Writing in the Harvard Business Review, McKinsey’s David Court points out that although Big Data is bringing big benefits to business, it can be a disruptive and difficult technology to implement.
The investment in time and money can be significant, says Court in the HBR Blog Network piece. For example, he cites the CIO’s perceived need to revamp the organization’s IT infrastructure to accommodate the all the requisite changes, as well as implementing the “black box models” needed to cope with unstructured data. And, all the while, business mangers are asking what the pay-off will be from introducing this potentially troublesome technology into their operations.
Court’s solution is simplicity itself: make a plan.
A good strategic plan highlights the critical decisions, or ‘trade-offs,’ that a company needs to make, and defines high priority initiatives: what businesses will get the most capital, whether to emphasize higher margins or faster growth, and what capabilities are needed to ensure strong performance,” Court explains. “In these early days of big data and analytics planning, companies need to address analogous issues: choosing the internal and external data they will integrate, selecting from a long list of potential analytic models and tools the ones that will best support their business goals, and building the organizational capabilities needed to exploit this potential. Successfully wrestling with these planning tradeoffs requires a cross-cutting, strategic dialogue at the top of the company that will build high-level confidence in the plan…”
The blog goes on to examine the three core elements of such a plan. Included are: a blueprint for assembling and integrating data; determining what advanced analytical models to select; and the need for intuitive tools that “integrate data into day-to-day processes and translate modeling output into tangible business actions.”
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