Posts tagged ‘HCM’

Cognitive dissonance and HR Analytics is a bad cocktail

HR Analytics (or workforce analytics) promise to give HR executives better data to make better decisions. The potential of analytics is however easy to evangelize and difficult to achieve. I find two psychically challenges with workforce analytics especially interesting; the problem with too much information and the problem with making wrong decisions even with the right data.

The first problem is eloquently described by Jeremy Shapiro, who in his recent post writes about “cognitive load“. Here he points out that too much information will make us make decisions which are either emotional driven or irrational. He use research from neuroscience to back this up. I agree with his point completely when he writes that “know what decision you are asking someone to make. What information is needed to make that decision? Keep that data, and strip out the rest”. In other words; although analytics can provide you will ton of data don’t use it all, but keep it down to the essentials. (Check out this TED-video to see how this can be done with medical data).

The second problem is however a bit more problematic. I would propose that data in itself – even in the right measure and presented the right way – will not necessarily lead to better decisions. Why? This is explained by the social psychological concept called “cognitive dissonance”.

Cognitive dissonance is essentially the discomfort we feel when we have two conflicting cognitions (beliefs, emotional reaction, values and ideas). Take for example the doctor who is smoking. He knows that smoking is bad for his health.  He may even know the exact science behind all the health problems smoking can cause but he continues to smoke anyway. If the doctor does nothing, he will continuously feel bad about his smoking habit – he will be plagued by guilt. However, because we humans don’t like this feeling  we will add a cognition to relieve us of this pain. In this example, the doctor can do several things: He may ‘accidently’ find research which questions how unhealthy smoking really is. He may conclude that smoking relieves him of his stress at work and therefore is worth the potential problems he may suffer later. He may conclude that because his father smoked all his life and didn’t suffer of any medical problems that he is genetically immune to smoking-related health problems. Whatever he choose to do, the doctor will create a belief that can make him live with his smoking habit.

In short, cognitive dissonance will create a bias for a certain decision despite other factors such as facts and evidence may favor the alternative. So even if HR executives are faced with facts supplied by analytics, it does not mean that he/she will use that data to make better decisions. Not if that data will create cognitive dissonance.

Let’s look at a simple example: The head of Talent Management has been presented with evidence which suggests that the current talent program has no tangible impact on productivity and talent turnover. Analytics is also able to show that the ROI on the program has been negative the last three years. However, the head of TM has not only designed and approved the project but she has also told the board of its successes and won praise for them. This presents her with a problem as the data suggests that she has not done her job well. The analytics data should now be used to change the program or to scrap it altogether, but it may not happen. The head of TM will have to find a way to live with this cognitive dissonance and not make that best decision.

So what to do? Social psychology theories suggests ways to overcome this bias. You can find a good overview on Wikipedia. Essentially, I believe a solution is to have a CAO (Chief Analytics Officer) who is powerful enough to challenge HR on the results. If analytics is a sub-department of HR or a non-powerful support function, the decision maker can get away with some of the typical cognitive dissonance strategies (avoidance, distortion, reassurance, confirmation, re-valuation).

Analytics is not a end it itself – it is a mean to create better HR decisions. Cognitive load and cognitive dissonance may stand in the way unless it is proactively dealt with.

23/05/2012 at 14:22 24 comments


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