likely to be contributing to the chaos.

<Leslie> Can you explain that a bit more? It feels like a very fundamental point you have just made.

 <Bob> OK. To do that let us work through the process by which the raw data from your system is converted into the externally reported KPI.  Choose any one of your KPIs

<Leslie> Easy! The 4-hour A&E target performance.

<Bob> What is the raw data that goes in to that?

<Leslie> The percentage of patients who breach 4-hours per day.

<Bob> And where does that ratio come from?

<Leslie> Oh! I see what you mean. That comes from a count of the number of patients who are in A&E for more than 4 hours divided by a count of the number of patients who attended.

<Bob> And where do those counts come come from?

<Leslie> We calculate the time the patient is in A&E and use the 4-hour target to label them as breaches or not.

<Bob> And what data goes into the calculation of that time?

<Leslie>The arrival and departure times for each patient. The arrive and depart events.

<Bob>OK. Is that the raw data?

<Leslie>Yes. Everything follows from that.

<Bob> Good.  Each of these two events is a time – which is a continuous metric.  In principle,  we could in record it to any degree of precision we like – milliseconds if we had a good enough enough clock.

<Leslie> Yes. We record it to an accuracy of of seconds – it is when the patient is ‘clicked through’ on the computer.

<Bob> Careful Leslie, do not confuse precision with accuracy. We need both.

<Leslie> Oops! Yes I remember we had that conversation before.

<Bob> And how often is the A&E 4-hour target KPI reported externally?

<Leslie> Quarterly. We either succeed or fail each quarter of the financial year.

<Bob> That is a binary metric. An “OK or not OK”. No gray zone.

<Leslie> Yes. It is rather blunt but that is how we are contractually obliged to report our performance.

<Bob> OK. And how many patients per day on average come to A&E?

<Leslie> About 200 per day.

<Bob> So the data analysis process is boiling down about 36,000 pieces of continuous data into one Yes-or-No bit of binary data.

<Leslie> Yes.

<Bob> And then that one bit is used to drive the action of the Board: if it is ‘OK last quarter’ then there is no ‘desperate directive’ and if it is a ‘Not OK last quarter’ then there is.

<Leslie> Yes.

<Bob> So you are throwing away 99.9999% of your data and wondering why what is left is not offering much insight in what to do.

<Leslie>Um, I guess so … when you say it like that.  But how does that relate to your phrase ‘Ratio Hazards’?

<Bob> A ratio is just one of the many ways that we throw away information. A ratio requires two numbers to calculate it; and it gives one number as an output so we are throwing half our information away.  And this is an irreversible act.  Two specific numbers will give one ratio; but that ratio can be created by an infinite number possible pairs of numbers and we have no way of knowing from the ratio what specific pair was used to create it.

<Leslie> So a ratio is an exercise in obfuscation!

<Bob> Well put! And there is an even more data-wasteful behaviour that we indulge in. We aggregate.

<Leslie> By that do you mean we summarise a whole set of numbers with an average?

<Bob> Yes. When we average we throw most of the data away and when we average over time then we abandon our ability to react in a timely way.

<Leslie>The Flaw of Averages!

<Bob> Yes. One of them. There are many.

<Leslie>No wonder it feels like we are flying blind and out of control!

<Bob> There is more. There is an even worse data-wasteful behaviour. We threshold.

<Leslie>Is that when we use a target to decide if the lead time is OK or Not OK.

<Bob> Yes. And using an arbitrary target makes it even worse.

<Leslie> Ah ha! I see what you are getting at.  The raw event data that we painstakingly collect is a treasure trove of information and potential insight that we could use to help us diagnose, design and deliver a better service. But we throw all but one single solitary binary digit when we put it through the DRAT Processor.

<Bob> Yup.

<Leslie> So why could we not do both? Why could we not use use the raw data for ourselves and the DRAT processed data for external reporting.

<Bob> We could.  So what is stopping us doing just that?

<Leslie> We do not know how to effectively and efficiently interpret the vast ocean of raw data.

<Bob> That is what a time-series chart is for. It turns the thousands of pieces of valuable information onto a picture that tells a story – without throwing the information away in the process. We just need to learn how to interpret the pictures.

<Leslie> Wow! Now I understand much better why you insist we ‘plot the dots’ first.

<Bob> And now you understand the Ratio Hazards a bit better too.

<Leslie> Indeed so.  And once again I have much to ponder on. Thank you again Bob.

Posted on

Synchronicity

Metronome[Beep, Beep, Beep, Beep, Beeeeep] The reminder roused Bob from deep reflection and he clicked the Webex link on his desktop to start the meeting. Leslie was already online.

<Bob> Hi Leslie. How are you? And what would you like to share and explore today?

<Leslie> Hi Bob, I am well thank you and I would like to talk about chaos again.

<Bob> OK. That is always a rich mine of new insights!  Is there a specific reason?

<Leslie>Yes. The story I want to share is of the chaos that I have been experiencing just trying to get a new piece of software available for my team to use.  You would not believe the amount of time, emails, frustration and angst it has taken to negotiate this through the ‘proper channels’.

<Bob> Let me guess … about six months?

<Leslie> Spot on! How did you know?

<Bob> Just prior experience of similar stories.  So what is your diagnosis of the cause of the chaos?

<Leslie> My intuition shouts at me that people are just being deliberately difficult and that makes me feel angry and want to shout at them … but I have learned that behaviour is counter-productive.

<Bob> So what did you do?

<Leslie> I escalated the ‘problem’ to my line manager.

<Bob> And what did they do?

<Leslie> I am not sure, I was not copied in, but it seemed to clear the ‘obstruction’.

<Bob> And were the ‘people’ you mentioned suddenly happy and willing to help?

<Leslie> Not really … they did what we needed but they did not seem very happy about it.

<Bob> OK.  You are describing a Drama Triangle, a game, and your behaviour was from the Persecutor role.

<Leslie>What! But I deliberately did not send any ANGRY emails or get into a childish argument. I escalated the issue I could not solve because that is what we are expected to do.

<Bob> Yes I know. If you had engaged in a direct angry conversation, by whatever means, that would have been an actively aggressive act.  By escalating the issue and someone Bigger having the angry conversation you have engaged in a passive aggressive act. It is still playing the game from the Persecutor role and in fact is the more common mode of Persecution.

<Leslie> But it got the barrier cleared and the problem sorted?

<Bob> And did it leave everyone feeling happier than before?

<Leslie> I guess not. I certainly felt like a bit of a ‘tale teller’ and the IT technician probably hates me and fears for his job, and the departmental heads probably distrust each other even more than before.

<Bob> So this approach may appear to work in the short term but it creates a much bigger long term problem – and it is that long term problem of ‘distrust’ that creates the chaos. So it is a self-sustaining design.

<Leslie> Oh dear! Is there a way to avoid this and to defuse the chronic distrust?

<Bob> Yes.  You have demonstrated a process that you would like to improve – you want the same short term outcome, your software installed and working, and you want it quicker and with less angst and leaving everyone feeling good about how they have played a part in achieving that objective.

<Leslie>Yes. That would be my ideal.

<Bob>So what is different between what you did and your ‘ideal’ scenario?  What did you do that you should not have and what did you not do that you could have?

<Leslie> Well I triggered off a drama  triangle which I should not have. I also assumed that the IT people would know what to do because I do not understand the technical nuances of getting new software procured and installed. What I could have done is make it much clearer for them what I needed, why I needed it and how and when I needed it.  I could have done a lot more homework before asking them for assistance. I could also have given my inner Chimp a banana and gone to talk to them face-to-face and ask their opinion  early on so I could see the problem from  their perspective as well as mine.

<Bob> Yes – that all sounds reasonable and respectful.  What you are doing is ‘synchronising‘.  You are engaging in understanding the process well enough so that you can align all the actions that need to be done, in the correct order and then sharing that.  It is rather like being the composer of a piece of music – you share the score so that the individual players know what to do and when.  There is one other task you need to do.

<Leslie>I need to be the conductor!

<Bob> Yes.  You are the metronome.  You set the pace and guide the orchestra. They are the specialists with their instruments – that is not your role.

<Leslie> And when I do that then the music is harmonious and pleasing-to-the-ear; not a chaotic cacophony!

<Bob> Indeed … and the music is the voice of the system – and is the feedback that everyone hears – and not only do the musicians derive pleasure from contributing then the wider audience will hear what can be achieved and see how it is achieved.

<Leslie> Wow!  That musical metaphor works really well for me. Thanks Bob, I need to go and work on my communicating, composing and conducting capabilities.

Posted on

Alignment of Purpose

woman_back_and_forth_questions_150_wht_12477<Lesley> Hi Bob, how are you today?

<Bob> I’m OK thanks Lesley. Having a bit of a break from the daily grind.

<Lesley> Oh! I am sorry, I had no idea you were on holiday. I will call when you are back at work.

<Bob> No need Lesley. Our chats are always a welcome opportunity to reflect and learn.

<Lesley> OK, if you are sure.  The top niggle on my list at the moment is that I do not feel my organisation values what I do.

<Bob> OK. Have you done the diagnostic Right-2-Left Map® backwards from that top niggle?

<Lesley>Yes. The final straw was that I was asked to justify my improvement role.

<Bob> OK, and before that?

<Lesley> There have been some changes in the senior management team.

<Bob> OK. This sounds like the ‘New Brush Sweeps Clean’ effect.

<Lesley> I have heard that phrase before. What does it mean in this context?

<Bob> Senior management changes are very disruptive events. The more senior the change the more disruptive it is.  Let us call it a form of ‘Disruptive Innovation’.  The trigger for the change is important.  One trigger might be a well-respected and effective leader retiring or moving to an even more senior role.  This leaves a leadership gap which is an opportunity for someone to grow and develop.  Another trigger might be a less-respected  and ineffective leader moving on and leaving a trail of rather-too-visible failures. It is the latter tends to be associated with the New Broom effect.

<Lesley> How is that?

<Bob>Well, put yourself in the shoes of the New Leader who has inherited a Trail of Disappointment – you need to establish your authority and expectation quickly and decisively. Ambiguity and lack of clarity will only contribute to further disappointment.  So you have to ask everyone to justify what they do.  And if they cannot then you need to know that.  And if they can then you need to decide if what they do is aligned with your purpose.  This is the New Brush.

<Lesley> So what if I can justify what I do and that does not fit with the ‘New Leader’s Plan’?

<Bob> If what you do is aligned to your Life Purpose but not with the New Brush then you have to choose.  And experience shows that the road to long term personal happiness is the one the aligns with your individual purpose.  And often it is just a matter of timing. The New Brush is indiscriminate and impatient – anything that does not fit neatly into the New Plan has to go.

<Lesley> OK my purpose is to improve the safety, flow, quality and productivity of healthcare processes – for the benefit of all. That is not negotiable. It is what fires my passion and fuels my day.  So does it matter really where or how I do that?

<Bob> Not really.  You do need be mindful of the pragmatic constraints though … your life circumstances.  There are many paths to your Purpose, so it is wise to choose one that is low enough risk to both you and those you love.

<Lesley> Ah! Now I see why you say that timing is important. You need to prepare to be able to make the decision.  You do not what to be caught by surprise and off balance.

<Bob>Yes. That is why as an ISP you always start with your own Purpose and your own Right-2-Left Map®.  Then you will know what to prepare and in what order so that you have the maximum number of options when you have to make a choice.  Sometimes the Universe will create the trigger and sometimes you have to initiate it yourself.

<Lesley> So this is just another facet of Improvement Science?

