Photo: Bill Lee, Advisory Partner, Ernst & Young Advisory.
"Most people use statistics the way a drunkard uses a lamp post, more for support than illumination."
These words by writer Mark Twain from over a century ago couldn't have been more relevant today. Communities and organisations generate and collect huge amounts of data in the highly technologised and connected world today—so much so that the terminology "big data" was coined. Yet, there ought to be little comfort in just knowing that this sheer amount of valuable data exists.
Organisations today struggle with making sense of their internal data and most are clueless about what to make of the deluge of data on the World Wide Web, let alone transform data into intelligence to drive revenue and performance, or store them safely to protect customers' personal information. These are at once both opportunities and risks for any organisation. It is hardly surprising that data analytics and data privacy are two of the most significant technology trends to reckon with, and fast gaining traction with CIOs and other C-suite executives.
Picture these: A major global brewing company can advise its retail outlets on what kind of beer their local customers are most likely to choose, which shelf positions will lead to the most sales, and what extra snacks they would prefer to pick up alongside these. A bank can predict the volume and value of checks transacted across its retail branches across the days of a week and deploy its manpower accordingly, while at the same time potentially identify anomalies or fraudulent checks. With data analytics, these scenarios of improved productivity, efficiency, quality and revenue sales are not far from reality.
"Analytics" has been one of the most misunderstood words, where it is commonly taken to be report generation or multidimensional reporting. Analytics is much more than that. Its predictive and forecast capabilities enable users to take a peek into what will happen and the relationship of available data. As such, it can predict to a certain degree of accuracy what might happen next. It is also capable of using organisational research methods to optimise events to the best of limitations offered. On top of that, all these functions can now be automated, and with available technologies, reduce data crunch time to real or near real time.
In short, analytics today allow users to understand the data, the relationship between them, predict what might happen next, and thereby enabling users to optimise the event. It allows users to be proactive in the manner they manage their business and address issues before these issues become problems.
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