Image by Stuck in Customs via FlickrCraig over at The Process Ninja has an interesting little post discussing 'Dead Time' in processes. Basically it comes from a study which occurred many years ago where 'fast' workers could only work flat out for a length of time before dropping back and becoming unproductive, whereas 'productive' workers worked constantly at a lower efficiency rate. Overall the 'productive' workers beat the 'fast' workers. The difference between the 100% worker rate and the 'productive' rate is what Craig calls "Dead Time". He gives a couple of, admittedly simple, examples:
...is it worth installing new lifts in a building that are super fast to enable employees to get to their desks quicker? I'd say probably not as this period of time may fall into 'dead time'. 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.Now this got me thinking about the application of 'dead time' within process management itself. It obviously has applications within aspects such as simulation: Whenever you are working through simulation there is always the temptation to try and load the figures one way or another to affect the results. In a given simulation step you will have metrics values such as 'Total work time' and 'total delay time' as well as 'transit time' and 'queuing time'. Nominally these times are gathered by monitoring existing processes and recording the time for the process steps there. The problem with that is that you can quite easily forget about the dead time in the process. Isn't it easy to watch two or three people who are working a process step and capture the fastest time as a 'best practice' timing? The obvious problem with this is that if this person is not the most productive person you could be falling into the trap of ignoring the 'dead time'
The other thing with 'dead time' is that it affects productivity for some people but can also then start to reduce the productivity of unproductive people even more. Let's follow Craig's example of the super fast coffee machine. If the '30%' worker comes into the kitchen and sees the '100%' worker chatting with someone over a super-fast cappuccino isn't there a chance that he or she will also stop and chat for a while? Suddenly the 30% worker then become a 50% worker. It's a slippery slope.
I honestly don't think we understand - or at least acknowledge - the concept of 'dead time' enough. Fundamentally it has the ability to change the way we view processes - or at least to alter our perception of productivity within a process. It can do this either in a positive or a negative fashion too.
I'm going to do some thinking about the effects of this and get back to you with more about this soon. In the meantime, do you have examples of 'dead-time'?
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