<Bob>  Yes.

Posted on

Our Iceberg Is Melting

hold_your_ground_rope_300_wht_6223[Dring Dring] The telephone soundbite announced the start of the coaching session.

<Bob> Good morning Leslie. How are you today?

<Leslie> I have been better.

<Bob> You seem upset. Do you want to talk about it?

<Leslie> Yes, please. The trigger for my unhappiness is that last week I received an email demanding that I justify the time I spend doing improvement work and  a summons to a meeting to ‘discuss some issues that have been raised‘.

<Bob> OK. I take it that you do not know what or who has triggered this inquiry.

<Leslie> You are correct. My working hypothesis is that it is the end of the financial year and budget holders are looking for opportunities to do some pruning – to meet their cost improvement program targets!

<Bob> So what is the problem? You have shared the output of your work. You have demonstrated significant improvements in safety, flow, quality and productivity and you have described both them and the methodology clearly.

<Leslie> I know. That us why I was so upset to get this email. It is as if everything that we have achieved has been ignored. It is almost as if it is resented.

<Bob> Ah! You may well be correct.  This is the nature of paradigm shifts. Those who have the greatest vested interest in the current paradigm get spooked when they feel it start to wobble. Each time you share the outcome of your improvement work you create emotional shock-waves. The effects are cumulative and eventually there will be is a ‘crisis of confidence’ in those who feel most challenged by the changes that you are demonstrating are possible.  The whole process is well described in Thomas Kuhn’s The Structure of Scientific Revolutions. That is not a book for an impatient reader though – for those who prefer something lighter I recommend “Our Iceberg is Melting” by John Kotter.

<Leslie> Thanks Bob. I will get a copy of Kotter’s book – that sounds more my cup of tea. Will that tell me what to do?

<Bob> It is a parable – a fictional story of a colony of penguins who discover that their iceberg is melting and are suddenly faced with a new and urgent potential risk of not surviving the storms of the approaching winter. It is not a factual account of a real crisis or a step-by-step recipe book for solving all problems  – it describes some effective engagement strategies in general terms.

<Leslie> I will still read it. What I need is something more specific to my actual context.

<Bob> This is an improvement-by-design challenge. The only difference from the challenges you have done already is that this time the outcome you are looking for is a smooth transition from the ‘old’ paradigm to the ‘new’ one.  Kuhn showed that this transition will not start to happen until there is a new paradigm because individuals choose to take the step from the old to the new and they do not all do that at the same time.  Your work is demonstrating that there is a new paradigm. Some will love that message, some will hate it. Rather like Marmite.

<Leslie> Yes, that make sense.  But how do I deal with an unseen enemy who is stirring up trouble behind my back?

<Bob> Are you are referring to those who have ‘raised some issues‘?

<Leslie> Yes.

<Bob> They will be the ones who have most invested in the current status quo and they will not be in senior enough positions to challenge you directly so they are going around spooking the inner Chimps of those who can. This is expected behaviour when the relentlessly changing reality starts to wobble the concrete current paradigm.

<Leslie> Yes! That is  exactly how it feels.

<Bob> The danger lurking here is that your inner Chimp is getting spooked too and is conjuring up Gremlins and Goblins from the Computer! Left to itself your inner Chimp will steer you straight into the Victim Vortex.  So you need to take it for a long walk, let it scream and wave its hairy arms about, listen to it, and give it lots of bananas to calm it down. Then put your put your calmed-down Chimp into its cage and your ‘paradigm transition design’ into the Computer. Only then will you be ready for the ‘so-justify-yourself’ meeting.  At the meeting your Chimp will be out of its cage like a shot and interpreting everything as a threat. It will disable you and go straight to the Computer for what to do – and it will read your design and follow the ‘wise’ instructions that you have put in there.

<Leslie> Wow! I see how you are using the Chimp Paradox metaphor to describe an incredibly complex emotional process in really simple language. My inner Chimp is feeling happier already!

<Bob> And remember that you are in all in the same race. Your collective goal is to cross the finish line as quickly as possible with the least chaos, pain and cost.  You are not in a battle – that is lose-lose inner Chimp thinking.  The only message that your interrogators must get from you is ‘Win-win is possible and here is how we can do it‘. That will be the best way to soothe their inner Chimps – the ones who fear that you are going to sink their boat by rocking it.

<Leslie> That is really helpful. Thank you again Bob. My inner Chimp is now snoring gently in its cage and while it is asleep I have some Improvement-by-Design work to do and then some Computer programming.

Posted on

Miserable or Motivated?

stick_figure_scribble_pen_150_wht_6418[Beep Beep] The alarm on Bob’s smartphone was the reminder that in a few minutes his e-mentoring session with Lesley was due. Bob had just finished the e-mail he was composing so he sent it and then fired-up the Webex session. Lesley was already logged in and on line.

<Bob> Hi Lesley. What aspect of Improvement Science shall we talk about today? What is next on your map?

<Lesley> Hi Bob. Let me see. It looks like ‘Employee Engagement‘ is the one that we have explored least yet – and it links to lots of other things.

<Bob> OK. What would you say the average level of Employee Engagement is in your organisation at the moment? On a scale of zero to ten where zero is defined as ‘complete apathy’.

<Lesley> Good question. I see a wide range of engagement and I would say the average is about four out of ten.  There are some very visible, fully-engaged, energetic, action-focused  movers-and-shakers.  There are many more nearer the apathy end of the spectrum. Most employees seem to turn up, do their jobs well enough to avoid being disciplined, and then go home.

<Bob> OK. And do you feel that is a problem?

<Lesley> You betcha!  Improvement means change and change means action.  Disengaged employees are a deadweight. They do not actively block change – they will go along with it if pushed  – but they do not contribute to making it happen. And that creates a different problem. The movers-and-shakers get frustrated and eventually get tired trying to move the deadweight up hill and give up  and then can become increasingly critical and then cynical. After they give up in despair they then actively block any new ideas saying – “Do not try you will fail.”

<Bob> So how would you describe the emotional state of those you describe as “disengaged”?

<Lesley> Miserable.

<Bob> And who is making them feel miserable?

<Lesley> That is another good question. They appear to be making themselves feel miserable. And it is not what is happening that triggers this emotion. It is what is not happening. Apathy seems to be self-sustaining.

<Bob> Can you explain in a bit more about what you mean by that and maybe share an example?

<Lesley> An example is easier.  I have reflected on this a bit and I have used one of the 6M Design® techniques to help me understand it better.  I used a Right-2-Left® map to compare a personal example of when I felt really motivated and delivered a significant and measurable improvement; with one where I felt miserable and no change happened.

<Bob> Excellent. What did you discover?

<Lesley> I discovered that there were four classes of  difference between the two examples. And I then understood what you mean by ‘Acts and Errors of  Omission and Commission’.

<Bob> OK. And which was the commonest of the four combinations in your example?

<Lesley> The Errors of Omission. And within just that group there were three different types that were most obvious.

<Bob> Can you list them for me?

<Lesley> For sure. The first is the miserableness I felt when what I was doing felt to me that it was irrelevant. When what I was being asked to do had no worthwhile purpose that I was aware of.

<Bob> So which was it? No worth or not being aware of the worth?

<Lesley>Me not being aware of the worth. I hoped it was of value to someone higher up the corporate food chain otherwise I would not have been asked to do it! But I was never sure. And that uncertainty generated some questions. What if what I am doing is of no worth to anyone?  What if I am just wasting my lifetime doing it? That fearful thought left me feeling more miserable than motivated.

<Bob> OK. What was the second Error of Omission?

<Lesley> It is linked to the first one. I had no objective way of knowing if I was doing a worthwhile job.  And the word objective is important.  I am not asking for subjective feedback – there is too much expectation, variation, assumption, prejudgement and politics mixed up in opinions of what I achieve.  I needed specific, objective and timely feedback. I associated my feeling of miserableness with not getting objective feedback that told me what I was doing was making a worthwhile difference to someone else. Anyone else!

<Bob> I thought that you get a lot of objective feedback on a whole raft of organisational performance metrics?

<Lesley> Oh yes! We do!! The problem is that it is high level, aggregated, anonymous, and delayed. To get a copy of a report that says as an organisation we did or did not meet last quarters arbitrary performance target for x, y or z usually generates a ‘So what? How does that relate to what I do?’ reaction. I need objective, specific and timely feedback about the effects of my work. Good or bad.

<Bob> OK.  And Error of Omission Three?

<Lesley> This was the trickiest one to nail down. What it came down to was being treated as a process and not as a person.  I felt anonymous.  I was just  a headcount, a number on a payroll ledger, an overhead cost. That feeling was actually the most demotivating of all.

<Bob> And did it require all Three Errors of Omission to be present for the ‘miserableness’ to become manifest?

<Lesley> Alas no! Any one of them was enough. The more of them at the same time the deeper the feeling of misery the less motivated I felt.

<Bob> Thank you for being so frank and open. So what have you ‘abstracted’ from your ‘reflection’?

<Lesley> That employee engagement requires that these Three Errors of Omission must be deliberately checked for and proactively addressed if discovered.

<Bob> And who would, could or should do this check-and-correct work?

<Lesley> H’mm. Another very god question. The employee could do it but it is difficult for them because a lot of the purpose-setting and feedback comes from outside their circle of control and from higher up. Approaching  a line-manager with a list of their Errors of Omission will be too much of a challenge!

<Bob> So?

<Lesley> The manager should do it.  They should ask themselves these questions.  Only they can correct their  own Errors of Omission.  I doubt if that would happen spontaneously though! Humility seems a bit of a rare commodity.

<Bob> I agree. So what can the employee do to help their boss?

<Lesley> They could ask how they can be of most value to their boss and they could ask for objective and timely feedback on how well they are performing as an individual on those measures of worth. It sounds so simple and obvious when said out loud. So why does no one do it?

<Bob> A very good question. Some do and they are the often described as ‘motivating leaders’. So does this insight suggest to you any strategies for grasping the ‘Employee Engagement’ nettle without getting stung?

<Lesley> Yes indeed! I am already planning my next action. A chat with my line-manager about what I could do. Thanks Bob.

<Bob> My pleasure. And remember that the same principle works for everyone that we work directly with – especially those immediately ‘upstream’ and ‘downstream’ of us in our daily work.

Posted on

Jiggling

hurry_with_the_SFQP_kit[Dring] Bob’s laptop signaled the arrival of Leslie for their regular ISP remote coaching session.

<Bob> Hi Leslie. Thanks for emailing me with a long list of things to choose from. It looks like you have been having some challenging conversations.

<Leslie> Hi Bob. Yes indeed! The deepening gloom and the last few blog topics seem to be polarising opinion. Some are claiming it is all hopeless and others, perhaps out of desperation, are trying the FISH stuff for themselves and discovering that it works.  The ‘What Ifs’ are engaged in war of words with the ‘Yes Buts’.

<Bob> I like your metaphor! Where would you like to start on the long list of topics?

<Leslie> That is my problem. I do not know where to start. They all look equally important.

<Bob> So, first we need a way to prioritise the topics to get the horse-before-the-cart.

<Leslie> Sounds like a good plan to me!

<Bob> One of the problems with the traditional improvement approaches is that they seem to start at the most difficult point. They focus on ‘quality’ first – and to be fair that has been the mantra from the gurus like W.E.Deming. ‘Quality Improvement’ is the Holy Grail.

<Leslie>But quality IS important … are you saying they are wrong?

<Bob> Not at all. I am saying that it is not the place to start … it is actually the third step.

<Leslie>So what is the first step?

