{"id":1274,"date":"2012-02-11T13:33:11","date_gmt":"2012-02-11T13:33:11","guid":{"rendered":"http:\/\/www.saasoft.com\/blog\/?p=1274"},"modified":"2012-02-11T13:33:11","modified_gmt":"2012-02-11T13:33:11","slug":"homeostasis","status":"publish","type":"post","link":"https:\/\/hcse.blog\/?p=1274","title":{"rendered":"Homeostasis"},"content":{"rendered":"

\"\"<\/a>Improvement Science is not just about removing the barriers that block improvement and\u00a0building barriers to\u00a0prevent deterioration – it is also about\u00a0maintaining acceptable, stable and predictable performance.<\/p>\n

In fact\u00a0most of the time this is what we\u00a0need our systems to do so that we can focus our attention on the areas\u00a0for improvement rather than running around keeping all the\u00a0plates\u00a0spinning.\u00a0 Improving the ability of a\u00a0system\u00a0to\u00a0maintain itself is a worthwhile and necessary objective.<\/p>\n

Long term stability cannot\u00a0be achieved by assuming\u00a0a stable context and creating\u00a0a rigid solution because the World is always changing. Long term stability is achieved by creating\u00a0resilient solutions that can adjust their behaviour, within limits, to\u00a0their ever-changing context.<\/p>\n

This self-adjusting behaviour of a system\u00a0is called homeostasis<\/em>.<\/p>\n

The foundation for\u00a0the concept of homeostasis was first proposed by Claude Bernard<\/strong> (1813-1878) who unlike<\/strong> most of his contemporaries, believed that all living creatures were bound by the same physical laws as inanimate matter.\u00a0\u00a0In his words:\u00a0“La fixit\u00e9 du milieu int\u00e9rieur est la condition d’une vie libre et ind\u00e9pendante” (“The constancy of the internal environment is the condition for a free and independent life”<\/em>).<\/p>\n

The term homeostasis<\/em> is attributed to Walter Bradford Cannon (1871 \u2013\u00a01945) who was\u00a0a professor of physiology at Harvard medical school\u00a0and who popularized his theories in a book called The Wisdom of the Body (1932). <\/em>Cannon described four principles of homeostasis:<\/p>\n

    \n
  1. Constancy in an open system requires mechanisms<\/strong> that act to maintain this constancy.<\/li>\n
  2. Steady-state conditions require that any tendency toward change automatically<\/strong> meets with factors that resist change.<\/li>\n
  3. The regulating system that determines the homeostatic state consists of a number of cooperating<\/strong> mechanisms acting simultaneously or successively.<\/li>\n
  4. Homeostasis does not occur by chance, but is the result of organised self-government<\/strong>.<\/li>\n<\/ol>\n

    Homeostasis is therefore an emergent\u00a0behaviour of\u00a0a\u00a0system and is the result of\u00a0organised,\u00a0cooperating, automatic mechanisms. We know this by another name – feedback control\u00a0– <\/strong>which is passing data from one part of a system to guide the actions of another part. <\/strong>Any system that does not have homeostatic\u00a0feedback loops\u00a0as part of its design will be inherently unstable\u00a0– especially in a changing environment.\u00a0 And unstable means untrustworthy.<\/p>\n

    \"\"<\/a>Take driving for example.\u00a0Our vehicle and its trusting passengers want\u00a0to get to their desired destination on time and in one piece. To achieve this we will need to keep our vehicle\u00a0within the boundaries of the road – the white lines – in order to avoid “disappointment”.<\/p>\n

    As their trusted driver\u00a0our\u00a0feedback loop consists of\u00a0a view of the road ahead via\u00a0the\u00a0front windscreen; our\u00a0vision connected through\u00a0a working\u00a0nervous system to the muscles in ours\u00a0arms and legs; to the steering wheel, accelerator and brakes; then to the engine, transmission, wheels and tyres and finally\u00a0to the road underneath the wheels. It is quite a complicated multi-step feedback system – but an effective one. The road can change direction and unpredictable things can happen\u00a0and we\u00a0can adapt, adjust\u00a0and remain in control.\u00a0\u00a0An inferior feedback design would be to\u00a0use only<\/strong> the rear-view mirror and to steer by looking at the whites lines\u00a0emerging from behind us.\u00a0This design\u00a0is just as complicated but it is much\u00a0less effective and much less safe because it is entirely reactive.\u00a0 We get\u00a0no early warning of what we are approaching.\u00a0 So, any system that uses the\u00a0output performance as the feedback\u00a0loop to the input decision step\u00a0is like driving with just a rear view mirror.\u00a0 Complex, expensive, unstable, ineffective\u00a0and unsafe.\u00a0\u00a0\u00a0\u00a0\u00a0<\/p>\n

    As the number of steps in a process increases the more important the design of \u00a0the feedback stabilisation becomes –\u00a0as does the number of ways we can get it wrong:\u00a0 Wrong feedback signal, or from the wrong place,\u00a0or to the wrong place, or at the wrong time, or with the wrong interpretation – any of which\u00a0result in the wrong decision, the wrong action and the wrong outcome. Getting it right means getting\u00a0all<\/strong> of it right all<\/strong> of the time\u00a0– not just some of it right some of the time. We can’t leave it to chance – we have to design it to work.<\/p>\n

