A question of perspective

Putting People Analytics into Action

On the one hand, the reluctance is understandable, because the analysis of HR data is always associated with particularly high legal and ethical hurdles compared to other areas of the company. In addition, decisions that directly affect the future and career of employees should not be lightly placed in the hands of an "artificial intelligence". Negative examples of failed people analytics projects that resulted in significant image damage are numerous. Although algorithms generally act more objectively than human decision-makers, the problem of structural disadvantage in particular can be transferred to the systems. 

On the other hand, the reluctance is regrettable, since the added value of AI has long since ceased to be a myth among consulting firms and technology providers. On the contrary, the added value has been scientifically proven. Empirical research by Sinan Aral and colleagues showed as early as 2012 that the use of people analytics is associated with higher business success. Moreover, the possible areas of application of machine learning and predictive analytics in HR are as diverse and far-reaching as HR management itself.

The added value must compete with the project costs and, if applicable, the opportunity costs of analytics projects in other departments. The biggest problem, however, is that in HR, as is so often the case with human actors, it is difficult to quantify qualitative added value in concrete terms. In the end, however, it is not only the goal that counts for pilot projects, but also the journey: According to the ideal-typical learning curve, the know-how built up in the first people analytics project leads to a 30 percent reduction in the effort required for the next people analytics projects. IT systems, know-how and, in particular, data are to be regarded as assets that will create added value for many projects.

As in so many projects, the stakeholders in the project are entrusted with a wide variety of interests and tasks. A change of perspective can be helpful in promoting understanding and communication among the individual stakeholders. Accordingly, agile project methodology takes on central importance in People Analytics. Roles such as the product owner or the Scrum master are central to merging the actors and perspectives into a homogeneous overall project.