<Bob> Safety. Eliminating avoidable harm. Primum Non Nocere. The NoNos. The Never Events. The stuff that generates the most fear for everyone. The fear of failure.

<Leslie> You mean having a service that we can trust not to harm us unnecessarily?

<Bob> Yes. It is not a good idea to make an unsafe design more efficient – it will deliver even more cumulative harm!

<Leslie> OK. That makes perfect sense to me. So how do we do that?

<Bob> It does not actually matter.  Well-designed and thoroughly field-tested checklists have been proven to be very effective in the ‘ultra-safe’ industries like aerospace and nuclear.

<Leslie> OK. Something like the WHO Safe Surgery Checklist?

<Bob> Yes, that is a good example – and it is well worth reading Atul Gawande’s book about how that happened – “The Checklist Manifesto“.  Gawande is a surgeon who had published a lot on improvement and even so was quite skeptical that something as simple as a checklist could possibly work in the complex world of surgery. In his book he describes a number of personal ‘Ah Ha!’ moments that illustrate a phenomenon that I call Jiggling.

<Leslie> OK. I have made a note to read Checklist Manifesto and I am curious to learn more about Jiggling – but can we stick to the point? Does quality come after safety?

<Bob> Yes, but not immediately after. As I said, Quality is the third step.

<Leslie> So what is the second one?

<Bob> Flow.

There was a long pause – and just as Bob was about to check that the connection had not been lost – Leslie spoke.

<Leslie> But none of the Improvement Schools teach basic flow science.  They all focus on quality, waste and variation!

<Bob> I know. And attempting to improve quality before improving flow is like papering the walls before doing the plastering.  Quality cannot grow in a chaotic context. The flow must be smooth before that. And the fear of harm must be removed first.

<Leslie> So the ‘Improving Quality through Leadership‘ bandwagon that everyone is jumping on will not work?

<Bob> Well that depends on what the ‘Leaders’ are doing. If they are leading the way to learning how to design-for-safety and then design-for-flow then the bandwagon might be a wise choice. If they are only facilitating collaborative agreement and group-think then they may be making an unsafe and ineffective system more efficient which will steer it over the edge into faster decline.

<Leslie>So, if we can stabilize safety using checklists do we focus on flow next?

<Bob>Yup.

<Leslie> OK. That makes a lot of sense to me. So what is Jiggling?

<Bob> This is Jiggling. This conversation.

<Leslie> Ah, I see. I am jiggling my understanding through a series of ‘nudges’ from you.

<Bob>Yes. And when the learning cogs are a bit rusty, some Improvement Science Oil and a bit of Jiggling is more effective and much safer than whacking the caveman wetware with a big emotional hammer.

<Leslie>Well the conversation has certainly jiggled Safety-Flow-Quality-and-Productivity into a sensible order for me. That has helped a lot. I will sort my to-do list into that order and start at the beginning. Let me see. I have a plan for safety, now I can focus on flow. Here is my top flow niggle. How do I design the resource capacity I need to ensure the flow is smooth and the waiting times are short enough to avoid ‘persecution’ by the Target Time Police?

<Bob> An excellent question! I will send you the first ISP Brainteaser that will nudge us towards an answer to that question.

<Leslie> I am ready and waiting to have my brain-teased and my niggles-nudged!

Posted on

Sticks or Carrots?

boss_dangling_carrot_for_employee_anim_150_wht_13061[Beep Beep] Bob’s laptop signaled the arrival of Leslie to their regular Webex mentoring session. Bob picked up the phone and connected to the conference call.

<Bob> Hi Leslie, how are you today?

<Leslie> Great thanks Bob. I am sorry but that I do not have a red-hot burning issue to talk about today.

<Bob> OK – so your world is completely calm and orderly now. Excellent.

<Leslie> I wish! The reason is that I have been busy preparing for the monthly 1-2-1 with my boss.

<Bob> OK. So do you have a few minutes to talk about that?

<Leslie> What can I tell you about it?

<Bob> Can you just describe the purpose and the process for me?

<Leslie> OK. The purpose is improvement – for both the department and the individual. The process is that all departmental managers have an annual appraisal based on their monthly 1-2-1 chats and the performance scores for their departments are used to reward the top 15% and to ‘performance manage’ the bottom 15%.

<Bob> H’mmm.  What is the commonest emotion that is associated with this process?

<Leslie> I would say somewhere between severe anxiety and abject terror. No one looks forward to it. The annual appraisal feels like a lottery where the odds are stacked against you.

<Bob> Can you explain that a bit more for me?

<Leslie> Well, the most fear comes from being in the bottom 15% – the fear of being ‘handed your hat’ so to speak. Fortunately that fear motivates us to try harder and that usually saves us from the chopper because our performance improves.  The cost is the extra stress, working late and taking ‘stuff’ home.

<Bob> OK. And the anxiety?

<Leslie> Paradoxically that mostly comes from the top 15%. They are anxious to sustain their performance. Most do not and the Boss’s Golden Manager can crash spectacularly! We have seen it so often. It is almost as if being the Best carries a curse! So most of us try to stay in the middle of the pack where we do not stick out – a sort of safety in the herd strategy.  It is illogical I know because there is always a ‘top’ 15% and a ‘bottom’ 15%.

<Bob> You mentioned before that it feels like a lottery. How come?

<Leslie> Yes – it feels like a lottery but I know it has a rational scientific basis. Someone once showed me the ‘statistically significant evidence’ that proves it works.

<Bob> That what works exactly?

<Leslie> That sticks are more effective than carrots!

<Bob> Really! And what does the performance run charts look like – over the long term – say monthly over 2-3 years?

<Leslie> That is a really good question. They are surprisingly stable – well completely stable in fact. The wobble up and down of course but there is no sign of improvement over the long term – no trend. If anything it is the other way.

<Bob> So what is the rationale for maintaining the stick-is-better-than-the-carrot policy?

<Leslie> Ah! The message we are getting  is ‘as performance is not improving and sticks have been scientifically proven to be more effective than carrots then we will be using a bigger stick in future‘.

<Bob> Hence the atmosphere of fear and anxiety?

<Leslie> Exactly. But that is the way it must be I suppose.

<Bob> Actually it is not. This is an invalid design based on rubbish intuitive assumptions and statistical smoke-and-mirrors that creates unmeasurable emotional pain and destroys both people and organisations!

<Leslie> Wow! Bob! I have never heard you use language like that. You are usually so calm and reasonable. This must be really important!

 <Bob> It is – and for that reason I need to shock you out of your apathy  – and I can do that best by you proving it to yourself – scientifically – with a simple experiment. Are you up for that?

<Leslie> You betcha! This sounds like it is going to be interesting. I had better fasten my safety belt! The Nerve Curve awaits.

 The Stick-or-Carrot Experiment

<Bob> Here we go. You will need five coins, some squared-paper and a pencil. Coloured ones are even better.

<Leslie> OK. Does it matter what sort of coins?

<Bob> No. Any will do. Imagine you have four managers called A,B,C and D respectively.  Each month the performance of their department is measured as the number of organisational targets that they are above average on. Above average is like throwing a ‘head’, below average is like throwing a ‘tail’. There are five targets – hence the coins

<Leslie>OK. That makes sense – and it feels better to use the measured average – we have demonstrated that arbitrary performance targets are dangers – especially when imposed blindly across all departments.

<Bob> Indeed. So can you design a score sheet to track the data for the experiment.

<Leslie>Give me a minute.  Will this suffice?

Stick_and_Carrot_Fig1<Bob> Perfect! Now simulate a month by tossing all five coins – once for each manager – and record the outcome of each as H to T , then tot up the number of heads for each manager.

<Leslie>  OK … here is what I got.

Stick_and_Carrot_Fig2<Bob>Good. Now repeat this 11 more times to give you the results for a whole year.  In the n(Heads) column colour the boxes that have scores of zero or one as red – these are the Losers. Then colour the boxes that have 4 or 5 as green – these are the Winners.

<Leslie>OK, that will take me a few minutes – do you want to get a coffee or something.

[Five minutes later]

Here you go. That gives 96 opportunities to win or lose and I counted 9 Losers and 9 Winners so just under 20% for each. The majority were in the unexceptional middle. The herd.

Stick_and_Carrot_Fig3<Bob> Excellent.  A useful way to visualise this is using a Tally chart. Just run down the column of n(Heads) and create the Tally chart as you go. This is one of the oldest forms of counting in existence. There are fossil records that show Tally charts being used thousands of years ago.

<Leslie> I think I understand what you mean. We do not wait until all the data is in then draw the chart, we update it as we go along – as the data comes in.

<Bob> Spot on!

<Leslie> Let me see. Wow! That is so cool!  I can see the pattern appearing almost magically – and the more data I have the clearer the pattern is.

 <Bob>Can you show me?

<Leslie> Here we go.

Stick_and_Carrot_Fig4<Bob> Good.  This is the expected picture. If you repeated this many times you would get the same general pattern with more 2 and 3 scores.

Now I want you to do an experiment.

Assume each manager that is classed as a Winner in one month is given a reward – a ‘pat on the back’ from their Boss. And each manager that is classed as a Loser is given a ‘written warning’. Now look for  the effect that this has.

<Leslie> But we are using coins – which means the outcome is just a matter of chance! It is a lottery.

<Bob> I know that and you know that but let us assume that the Boss believes that the monthly feedback has an effect. The experiment we are doing is to compare the effect of the carrot with the stick. The Boss wants to know which results in more improvement and to know that with scientific and statistical confidence!

<Leslie> OK. So what I will do is look at the score the following month for each manager that was either a Winner or a  Loser; work out the difference, and then calculate the average of those differences and compare them with each other. That feels suitably scientific!

<Bob> OK. What do you get.

<Leslie> Just a minute, I need to do this carefully. OK – here it is.

<Bob>Stick_and_Carrot_Fig5 Excellent.  Just eye-balling the ‘Measured improvement after feedback’ columns I would say the Losers have improved and the Winners have deteriorated!

<Leslie> Yes! And the Losers have improved by 1.29 on average and the Winners have deteriorated by 1.78 – and that is a big difference for such small sample. I am sure that with enough data this would be a statistically significant difference! So it is true, sticks work better than carrots!

<Bob>Not so fast. What you are seeing is a completely expected behaviour called “Regression to the Mean“. Remember we know that the score for each manager each month is the result of a game of chance, a coin toss, a lottery. So no amount of stick or carrot feedback is going to influence that.

<Leslie>But the data is saying there is a difference! And that feels like the experience we have – and why fear stalks the management corridors. This is really confusing!

<Bob>Remember that confusion arises from invalid or conflicting unconscious assumptions. There is a flaw in the statistical design of this experiment. The ‘obvious’ conclusion is invalid because of this flaw. And do not be too hard on yourself. The flaw eluded mathematicians for centuries. But now you know there is one can you find it?

<Leslie>OMG!  The use of the average to classify the managers into Winners or Losers is the flaw!  That is just a lottery. Who the managers are is irrelevant. This is just a demonstration of how chance works.

But that means … OMG!  If the conclusion is invalid then sticks are not better than carrots and we have been brain-washed for decades into accepting a performance management system that is invalid – and worse still is used to ‘scientifically’ justify systematic persecution! I can see now why you get so angry!

<Bob>Bravo Leslie.  We  need to check your understanding. Does that mean carrots are better than sticks?

<Leslie>No!  The conclusion is invalid because the assumptions are invalid and the design is fatally flawed. It does not matter what the conclusion actually is.

<Bob>Excellent. So what conclusion can you draw?

