Evidence might often involve numbers and measures but you don’t have to be a genius at statistics to be an EB manager.  If there is one single, generic, piece of evidence that every manager should have at their finger tips it is the normal distribution, or bell curve.  It is the basis for probability theory and all of the statistics that follow. If you measure any variable, for a large enough population, the theory of probability predicts the data will produce a curve like this. So if we measure the height or shoe size  of the population we are likely to find that the majority of people are of ‘average’ size with a few at either end of the spectrum being unusually small or large. The curve is simply a mathematically sound, graphical representation of reality.  It is a truism that has been demonstrated, with real data, time and time again – it works.  Would you choose to be operated on by a surgeon who came bottom of their peer group?  Would you vote for a politician who spent the least amount of time in the constituency or had the worst record on making things happen? It is a solid foundation for the whole of EB-HR but it does throw up some challenges in practice.

Everything the EB-HR manager does can be related to this curve when it measures employee performance – the EB manager is trying to shift the whole curve to the right (better performance) but they will only know that is happening when they measure performance effectively.  But before we get into the practicalities we first have to ask the particular manager whether they subscribe to this theory or not? If they do then we can address the measurement question but if they do not it might be a salutary lesson to ask them on what basis they manage employee performance?

Of course one of the first challenges in using the curve is what constitutes a meaningful and valid performance measure?  We all know people who are technically competent or driven to high performance but there can be other factors that need addressing such as poor cooperation, short term performance at the expense of long term customer satisfaction etc. A single measure of performance can never be viewed in isolation and how do you measure ‘cooperation’ anyway?

This is more of a theoretical conundrum, that might bother the academic theorist looking for a purist model, but it should not trouble the pragmatic EB manager unduly. Let us imagine a team of 10 people where the highest performing individual, say in terms of sales, is actually the most unpopular member of the team and someone who is only interested in pursuing their own ambitious career goals. So let us construct 2 performance curves for this team but we will introduce a few grounds rules first.

Ground rules for EB performance management

1. The purpose of the exercise is to shift the whole curve to the right, not just a part of it.
2. We assume everyone can improve (even the ‘best’)
3. The person with the highest score should not automatically be called the ‘best’ (there could be other factors such as having the easiest customers or the most profitable territory)
4. No one should be blamed for their current performance – it is just a Baseline for gauging improvement.
5. Whatever measures are chosen, they have to be credible with everyone in the team (or they will cry foul)
6. The only measures that are meaningful are ones that can be connected with value (i.e. output, cost, revenue, quality)
7. Ideally, objective measures will be used (e.g. actual sales figures) but subjective scores can be acceptable when there appears to be an obvious connection (e.g. arranging a second visit with prospective customers can be read as positive progress)
8. Whatever improvements (shift in the curve) are made it just becomes the baseline for future improvements – performance management is never static.

The only other key element in this EB performance management system is the scale on the x-axis.  This works best when it is a 1 to 10 scale (where 1 is the lowest score and 10 the highest – e.g. the highest sales).  Why? Because having a ‘0’ on the scale is not a great motivator and there is no half-way stage on a 1 to 10 scale – so prevaricating managers cannot sit on the fence and give someone a ‘5’ – they have to decide which side of the fence each person sits (a ‘5’ is below and a ‘6’ is above).

Also we need two goalposts – a ‘3’ or less is ‘unacceptable’ and an ‘8’ or above is superior.  This forces us to think in terms of who really needs to perform better and who might be ready for some advanced development?

The final piece in the jigsaw is the use of ‘intangible’ measures.  Let us go back to the question of cooperation. We either get everyone to score every other member of the team in their own subjective ways (i.e. if you think John is not very cooperative then you give him a ‘3’) and aggregate the scores or we accept the team leader’s views. We do not need to ask everyone how they arrived at their own subjective scores – all we need to ask them is what a one point shift on the scale means? So if someone gives John an ‘8’ we ask what he would have to do to score a ‘9’.  This is a very simple system and only works well when you take blame and pressure out of the equation (unlike ‘forced ranking’ which is predicated on pressure and the threat of dismissal).

Once you are skilled in using this system it can be applied to –

• leadership development (how would you score their leadership capability?)
• talent management (who has the most talent and in what?)
• equal opportunities and diversity (why haven’t we put the highest performers in the highest positions, regardless of gender?)

Performance management does not have to be complicated but any HR policies that are not based on a meaningful performance curve could be moving the organisation backwards.

For personal development linked to this topic visit the Consummate Professional Series