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Four steps to a data business

by Thomas H. Davenport
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15 September 2014

Four steps to a data business

16 September 2014
  • Thomas H. Davenport United States
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You should already be embarking on four key steps to get to a viable position in the data economy.

Whatever business or industry you think you are in, you are increasingly in the data business. We’re entering the data economy, where firms make money from offering data- and analytics-based products and services to their customers. If your company hasn’t already had extensive discussions about its potential role in the data economy, you risk being left behind. You should already be embarking on four key steps to get to a viable position in the data economy.

Step one is to envision what your offering will be. This step applies no matter what business you’ve been focused on in the past. You may have previously sold drugs (I mean the legal kind), banking transactions, mobile phones, cars and trucks, or watches, but now you could be selling data, analytics, and insights around those offerings as well. Like it or not, you are competing with those Silicon Valley companies that have been in the data economy for a while.

Pharmaceuticals, for example, will increasingly come with data- and analytics-based recommendations on the specific genomes and proteomes for which they are effective. Banking transactions will someday be accompanied by analyses of how a customer’s spending compares to benchmarks, and projections of their future wealth. Mobile devices should tell you more about both your communication and your physical movement patterns. Cars and trucks already come with sensors that record how you drive, and soon they will come with insights for their drivers, not to mention self-driving capabilities. Watches are rapidly becoming “smartwatches”—another small, intelligent, mobile device—with plenty of sensors measuring not only time, but our locations, steps, heart rates, sleep efficiency, and so forth, and informing us of the implications. So you should get your management team together, have them think about what data you have and what functions and insights your customers need, and decide what data products or services you will pursue.

Step two is to think about the legal implications of your offering. You’ve probably already begun to collect some data that your existing products and services spew out as exhaust. So it’s time—if you haven’t done so already—to determine what you can do with it legally. Companies that already participate in the data economy can offer new products based on their data and analytics in part because they made sure that they carefully negotiated rights to use them. Their agreements with customers were constructed so that they would be able to use data (typically anonymized) for their own commercial purposes. So get your lawyers busy on this step, and pray that someone was thinking about the issue before now.

Step three is to ensure that you can create your new data product or service from an operational standpoint. This is the same type of activity that your organization has been doing for a while to support internally oriented applications. Companies wishing to do data products have to ensure that they collected or acquired the right data over time, that it was cleaned and integrated, and that analysis tools are able to give customers the insights they need around the data. In the course of this step you will undoubtedly have to do some new software development, so be ready for that. You may also need to acquire some data externally; Monsanto, for example, anted up $930 million to buy The Climate Corporation, which had the granular climate data that Monsanto needed to round out its data product offerings for farmers.

Step four is to try out a business model for your data product or service. Who knows for sure whether customers will be willing to pay for your new product by itself, or whether you will have to bundle it in with existing offerings? Who knows which data or insights they will value most? Who knows how much you can charge? Nobody really knows these things, which is why you need to begin a series of iterative activities to find out. Everyone has a lot of learning to be done on what works as a business model in the data economy, so the sooner you start, the better.

There are huge organizational implications of being a data business in the data economy for every key role in the company. If you’re a CIO, it means you had better move beyond a focus on internal applications and infrastructure. Such a focus is one way to ensure you will not be at the table when the “data business” discussions are taking place. There is no better way to lower your prestige and salary than to cede data business work to some other executive and department.

If you’re a product manager of an existing product, you’ll be asked to make room for some new offerings involving data from that product. You may not be comfortable with new products and services based on data and analytics. You may be used to more tangible features and functions, and product capabilities that are embedded in the device, rather than in some cloud somewhere. Get over it—this is the future of your business.

If you’re a CEO or business unit leader, you should immediately convene your senior team to discuss what all of this means for your company. It’s not easy to make the transition to the data economy, and you need to start now. If you’re only on the first step of this journey, somebody in your former industry is probably already ahead of you.

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Written by: Thomas H. Davenport

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Analytics , Big Data

Deloitte Consulting

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Thomas H. Davenport

Thomas H. Davenport

Senior Advisor | Deloitte Analytics and AI Practice

Thomas H. Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College. He is also a visiting professor at Oxford’s Said Business School, a fellow of the MIT Initiative on the Digital Economy, and a senior advisor to Deloitte’s AI practice. His most recent book is Working with AI: Real Stories of Human-Machine Collaboration (MIT Press, 2022).

  • tdavenport@babson.edu

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