<Leslie>That this short-term carrot-or-stick feedback design for achieving improvement in a stable system  is both ineffective and emotionally damaging. In fact it could well be achieving precisely the opposite effect that it is intended to. It may be preventing improvement! But the story feels so plausible and the data appears to back it up. What is happening here is we are using statistical smoke-and-mirrors to justify what we have already decided – and only an true expert would spot the flaw! Once again our intuition has tricked us!

<Bob>Well done! And with this new insight – how would you do it differently?  What would be a better design?

<Leslie>That is a very good question. I am going to have to think about that – before my 1-2-1 tomorrow. I wonder what might happen if I show this demonstration to my Boss? Thanks Bob, as always … lots of food for thought.

Posted on

The Time Trap

clock_hands_spinning_import_150_wht_3149[Hmmmmmm]

The desk amplified the vibration of Bob’s smartphone as it signaled the time for his planned e-mentoring session with Leslie.

<Bob> Hi Leslie, right-on-time, how are you today?

<Leslie> Good thanks Bob. I have a specific topic to explore if that is OK. Can we talk about time traps.

<Bob> OK – do you have a specific reason for choosing that topic?

<Leslie> Yes. The blog last week about ‘Recipe for Chaos‘ set me thinking and I remembered that time-traps were mentioned in the FISH course but I confess, at the time, I did not understand them. I still do not.

<Bob> Can you describe how the ‘Recipe for Chaos‘ blog triggered this renewed interest in time-traps?

<Leslie> Yes – the question that occurred to me was: ‘Is a time-trap a recipe for chaos?’

<Bob> A very good question! What do you feel the answer is?

<Leslie> I feel that time-traps can and do trigger chaos but I cannot explain how. I feel confused.

<Bob> Your intuition is spot on – so can you localize the source of your confusion?

<Leslie> OK. I will try. I confess I got the answer to the MCQ correct by guessing – and I wrote down the answer when I eventually guessed correctly – but I did not understand it.

<Bob> What did you write down?

<Leslie> “The lead time is independent of the flow”.

<Bob> OK. That is accurate – though I agree it is perhaps a bit abstract. One source of confusion may be that there are different causes of time-traps and there is a lot of overlap with other chaos-creating policies. Do you have a specific example we can use to connect theory with reality?

<Leslie> OK – that might explain my confusion.  The example that jumped to mind is the RTT target.

<Bob> RTT?

<Leslie> Oops – sorry – I know I should not use undefined abbreviations. Referral to Treatment Time.

<Bob> OK – can you describe what you have mapped and measured already?

<Leslie> Yes.  When I plot the lead-time for patients in date-of-treatment order the process looks stable but the histogram is multi-modal with a big spike just underneath the RTT target of 18 weeks. What you describe as the ‘Horned Gaussian’ – the sign that the performance target is distorting the behaviour of the system and the design of the system is not capable on its own.

<Bob> OK, and have you investigated why there is not just one spike?

<Leslie> Yes – the factor that best explains that is the ‘priority’ of the referral.  The  ‘urgents’ jump in front of the ‘soons’ and both jump in front of the ‘routines’. The chart has three overlapping spikes.

<Bob> That sounds like a reasonable policy for mixed-priority demand. So what is the problem?

<Leslie> The ‘Routine’ group is the one that clusters just underneath the target. The lead time for routines is almost constant but most of the time those patients sit in one queue or another being leap-frogged by other higher-priority patients. Until they become high-priority – then they do the leap frogging.

<Bob> OK – and what is the condition for a time trap again?

<Leslie> That the lead time is independent of flow.

<Bob> Which implies?

<Leslie> Um. Let me think. That the flow can be varying but the lead time stays the same?

<Bob> Yup. So is the flow of routine referrals varying?

<Leslie> Not over the long term. The chart is stable.

<Bob> What about over the short term? Is demand constant?

<Leslie> No of course not – it varies – but that is expected for all systems. Constant means ‘over-smoothed data’ – the Flaw of Averages trap!

<Bob> OK. And how close is the average lead time for routines to the RTT maximum allowable target?

<Leslie> Ah! I see what you mean. The average is about 17 weeks and the target is 18 weeks.

<Bob> So, what is the flow variation on a week-to-week time scale?

<Leslie> Demand or Activity?

<Bob> Both.

<Leslie> H’mm – give me a minute to re-plot flow as a weekly-aggregated chart. Oh! I see what you mean – both the weekly activity and demand are both varying widely and they are not in sync with each other. Work in progress must be wobbling up and down a lot! So how can the lead time variation be so low?

<Bob> What do the flow histograms look like?

<Leslie> Um. Just a second. That is weird! They are both bi-modal with peaks at the extremes and not much in the middle – the exact opposite of what I expected to see! I expected a centered peak.

<Bob> What you are looking at is the characteristic flow fingerprint of a chaotic system – it is called ‘thrashing’.

<Leslie> So, I was right!

<Bob> Yes. And now you know the characteristic pattern to look for. So, what is the policy design flaw here?

<Leslie> The DRAT – the delusional ratio and arbitrary target?

<Bob> That is part of it – that is the external driver policy. The one you cannot change easily. What is the internally driven policy? The reaction to the DRAT?

<Leslie> The policy of leaving routine patients until they are about to breach then re-classifying them as ‘urgent’.

<Bob> Yes! It is called a ‘Prevarication Policy’ and it is surprisingly and uncomfortably common. Ask yourself – do you ever prevaricate? Do you ever put off ‘lower priority’ tasks until later and then not fill the time freed up with ‘higher priority tasks’?

<Leslie> OMG! I do that all the time! I put low priority and unexciting jobs on a ‘to do later’ heap but I do not sit idle – I do then focus on the high priority ones.

<Bob> High priority for whom?

<Leslie> Ah! I see what you mean. High priority for me. The ones that give me the biggest reward! The fun stuff or the stuff that I get a pat on the back for doing or that I feel good about.

<Bob> And what happens?

<Leslie> The heap of ‘no-fun-for-me-to-do’ jobs gets bigger and I await the ‘reminders’ and then have to rush round in a mad panic to avoid disappointment, criticism and blame. It feels chaotic. I get grumpy. I make more mistakes and I deliver lower-quality work. If I do not get a reminder I assume that the job was not that urgent after all and if I am challenged I claim I am too busy doing the other stuff.

<Bob> And have you avoided disappointment?

<Leslie> Ah! No – that I needed to be reminded meant that I had already disappointed. And when I do not get a reminded does not prove I have not disappointed either. Most people blame rather than complain. I have just managed to erode other people’s trust in my reliability. I have disappointed myself. I have achieved exactly the opposite of what I intended. Drat!

<Bob> So, what is the reason that you work this way? There will be a reason.  A good reason.

<Leslie> That is a very good question! I will reflect on that because I believe it will help me understand why others behave this way too.

<Bob> OK – I will be interested to hear your conclusion.  Let us return to the question. What is the  downside of a ‘Prevarication Policy’?

<Leslie> It creates stress, chaos, fire-fighting, last minute changes, increased risk of errors,  more work and it erodes both quality, confidence and trust.

<Bob> Indeed so – and the impact on productivity?

<Leslie> The activity falls, the system productivity falls, revenue falls, queues increase, waiting times increase and the chaos increases!

<Bob> And?

<Leslie> We treat the symptoms by throwing resources at the problem – waiting list initiatives – and that pushes our costs up. Either way we are heading into a spiral of decline and disappointment. We do not address the root cause.

<Bob> So what is the way out of chaos?

<Leslie> Reduce the volume on the destabilizing feedback loop? Stop the managers meddling!

<Bob> Or?

<Leslie> Eh? I do not understand what you mean. The blog last week said management meddling was the problem.

<Bob> It is a problem. How many feedback loops are there?

<Leslie> Two – that need to be balanced.

<Bob> So, what is another option?

<Leslie> OMG! I see. Turn UP the volume of the stabilizing feedback loop!

<Bob> Yup. And that is a lot easier to do in reality. So, that is your other challenge to reflect on this week. And I am delighted to hear you using the terms ‘stabilizing feedback loop’ and ‘destabilizing feedback loop’.

<Leslie> Thank you. That was a lesson for me after last week – when I used the terms ‘positive and negative feedback’ it was interpreted in the emotional context – positive feedback as encouragement and negative feedback as criticism.  So ‘reducing positive feedback’ in that sense is the exact opposite of what I was intending. So I switched my language to using ‘stabilizing and destabilizing’ feedback loops that are much less ambiguous and the confusion and conflict disappeared.

<Bob> That is very useful learning Leslie … I think I need to emphasize that distinction more in the blog. That is one advantage of online media – it can be updated!

 <Leslie> Thanks again Bob!  And I have the perfect opportunity to test a new no-prevarication-policy design – in part of the system that I have complete control over – me!

Posted on

Space-and-Time

line_figure_phone_400_wht_9858<Lesley>Hi Bob! How are you today?

<Bob>OK thanks Lesley. And you?

<Lesley>I am looking forward to our conversation. I have two questions this week.

<Bob>OK. What is the first one?

<Lesley>You have taught me that improvement-by-design starts with the “purpose” question and that makes sense to me. But when I ask that question in a session I get an “eh?” reaction and I get nowhere.

<Bob>Quod facere bonum opus et quomodo te cognovi unum?

<Lesley>Eh?

<Bob>I asked you a purpose question.

<Lesley>Did you? What language is that? Latin? I do not understand Latin.

<Bob>So although you recognize the language you do not understand what I asked, the words have no meaning. So you are unable to answer my question and your reaction is “eh?”. I suspect the same is happening with your audience. Who are they?

<Lesley>Front-line clinicians and managers who have come to me to ask how to solve their problems. There Niggles. They want a how-to-recipe and they want it yesterday!

<Bob>OK. Remember the Temperament Treacle conversation last week. What is the commonest Myers-Briggs Type preference in your audience?

<Lesley>It is xSTJ – tough minded Guardians.  We did that exercise. It was good fun! Lots of OMG moments!

<Bob>OK – is your “purpose” question framed in a language that the xSTJ preference will understand naturally?

<Lesley>Ah! Probably not! The “purpose” question is future-focused, conceptual , strategic, value-loaded and subjective.

<Bob>Indeed – it is an iNtuitor question. xNTx or xNFx. Pose that question to a roomful of academics or executives and they will debate it ad infinitum.

<Lesley>More Latin – but that phrase I understand. You are right.  And my own preference is xNTP so I need to translate my xNTP “purpose” question into their xSTJ language?

<Bob>Yes. And what language do they use?

<Lesley>The language of facts, figures, jobs-to-do, work-schedules, targets, budgets, rational, logical, problem-solving, tough-decisions, and action-plans. Objective, pragmatic, necessary stuff that keep the operational-wheels-turning.

<Bob>OK – so what would “purpose” look like in xSTJ language?

<Lesley>Um. Good question. Let me start at the beginning. They came to me in desperation because they are now scared enough to ask for help.

<Bob>Scared of what?

<Lesley>Unintentionally failing. They do not want to fail and they do not need beating with sticks. They are tough enough on themselves and each other.

<Bob>OK that is part of their purpose. The “Avoid” part. The bit they do not want. What do they want? What is the “Achieve” part? What is their “Nice If”?

<Lesley>To do a good job.

<Bob>Yes. And that is what I asked you – but in an unfamiliar language. Translated into English I asked “What is a good job and how do you know you are doing one?”

<Lesley>Ah ha! That is it! That is the question I need to ask. And that links in the first map – The 4N Chart®. And it links in measurement, time-series charts and BaseLine© too. Wow!

