Here is an excerpt from an article written by Tom Davenport for Deloitte University Press (August 6, 2014). According to Tom, ten types of innovation can be driven, supported, or measured with analytics. If you’re not using analytics for all ten types, you may not be optimizing your analytical capabilities. To read the complete article, check out other resources, learn more about the firm, and sign up for email alerts, please click here.

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A few weeks ago, I heard an interesting presentation by Larry Keeley of Deloitte Monitor’s Doblin Group, a company that consults on innovation. I had seen Doblin’s “Ten Types of Innovation” before, but hadn’t really paid enough attention to it. Keeley’s presentation reminded me that I thought it was the most complete listing of how companies can be innovative. It also made me wonder how many of the 10 types of innovation might involve analytics in some way.

So I started going through the list, one by one. I didn’t know how many might result in a hit — a link to analytics — when I started. Through the magic of ex-post-facto editing, I now know how many. I won’t spoil the secret, but here’s a hint: This essay is pretty long.

[Here are four of the ten.]

Profit model: Profit model innovation involves new ways to monetize a company’s offerings and assets. There is certainly an analytics spin on this form of innovation, in that many companies in both online and offline businesses are attempting to make profits with new data and analytics-based products and services. GE, Monsanto, and several large banks are among the traditional businesses that are exploring profit model innovation with analytics.

Network: Network-oriented innovations involve new products, services, or processes that are delivered across a business network or ecosystem. In analytics terms, this might involve delivering analytics to suppliers or partners in order to help them make better decisions. In another context, with the Internet of Things, companies almost always need to share sensor data with their ecosystems, and to define standards so that the information can be integrated and analyzed. More about this below.

Structure: To quote the Doblin/Deloitte website, “Structure innovations are focused on organizing company assets—hard, human, or intangible—in unique ways that create value.” In an analytics context, this would most likely mean creating new business units that focus on analytics or using new organizational formats that allow analysts to work with decision makers. Large banks, for example, have formed new business units to analyze customer data. Similarly, other businesses create a centralized group of analysts, and then “embed” many of them with key decision makers in business units and functions. Both of these could qualify as structural innovations.

Process: These types of innovations are, of course, about improvements—small or large—in how organizations go about their operations. Process improvement was perhaps the most common use of analytics in the earliest days—particularly for supply chains and logistical processes. Today, companies use analytics to enable process improvements and innovations in pricing, marketing, sales, and manufacturing. Of course, a firm can never stop innovating with its processes, using analytics or other resources. Otherwise, competitors will adopt the same process innovations and can quickly catch up.

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I wasn’t sure when I started, but as you have probably counted, I am now quite convinced that all 10 types of innovation can be driven, supported, or measured with analytics. If you’re not using analytics for all 10 types, you may not be optimizing your analytical capabilities.

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Here is a direct link to the complete article.

A world-renowned thought leader and author, Tom Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College, a Fellow of the MIT Center for Digital Business, and an independent senior advisor to Deloitte Analytics. His latest book, Big Data at Work: Dispelling the Myths, Uncovering the Opportunities, was publi9shed by Harvard Business Review Press (2014).