{"id":2263,"date":"2012-11-03T11:43:27","date_gmt":"2012-11-03T11:43:27","guid":{"rendered":"http:\/\/www.saasoft.com\/blog\/?p=2263"},"modified":"2012-11-03T11:43:27","modified_gmt":"2012-11-03T11:43:27","slug":"a-recipe-for-improvement-pie","status":"publish","type":"post","link":"https:\/\/hcse.blog\/?p=2263","title":{"rendered":"A Recipe for Improvement PIE."},"content":{"rendered":"

\"\"<\/a>Most of us are realists. We have to solve problems in the real world so we prefer real\u00a0examples and step-by-step how-to-do recipes.<\/p>\n

A minority of us are theorists and are more comfortable with abstract models and\u00a0solving rhetorical problems.<\/p>\n

Many of these Improvement Science blog articles\u00a0debate abstract concepts – because I\u00a0am a strong iNtuitor by nature.\u00a0Most\u00a0realists are Sensors –\u00a0so by popular request\u00a0here is a “how-to-do”\u00a0recipe for a Productivity Improvement Exercise (PIE)<\/p>\n

Step 1 – Define Productivity.<\/strong><\/p>\n

There are many definitions we could choose because productivity means the results delivered divided by the resources used.\u00a0 We could use any of the three currencies – quality, time or money – but the easiest is money. And that is because it is easier to measure and we have well established department for doing it – Finance – the guardians of the money.\u00a0 There are two other departments who may need to be involved – Governance (the guardians of the safety) and Operations (the guardians of the delivery).<\/p>\n

So the definition we will use is productivity = revenue generated divided cost incurred.<\/em><\/p>\n

Step 2 – Draw a map of the process we want to make more productive.<\/strong><\/p>\n

This means creating a picture of the parts and their relationships to each other – in particular what the steps in the process are; who does what, where and when; what is done in parallel and what is done in sequence; what feeds into what and what depends on what.\u00a0The output of this step is a diagram with boxes and arrows and annotations – called a process map<\/strong>. It tells us at a glance how complex our\u00a0process is – the number of boxes and the number of arrows. \u00a0The simpler the process the easier it is to demonstrate a productivity improvement quickly and unambiguously.<\/p>\n

Step 3 – Decide the objective metrics that will tell us our productivity.<\/strong><\/p>\n

We have chosen a finanical measure of productivity so we need to measure revenue and cost over time – and our Finance department do that already so we do not need to do anything new. We just ask them for the data. It will probably come as a monthly\u00a0report because that is how\u00a0Finance\u00a0processes are designed – the calendar month accounting cycle is\u00a0not negotiable.<\/p>\n

We will also need some internal process metrics (IPMs) that will link to the end of month productivity\u00a0report values because we need to be observing our process more often than monthly. Weekly, daily or even task-by-task may be necessary – and our monthly finance reports will not meet that time-granularity requirement.<\/p>\n

These internal process metrics will be time<\/strong> metrics.<\/p>\n

Start with objective metrics\u00a0and avoid the subjective ones at this stage. They are\u00a0necessary but they come later.<\/p>\n

Step\u00a04 – Measure the process<\/strong>.<\/p>\n

There are three essential measures we\u00a0usually need\u00a0for each step in the process: A measure of quality, a measure of time and a measure of cost. \u00a0For the purposes of this example we will simplify by making three assumptions. Quality is 100% (no mistakes) and Predictability is 100% (no variation) and Necessity is 100% (no worthless steps). This means that we are considering a simplified and theoretical situation but we are novices and we need to start with the wood and not get lost in the trees.<\/em><\/p>\n

The 100% Quality means that we do not need to worry about Governance for the purposes of this basic recipe.<\/p>\n

The 100% Predictability means that we can use averages – so long as we are careful.<\/p>\n

The 100% Necessity means that we must have all the steps in there or the process will not work.<\/p>\n