<Bob>OK. So what is your second question?

<Lesley>Oh yes! I keep getting asked “How do we work out how much extra capacity we need?” and I answer “I doubt that you need any more capacity.”

<Bob>And their response is?

<Lesley>Anger and frustration! They say “That is obvious rubbish! We have a constant stream of complaints from patients about waiting too long and we are all maxed out so of course we need more capacity! We just need to know the minimum we can get away with – the what, where and when so we can work out how much it will cost for the business case.”

<Bob>OK. So what do they mean by the word “capacity”. And what do you mean?

<Lesley>Capacity to do a good job?

<Bob>Very quick! Ho ho! That is a bit imprecise and subjective for a process designer though. The Laws of Physics need the terms “capacity”, “good” and “job” clearly defined – with units of measurement that are meaningful.

<Lesley>OK. Let us define “good” as “delivered on time” and “job” as “a patient with a health problem”.

<Bob>OK. So how do we define and measure capacity? What are the units of measurement?

<Lesley>Ah yes – I see what you mean. We touched on that in FISH but did not go into much depth.

<Bob>Now we dig deeper.

<Lesley>OK. FISH talks about three interdependent forms of capacity: flow-capacity, resource-capacity, and space-capacity.

<Bob>Yes. They are the space-and-time capacities. If we are too loose with our use of these and treat them as interchangeable then we will create the confusion and conflict that you have experienced. What are the units of measurement of each?

<Lesley>Um. Flow-capacity will be in the same units as flow, the same units as demand and activity – tasks per unit time.

<Bob>Yes. Good. And space-capacity?

<Lesley>That will be in the same units as work in progress or inventory – tasks.

<Bob>Good! And what about resource-capacity?

<Lesley>Um – Will that be resource-time – so time?

<Bob>Actually it is resource-time per unit time. So they have different units of measurement. It is invalid to mix them up any-old-way. It would be meaningless to add them for example.

<Lesley>OK. So I cannot see how to create a valid combination from these three! I cannot get the units of measurement to work.

<Bob>This is a critical insight. So what does that mean?

<Lesley>There is something missing?

<Bob>Yes. Excellent! Your homework this week is to work out what the missing pieces of the capacity-jigsaw are.

<Lesley>You are not going to tell me the answer?

<Bob>Nope. You are doing ISP training now. You already know enough to work it out.

<Lesley>OK. Now you have got me thinking. I like it. Until next week then.

<Bob>Have a good week.

Posted on

The Mirror

mirror_mirror[Dring Dring]

The phone announced the arrival of Leslie for the weekly ISP mentoring conversation with Bob.

<Leslie> Hi Bob.

<Bob> Hi Leslie. What would you like to talk about today?

<Leslie> A new challenge – one that I have not encountered before.

<Bob>Excellent. As ever you have pricked my curiosity. Tell me more.

<Leslie> OK. Up until very recently whenever I have demonstrated the results of our improvement work to individuals or groups the usual response has been “Yes, but“. The habitual discount as you call it. “Yes, but your service is simpler; Yes, but your budget is bigger; Yes, but your staff are less militant.” I have learned to expect it so I do not get angry any more.

<Bob> OK. The mantra of the skeptics is to be expected and you have learned to stay calm and maintain respect. So what is the new challenge?

<Leslie>There are two parts to it.  Firstly, because the habitual discounting is such an effective barrier to diffusion of learning;  our system has not changed; the performance is steadily deteriorating; the chaos is worsening and everything that is ‘obvious’ has been tried and has not worked. More red lights are flashing on the patient-harm dashboard and the Inspectors are on their way. There is an increasing  turnover of staff at all levels – including Executive.  There is an anguished call for “A return to compassion first” and “A search for new leaders” and “A cultural transformation“.

<Bob> OK. It sounds like the tipping point of awareness has been reached, enough people now appreciate that their platform is burning and radical change of strategy is required to avoid the ship sinking and them all drowning. What is the second part?

<Leslie> I am getting more emails along the line of “What would you do?”

<Bob> And your reply?

<Leslie> I say that I do not know because I do not have a diagnosis of the cause of the problem. I do know a lot of possible causes but I do not know which plausible ones are the actual ones.

<Bob> That is a good answer.  What was the response?

<Leslie>The commonest one is “Yes, but you have shown us that Plan-Do-Study-Act is the way to improve – and we have tried that and it does not work for us. So we think that improvement science is just more snake oil!”

<Bob>Ah ha. And how do you feel about that?

<Leslie>I have learned the hard way to respect the opinion of skeptics. PDSA does work for me but not for them. And I do not understand why that is. I would like to conclude that they are not doing it right but that is just discounting them and I am wary of doing that.

<Bob>OK. You are wise to be wary. We have reached what I call the Mirror-on-the-Wall moment.  Let me ask what your understanding of the history of PDSA is?

<Leslie>It was called Plan-Do-Check-Act by Walter Shewhart in the 1930’s and was presented as a form of the scientific method that could be applied on the factory floor to improving the quality of manufactured products.  W Edwards Deming modified it to PDSA where the “Check” was changed to “Study”.  Since then it has been the key tool in the improvement toolbox.

<Bob>Good. That is an excellent summary.  What the Zealots do not talk about are the limitations of their wonder-tool.  Perhaps that is because they believe it has no limitations.  Your experience would seem to suggest otherwise though.

<Leslie>Spot on Bob. I have a nagging doubt that I am missing something here. And not just me.

<Bob>The reason PDSA works for you is because you are using it for the purpose it was designed for: incremental improvement of small bits of the big system; the steps; the points where the streams cross the stages.  You are using your FISH training to come up with change plans that will work because you understand the Physics of Flow better. You make wise improvement decisions.  In fact you are using PDSA in two separate modes: discovery mode and delivery mode.  In discovery mode we use the Study phase to build your competence – and we learn most when what happens is not what we expected.  In delivery mode we use the Study phase to build our confidence – and that grows most when what happens is what we predicted.

<Leslie>Yes, that makes sense. I see the two modes clearly now you have framed it that way – and I see that I am doing both at the same time, almost by second nature.

<Bob>Yes – so when you demonstrate it you describe PDSA generically – not as two complimentary but contrasting modes. And by demonstrating success you omit to show that there are some design challenges that cannot be solved with either mode.  That hidden gap attracts some of the “Yes, but” reactions.

<Leslie>Do you mean the challenges that others are trying to solve and failing?

<Bob>Yes. The commonest error is to discount the value of improvement science in general; so nothing is done and the inevitable crisis happens because the system design is increasingly unfit for the evolving needs.  The toast is not just burned it is on fire and is now too late to  use the discovery mode of PDSA because prompt and effective action is needed.  So the delivery mode of PDSA is applied to a emergent, ill-understood crisis. The Plan is created using invalid assumptions and guesswork so it is fundamentally flawed and the Do then just makes the chaos worse.  In the ensuing panic the Study and Act steps are skipped so all hope of learning is lost and and a vicious and damaging spiral of knee-jerk Plan-Do-Plan-Do follows. The chaos worsens, quality falls, safety falls, confidence falls, trust falls, expectation falls and depression and despair increase.

<Leslie>That is exactly what is happening and why I feel powerless to help. What do I do?

<Bob>The toughest bit is past. You have looked squarely in the mirror and can now see harsh reality rather than hasty rhetoric. Now you can look out of the window with different eyes.  And you are now looking for a real-world example of where complex problems are solved effectively and efficiently. Can you think of one?

<Leslie>Well medicine is one that jumps to mind.  Solving a complex, emergent clinical problems requires a clear diagnosis and prompt and effective action to stabilise the patient and then to cure the underlying cause: the disease.

<Bob>An excellent example. Can you describe what happens as a PDSA sequence?

<Leslie>That is a really interesting question.  I can say for starters that it does not start with P – we have learned are not to have a preconceived idea of what to do at the start because it badly distorts our clinical judgement.  The first thing we do is assess the patient to see how sick and unstable they are – we use the Vital Signs. So that means that we decide to Act first and our first action is to Study the patient.

<Bob>OK – what happens next?

<Leslie>Then we will do whatever is needed to stabilise the patient based on what we have observed – it is called resuscitation – and only then we can plan how we will establish the diagnosis; the root cause of the crisis.

<Bob> So what does that spell?

<Leslie> A-S-D-P.  It is the exact opposite of P-D-S-A … the mirror image!

<Bob>Yes. Now consider the treatment that addresses the root cause and that cures the patient. What happens then?

<Leslie>We use the diagnosis is used to create a treatment Plan for the specific patient; we then Do that, and we Study the effect of the treatment in that specific patient, using our various charts to compare what actually happens with what we predicted would happen. Then we decide what to do next: the final action.  We may stop because we have achieved our goal, or repeat the whole cycle to achieve further improvement. So that is our old friend P-D-S-A.

<Bob>Yes. And what links the two bits together … what is the bit in the middle?

<Leslie>Once we have a diagnosis we look up the appropriate treatment options that have been proven to work through research trials and experience; and we tailor the treatment to the specific patient. Oh I see! The missing link is design. We design a specific treatment plan using generic principles.

<Bob>Yup.  The design step is the jam in the improvement sandwich and it acts like a mirror: A-S-D-P is reflected back as P-D-S-A

<Leslie>So I need to teach this backwards: P-D-S-A and then Design and then A-S-P-D!

<Bob>Yup – and you know that by another name.

<Leslie> 6M Design®! That is what my Improvement Science Practitioner course is all about.

<Bob> Yup.

<Leslie> If you had told me that at the start it would not have made much sense – it would just have confused me.

<Bob>I know. That is the reason I did not. The Mirror needs to be discovered in order for the true value to appreciated. At the start we look in the mirror and perceive what we want to see. We have to learn to see what is actually there. Us. Now you can see clearly where P-D-S-A and Design fit together and the missing A-S-D-P component that is needed to assemble a 6M Design® engine. That is Improvement-by-Design in a nine-letter nutshell.

<Leslie> Wow! I can’t wait to share this.

<Bob> And what do you expect the response to be?

<Leslie>”Yes, but”?

<Bob> From the die hard skeptics – yes. It is the ones who do not say “Yes, but” that you want to engage with. The ones who are quiet. It is always the quiet ones that hold the key.

Posted on

The Victim Vortex

[Beep Beep] Bob tapped the “Answer” button on his smartphone – it was Lesley calling in for their regular ISP coaching session.

<Bob>Hi Lesley. How are you today? And which tunnel in the ISP Learning Labyrinth shall we explore today?

<Lesley>Hi Bob. I am OK thank you. Can we invest some time in the Engagement Maze?

<Bob>OK. Do you have a specific example?

<Lesley>Sort of. This week I had a conversation with our Chief Executive about the potential of Improvement Science and the reply I got was “I am convinced by what you say but it is your colleagues who need to engage. If you have not succeeded in convincing them then how can I?” I was surprised by that response and slightly niggled because it had an uncomfortable nugget of truth in it.

<Bob>That sounds like the wisdom of a leader who understands that the “power” to make things happen does not sit wholly in the lap of those charged with accountability.

<Lesley> I agree.  And at the same time everything that the “Top Team” suggest gets shot down in flames by a small and very vocal group of my more skeptical colleagues.

<Bob>Ah ha!  It sounds like the Victim Vortex is causing trouble here.

<Lesley>The Victim Vortex?

