What you measure is what gets done. True or False?

An entire industry of books, gurus and consultants is based on the very idea that ‘what you measure is what gets done’. Countless people around the world people get performance managed but yet, the right things don’t always get done. It seems that innovation and performance cannot live in the same space.

Look at the strategic plan of any large organisation and you will be impressed. Yet with all the balanced scorecards, KRA’s and KPI’s seemingly well thought through at the top of any organisation, somehow the further you drill down the less clarity people have about what is really required of them. As just one example: Regenesys Business School’s extensive experience with Skills Audits shows that there is invariably a sizable gap between how important the individual thinks a skill is to their job versus how important their manager thinks it is. The gap is often as much as 80%. Yet for many companies, these performance management systems are based on continuing to define and institutionalise these gaps. By asking an employee what they believe their KPAs should be – the whole system of cascaded goal setting has failed.

Organisations often do not meet their service delivery targets. Interesting research also shows that most people do not like having set goals and tend to have a lower financial performance when there is an over-definition of goals. It begs the question why bother with these measurements? Well, the proposition is that of course there will be utter chaos without measurement – but it’s worth thinking about, as there is growing evidence that it may not be. We still hang on to performance measurement as the only answer as your worth as an employee is based on a measurement, your increase and your bonus depend on it, and your customers measure you every single time they engage with you.

Most companies agree that 2-3 really key performance measurements is required to drive effective financial performance. But performance is not only about the bottom line – it is also about ensuring that employees are maximally engaged and happy with what they are doing.

Firstly, let’s not kid ourselves, human beings do what makes them happy and not necessarily what is best for them. So it follows that if we can work out what makes people happy to their very core, we are in the starting blocks in the race to get them to do what we want them to – be it in the workplace or market-place. Of course happiness has been measured. So below is the quick answer by Daniel Kahneman a Noble prize winning Professor of Psychology and Public Affairs at Princeton University, who reviewed some studies and came up with the following.

Correlates of High Life Satisfaction and Happiness

  • Smiling frequency
  • Smiling with the eyes (“unfakeable smile”)
  • Ratings of one’s happiness made by friends
  • Frequent verbal expressions of positive emotions
  • Sociability and extraversion
  • Sleep quality
  • Happiness of close relatives
  • Self-reported health
  • High income, and high income rank in a reference group
  • Active involvement in religion
  • Recent positive changes of circumstances (increased income, marriage)

Sources: Diener and Suh (1999), Layard (2005) and Frey and Stutzer (2002).

Again, you might ask why even bother to measure. You probably could have guessed most of these answers yourself except for the notable absence from the list of chocolate, wine and good reading material and it probably won’t help one bit in getting a decent KPI out of your boss – well not ones that won’t leave her doubling over in laughter at your linkage of double your salary in order to achieve double service delivery.

According to Daniel Kahneman a Noble prize winning Professor of Psychology and Public Affairs at Princeton University a large body of literature from behavioural economics and psychology finds that people often make inconsistent choices, fail to learn from experience, exhibit reluctance to trade, base their own satisfaction on how their situation compares with the satisfaction of others and depart from the standard model of the rational economic agent in other ways. It seems that by our very nature we are irrational enough to defy any rational measurement!

But then one must delve deeper into what measurement means:   How we generally go about measuring is assigning values based on observation. Measurement is a reduction in uncertainty, almost never the elimination of uncertainty. In effect, science uses the term measurement to mean “observations that reduce uncertainty about a quantity”.

Douglas Hubbard author of “How to measure anything” suggests that where we go wrong is we assume that the existence of any kind of error undermines the value of the measurement – what we need to do is reframe measurement in our minds, not as a certainty but a process that helps to reduce uncertainty. It is the direction that matters – not the result.

For example, in a process like setting service levels (e.g. responding to support requests, delivery of goods and services within a certain time frame) for employees it is worth knowing what kind of service levels the organization is able to provide in the first place. You first need to measure what level of service you can more or less guarantee before you set the goal. By doing this you will reduce the level of uncertainty in the measurement of the goal. Often in organisations, the measurement before setting a goal or level of measurement is not done. Most of the time organizations define service levels without any guarantee if these levels can be met which partly explains, how, when you drill down – those beautifully crafted strategic goals lose their impact. This parameter based approach to measurement is the basis of six sigma and other measurement-based disciplines that emerged in the past few years.

Measures don’t have to be 100% correct for them to have value. The joy and indeed the usefulness of statistics is to be found in treating them with as much respect as irreverence – only then can you use them imaginatively (which is a pre-condition for envisioning the future suggested by the statistic). Only then can they act as a springboard for decision making that accommodates both the numbers and your intuition (which it seems you are going to use no matter what you learn to the contrary). Measures are useful where they show how a system functions and disconnect and through experimentation new limits can be set for processes.

What about big hairy audacious measures and goals and your KPI ’s? For many people, they are frightening, to the extent that they get ignored. Research shows that people fear being measured more than the actual goal. On the other hand, settling for a little better or the same is like getting onto a slow train to Poffadder for your reward.

So, set the big hairy audacious goal and the testing KPI and then keep on measuring how far it pulls you forward not how much you’ve missed it by!

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