[pullquote]The implications of having bad health and dietary habits identified and used in a performance management discussion when someone is not performing in the call centre raise serious ethical concerns.”[/pullquote]So detailed was the data collected, that the organisation was able to model the ideal profile of meals, lunchtime exercise patterns and even specific gym equipment associated with high performance by call-centre staff in the afternoon. Such an approach may be useful in helping to identify the profile of high performers, “but the Big Brother or surveillance implication of this kind of analysis are really quite profound”, argue the authors. They go on: “The implications of having bad health and dietary habits identified and used in a performance management discussion when someone is not performing in the call centre raise serious ethical concerns.” They also point out that profiling top performers may lead to legal concerns depending on what actions are taken, citing the example of a data analysis which reveals that women in a particular age group are the best performers on supermarket checkouts. “One response would be to introduce a policy of only hiring women between the ages of 30 and 35 to work on the checkouts. “Such an approach, whilst rational to some degree, may have a number of implications. It would, of course, end up exposing the organisation to potential gender and age discrimination challenges.” The authors conclude: “Given that predictive HR analytics is an emerging but growing field, it will be important that some kind of ethical principles can be identified to potentially guide HR analytic activities.” The book, Predictive HR Analytics: Mastering the HR Metric, by Martin R Edwards and Kirsten Edwards (Kogan Page), aims to fill the need for “a straightforward how-to guide book to help people carry out some basic statistical analysis on the data available in organisations”.