    Let us consider a real example. The NHS 18-week performance requirement.<\/p>\n

    \"\"<\/a>The stream map shows a simple system with two\u00a0parallel streams: A and B\u00a0that each has two steps 1 and 2. A typical example would be generic referral of patients for investigations and treatment to one of a number of consultants who offer that service. The two streams do the same thing so the first step of the system\u00a0is to decide which way to direct new tasks\u00a0– to Step A1 or to Step B1. The whole system is required to\u00a0deliver completed tasks in less than 18 weeks (18\/52)\u00a0– irrespective of which stream we\u00a0direct work into.\u00a0\u00a0\u00a0What\u00a0feedback\u00a0data do we\u00a0use to decide where to direct the next referral?<\/p>\n

    The do nothing option is to just allocate work without using any feedback. We might do that\u00a0randomly, alternately or by some other means that are independent of the system.\u00a0 This\u00a0is called a push<\/strong>\u00a0design and\u00a0is\u00a0equivalent to driving with your eyes shut\u00a0but relying on hope<\/strong> and\u00a0luck<\/strong> <\/em>for a favourable outcome. We will\u00a0know when we have got it wrong – but it is too late then – we have crashed the system!\u00a0<\/p>\n

    A more plausible\u00a0option is to use the waiting time for the first step\u00a0as the feedback signal – streaming work to the first step with the shortest waiting time. This makes sense\u00a0because\u00a0the time waiting for the first step is part of the lead time for the whole stream so minimising this first wait feels reasonable –\u00a0and it is –\u00a0BUT only in one situation: when the first steps\u00a0are the constraint steps in both\u00a0streams [the constraint step is one one that\u00a0defines the maximum stream flow].\u00a0 If\u00a0this condition is not met then\u00a0we heading for trouble and the\u00a0map above illustrates\u00a0why. In this case Stream A is\u00a0just failing\u00a0the 18-week performance target\u00a0but\u00a0because the waiting time for Step A1 is the shorter we would continue to load more work onto the failing\u00a0 stream – and literally push it over the edge. In contrast Stream B is not failing\u00a0and because the\u00a0waiting time for Step B1 is the longer it is\u00a0not being overloaded – it may even be underloaded.\u00a0 So this “plausible” feedback design\u00a0can actually make the system less<\/em> stable. Oops!<\/p>\n

    In our\u00a0transport metaphor – this is like driving too fast at night or\u00a0in fog – only being able to see what is immediately\u00a0ahead – and then braking and swerving to get around corners when they “suddenly” appear and running off the road unintentionally! Dangerous and expensive.<\/p>\n

    With this new insight we might\u00a0now reasonably suggest using\u00a0the actual output performance to decide\u00a0which way to\u00a0direct new work – but this is back to driving by watching\u00a0the rear-view mirror!\u00a0 So what is the answer?<\/p>\n

    The solution is to design the system to use the most appropriate\u00a0feedback signal to guide the streaming decision. That feedback signal needs to be forward looking,\u00a0responsive and to lead to\u00a0stable and equitable\u00a0performance of the whole system – and it may orginate from inside <\/em>the system. The diagram above holds the\u00a0hint: the predicted waiting time for the second step would be\u00a0a better choice.\u00a0 Please note that I said the predicted waiting time<\/em> – which is estimated\u00a0when the task leaves Step 1 and joins the back of the queue between\u00a0Step 1 and Step 2. It is not\u00a0the actual time the most recent task came off the\u00a0queue:\u00a0that is rear-view mirror gazing again.<\/p>\n

    When driving\u00a0we\u00a0look as far ahead as we can,\u00a0for what we are heading towards, and we combine\u00a0that feedback with our present speed to predict\u00a0how much time we have\u00a0before we need to\u00a0slow down,\u00a0when to turn,\u00a0in which direction, by how much, and for how long. With effective\u00a0feedback we can behave proactively,\u00a0avoid\u00a0surprises,\u00a0and eliminate sudden braking and swerving! Our passengers will have a more comfortable ride and are more likely to\u00a0survive the journey! And the better we can do all that the faster we can\u00a0travel in both comfort and safety – even on an unfamiliar road.\u00a0\u00a0It may be less exciting but excitement\u00a0is not our objective. On time delivery is our goal.<\/p>\n

    Excitement comes from anticipating improvement – maintaining what we have already improved\u00a0is rewarding.\u00a0 We need both to\u00a0sustain us and to free us\u00a0to focus\u00a0on the improvement work!\u00a0<\/p>\n

    \u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"

    Improvement Science is not just about removing the barriers that block improvement and\u00a0building barriers to\u00a0prevent deterioration – it is also about\u00a0maintaining acceptable, stable and predictable performance. In fact\u00a0most of the time this is what we\u00a0need our systems to do so that we can focus our attention on the areas\u00a0for improvement rather than running around keeping … <\/p>\n

    Continue reading “Homeostasis”<\/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":[17,22,35,36,42,43,45,46,48],"tags":[],"class_list":["post-1274","post","type-post","status-publish","format-standard","hentry","category-examples","category-healthcare","category-reflections","category-resilient","category-how","category-why","category-what","category-teach","category-trust"],"_links":{"self":[{"href":"https:\/\/hcse.blog\/index.php?rest_route=\/wp\/v2\/posts\/1274","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=1274"}],"version-history":[{"count":0,"href":"https:\/\/hcse.blog\/index.php?rest_route=\/wp\/v2\/posts\/1274\/revisions"}],"wp:attachment":[{"href":"https:\/\/hcse.blog\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1274"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hcse.blog\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1274"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hcse.blog\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1274"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}