Data is the new oil and Big Data is the new prospecting ground. In its raw state, it’s crude and needs refining through analysis, but the promise is that if you get it right, you’ll hit pay dirt with insight into your market or your customers that will release a new pipeline of revenue and profit. [OK, it’s safe to keep reading as I’ve pulled the plug on the analogy generator from hereon in].
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The argument is that most companies are missing new signals that are hidden in this data and they are still looking in the rear-view mirror at historical financial and performance information when they should be focusing on what’s actually happening in the business in the here and now. Most companies don’t need to be told this and are already monitoring metrics such as customer churn and renewal rates that are often compiled from aggregating many millions of individual transactions. Analytics doesn’t always need to be on the freshest, real-time data either as it’s unlikely that anyone is going to make a considered decision on anything other than trends and moving averages calculated over some time period that is appropriate to both the business cycle and the type of decision being made.
And before anyone points out that real-time decision-making based on real-time data happens in the cross selling and up-selling that occurs in contact centers and with online retailers, can I point out that the choice of what product to promote is usually based on the historic analysis of what customers that have purchased similar products also bought – and that such deterministic operational automation can hardly be called decision-making. The same goes for other important uses of big data analytics such as real-time fraud detection, preventative maintenance using machine to machine data flows, and the like. It’s all amazing stuff that will drive service, revenue opportunities, and profit. But to my mind, it’s robotics based on predictive modelling rather than “real” decision-making.
Big Data is still important to “real” decision making though in that being able to instantly incorporate the most recent data, (the last hour’s, today’s or yesterday’s), into the moving averages and trends that finance and others use as a basis for their decisions will always be better than waiting for period end reports to be crunched. Likewise, having an alert of some anomaly on a mobile device will make the enterprise more agile and responsive, even if the collaborative decision about what corrective action to take comes some days later. That’s right, “real” decision making needs one or more cognizant brains involved in the process, just like the one in my logo.
