Secrets to pulling off the big data conglomerate hat trick

John Weathington says only a very unique company should try to incorporate three big data strategies into one. Discover what he thinks is the only way for a big data conglomerate to work.


Can one company cater to everyone's big data needs?

I often talk about the three ways big data can be used in a corporate strategy. There are:

  • those that pursue big data as a core strategy and offer big data products and services to data scientists and other big data enthusiasts;
  • those that adopt big data as a supporting strategy and incorporate big data analytics into traditional products and services, providing their offerings to a wider variety of markets;
  • and those that build big data analytic capability within their organization to identify and exploit operational efficiencies.

It's important to be clear about which big data path you're following with your corporate strategy; however, nobody said these strategies are mutually exclusive. In fact, there's nothing preventing you from incorporating all three ideas into one corporate strategy -- this is what I call a big data conglomerate. A big data conglomerate is an interesting strategy, yet only a very unique company should pursue this route.

May the driving force be with you

A vital aspect of building any corporate strategy is clarifying your driving force. The driving force concept was originally created and pioneered by Kepner-Tregoe, Inc. to help corporate leaders understand exactly what business they're in. For instance, those with a products-offered driving force focus on building great products, whereas those with a market-needs driving force focus on understanding a particular market. These two driving forces are appropriate for those using big data to support their corporate strategy.

Companies that are adopting big data as a core strategy likely have a market-needs driving force, so their focus is on understanding the needs of data scientists and other big data visionaries. However, if you're using big data as a core strategy that revolves around a proprietary algorithm or a data model, you might have a technology driving force.

Kepner-Tregoe identified a total of nine driving forces, and products-offered and market-needs are by far the most common. They strongly advise that a company should have only one driving force. So, how does a company form a big data conglomerate, where big data is used simultaneously in all capacities, without violating the single driving force rule? They adopt a strategy with a return/profit driving force.

Make the big data conglomerate work

A company with a return/profit driving force focuses on building entities that generate the best returns or profits. The classic paragon for this model is GE -- from commercial finance to power transmission, as long as they can excel in a marketplace, they're open to running that business as a division. When you run your company under this type of strategy and big data analytics is embedded into everything you do, you have what I call a big data conglomerate.

For instance, you might commission your data scientists to create a proprietary machine-learning algorithm. As a big data conglomerate, you would then set out to launch a good number of divisions. You would enter multiple industries with a wide array of products and services, with your proprietary machine-learning algorithm providing the competitive advantage in all cases. One or more divisions would target data scientists and other big data experts with products that embed your algorithm. To top it off, you would diffuse your algorithm throughout the organization to boost organizational capability in key areas of Finance, Marketing, and Operations.


Options abound for incorporating big data into your corporate strategy: You could build big data products; you could incorporate big data into your traditional products; you could boost your organization's big data analytic capability; or you could do all three!

If you're brave enough to consider this big data hat trick, you should keep a few things in mind:

  • Lead with a proprietary algorithm, data model, or technology;
  • Stay impartial to products, services, and markets; and
  • Make sure each business in your corral dominates its market: staying true to the return/profit driving force.

Take some time today to work through the possibility of running a big data conglomerate. Who knows? You might end up with the next GE.

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