By Andrew Marritt, a member of the CIPD’s HR Analytics Advisory Group and Founder of OrganizationView - a Swiss-based People Analytics practice.
There’s a belief, that I hear frequently in the HR analytics community, that HR Analytics means a move away from intuition. This isn’t true.
Analytics using your own data is just one tool needed to conduct empirical decision making. Doing analysis - however sophisticated - can only be part of what you need to make great decisions. ‘Numbers are just another voice at the table’ as the saying goes.
As Sam Hill mentioned in his post on this blog ‘People Analytics - It’s a mug’s game. Isn’t it?’:
'The People Analyst will keep formal and informal channels of communication open with HR process owners, line managers, senior managers, HR Business Partners and potentially external stakeholders to measure the pulse of their organisation and to identify emerging workforce issues or opportunities.'
As HR professionals there is usually a good reason that we hold the beliefs that we do. Many of us have built up knowledge and experience over many years of seeing similar situations, reading case studies and books or speaking to peers.
Managers too have built valuable experience. Many tend to have a good knowledge about what is happening in their organisations. They will have seen similar situations or even studied organisation theory on a general business course.
Discounting this experience and knowledge would be like starting with your hands tied behind your back, but unfortunately it’s common with some HR analytics teams.
Let me illustrate this with an example.
Suppose we are asked by a friend whether a coin is fair (ie as likely to come up heads as tails). They then toss the coin 10 times and it comes up heads 7 times. The chance that this will happen is in the region of 12%. This would be unusual but certainly not impossible. Do you tell the friend it’s fair? I suspect you might.
Now let’s change the situation slightly. Let’s say your friend then tells you he was given the coin by a magician at his daughter’s birthday party. My guess is that this bit of information would make you think that the coin probably isn’t fair. Maybe you’d think you were lucky to see 3 tails.
In both instances you’re updating your view based on the information that you had before. In the first instance you start with an expectation that the coin is fair as most coins have an equal chance of coming up heads or tails. You probably have some doubt but not enough for you to switch your view built upon a lot of previous experience.
In the second instance the knowledge the coin came from a magician changes everything. Given the source you’re now comfortable declaring the coin isn’t fair. Background information makes a big difference!
Inexperienced analysts rely too much on their data. They’d look at their data only, without any context, and say there isn’t enough evidence to say the coin isn’t fair. For them the data is everything. HR Analytics without incorporating experience or intuition is like this.
Good analysts, as Sam previously mentioned, start by collecting as much evidence as they can. They’ll ask managers and HR colleagues, they’ll probably do some desk research and see what others have found. Then they’ll take their data and update their view. The more data they have the more their recommendation will be based on the data. Conversely the less data they have the stronger will be their weighting towards intuition and experience.
Analytics models are only as good as the information they have. Intuition and experience are valuable sources of information. It’s crazy to ignore them as we move to using analytics in HR.
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