<Bob>Yes.  Let me give you an example.  One of the common initiators of the Victim Vortex is the data flow part of a complex system design.  The Sixth Flow.  So can I ask you: “How are new information systems developed in your organization?“

<Lesley>Wow!  You hit the nail on the head first time!  Just this week there has been another firestorm of angry emails triggered by yet another silver-bullet IT system being foisted on us!

<Bob>Interesting use of language Lesley.  You sound quite “niggled”.

<Lesley>I am.  Not by the constant “drizzle of IT magic” – that is irritating enough – but more by the vehemently cynical reaction of my peers.

<Bob>OK.  This sounds like good enough example of the Victim Vortex.  What do you expect the outcome will be?

<Lesley>Well, if past experience is a predictor for future performance – an expensive failure, more frustration and a deeper well of cynicism.

<Bob>Frustrating for whom?

<Lesley>Everyone.  The IT department as well.  It feels like we are all being sucked into a lose-lose-lose black hole of depression and despair!

<Bob>A very good description of the Victim Vortex.

<Lesley>So the Victim Vortex is an example of the Drama Triangle acting on an organizational level?

tornada_150_wht_10155<Bob>Yes. Visualize a cultural tornado.  The energy that drives it is the emotional  currency spent in playing the OK – Not OK Games.  It is a self-fueling system, a stable design, very destructive and very resistant to change.

<Lesley>That metaphor works really well for me!

<Bob>A similar one is a whirlpool – a water vortex.  If you were out swimming and were caught up in a whirlpool what are your exit strategy options?

<Lesley>An interesting question.  I have never had that experience and would not want it – it sounds rather hazardous.  Let me think.  If I do nothing I will just get swept around in the chaos and I am at risk of  getting bashed, bruised and then sucked under.

<Bob>Yes – you would probably spend all your time and energy just treading water and dodging the flotsam and jetsam that has been sucked into the Vortex.  That is what most people do.  It is called the Hamster Wheel effect.

<Lesley>So another option is to actively swim towards the middle of the Vortex – the end would at least be quick! But that is giving up and adopting the Hopelessness attitude of burned out Victim.  That would be the equivalent of taking voluntary redundancy or early retirement.  It is not my style!

<Bob>Yes.  It does not solve the problem either.  The Vortex is always hoovering up new Victims.  It is insatiable.

<Lesley> And another option would be to swim with the flow to avoid being “got” from behind.  That would be seem sensible and is possible; and at least I would feel better for doing something. I might even escape if I swim fast enough!

<Bob>That is indeed what some try.  The movers and shakers.  The pace setters.  The optimists.  The extrovert leaders.  The problem is that it makes the Vortex spin even faster.  It actually makes the Vortex bigger,  more chaotic and more dangerous than before.

<Lesley>Yes – I can see that.  So my other option is to swim against the flow in an attempt to slow the Vortex down.  Would that work?

<Bob>If everyone did that at the same time it might but that is unlikely to happen spontaneously.  If you could achieve that degree of action alignment you would not have a Victim Vortex in the first place.  Trying to do it alone is ineffective, you tire very quickly, the other Victims bash into you, you slow them down, and then you all get sucked down the Plughole of Despair.

<Lesley>And I suppose a small group of like-minded champions who try to swim-against the flow might last longer if they stick together but even then eventually they would get bashed up and broken up too.  I have seen that happen.  And that is probably where our team are heading at the moment.  I am out of options.  Is it impossible to escape the Victim Vortex?

<Bob>There is one more direction you can swim.

<Lesley>Um?  You mean across the flow heading directly away from the center?

<Bob>Exactly.  Consider that option.

<Lesley>Well, it would still be hard work and I would still be going around with the Vortex and I would still need to watch out for flotsam but every stroke I make would take me further from the center.  The chaos would get gradually less and eventually I would be in clear water and out of danger.  I could escape the Victim Vortex!

<Bob>Yes. And what would happen if others saw you do that and did the same?

<Lesley>The Victim Vortex would dissipate!

<Bob>Yes.  So that is your best strategy.  It is a win-win-win strategy too. You can lead others out of the Victim Vortex.

<Lesley>Wow!  That is so cool!  So how would I apply that metaphor to the Information System niggle?

<Bob>I will leave you to ponder on that.  Think about it as a design assignment.  The design of the system that generates IT solutions that are fit-for-purpose.

<Lesley> Somehow I knew you were going to say that!  I have my squared-paper and sharpened pencil at the ready.  Yes – an improvement-by-design assignment.  Thank you once again Bob.  This ISP course is the business!

Posted on

DRAT!

[Bing Bong]  The sound bite heralded Leslie joining the regular Improvement Science mentoring session with Bob.  They were now using web-technology to run virtual meetings because it allows a richer conversation and saves a lot of time. It is a big improvement.

<Bob> Hi Lesley, how are you today?

<Leslie> OK thank you Bob.  I have a thorny issue to ask you about today. It has been niggling me even since we started to share the experience we are gaining from our current improvement-by-design project.

<Bob> OK. That sounds interesting. Can you paint the picture for me?

<Leslie> Better than that – I can show you the picture, I will share my screen with you.

DRAT_01 <Bob> OK. I can see that RAG table. Can you give me a bit more context?

<Leslie> Yes. This is how our performance management team have been asked to produce their 4-weekly reports for the monthly performance committee meetings.

<Bob> OK. I assume the “Period” means sequential four week periods … so what is Count, Fail and Fail%?

<Leslie> Count is the number of discharges in that 4 week period, Fail is the number whose length of stay is longer than the target, and Fail% is the ratio of Fail/Count for each 4 week period.

<Bob> It looks odd that the counts are all 28.  Is there some form of admission slot carve-out policy?

<Leslie> Yes. There is one admission slot per day for this particular stream – that has been worked out from the average historical activity.

<Bob> Ah! And the Red, Amber, Green indicates what?

<Leslie> That is depends where the Fail% falls in a set of predefined target ranges; less than 5% is green, 5-10% is Amber and more than 10% is red.

<Bob> OK. So what is the niggle?

<Leslie>Each month when we are in the green we get no feedback – a deafening silence. Each month we are in amber we get a warning email.  Each month we are in the red we have to “go and explain ourselves” and provide a “back-on-track” plan.

<Bob> Let me guess – this feedback design is not helping much.

<Leslie> It is worse than that – it creates a perpetual sense of fear. The risk of breaching the target is distorting people’s priorities and their behaviour.

<Bob> Do you have any evidence of that?

<Leslie> Yes – but it is anecdotal.  There is a daily operational meeting and the highest priority topic is “Which patients are closest to the target length of stay and therefore need to have their  discharge expedited?“.

<Bob> Ah yes.  The “target tail wagging the quality dog” problem. So what is your question?

<Leslie> How do we focus on the cause of the problem rather than the symptoms?  We want to be rid of the “fear of the stick”.

<Bob> OK. What you have hear is a very common system design flaw. It is called a DRAT.

<Leslie> DRAT?

<Bob> “Delusional Ratio and Arbitrary Target”.

<Leslie> Ha! That sounds spot on!  “DRAT” is what we say every time we miss the target!

<Bob> Indeed.  So first plot this yield data as a time series chart.

<Leslie> Here we go.

DRAT_02<Bob>Good. I see you have added the cut-off thresholds for the RAG chart. These 5% and 10% thresholds are arbitrary and the data shows your current system is unable to meet them. Your design looks incapable.

<Leslie>Yes – and it also shows that the % expressed to one decimal place is meaningless because there are limited possibilities for the value.

<Bob> Yes. These are two reasons that this is a Delusional Ratio; there are quite a few more.

DRAT_03<Leslie> OK  and if I plot this as an Individuals charts I can see that this variation is not exceptional.

<Bob> Careful Leslie. It can be dangerous to do this: an Individuals chart of aggregate yield becomes quite insensitive with aggregated counts of relatively rare events, a small number of levels that go down to zero, and a limited number of points.  The SPC zealots are compounding the problem and plotting this data as a C-chart or a P-chart makes no difference.

This is all the effect of the common practice of applying  an arbitrary performance target then counting the failures and using that as means of control.

It is poor feedback loop design – but a depressingly common one.

<Leslie> So what do we do? What is a better design?

<Bob> First ask what the purpose of the feedback is?

<Leslie> To reduce the number of beds and save money by forcing down the length of stay so that the bed-day load is reduced and so we can do the same activity with fewer beds and at the same time avoid cancellations.

<Bob> OK. That sounds reasonable from the perspective of a tax-payer and a patient. It would also be a more productive design.

<Leslie> I agree but it seems to be having the opposite effect.  We are focusing on avoiding breaches so much that other patients get delayed who could have gone home sooner and we end up with more patients to expedite. It is like a vicious circle.  And every time we fail we get whacked with the RAG stick again. It is very demoralizing and it generates a lot of resentment and conflict. That is not good for anyone – least of all the patients.

<Bob>Yes.  That is the usual effect of a DRAT design. Remember that senior managers have not been trained in process improvement-by-design either so blaming them is also counter-productive.  We need to go back to the raw data. Can you plot actual LOS by patient in order of discharge as a run chart.

DRAT_04

<Bob> OK – is the maximum LOS target 8 days?

<Leslie> Yes – and this shows  we are meeting it most of the time.  But it is only with a huge amount of effort.

<Bob> Do you know where 8 days came from?

<Leslie> I think it was the historical average divided by 85% – someone read in a book somewhere that 85%  average occupancy was optimum and put 2 and 2 together.

<Bob> Oh dear! The “85% Occupancy is Best” myth combined with the “Flaw of Averages” trap. Never mind – let me explain the reasons why it is invalid to do this.

<Leslie> Yes please!

<Bob> First plot the data as a run chart and  as a histogram – do not plot the natural process limits yet as you have done. We need to do some validity checks first.

DRAT_05

<Leslie> Here you go.

<Bob> What do you see?

<Leslie> The histogram  has more than one peak – and there is a big one sitting just under the target.

<Bob>Yes. This is called the “Horned Gaussian” and is the characteristic pattern of an arbitrary lead-time target that is distorting the behaviour of the system.  Just as you have described subjectively. There is a smaller peak with a mode of 4 days and are a few very long length of stay outliers.  This multi-modal pattern means that the mean and standard deviation of this data are meaningless numbers as are any numbers derived from them. It is like having a bag of mixed fruit and then setting a maximum allowable size for an unspecified piece of fruit. Meaningless.

<Leslie> And the cases causing the breaches are completely different and could never realistically achieve that target! So we are effectively being randomly beaten with a stick. That is certainly how it feels.

<Bob> They are certainly different but you cannot yet assume that their longer LOS is inevitable. This chart just says – “go and have a look at these specific cases for a possible cause for the difference“.

<Leslie> OK … so if they are from a different system and I exclude them from the analysis what happens?

<Bob> It will not change reality.  The current design of  this process may not be capable of delivering an 8 day upper limit for the LOS.  Imposing  a DRAT does not help – it actually makes the design worse! As you can see. Only removing the DRAT will remove the distortion and reveal the underlying process behaviour.

<Leslie> So what do we do? There is no way that will happen in the current chaos!

<Bob> Apply the 6M Design® method. Map, Measure and Model it. Understand how it is behaving as it is then design out all the causes of longer LOS and that way deliver with a shorter and less variable LOS. Your chart shows that your process is stable.  That means you have enough flow capacity – so look at the policies. Draw on all your FISH training. That way you achieve your common purpose, and the big nasty stick goes away, and everyone feels better. And in the process you will demonstrate that there is a better feedback design than DRATs and RAGs. A win-win-win design.

<Leslie> OK. That makes complete sense. Thanks Bob!  But what you have described is not part of the FISH course.

