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Have you ever considered why doctor’s appointments are usually delayed? Even if we schedule the exact date and time in advance, we end up waiting long time in the doctor’s waiting room. Let’s look at this example from flow perspective. Patients in this case are workable items that the doctor (our resource) need to process.
Usually visits are planned one by one, not leaving any empty gap in doctor’s schedule. This is an attempt to optimize resource efficiency by making sure that 100% of doctor’s time is utilized.
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Tuesday |
Wednesday |
9:00 |
John |
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9:30 |
Tom |
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10:00 |
Paul |
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10:30 |
Anna |
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11:00 |
Michael |
Mona |
11:30 |
Andrea |
Phil |
12:00 |
Stephen |
Mike |
12:30 |
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Elton |
13:00 |
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Alex |
13:30 |
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Janet |
14:00 |
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14:30 |
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In an ideal scenario every patient comes on time and his/her visit lasts not more than 30 minutes. Let’s ask ourselves how often does this ideal scenario become a reality? The answer is: almost never! The reason is that it is very difficult to predict how long will the visit last and what steps and tests will the doctor need to perform for every patient.
Do you see any analogy to software development? If we add to our doctor visit scenario urgent cases that may come up, (expedite items), it looks even more similar. The two mentioned circumstances (unpredictability of work and expedite items) are the main reasons why optimising work by high resource utilization in software development simply doesn’t work! Instead of benefits we get big delays, long queues, low employee satisfaction and high pressure.
Fortunately there are alternatives to arranging high resource utilization, and that is to first optimize flow efficiency and then look at resource utilization.
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What does this mean in practice? It means that firstly we aim to make sure that we deliver early and often rather than to keep everyone busy with 100% utilization. The prerequisite of achieving that is to optimize systemically (full product development) process, rather than locally (only at the level of a single team). Local optimization causes that every party of the process cares only for his/her “little island”, which is part of the process. In local optimization we face problems and most of the waiting time in between steps (islands). If we compare that again to the medical sector we have the situation of high utilization of every single doctor, but when additional tests or other specialist consultations are necessary, we face huge gaps and waiting times between visits.
Think about highways… A 100% utilized highway is simply a big traffic jam. No-one can move anywhere and is frustrating; We have all experienced that. The simplest way to optimize flow while considering the whole process is to limit workable items. Process them one item at a time. Think about the speed with which you drive on totally empty highway, loaded at 50% and loaded at 90%?
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One of the basic principles of the Lean approach and therefore Toyota Production System is to deliver Just in time. It means that we need to constantly limit the WIP and review our queue; ask yourself the following questions: what? when and in what amount?
This approach leads to continuous reduction of lead time. In practice that means that we can deliver more items in total, with shorter time needed for each of them.
Theoretical confirmation of the above thesis is Little’s Law that tells us that the average number of items in progress, is the rate of items that we can process in given time, times the average time that it takes to process an item.
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In order to achieve better productivity, we need to first optimize flow efficiency. High utilization of resources causes problems whenever unforeseen scope of work comes or high priority work arrives. Optimizing flow efficiency results in being able to respond to customer needs quicker with higher quality and more focused teams.
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