The best way to measure the process is to observe it and record the events as they happen. There is no place for rhetoric here. Only reality is acceptable. And avoid computers getting in the way of the measurement. The place for computers is to assist the analysis – and only later may they be used to assist the maintenance – after the improvement has been achieved.<\/p>\n

Many attempts at productivity improvement fail at this point – because there is a strong belief that the more computers we add\u00a0the better. Experience shows the opposite is usually the case – adding computers adds complexity, cost and the opportunity for errors\u00a0– so beware<\/strong>.<\/p>\n

Step\u00a05 – Identify the Constraint Step.<\/strong><\/p>\n

The meaning of the term constraint<\/strong> in this context is very specific – it means the step that controls the flow in the whole process<\/em>.\u00a0 The critical word here is flow<\/strong>. We need to identify the current flow constraint<\/em>.<\/p>\n

A tap or valve on a pipe is a good example of a flow constraint – we adjust the tap to\u00a0control the flow in the whole pipe. It makes no difference how long or fat the pipe is or where the tap is, begining, middle\u00a0or\u00a0end.\u00a0(So long as the pipe is not too long or too narrow or the fluid too\u00a0gloopy\u00a0because if\u00a0they are\u00a0then\u00a0the pipe\u00a0will become the flow constraint and we do not want that).<\/p>\n

The way to identify the constraint in the system is to look at the time<\/strong> measurements. The step that shows the same flow as the output is the constraint step<\/em>. (And remember we are using the simplified example of no errors and no variation – in real life there is a bit more to identifying the constraint step).<\/p>\n

Step 6 – Identify the ideal place for the Constraint Step.<\/strong><\/p>\n

This is the critical-to-success step in the PIE recipe. Get this wrong and it will not work.<\/em><\/p>\n

This step\u00a0requires two pieces of measurement data for each step – the time data and the cost data. So the Operational team and the Finance team will need to collaborate here. Tricky I know but if\u00a0we want improved productivity then there is no alternative.<\/p>\n

Lots of productivity improvement initiatives fall at the Sixth Fence – so beware<\/strong>.\u00a0 If our Finance and Operations departments are at war then we should not consider even starting the race.\u00a0It will only make the bad situation even worse!<\/p>\n

If they are able to maintain an adult and respectful face-to-face conversation then we can proceed.<\/p>\n

\"\"<\/a>The time measure for each step we need is called the cycle time<\/strong> – which is the time interval from starting one task to being ready to start the next one<\/em>. Please note this is a precise definition and it should be used exactly as defined.<\/p>\n

The money measure for each step we need is the fully absorbed cost of time<\/strong> of providing the resource. \u00a0Your Finance department will understand that – they are Masters of FACTs!<\/p>\n

The magic number<\/strong> we need to identify the Ideal Constraint is the product of the Cycle Time and the FACT – the step with the highest\u00a0magic number should be the constraint step. It should control the flow in the whole process. (In reality there is a bit more to it than this but I am trying hard to stay out of the trees).<\/p>\n

Step\u00a07 – Design the capacity so that the Ideal Constraint is the Actual Constraint.<\/strong><\/p>\n

We\u00a0are using a precise definition of the term capacity<\/strong> here – the amount of resource-time available <\/em>– not just the number of resources available. Again this is a precise definition and should be used as defined.<\/p>\n

The capacity design\u00a0sequence \u00a0means adding and removing capacity to and from steps so that the constraint moves to where we want it.<\/p>\n

The sequence\u00a0 is:
\n7a) Set the capacity of the Ideal Constraint so it is capable of delivering the required activity and revenue.
\n7b) Increase the capacity of the all the other steps so that the Ideal Constraint actually controls the flow.
\n7c) Reduce the capacity of each step in turn, a click at a time until it becomes the constraint then back off one click.<\/p>\n

Step\u00a08 – Model your whole design to\u00a0predict the expected productivity improvement.<\/strong><\/p>\n

