HR Analytics bring a strong competitive advantage
The human resources sector has been slow in using data, says Alain Labouverie, of UCB. He lays out the valuable contribution of data, especially the improvement of the speed and quality of decision-making.
"All business decisions involve human capital," says Alain Labouverie, Head of Talent Analytics & Technology at UCB. "Our Talent Analytics team - three full-time people - works almost exclusively on projects. We translate each decision into a question solved by an equation. Imagine that we have the ambition to develop a new competitive advantage in a field. What skills will be needed? How many people within the company have these skills? What mechanisms will allow these skills to be mobilized - training, recognition, systems, structure, corporate values, etc.? All this, done in close cooperation with the IT department, makes it possible to objectify decision-making and often to reveal previously unseen implications. "
Do not be afraid to go wrong
An example? If the company wishes to accelerate the development of new products, it may decide to prepare a research phase before closing a previous phase. The Talent Analytics service assesses the best way to add agility, more entrepreneurial thinking in processes, respecting all ethical and legal requirements. Having good data was already crucial for the production, marketing, finance and other departments. Adding HR data and making all of this data accessible to key people on a single platform - meeting all privacy requirements - offers an indisputable competitive advantage. Also, by bringing together the teams adapted to each project, transversal logics that break the silos are favoured. A prerequisite is the quality of data coming from each department. "Every employee has to say to himself: to introduce good data into the system is also my job", insists the expert.
Predictive tools on departures
There is no magic equation for each decision, warns Alain Labouverie. However, we can develop interesting predictive tools, for example on the risk that an employee can leave the company. To do this, we compute all the data relating to previous departures: how many times has the person changed positions, managers, how quickly she has been promoted, etc.? The machine then establishes correlations and evaluates the starting probabilities. "In a more general way, it is essential to give some latitude to test new ideas," warns Alain Labouverie.
"We must admit that sometimes we do not find the perfect answer to a question. But not finding that answer is also an answer, and the investment is not lost if we come to that conclusion quickly and learn during the process. At all levels, teams must be imbued with this idea: we learn a lot from the mistakes we make! "
Learn more about the ways Agilytic helps HR teams reach their goals through smarter use of data.
