Why doesn’t HR predictive exist?
In 2016, economic reality is pushing companies to challenge themselves, to reinvent themselves in a world where uncertainty has become certain. It is in this context that the predictive trend has developed strongly. Predicting the future becomes a seemingly accessible “Holy Grail”.
In the context of human resources, predictive technology appears to be THE solution to all the problems encountered. It would make it possible, among other things, to anticipate the development wishes of employees, assess their skills, predict the performance of candidates or even prevent the risk of departure.
The less cautious HR experts have thus seized on new “predictive” tools, seeing them as a stable and reassuring source of information.
Prediction is a mirage
Prediction is impossible. Prediction is a decoy. Foresight is the only possible answer in the face of uncertainty.
Predictive is based on the processing and exploitation of a large volume of data. Although data offers the possibility of reading and analyzing past and present reality from factual elements, in no way can it predict the future.
In human resources, it is neither possible to predict nor predict human behavior in a context of uncertainty and complexity. In the context of recruitment, for example, no one is able to fully confirm the relevance of a profile for a vacant position, the human bias (personality, integration into the team, skills in the field, etc.) being an integral part of the equation.
There is not one, but truths
Conferring the power to prepare the future on algorithmic models that claim to hold THE truth would even be risky. Because there is not a single truth, but an infinity, just as there are many ways of reading the past and the present. Relying on a single model makes HR lose all the richness and diversity of reality.
Nevertheless, the HR function needs to be able to anticipate its actions, faced with growing challenges: turnover, talent drain, etc. The best way to obtain signals allowing to arbitrate in anticipation is to proceed with an inductive and prospective approach.
HR can observe the internal and external reality of careers, challenge ready-made representations and preconceived ideas to induce proposals from these observations,
HR has at its disposal an inexhaustible source of data, which they must learn to master by defining interpretation grids, in order to be able to formulate several hypotheses. and imagine several scenarios in order to continuously adapt by proposing various action plans.
The role of HR tomorrow: data-driven prescriber
Among the different scenarios, only HR is able to choose the most relevant recommendations for the company. Because who better than an HR knows the company, its employees and its strategy? Certainly not an algorithm!
To go further, it is necessary to be prescriptive, that is to say to put forward certain solutions rather than others in the proposals which emerge, by selecting in particular those which will most allow the company to get ahead.
Use algorithms to collect and analyze the internal and external reality of professional career paths;
Benefit from the recommendations they offer and analyze their justification;
Define scenarios, based on these results, which emerge from received ideas, to better prepare yourself for the changes to come;
Use your expertise and business intelligence to prescribe the solutions that will allow the company to get further ahead.
Bénédicte de Raphélis Soissan is the founder and CEO of Clustree, a cloud platform for HR decision support. Before setting up her company, she was a senior manager at Intelleco, a business development, strategic marketing and innovation consultancy firm.