<Bob> You are right. It is part of the ISP training that comes after FISH. Improvement Science Practitioner.

<Leslie> I think we will need to get a few more people trained in the theory, techniques and tools of Improvement Science.

<Bob> That would appear to be the case. They will need a real example to see what is possible.

<Leslie> OK. I am on the case!

Posted on

Resistance and Persistence

[Bing-Bong]

The email from Leslie was unexpected.

“Hi Bob, can I change the planned topic of our session today to talk about resistance. We got off to a great start with our improvement project but now I am hitting brick walls and we are losing momentum. I am getting scared we will stall. Leslie”

Bob replied immediately – it was only a few minutes until their regular teleconference call.

“Hi Leslie, no problem. Just firing up the Webex session now. Bob”

[Whoop-Whoop]

The sound bite announced Leslie joining in the teleconference.

<Leslie> Hi Bob. Sorry about the last minute change of plan. Can I describe the scenario?

<Bob> Hi Leslie. Please do.

<Leslie> Well we are at stage five of the 6M Design® sequence and we are monitoring the effect of the first set of design changes that we have made. We started by eliminating design flaws that were generating errors and impairing quality.   The information coming in confirms what we predicted at stage 3.  The problem is that a bunch of “fence-sitters” that said nothing at the start are now saying that the data is a load of rubbish and implying we are cooking the books to make it look better than it is! I am pulling my hair out trying to convince them that it is working.

<Bob> OK. What is your measure for improvement?

<Leslie> The percentage yield from the new quality-by-design process. It is improving. The BaseLine© chart says so.

<Bob> And how is that improvement being reported?

<Leslie> As the average yield per week.  I know we should not aggregate for a month because we need to see the impact of the change as it happens and I know there is a seven-day cycle in the system so we set the report interval at one week.

<Bob> Yes. Those are all valid reasons. What is the essence of the argument against your data?

<Leslie> There is no specific argument – it is just being discounted as “rubbish”.

<Bob> So you are feeling resistance?

<Leslie> You betcha!

<Bob> OK. Let us take a different tack on this. How often do you measure the yield?

<Leslie> Daily.

<Bob> And what is the reason you are using the percentage yield as your metric?

<Leslie> So we can compare one day with the next more easily and plot it on a time-series chart. The denominator is different every day so we cannot use just the count of errors.

<Bob> OK. And how do you calculate the weekly average?

<Leslie> From the daily percentage yields. It is not a difficult calculation!

There was a definite hint of irritation and sarcasm in Leslie’s voice.

<Bob> And how confident are you in your answer?

<Leslie> Completely confident. The team are fantastic. They see the value of this and are collecting the data assiduously. They can feel the improvement. They do not need the data to prove it. The feedback is to convince the fence-sitters and skeptics and they are discounting it.

<Bob> OK so you are confident in the quality of the data going in to your calculation – how confident are you in the data coming out?

<Leslie> What do you mean!  It is a simple calculation – a 12 year old could do.

<Bob> How are you feeling Leslie?

<Leslie>Irritated!

<Bob> Does it feel as if I am resisting too?

<Leslie>Yes!!

<Bob> Irritation is anger – the sense of loss in the present. What do you feel you are losing?

<Leslie> My patience and my self-confidence.

<Bob> So what might be my reasons for resisting?

<Leslie> You could be playing games or you could have a good reason.

<Bob> Do I play games?

<Leslie> Not so far! Sorry … no. You do not do that.

<Bob> So what could be my good reason?

<Leslie> Um. You can feel or see something that I cannot. An error?

<Bob> Yes. If I just feel something is not right I cannot do much else but say “That does not feel right”.  If I can see what I is not right I can explain my rationale for resisting.  Can I try to illuminate?

<Leslie> Yes please!

<Bob> OK – have you got a spreadsheet handy?

<Leslie> Yes.

<Bob> OK – create a column of twenty random numbers in the range 20-80 and label them “daily successes”. Next to them create a second column of random numbers in the range 20-100 and label then “daily activity”.

<Leslie> OK – done that.

<Bob> OK – calculate the % yield by day then the average of the column of daily % yield.

<Leslie> OK – that is exactly how I do it.

<Bob> OK – now sum the columns of successes and activities and calculate the average % yield from those two totals.

<Leslie> Yes – I could do that and it will give the same final answer but I do not do that because I cannot use that data on my run chart – for the reasons I said before.

<Bob> Does it give the same answer?

<Leslie> Um – no. Wait. I must have made an error. Let me check. No. I have done it correctly. They are not the same. Uh?

<Bob> What are you feeling?

<Leslie> Confused!  But the evidence is right there in front of me.

<Bob> An assumption you have been making has just been exposed to be invalid. Your rhetoric does not match reality.

<Leslie> But everyone does this … it is standard practice.

<Bob> And that makes it valid?

<Leslie> No .. of course not. That is one of the fundamental principles of Improvement Science. Just doing what everyone else does is not necessarily correct.

<Bob> So now we must understand what is happening. Can you now change the Daily Activity column so it is the same every day – say 60.

<Leslie> OK. Now my method works. The yield answers are the same.

<Bob> Yes.

<Leslie> Why is that?

<Bob> The story goes back to 1948 when Claude Shannon described “Information Theory”.  When you create a ratio you start with two numbers and end up with only one which implies that information is lost in the conversion.  Two numbers can only give one ratio, but that same ratio can be created by an infinite set of two numbers.  The relationship is asymmetric. It is not an equality. And it has nothing to do with the precision of the data. When we throw data away we create ambiguity.

<Leslie> And in my data the activity by day does vary. There is a regular weekly cycle and some random noise. So the way I am calculating the average yield is incorrect, and the message I am sharing is distorted, so others can quite reasonably challenge the data, and because I was 100% confident I was correct I have been assuming that their resistance was just due to cussedness!

<Bob> There may be some cussedness too. It is sometimes difficult to separate skepticism and cynicism.

<Leslie> So what is the lesson here? There must be more to your example than just exposing a basic arithmetic error.

<Bob> The message is that when you feel resistance you must accept the possibility that you are making an error that you cannot see.  The person demonstrating resistance can feel the emotional pain of a rhetoric-reality mismatch but can not explain the cause. You need to strive to see the problem through their eyes. It is OK to say “With respect I do not see it that way because …”.

<Leslie> So feeling “resistance” signals an opportunity for learning?

<Bob> Yes. Always.

<Leslie> So the better response is to pull back and to check assumptions and not to push forward and make the resistance greater or worse still break through the barrier of resistance, celebrate the victory, and then commit an inevitable and avoidable blunder – and then add insult to injury and blame someone else creating even more cynicism on the future.

<Bob> Yes. Well put.

<Leslie> Wow!  And that is why patience and persistence are necessary.  Not persistently pushing but persistently searching for the unconscious assumptions that underpin resistance; consistently using Reality as the arbiter;  and having enough patience to let Reality tell its own story.

<Bob> Yes. And having the patience and persistence to keep learning from our confusion and to keep learning how to explain what we have discovered better and better.

<Leslie> Thanks Bob. Once again you have  opened a new door for me.

<Bob> A door that was always there and yet hidden from view until it was illuminated with an example.

Posted on

Middle-Aware

line_figure_phone_400_wht_9858[Dring Dring]

<Bob> Hi Leslie, how are you today?

<Leslie> Really good thanks. We are making progress and it is really exciting to see tangible and measurable improvement in safety, delivery, quality and financial stability.

<Bob> That is good to hear. So what topic shall we explore today?

<Leslie> I would like to return to the topic of engagement.

<Bob> OK. I am sensing that you have a specific Niggle that you would like to share.

<Leslie> Yes.  Specifically it is engaging the Board.

<Bob> Ah ha. I wondered when we would get to that. Can you describe your Niggle?

<Leslie> Well, the feeling is fear and that follows from the risk of being identified as a trouble-maker which follows from exposing gaps in knowledge and understanding of seniors.

<Bob> Well put.  This is an expected hurdle that all Improvement Scientists have to learn to leap reliably. What is the barrier that you see?

<Leslie> That I do not know how to do it and I have seen a  lot of people try and commit career-suicide – like moths on a flame.

<Bob> OK – so it is a real fear based on real evidence. What methods did the “toasted moths” try?

<Leslie> Some got angry and blasted off angry send-to-all emails.  They just succeeded in identifying themselves as “terrorists” and were dismissed – politically and actually. Others channeled  their passion more effectively by heroic acts that held the system together for a while – and they succeeded in burning themselves out. The end result was the same: toasted!

<Bob> So with your understanding of design principles what does that say?

<Leslie> That the design of their engagement process is wrong.

<Bob> Wrong?

<Leslie> I mean “not fit for purpose”.

<Bob> And the difference is?

<Leslie> “Wrong” is a subjective judgement, “not fit for purpose” is an objective assessment.

<Bob> Yes. We need to be careful with words. So what is the “purpose”?

<Leslie> An organisation that is capable of consistently delivering improvement on all dimensions, safety, delivery, quality and affordability.

<Bob> Which requires?

<Leslie> All the parts working in synergy to a common purpose.

<Bob> So what are the parts?

<Leslie> The departments.

<Bob> They are the stages that the streams cross – they are parts of system structure. I am thinking more broadly.

<Leslie> The workers, the managers and the executives?

<Bob> Yes.  And how is that usually perceived?

<Leslie> As a power hierarchy.

<Bob> And do physical systems have power hierarchies?

<Leslie> No … they have components with different and complementary roles.

<Bob> So does that help?

<Leslie> Yes! To achieve synergy each component has to know its complementary role and be competent to do it.

<Bob> And each must understand the roles of the others,  respect the difference, and develop trust in their competence.

<Leslie> And the concepts of understanding, respect and trust appears again.

<Bob> Indeed.  They are always there in one form or another.

<Leslie> So as learning and improvement is a challenge then engagement is respectful challenge …

<Bob> … uh huh …

<Leslie> … and each part is different so requires a different form of respectful challenge?

<Bob> Yes. And with three parts there are six relationships between them – so six different ways of one part respectfully challenging another. Six different designs that have the same purpose but a different context.

<Leslie> Ah ha!  And if we do not use the context-dependent-fit-for-purpose-respectful-challenge-design we do not achieve our purpose?

<Bob> Correct. The principles of design are generic.

<Leslie> So what are the six designs?

<Bob> Let us explore three of them. First the context of a manager respectfully challenging a worker to improve.

<Leslie> That would require some form of training. Either the manager trains the worker or employs someone else to.

<Bob> Yes – and when might a manager delegate training?

<Leslie> When they do not have time to or do not know how to.

<Bob> Yes. So how would the flaw in that design be avoided?

<Leslie> By the manager maintaining their own know-how by doing enough training themselves and delegating the rest.

<Bob> Yup. Well done. OK let us consider a manager respectfully challenging other managers to improve.

<Leslie> I see what you mean. That is a completely different dynamic. The closest I can think of is a coaching arrangement.

<Bob> Yes. Coaching is quite different from training. It is more of a two-way relationship and I prefer to refer to it as “informal co-coaching” because both respectfully challenge each other in different ways; both share knowledge; and both learn and develop.

<Leslie> And that is what you are doing now?

<Bob> Yes. The only difference is that we have agreed a formal coaching contract. So what about a worker respectfully challenging a manager or a manager respectfully challenging an executive?

<Leslie>That is a very different dynamic. It is not training and it is not coaching.

<Bob> What other options are there?

<Leslie>Not formal coaching!  An executive is not going to ask a middle manager to coach them!

