Figure 1: Companies vary widely in their abilities to create and use predictive information. There
are seven stages of development for predictive analytic capabilities, and each has a level of
investment and an expected return. The companies with the most mature capabilities will have
invested in all seven stages shown in the illustration and, depending on individual jurisdictional
restrictions, will have deployed analytic models to serve their customers and compete for others.
effectively the logistics of moving people,
packages and pallets. Similarly, individual consumers make daily choices to
move themselves, their passengers and
their belongings along the same roadways and flyways and use all sorts of
new navigation and alerting applications
and devices to do so. (I’ve seen a mobile
tablet computer go from a plane to a car
to a sofa all in the hands of the same individual within one morning.)
Peering into the future, if a submersible helicopter car becomes commonplace, we’d have a truly three-dimensional
A NA L Y T I C S
driving experience. And on those journeys, we might need to dodge Amazon’s
Octocopter self-driving delivery micro
bots along the way.
In the ubiquity of an instrumented
world, such a trend is unstoppable. Our
challenge will be how we will use analytics to interact with decision-making. If
consumers continue to make their own
decisions, it’s a certainty that marketing
analytics, advertising effectiveness and
brand campaigning will merge into mobile and content messaging more than
ever before. The next frontier will involve
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