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feature | DATA & ANALYTICS


ANALYTICS DATA & own company abacus...” “and, your very


To live without digital, data-driven HR is to resign the people department to some kind of spreadsheet nightmare, mired with inconsistency and frustration. It can be argued that, although HR has long understood the value of data’s capacity to provide actionable insight, data constraints still exist for many and the lack of real-time data - and capacity to make sense of the analytics - is making the future even harder to predict.


ARTICLE BY SUE LINGARD, DIRECTOR - CEZANNE HR


The power of predictive data is game changing, and so the advantages that an organisation that utilises it over a competitor that doesn’t, is clear to see. The capacity to predict who the best performers in your business are going to be, before they even walk through the door, is full of mystical wonder, but it is a potential that can be delivered, along with knowing with confident exactitude, which employees will stay and which ones are most likely to leave at the nearest opportunity. The cost-saving potential would be huge. This of course is nothing new, consumer-targeting businesses have been marrying together seemingly unattached data from different sources such as; weather forecasts, school holidays and staff availability - in order to predict and respond to demand - with great accuracy for years. In relative terms,


however, using HR data for predictive analytics is still in its infancy, and the majority are not yet even on the adoption curve. According to an article in Forbes, 53 percent of businesses have adopted Big Data, but only a fraction of these are beyond contemplating the potential of predictive analytics. Indeed, whilst HR leaders recognise that analytics are essential, this does not yet translate into predictive HR analytics, due to there being too many variables to ensure valid and accurate people predictions. While predictive techniques seem to be meeting with some success - augmented AI video interviewing for example - high-profile examples of biased outcomes have, understandably, raised concerns amongst HR professionals. HR Director, Justine Brown said: “It’s important to question whether trends in the past can be


trusted as a guide to the future, especially when you’ll never have the complete picture in data terms. There are just too many variables to guarantee accurate results.”


There is also the question of bias in the algorithms themselves. In her book Weapons of Math Destruction, Harvard PhD and data scientist Cathy O’Neil writes about the dangers of algorithms, and warns that we are too trusting of them. She says that we must all become more clued up on the models that govern our lives and calls on policy makers to regulate their use. Meanwhile, technology companies are working hard to manage out biases arising from predictive analytics based on historic data - and while this is entirely possible, it does not address the biggest challenge of all - the fact that when it comes to predicting people


44 | thehrdirector | MAY 2019


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