Do you represent one of the many organisations struggling to get the expected value out of your big data investments? If so, the temptation can be to focus exclusively on the analytics capabilities. However you might just find the problem lies not with the software but with how you view your data.
It may sound simple but the primary reason most organisations fail to derive value from big data is that the right people cannot see and interact with it in one place. Backend data scientists play an important role but ultimately they’re not the ones making the final decisions in relation to key business problems. True decision support can only be achieved by putting all of the relevant information in front of the senior management teams and process owners at the point that actions are being discussed and agreed.
For example, I’m sure we’ve all sat in one of those meetings in which we expected to arrive at a clear actionable outcome, only to find that the data we are evaluating prompt more questions than they answer. The very precise questions we have asked have resulted in very precise answers. However, when we see the resulting outputs we suddenly realise there are other equally important factors we haven’t considered or accounted for. What follows is a request for further analysis which delays the reaching of an actionable outcome. In the worst cases it leads to an organisational stupor in which the status quo is retained simply because doing anything new is too difficult.
Business leaders tasked with seeing and acting based on the big picture are too often forced to do so based on a narrow view of the business which frequently leads to sub-optimal long-term decisions. For example, looking at a single performance measure such as sales data in isolation could obscure the significant impact of variables such as currency fluctuations, supply chain problems or even disparities in staffing levels.