After a brief presentation of Proxem and big data by François-Régis Chaumartin, the discussion centred on the possible uses of verbatim analysis in the domain of human resources. Companies have a considerable amount of HR data that is still only very marginally exploited: personnel files, performance data, data on employee skills, CV, cover letters etc… Proxem strives to develop products and HR offers that make it possible to analyse these large volumes of information.
How can the semantic analysis of big data be applied to human resources?
Applied to the field of recruitment, semantic analysis makes it possible to identify and extract the major concepts emerging from each CV and from each job offer published and bring them closer together. For example, Proxem collaborated with Apec to facilitate the meeting between supply and demand for recruitment. By building a repository of concepts, trades, skills and sectors, Proxem’s tools identify the salient elements of a CV or job offer and relate them to a conceptual universe. This analysis at the conceptual level opens the way to more effective matching.
But the semantic analysis of Big Data is not only applicable to recruitment. I can also be very useful to career management. On the Apec website, you can tag CVs, jobs and skill terms. We then have a database of changes in skills, occupations and career paths over time. One can thus identify the different occupations related to an employee, given his or her training and professional experience, can lead, or the skills currently required on the job market.
Social barometers, internet surveillance, skills mapping.
After this case study, François-Régis Chaumartin presented Proxem’s HR offer. Social barometers, surveillance of the internet on the watch for “employer brand,” legal control of offers, skills mapping and talent management… Proxem’s offers multiple services in multiple languages, as François-Régis Chaumartin demonstrated by presenting a case study. Starting from a concept like “technical advisor,” Proxem’s tools allow us to explore the semantic universe around this term and to project it towards other languages.
The “questions / answers” session focused mainly on the other possible uses of HR Big Data: why not exploit the trend of “connected collaborators” today, collect data on each employee to know his / her state of health and possibly give them more days off if they are too stressed etc.
The role of an HR manager is thus marked by its qualitative dimension and brews considerable volumes of information. However, this information is unstructured and therefore difficult to analyse. To make it workable, a semantic analysis solution is required in all areas of the broad spectrum of human resources.