Sometimes people come up to me and say: “Where is the human factor in HR analytics? You can not put a number on everything, in the end we are talking about people, right?” I really think we have to turn that around. I believe that you are forgetting the human factor if you are not applying analytics. Let me explain.
Most people will agree on the fact that analytics is improving decision-making. The combination of your experience and intuition together with the use of advanced analytics will increase the value of your insights. It is the experience and intuition that allows us to focus on the right business question, to interpret the anomalies in the data, to challenge the outcomes of the analyses and to efficiently drive insights into effective action. It is the analytics that allows us to minimise human bias and to discover new relationships in the data that we didn’t think of.
Human bias can result, for instance, in not hiring or promoting the ‘right’ candidate for a specific job. Do you think it is ‘fair’ for employees if we reject them for the wrong reasons? Human bias can also result in ‘inefficient’ interventions to maximize employee’s health, engagement or development. Is it ‘fair’ if we send employees to a training program that is not helping them to develop or to be more engaged? In other words, human bias can ‘hurt’ your employees. And do not think that you are immune to human bias. Simply read Kahneman. So if you have an instrument like analytics to minimise human bias, why wouldn’t you use it?
On top of that analytics can provide you with new insights, sometimes counter-intuitive, that ‘help’ employees. For instance you might find a relationship between specific working conditions and absenteeism. Or you might find a relationship between team characteristics and employee engagement (and maybe even customer satisfaction). Why would you not try to do everything possible to enable your employees to be as healthy, engaged, effective and productive as possible and help your organization at the same time?
I am not naïve; of course you can misuse analytics only for the benefit of the organization if you want. But misusing analytics is not caused by using advanced statistics or data mining techniques but by the fact that analytics is used for the wrong reason. Ironically it is a ‘human’ that sometimes forgets the human factor, not the ‘analytics’. So when you are serious about the human factor in HR and you are willing to use it for the better of your employees within the boundaries of privacy legislation, you should start implementing analytics right now!
Creating insights and using insights
In most cases people also think that technical skills and techniques are at the heart of analytics. I disagree. Don’t get me wrong they are important, but creating insights means nothing if your organization will not use them. To my opinion creating insights is the easier part because it is a technique that can be learned or outsourced. Using analytics is much more difficult because this deals with human beings having to understand the possibilities of analytics, accepting unexpected or counter-intuitive study outcomes and having the courage and will to act on it.
Creating insights is about applying sophisticated analytical methods like multiple regression, SEM, K-means, Random Forest, K-nearest Neighbour and other data mining techniques. Please do also have a look beyond ‘classical’ statistics and start exploring these data mining techniques. The purpose is to squeeze out as much information as possible out of your data that is relevant to your business question. In the world of HR or people analytics these methods are used on HR datasets combined with business datasets. So for instance analytics can provide insights on the relationship between team dynamics or characteristics and revenue per department.
And again, do not think that data techniques by itself are enough to create insights. You will need the experience and sometimes-even intuition to explain and improve the models. I guess, here as well, some human factor is needed to create the best insights. The insights are in most cases very powerful and valuable but they mean nothing if you cannot turn them into action.
Using insights is about your organization accepting new insights, making decisions and acting on them. This all starts with being able to tell a story based on your research. There are many examples where great insights are presented poorly with too many technical details. You basically need some consultancy skills in your team to ‘sell’ the insights to your customer. Use business language, business examples, strong visualizations and keep it simple.
Second, your HR managers and experts should really understand the possibilities of analytics. They are the ones who are having valuable discussions within the business or they are the ones who are developing new HR policies or services. So make sure the power of HR analytics is not only known by your analytical team, but also by the rest of HR and your business. They should be able to recognize the opportunities of analytics for their business.
Demand and supply of analytics
It is going to be very difficult to scale up and improve analytics solely by the efforts of your analytical team. You need ambassadors or translators if you will. Also read “HR business partner, are you an analytics translator?” by Luk Smeyers. These ambassadors should and will drive demand for analytics in your organization, where your analytical team is responsible for the supply. Demand and supply should preferably not be in synch! Nobody wants a status quo! Your analytical team (supply) should inspire and motivate your organization to use analytics, where your organization should ask for more insights (demands) what will drive the maturity of your analytical team.
Finally HR should start to think in relevant data spots. Are you collecting the right and relevant data to help your employees or your business? Do you have the right measurements of success defined in recruitment, learning and development or for example succession management? Counting your vacancies filled is important, but counting and analyzing your hires that are still engaged and productive after three years really adds value for recruitment and your business. Policy makers and product owners within HR must re-assess their policies and processes on relevant data. This will require some process and data design thinking in HR.
All of the above is about the bigger picture of HR analytics and based on our experience in the last years. It is not only about using advanced techniques. It is also about minimizing human bias, creating new insights, helping employees, using the insights, creating relevant data and creating a high demand for analytics. So the question people should ask to approximately 90% of all organizations is: “Why are you not using analytics? Do you not care about the health, engagement, development and productivity of your employees?
Experts to follow
Here are some highly appreciated experts you should follow if you want to know more on HR analytics; Luk Smeyers & Jeroen Delmotte (iNostix by Deloitte), David Green, Dave Millner & Jonathan Ferrar (IBM), Jeremy Shapiro (Morgan Stanley), Esther Bongenaar (Shell), Evan Sinar (DDI), Tracey Smith (Numerical Insights), Andrew Marritt (OrganizationView), Bernard Marr (Advance Performance Institute), Max Blumberg (Blumberg Partnership) Greta Roberts (Talent Analytics) and Mark Berry (CGB). My apologies if I missed one…