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Analytics and Dynamic Customer Strategy: Big Profits from Big Data by John F. Tanner Jr.

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Chapter 4Creating a Big Data Strategy

Dynamic Customer Strategy requires data—Big Data—lots of it high-volume, at faster velocity, in greater variety. The goals are to accelerate learning and develop the capacity for streaming insight, the ability to make decisions and act on those decisions at the speed of data.

But data without insight isn't knowledge—one could argue that it isn't even information. The conceptual map or model is what makes the data meaningful, but it takes a strategy for Big Data to have the right data at the right time and interpreted in the right way (see Figure 4.1).

Big data strategy and Organizational learning and absorptive capacity, in this framework, help form Dynamic customer strategy, which comprise conceptual and operational map.

Figure 4.1 The Big Data and Dynamic Customer Strategy Framework

Beginning with this chapter and running through Chapter 8, we focus on developing a Big Data Strategy within the Big Data/DCS Framework.

I've shared this story many times to make the point, and frankly, I haven't come across anything better. More than a few years ago, a washing machine manufacturer in India noticed that buyers were ordering eight, 10, or even 20 washing machines but no dryers. Who needs a lot of washing machines? Laundromats, prisons, university dormitories, hotels, perhaps, but don't they need dryers too? Thinking these buyers were laundromats, the company sent a sales representative to one particularly large customer to offer coin-operated attachments and heavier-duty machines, as well as dryers. Imagine the ...

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