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November 19, 2011

Beware the Unintended Consequences of Performance Measures

What are the behaviours that your organisation’s performance measures encourage? The fact is that all performance measures have consequences and, sometimes, those consequences are unintended, or unforeseen.

Let us take an example. Consider a company where “machine efficiency” or “labour efficiency” are KPI’s for managers. What do you get? Well, I can assure you that you will get good “efficiency” measures; but you are also very likely to have work-in-progress and finished goods stocks pretty much out of control. The reason? To get those efficiencies up managers are likely to push work into the process – work which has not been bought by customers – and that will lead to rising inventories (not to mention the drain on cash).

So the company might add some inventory reduction target to its KPIs. If the business retains the machine efficiency” or “labour efficiency” measures too, then even more unexpected consequences are likely to result. Perhaps the managers will convince customers to take “consignment stock” – if this is not part of the inventory target. Or perhaps they’ll be able to find “quality” problems with the stock so it has to be reworked – keeping up the “efficiencies” without increasing stock levels!

All performance measures have consequences. The trick is to think through what those consequences might be and to choose the measures that have the least damaging consequences.

So what are the right measures? It is difficult to generalise but let us consider a couple of the options.

In his book “It’s About Time”, Rajan Suri argues that manufacturing lead time should be the key indicator of manufacturing performance. Indeed, he argues that it should be the only indicator to avoid unintended consequences. I am not sure I agree with that point since lead time could be speeded up by ignoring quality: so I reckon First Time Through quality also needs to be an indicator and probably delivery performance too (though Mr Suri warns that delivery performance can lead to the unintended consequence of increasing finished goods stock to ensure that deliveries are made on time).

The definition of manufacturing lead time can vary according to circumstances, but, broadly, is the time between initiating an order and delivery to the customer. Where goods are made to stock, this would need to be amended.

I certainly think a measure of “flow” time is essential in manufacturing and service organisations. Lead time is the most common measure. Raw material days, plus WIP days, plus finished goods days also provides a measure of the time materials (and, therefore, the product) take to move through a business process.

In “The Goal”, Eli Goldratt argues that we only need focus on the efficiency of the constraint step – since this is what is constraining the whole process. If we improve the throughput of the constraint step we improve the output (and thus efficiency) of the whole process. By “efficiency” Goldratt doesn’t mean the acccounting measure, but rather the “capacity” – i.e. maximise the throughput of right-first-time components for customer orders through the bottleneck step.

Flow time, quality, the efficiency of the constraint process, and customer service are all good measures, but whichever measures that we choose, we need to think through the unintended consequences and behaviours that they may give rise to. In particular, we need to be careful about “appraising” individuals on their performance against some performance measure target as this will inevitably lead to massaging the figures and internal political frictions as managers try to push problems out of their “area”. Even more importantly, I believe that basing individual financial rewards on individual measures should be avoided as this will exacerbate dysfunctional behaviours – group rewards based on overall performance will encourage cooperation.

As Alfie Kohn said in “Punished by Rewards – “When we are working for a reward, we do exactly what is necessary to get it, and no more”.