I recently hosted a CFO round-table discussion in Bangalore where the subject of data overload came up. It was clear that many of the CFOs were still working out how to link such data more effectively--purchase values to supplier quality, for instance. One of the big obstacles to this is the lack of a common terminology used by data scientists and management accountants--a key concern to address.
According to the Harvard Business
Review, big data is set to challenge long-standing ideas about the value of experience, the nature of expertise and the practice of management. But what evidence is there to show that using big data more intelligently can actually improve business performance?
Academics led by a team at MIT Sloan School of Management applied some rigour to this question and came up with some striking results. Their study of 330 plcs in North America found that the more a firm considered itself to be "data driven", the better its operational and financial results were. On average, respondents that were ranked in the top third of their industries for the application of data were 5 per cent more productive and 6 per cent more profitable than their rivals. Yet a recent CIMA/AICPA survey of more than 2,000 finance professionals found that 86 per cent of organisations were still struggling to extract valuable insights from their data.
A separate study by McKinsey & Co has made some optimistic predictions about the future benefits of big data. For example, the management consultancy calculated that retailers which optimised their use of big data could increase their operating margins by more than 60 per cent. Its researchers argued that, if the US healthcare industry could harness big data to improve efficiency and quality, it could create more than $300bn in value every year. They added that government administrators in Europe could achieve nearly $150bn in cost savings by making operational efficiency...