Posts tagged ‘People analytics’

Why evidence-based HR is critical to success and how to get started

I am huge fan of HR Data & Analytics and I have had the privilege of working with it for many years now. However, it is important to remember one thing; HR Analytics is only a mean to and end; one tool and one mean to better HR.

I talked about exactly that at Human Consult Network with Annemarie Malchow-Knudsen. We discussed among others the need for more evidence in HR and how you in small- and medium sized companies can get started.

Place your bet where you have the highest chances of winning

The purpose of evidence-based HR is not to find “the Right Answer” – we are dealing with people after all. The purpose is to use all available evidence (research, internal data, analysis, experience, interviews etc.) to find the solution with the highest probability of adding the most value to your organization and start out from there. If that doesn’t sound strong enough, believe me, it will be a huge improvement from where we are.

Why will the solutions be better? Psychological research shows that even the most reflected people fall into pitfalls such as biases (see some of the most common ones here, here and here)and prejudices when judging what the best thing to do is. We simply often choose less probable outcomes over more probable ones without even knowing it. Ordinary people like you and I do it all the time.

One way to get around it is to apply an evidence-based approach to establishing the most optimal people interventions. And this is where data comes into the picture. By being better at testing your HR-hypotheses with the use of data and valid analytical tools, you will eliminate the number of times where you decide to go for an HR intervention, which sounds appealing does not have the effect you hope for.

Start with the business challenge and then identify the data

I have seen too many good people get stuck in data cleaning, data management and tough IT-implementations without getting any business results to know that there must be a better way. So, if you don’t want to end up in that situation start with the business challenge and focus where you can add value quickly. My experience is that many start the other way around as the only option and that can mean that business results take too long to materialize.

HR Data Value Chain

Start from the top of the figure (for more info about the content of the pyramid see here) shown above by asking for the business issue, which you will help solving. If the primary business focus is on cost-optimization, your people activities should also focus on cost-optimization. You should focus on getting most value for money invested whether you are involved in leadership development, induction programs, talent management, staffing or something else.

Then ask which knowledge you will need to get that insight: do you need more knowledge of learning efficiency, more knowledge of staffing costs versus performance outcomes of different staffing strategies, insight to identify the best-fit candidates when recruiting etc.

Then identify the information you will need to create that knowledge. You can get inspiration externally from scientific research and best practices, and you can strengthen the argument by analyzing your own organization.

Only then, will you know which data you will need to establish to underpin your intervention with convincing evidence. You can now gather exactly the data required to make an ROI-assessment to underpin your argument – and help you chose the approach with the highest probability of success.

Taking this agile approach will enable you to build your data foundation along with creating value-adding insights to inform business decisions. You cannot avoid investing in data and technology, but providing a flow of value adding insights will ease the funding.

 

14/09/2017 at 11:43 Leave a comment

Storytelling is nothing without a proper theory – here’s why

Storytelling is rightly hailed as a must-have competence in people analytics. In my own competency model, it is one of the six core competencies any analytics team must have. Other models do the same. Compelling arguments are being made about the value of good storytelling. In other words; master it or beat it.

So don’t get me wrong; it is important. But my point in this post is that storytelling requires the presence of a theory to be successful. If you do not have a proper – i.e. a plausible and documented – theory behind your data, storytelling can do more harm than good.

Angela Duckworth observes in her book: Grit – the power of passion and perseverance, that “a theory is an explanation. A theory takes a blizzard of facts and observations and explains, in the most basic terms, what the heck is going on”. I could not have put it better myself. And funnily enough, this is also what storytelling is doing – explaining what the data says.

Let me give you an example why you need a theory to tell a story: ZengerFolkman – an excellent US data-driven leadership development consultancy company – has compared the combined leadership effectiveness scores as measured on 360-degree evaluations for men and women respectively at different leadership levels. The result is, as you can see below, that women score better than men at all levels and that this difference is more significant the more senior the leaders are.

Screen Shot 08-01-16 at 10.33 PM

I recently made the same observation within a financial institution. They had collected performance data for all their leaders and we were comparing performance data – split into different KPI groups – and it was clear that the performance rating was significantly better for the female leaders and also that difference was greater the more senior the leaders were. The data at this company confirmed the international data I had found. I had data and I had other similar data points to back them up.

So far so good.

The problem is, that although the difference between performance scores is significant the data makes little sense without a theory to explain the observations. Why are women leaders rated better than men? All we know is that the performance ratings/360-degree evaluations put women higher than men. It may be that women are better leaders than men. It could also be that women are reported to be better leaders but in reality are on par with men. Maybe there is a bias in the evaluation of female leaders. Or it could be a third reason.

Another thing to consider is the relationship between the portion of female to male leaders vs. overall performance. Is it linear or does it have another shape as depicted in the figure below? If it is linear and you conclude that females are better than male leaders, then a natural recommendation is that you should replace all male leaders with female. If on the other hand the relationship has some other shape – such as the one in the second figure below – you should identify the optimal point to reach leadership effectiveness.

Screen Shot 08-01-16 at 10.30 PM

My point is that without an answer as to why there is a difference you cannot create a story and a recommendation. To come up with a proper recommendation you must have a proper theory to explain the why. The basic analysis cannot explain it and you cannot go straight to storytelling because you are still left with the basic question of ‘why’. And what you will be left with are leaders sitting around a table wondering what to do. In this case, maybe there is a good theory. I don’t know of it (but would love to hear it if you happen to have one).

So you need a theory behind your data. An explanation if you will. It does not need to be verified by Harvard or any such institution. But you do need an explanation. Let’s say that you find that the talent you source from one university performs significantly better than the talent you source from another. You need to understand why. If you cannot explain why through a theory, your storytelling will lack the power it has the potential to have.

So: please do not do storytelling on people analytics without a proper theory explaining your data. It really makes no sense.

02/08/2016 at 18:42 2 comments


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