This is critical because we are not interested in suck-it-and-see incremental improvement. We need to be able to decide if the expected benefit is worth the effort before we authorise and action any changes.\u00a0\u00a0And we will be asked for a business case. That necessity\u00a0is not negotiable either.<\/p>\n

Lots of productivity improvement projects\u00a0try to dodge this particularly thorny fence behind a smoke screen of a plausible looking business case that is more fiction than fact. This happens when any of\u00a0Steps 2 to 7 are omitted or done incorrectly.\u00a0 What we need here is a model and if we are not prepared to learn how to\u00a0build one\u00a0then we should not start. It may only need a simple model – but it will need one. Intuition is too unreliable.<\/p>\n

A model is defined as a simplified representation of reality used for making predictions.<\/em><\/p>\n

All models are approximations of reality. That is OK.<\/p>\n

\"\"<\/a>The art of modeling<\/strong> is to define the questions the model needs to be designed to answer (and the precision and accuracy needed) and then design, build and test the model so that it is just simple enough and no simpler. Adding unnecessary complexity is difficult, time consuming, error prone and expensive. Using a computer model when a simple pen-and-paper model would suffice is a good example of over-complicating the recipe!<\/p>\n

Many productivity improvement projects that\u00a0get this\u00a0far still fall at this fence.\u00a0 There is a belief that\u00a0modeling\u00a0can only be done by Marvins with brains the size of planets. This is incorrect.\u00a0 There is also a belief that just using a spreadsheet\u00a0or modelling software\u00a0is all that is needed. This is incorrect too. Competent modelling requires\u00a0tools and training – and experience because it is as much art as science.<\/p>\n

Step\u00a09 – Modify your system as per the\u00a0tested design.<\/strong><\/p>\n

Once you have demonstrated\u00a0how the proposed design will deliver a valuable increase in productivity then get on with it.<\/p>\n

\"\"<\/a>Not by imposing it as a fait accompli<\/em> – but by sharing the story along with the rationale, real data, explanation and results. Ask for balanced, reasoned and respectful feedback. The question to ask is \u201cCan you think of any reasons why this would not work?\u201d<\/em> Very often the reply is \u201cIt all looks OK in theory but I bet it won\u2019t work in practice but I can\u2019t explain why\u201d. This is an emotional reaction which may have some basis in fact. It may also just be habitual skepticism\/cynicism. Further debate is usually \u00a0worthless – the only way to know for sure is by doing the experiment. As an experiment – as a small-scale and time-limited pilot. Set the date and do it. Waiting and debating will add no value. The proof of the\u00a0pie is in the eating.<\/p>\n

Step\u00a010 – Measure and maintain your system productivity.<\/strong><\/p>\n

Keep measuring the same metrics that you need to calculate productivity and in addition monitor the old constraint step and the new constraint steps like a hawk – capturing their time metrics for every task – and tracking what you see against what the model predicted you should see.<\/p>\n

The correct tool to use here is a system behaviour chart for each constraint metric.\u00a0\u00a0The before-the-change data is the baseline from which improvement is measured over time; \u00a0and with a dot plotted\u00a0for each task in real time and made visible to all the stakeholders. This is the voice of the process (VoP).<\/p>\n

A\u00a0review after three months\u00a0with a retrospective financial analysis will not be enough. The feedback needs to be immediate. The voice of the process will dictate if and when to celebrate. (There is a bit more to this step too and the trees are clamoring for attention but we must stay out of the wood a bit longer).<\/p>\n

And\u00a0after the charts-on-the-wall have revealed the expected improvement has actually happened; and after the\u00a0skeptics have deleted their ‘we told you so’ emails; and after\u00a0the cynics have slunk off to sulk; and after the celebration party is over; and after the fame and glory has been\u00a0snatched\u00a0by the non-participants – after all of that expected change management stuff has happened …. there is a bit more work to do.<\/p>\n

And that is to establish the new higher productivity design as business-as-usual which means tearing up all the old policies and writing new ones: New Policies that capture the New Reality. Bin the out-of-date rubbish.<\/p>\n

