There are times when the HR function is given a hard time on where it sits in the C suite hierarchy and how advanced it is in the strategic element of driving business performance as opposed to practitioners in its field of operational delivery.
This article which was in The Harvard Business Review talks glowingly of the advancements HR are making globally in using analytics to make key decisions that impact on company performance. The research puts HR ahead of both Finance and General Management in the use of analytics to drive competitive advantage.
In a world where skills shortages and talent attraction and retention appear at the top of the priority lists for senior HR professionals then using data for predictive and prescriptive analytics is important today and even more important for thew future.
Figuring out talent that is a flight risk in key roles then proactively preventing attrition as well as using data to better understand great performance and modelling attraction and selection around increasing the number of high performing employees are just two examples of how this is practically adding value with many more benefits being recognised.
Today, the trajectory of data and analytics use in HR is among the steepest in any function and this will only enhance the standing of the HR function in board rooms globally.
* 51% HR respondents said that they could perform predictive or prescriptive analytics, whereas only 37% Finance respondents could undertake these forms of analytics. * 89% agreed/agreed strongly that “My HR function is highly skilled using data to determine future workforce plans currently (e.g. talent needed),” and only 1% disagreed. * 94% agreed that “We are able to predict the likelihood of turnover in critical roles with a high degree of confidence ” * 94% agreed that, “We have accurate, real-time insight into our employees’ career development goals currently.” * When asked “Which of the following analytics are you using?” “artificial intelligence” received the highest response, with 31%. When asked for further detail on how respondents were using AI, the most common responses were “identifying at-risk talent through attrition modeling,” “predicting high-performing recruits,” and “sourcing best-fit candidates with resume analysis.”