Predictive text: do CEO letters glimpse the writer's fate?
HR analytics may be a relatively new field, but data-crunching software in the quest to predict, for example, CEO longevity has made some headway, as this FT article by FT technology writer Jonathan Margolis reveals.
Dr Qingan Huang of University of East London’s School of Business and Law claims a 73% success rate in predicting CEO departures, based on his analysis of shareholder letters in some 600 FTSE listed companies in 2002-08. Using Linguistic Inquiry Word Count software, he matches the use of future-focussed and negative words and phrases to eventual outcomes, such as dismissal or voluntary departures Whether or not the methodology is sufficiently robust, one cannot ignore the trend for using ‘scientific method to assess, exploit and perhaps ultimately engineer emotion for commercial benefit’, Margolis writes.
This extends to emotion-tracking technologies, voice analysis and bio-sensors. Just as retailers map out customer lifestyles from their purchases, HR departments are now trying to determine when an employee might quit from observing patterns of sick days. But as FT|IE corporate learning alliance recently argued: ‘Assuming it was possible to predict when a key employee might leave… why would such information be so useful? Wouldn’t resources be better spent reducing the organisation’s dependence on specific individuals?’