Big Data is seen as the next big thing in management. Powered by technology, Big Data promises to radically transform management by replacing hunch and rules of thumb with decision heuristics based on finely analysed data. Ever since the advent of information processing, managers have had varying levels of data on which to base their decisions and with which to control business.
The difference now is simply this: While information systems have hitherto largely focused on historical data, Big Data provides managers with tools with which to predict what might be. Can we know which of our employees is likely to leave us in the next six months? Can we tell if hiring a certain profile of employee from a specific catchment area will help us retain employees for longer? Big Data helps us answer such questions.
The analytics maturity curve in the graph depicts the evolution of information science from ad hoc reports and MIS to advanced, predictive analytics. Big Data uses the power of technology to carry out statistical analyses of seemingly disparate data to unearth nuggets of insights, which managers can use to make more effective and informed decisions. Thus, retailers analyse buying behaviours to develop marketing and product positioning strategies. Banks use Big Data to predict rates of default amongst groups of borrowers. Thus, Big Data helps generate insight from data through the following continuum: Data-information-analysis- insight.
Working with Big Data requires a rudimentary understanding of statistical theory, concepts and applications. It also requires the ability to frame a problem imaginatively and the discipline to seek and use data and analyses in decision-making. Predictive analytics based on Big Data entails developing and testing hypotheses, assisting in the development of appropriate statistical models, populating and running the model with the right data and lastly, acting on the results.
How can HR practitioners benefit from the Big Data revolution?
First, they need to frame HR problems that can benefit through Big Data. A useful way of doing this would be to enumerate or identify problems concerning which we have often lamented “if only we knew...” or “if only we had this data...” or “what if ...” HR directors can encourage their staff to think about problems in their area of expertise (be it recruitment or engagement or performance management) along these lines to identify problems that Big Data can help solve. In doing so, the benefits to be gained from Big Data-led solutions to such problems must be weighed against the additional costs (including time, processing and storage costs and additional data procurement costs) involved so as to prioritise the effective use of Big Data resources.
Second, rather than leave it to the Data Scientist and his team, HR should own the problem and the process of finding a solution. They should develop hypotheses and work with the Data Scientist to identify data sets that are required to test them, secure the data and review and validate the results of the analyses.
If the right hypothesis emerges, they should then work with the Data Scientist to construct and populate the model, train staff in its use and take decisions based on the analyses.
However, no matter how sophisticated, information can never replace managerial judgment. When decisions of the greatest import and the widest ramifications are to be taken, judgment and timing are as important as data, information and insight. While data provides pointers to a decision, the manager has to apply his experience and judgment to think through the implications of the decisions from the viewpoint of the various affected parties as well as from the short and longer term points of view.
Often good decisions sour because they were taken at the wrong time. Often too, decisions fail not because they are wrong but because they were badly acted upon. To the HR manager, who has traditionally been seen as not very data savvy, Big Data presents both a challenge and an opportunity.