Across industries, “big data” and analytics are helping businesses to become smarter, more productive, and better at making predictions. Tapping this potential for your organization begins with shaping a plan.
Data analytics: Three key challenges
By now, most companies recognize that they have opportunities to use data and analytics to raise productivity, improve decision making, and gain competitive advantage. "Analytics will define the difference between the losers and winners going forward," says Tim McGuire, a McKinsey director.
But actually mapping out an analytics plan is complicated. You have to set a strategy; draw a detailed road map for investing in assets such as technology, tools, and data sets; and tackle the intrinsic challenges of securing commitment, reinventing processes, and changing organizational behavior. Our collection of content, which synthesizes key insights drawn from many analytics projects, sets out the key issues, whether you are launching a pilot project or a large-scale transformation.
Building a data-driven organization
Matt Ariker, COO, McKinsey Consumer Marketing Analytics Center
"Big data: What's your plan?" sets out the imperative task: to develop a plan that brings together data, analytics, frontline tools, and people to create business value. Only by spending the time to craft a plan can executives establish a common language to focus on goals and on ways of getting started.
Above, in the first of three videos, Tim McGuire sets out the triple challenge that companies face: deciding which data to use (and where outside your organization to look), handling analytics (and securing the right capabilities to do so), and using the insights you've gained to transform your operations. Misconceptions around these tasks trip up many companies.
Matthias Roggendorf, McKinsey senior expert
In another video, Matt Ariker, of McKinsey's Consumer Marketing Analytics Center, focuses on the human element: the skills needed; how to organize and integrate new capabilities, people, and roles; and the mind-set and behavioral changes organizations must make to become data driven. Finally, McKinsey expert Matthias Roggendorf outlines the essentials of a business case for implementing a data transformation.