<Bob> You are right on both counts – so what is the essence of informal coaching?

<Leslie> An informal coach provides a different perspective and will say what they see if asked and will ask questions that help to illustrate alternative perspectives and offer evidence of alternative options. This is just well-structured, judgement-free feedback.

<Bob> Yes. We do it all the time. And we are often “coached” by those much younger than ourselves who have a more modern perspective. Our children for instance.

<Leslie> So the judgement free feedback metaphor is the one that a manager can use to engage an executive.

<Bob> Yes. And look at it from the perspective of the executive – they want feedback that can help them made wiser strategic decisions. That is their role. Boards are always asking for customer feedback, staff feedback and performance feedback.  They want to know the Nuggets, the Niggles, the Nice Ifs and the NoNos.  They just do not ask for it like that.

<Leslie> So they are no different from the rest of us?

<Bob> Not in respect of an insatiable appetite for unfiltered and undistorted feedback. What is different is their role. They are responsible for the strategic decisions – the ones that affect us all – so we can help ourselves by helping them make those decisions. A well-designed feedback model is fit-for-that-purpose.

<Leslie> And an Improvement Scientist needs to be able to do all three – training, coaching and communicating in a collaborative informal style. Is that leadership?

<Bob> I call it “middle-aware”.

<Leslie> It makes complete sense to me. There is a lot of new stuff here and I will need to reflect on it. Thank you once again for showing me a different perspective on the problem.

<Bob> I enjoyed it too – talking it through helps me to learn to explain it better – and I look forward to hearing the conclusions from your reflections because I know I will learn from that too.

Posted on

The Six Dice Game

<Ring Ring><Ring Ring>

Hello, you are through to the Improvement Science Helpline. How can we help?

This is Leslie, one of your apprentices.  Could I speak to Bob – my Improvement Science coach?

Yes, Bob is free. I will connect you now.

<Ring Ring><Ring Ring>

B: Hello Leslie, Bob here. What is on your mind?

L: Hi Bob, I have a problem that I do not feel my Foundation training has equipped me to solve. Can I talk it through with you?

B: Of course. Can you outline the context for me?

L: OK. The context is a department that is delivering an acceptable quality-of-service and is delivering on-time but is failing financially. As you know we are all being forced to adopt austerity measures and I am concerned that if their budget is cut then they will fail on delivery and may start cutting corners and then fail on quality too.  We need a win-win-win outcome and I do not know where to start with this one.

B: OK – are you using the 6M Design method?

L: Yes – of course!

B: OK – have you done The 4N Chart for the customer of their service?

L: Yes – it was their customers who asked me if I could help and that is what I used to get the context.

B: OK – have you done The 4N Chart for the department?

L: Yes. And that is where my major concerns come from. They feel under extreme pressure; they feel they are working flat out just to maintain the current level of quality and on-time delivery; they feel undervalued and frustrated that their requests for more resources are refused; they feel demoralized; demotivated and scared that their service may be ‘outsourced’. On the positive side they feel that they work well as a team and are willing to learn. I do not know what to do next.

B: OK. Dispair not. This sounds like a very common and treatable system illness.  It is a stream design problem which may be the reason your Foundations training feels insufficient. Would you like to see how a Practitioner would approach this?

L: Yes please!

B: OK. Have you mapped their internal process?

L: Yes. It is a six-step process for each job. Each step has different requirements and are done by different people with different skills. In the past they had a problem with poor service quality so extra safety and quality checks were imposed by the Governance department.  Now the quality of each step is measured on a 1-6 scale and the quality of the whole process is the sum of the individual steps so is measured on a scale of 6 to 36. They now have been given a minimum quality target of 21 to achieve for every job. How they achieve that is not specified – it was left up to them.

B: OK – do they record their quality measurement data?

L: Yes – I have their report.

B: OK – how is the information presented?

L: As an average for the previous month which is reported up to the Quality Performance Committee.

B: OK – what was the average for last month?

L: Their results were 24 – so they do not have an issue delivering the required quality. The problem is the costs they are incurring and they are being labelled by others as ‘inefficient’. Especially the departments who are in budget and they are annoyed that this failing department keeps getting ‘bailed out’.

B: OK. One issue here is the quality reporting process is not alerting you to the real issue. It sounds from what you say that you have fallen into the Flaw of Averages trap.

L: I don’t understand. What is the Flaw of Averages trap?

B: The answer to your question will become clear. The finance issue is a symptom – an effect – it is unlikely to be the cause. When did this finance issue appear?

L: Just after the Safety and Quality Review. They needed to employ more agency staff to do the extra work created by having to meet the new Minimum Quality target.

B: OK. I need to ask you a personal question. Do you believe that improving quality always costs more?

L: I have to say that I am coming to that conclusion. Our Governance and Finance departments are always arguing about it. Governance state ‘a minimum standard of safety and quality is not optional’ and finance say ‘but we are going out of business’. They are at loggerheads. The service departments get caught in the cross-fire.

B: OK. We will need to use reality to demonstrate that this belief is incorrect. Rhetoric alone does not work. If it did then we would not be having this conversation. Do you have the raw data from which the averages are calculated?

L: Yes. We have the data. The quality inspectors are very thorough!

B: OK – can you plot the quality scores for the last fifty jobs as a BaseLine chart?

L: Yes – give me a second. The average is 24 as I said.

B: OK – is the process stable?

L: Yes – there is only one flag for the fifty. I know from my Foundations training that is not a cause for alarm.

B: OK – what is the process capability?

L: I am sorry – I don’t know what you mean by that?

B: My apologies. I forgot that you have not completed the Practitioner training yet. The capability is the range between the red lines on the chart.

L: Um – the lower line is at 17 and the upper line is at 31.

L: OK – how many points lie below the target of 21.

B: None of course. They are meeting their Minimum Quality target. The issue is not quality – it is money.

There was a pause.  Leslie knew from experience that when Bob paused there was a surprise coming.

B: Can you email me your chart?

A cold-shiver went down Leslie’s back. What was the problem here? Bob had never asked to see the data before.

Sure. I will send it now.  The recent fifty is on the right, the data on the left is from after the quality inspectors went in and before the the Minimum Quality target was imposed. This is the chart that Governance has been using as evidence to justify their existence because they are claiming the credit for improving the quality.

B: OK – thanks. I have got it – let me see.  Oh dear.

Leslie was shocked. She had never heard Bob use language like ‘Oh dear’.

There was another pause.

B: Leslie, what is the context for this data? What does the X-axis represent?

Leslie looked at the chart again – more closely this time. Then she saw what Bob was getting at. There were fifty points in the first group, and about the same number in the second group. That was not the interesting part. In the first group the X-axis went up to 50 in regular steps of five; in the second group it went from 50 to just over 149 and was no longer regularly spaced. Eventually she replied.

Bob, that is a really good question. My guess it is that this is the quality of the completed work.

B: It is unwise to guess. It is better to go and see reality.

You are right. I knew that. It is drummed into us during the Foundations training! I will go and ask. Can I call you back?

B: Of course. I will email you my direct number.

<Ring Ring><Ring Ring>

B: Hello, Bob here.

L: Bob – it is Leslie. I am  so excited! I have discovered something amazing.

B: Hello Leslie. That is good to hear. Can you tell me what you have discovered?

L: I have discovered that better quality does not always cost more.

B: That is a good discovery. Can you prove it with data?

L: Yes I can!  I am emailing you the chart now.

B: OK – I am looking at your chart. Can you explain to me what you have discovered?

L: Yes. When I went to see for myself I saw that when a job failed the Minimum Quality check at the end then the whole job had to be re-done because there was no time to investigate and correct the causes of the failure.  The people doing the work said that they were helpless victims of errors that were made upstream of them – and they could not predict from one job to the next what the error would be. They said it felt like quality was a lottery and that they were just firefighting all the time. They knew that just repeating the work was not solving the problem but they had no other choice because they were under enormous pressure to deliver on-time as well. The only solution they could see is was to get more resources but their requests were being refused by Finance on the grounds that there is no more money. They felt completely trapped.

B: OK. Can you describe what you did?

L: Yes. I saw immediately that there were so many sources of errors that it would be impossible for me to tackle them all. So I used the tool that I had learned in the Foundations training: the Niggle-o-Gram. That focussed us and led to a surprisingly simple, quick, zero-cost process design change. We deliberately did not remove the Inspection-and-Correction policy because we needed to know what the impact of the change would be. Oh, and we did one other thing that challenged the current methods. We plotted every attempt, both the successes and the failures, on the BaseLine chart so we could see both the the quality and the work done on one chart.  And we updated the chart every day and posted it chart on the notice board so everyone in the department could see the effect of the change that they had designed. It worked like magic! They have already slashed their agency staff costs, the whole department feels calmer and they are still delivering on-time. And best of all they now feel that they have the energy and time to start looking at the next niggle. Thank you so much! Now I see how the tools and techniques I learned in Foundations are so powerful and now I understand better the reason we learned them first.

B: Well done Leslie. You have taken an important step to becoming a fully fledged Practitioner. You have learned some critical lessons in this challenge.

This scenario is fictional but realistic.

And it has been designed so that it can be replicated easily using a simple game that requires only pencil, paper and some dice.

If you do not have some dice handy then you can use this little program that simulates rolling six dice.

The Six Digital Dice program (for PC only).

Instructions
1. Prepare a piece of A4 squared paper with the Y-axis marked from zero to 40 and the X-axis from 1 to 80.
2. Roll six dice and record the score on each (or roll one die six times) – then calculate the total.
3. Plot the total on your graph. Left-to-right in time order. Link the dots with lines.
4. After 25 dots look at the chart. It should resemble the leftmost data in the charts above.
5. Now draw a horizontal line at 21. This is the Minimum Quality Target.
6. Keep rolling the dice – six per cycle, adding the totals to the right of your previous data.

But this time if the total is less than 21 then repeat the cycle of six dice rolls until the score is 21 or more. Record on your chart the output of all the cycles – not just the acceptable ones.

7. Keep going until you have 25 acceptable outcomes. As long as it takes.

Now count how many cycles you needed to complete in order to get 25 acceptable outcomes.  You should find that it is about twice as many as before you “imposed” the Inspect-and-Correct QI policy.

This illustrates the problem of an Inspection-and-Correction design for quality improvement.  It does improve the quality of the final output – but at a higher cost.

We are treating the symptoms (effects) and ignoring the disease (causes).

The internal design of the process is unchanged so it is still generating mistakes.

How much quality improvement you get and how much it costs you is determined by the design of the underlying process – which has not changed. There is a Law of Diminishing returns here – and a big risk.

The risk is that if quality improves as the result of applying a quality target then it encourages the Governance thumbscrews to be tightened further and forces those delivering the service further into cross-fire between Governance and Finance.

The other negative consequence of the Inspect-and-Correct approach is that it increases both the average and the variation in lead time which also fuels the calls for more targets, more sticks, calls for  more resources and pushes costs up even further.

The lesson from this simple exercise seems clear.

The better strategy for improving quality is to design the root causes of errors out of the processes  because then we will get improved quality and improved delivery and improved productivity and we will discover that we have improved safety as well.  Win-win-win-win.

The Six Dice Game is a simpler version of the famous Red Bead Game that W Edwards Deming used to explain why, in the modern world, the arbitrary-target-driven-command-and-control-stick-and-carrot style of performance management creates more problems than it solves.

The illusion is of short-term gain but the reality is of long-term pain.

And if you would like to see and hear Deming talking about the science of improvement there is a video of him speaking in 1984. He is at the bottom of the page.  Click here.