This is an essential step because culture changes slowly.\u00a0\u00a0If this step is omitted then out-of-date beliefs, attitudes, habits and behaviours will start to diffuse back in, poison the pond, and undo all the good work. \u00a0The New Policies are the reference – but they alone will not ensure the improvement is maintained. What is also needed is a PFL – a performance feedback loop.<\/p>\n

And we have already demonstrated what that needs to be – the tactical system behaviour charts for the Intended Constraint step.<\/p>\n

The finanical productivity metric is the strategic output and is reported monthly – as a system behaviour chart! Just comparing this month with last month is meaningless.\u00a0\u00a0The tactical\u00a0SBCs for the constraint step must be maintained continuously by the people who own the constraint step – because they control the productivity of the whole process.\u00a0 They are the guardians of the productivity improvement and their SBCs are the Early Warning System (EWS).<\/p>\n

If the tactical\u00a0SBCs set off an alarm then investigate the root cause immediately\u00a0– and address it. If they do not then leave it alone and do not meddle<\/strong>.<\/p>\n

This is the simplified version of the recipe. The essential framework.<\/p>\n

Reality is messier. More complicated. More fun!<\/p>\n

Reality throws in lots of rusty spanners so we do also need to understand how to manage the complexity; the unnecessary steps; the errors; the meddlers; and the inevitable variation.\u00a0 It is possible (though not trivial) to design real systems to deliver much higher productivity by using the framework above and by mastering a number of other tools and techniques. \u00a0And for that to succeed the Governance, Operations and Finance functions need to collaborate closely with the People and the Process – initially with guidance from an experienced and competent Improvement Scientist.\u00a0But only initially. This is a learnable skill. And it takes practice to master – so start with easy ones and work up.<\/p>\n

If any of these bits are missing or are dysfunctional\u00a0the recipe\u00a0will not work. So that is the first\u00a0nettle the Executive must grasp. Get everyone who is necessary on the same bus going in the same direction – and show the cynics the exit. Skeptics are OK – they will counter-balance the Optimists. Cynics add no value and are a liability.<\/p>\n

What you may have noticed is that 8 of the 10 steps happen before<\/span> any change is made. 80% of the effort is in the design – only 20% is in the doing.<\/p>\n

If we get the design wrong the the doing will be an ineffective\u00a0and inefficient waste of effort, time and money.<\/p>\n

\n

The best complement to real Improvement PIE is a FISH<\/a> course.<\/strong><\/p>\n

\n","protected":false},"excerpt":{"rendered":"

Most of us are realists. We have to solve problems in the real world so we prefer real\u00a0examples and step-by-step how-to-do recipes. A minority of us are theorists and are more comfortable with abstract models and\u00a0solving rhetorical problems. Many of these Improvement Science blog articles\u00a0debate abstract concepts – because I\u00a0am a strong iNtuitor by nature.\u00a0Most\u00a0realists … <\/p>\n

Continue reading “A Recipe for Improvement PIE.”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6,7,15,17,18,20,24,30,32,38,42,44,45,46],"tags":[],"class_list":["post-2263","post","type-post","status-publish","format-standard","hentry","category-6m-design","category-baseline","category-design","category-examples","category-finance","category-flow","category-improvementology","category-operations","category-productivity","category-safety","category-how","category-three-wins-r","category-what","category-teach"],"_links":{"self":[{"href":"https:\/\/hcse.blog\/index.php?rest_route=\/wp\/v2\/posts\/2263","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hcse.blog\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hcse.blog\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hcse.blog\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/hcse.blog\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2263"}],"version-history":[{"count":0,"href":"https:\/\/hcse.blog\/index.php?rest_route=\/wp\/v2\/posts\/2263\/revisions"}],"wp:attachment":[{"href":"https:\/\/hcse.blog\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2263"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hcse.blog\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2263"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hcse.blog\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2263"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}