If data is the new oil, then knowing how to refine it into actionable intelligence is the key to leveraging its potential. To this end, CIOs are playing with predictive analytics tools, crafting machine learning algorithms and battle-testing other solutions in pursuit of businesses efficiencies and new ways to serve customers.
Hyperaware that reducing costs or boosting revenues can help them shine in the eyes of the C-suite and board of directors, CIOs are spending more than ever on technologies that support data science. Worldwide revenues for big data and business analytics will reach $150.8 billion in 2017, an increase of 12.4 percent over 2016, according to IDC. Commercial purchases of hardware, software and services intended to support big data and analytics are expected to exceed $210 billion. IDC analyst Dan Vesset notes that big data analytics solutions have become key pillars of enabling digital transformation efforts across industries and business processes worldwide.
But there is a dark side to this delirious spending: Most data analytics projects fail to yield measurable value. Legacy systems and business-line bureaucracies have spawned data siloes and perpetuated poor data quality. And CIOs are still struggling to fill the gaps in talent required to manipulate data for insights. The war for talent is fierce and the rise of university analytics programs isn’t producing qualified candidates fast enough.
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