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Why 100% Productivity Doesn't Exist

By Craig Reid | Craig Reid, Leadership, CFO, Migrate |
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Many years ago, whilst at University, I studied a set of famous productivity experiments which resulted in the coining of the term “The Hawthone Effect” (after the Hawthorne works where the experiments were conducted).

The experiments showed that the act of observation and interaction with the employees involved with the experiments resulted in a significant jump in levels of work productivity. Debate still rages over the factors that caused this jump in productivity and the specific causes (more of which you can read here), but one fact that cannot be refuted is that before the experiments were conducted, the employees were not operating at 100% productivity. Logic would argue that if they had been, there would be no way that further improvement could have been achieved.

But what is 100% productivity anyway? I liken work productivity to running. You can sprint for short periods, you can walk for long periods, but neither is sustainable. Walking is too boring and lacks challenge and sprinting is too exhausting to be done for long. As humans we tend to jog along at work at a comfortable but challenging pace. If we run too fast we burn out.

In any process where human beings are involved you will never have 100% productivity - it's just not our nature. "Dead time" is what I call the gap between 100% productivity and actual productivity.

So why is this important? Well it needs to be considered when looking at processes. This is because it is unproductive to improve process steps that fall into "dead time". For example is it worth installing new lifts in a building that are super-fast to enable employees to get to their desks quicker? Probably not. Is it worth spending money on a super-fast coffee machine in the kitchen? Probably not (because people will still stand around and talk to whoever is in the kitchen at the time).

These are simple examples, but it is always important to realise that there will always be a percentage of "dead time" in every process - it isn't always worth optimising every step of the process - making the judgment call of what fits into "dead time" is the tricky part.

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