More than twenty years ago, consultants Stan Davis and Bill Davidson, in the book 2020 Vision, argued that a company’s “information exhaust” (information byproducts gathered in the course of its normal business) could be used to “informationalize” a business (develop products and services based on information) and turbocharge its performance. Their primary examples of this phenomenon were information companies—Quotron, TV Guide, TRW, and the like. They did argue, however, that any company in any industry had the potential to be informationalized by its data exhaust.
Davis and Davidson’s vision may have taken a while to come true, but it has surely been verified in the big data era. Many companies are creating products and services based on data. These offerings help customers use a company’s traditional products more effectively, optimize business processes around the use of the products, and compare their performance to other customers.
I have discussed this topic recently with two companies for which I am an advisor that are making hay from data products. MarketShare, a provider of analytics software for evaluating and optimizing marketing investments, has gathered aggregated, anonymized data that quantifies improvements in sales and profits that can be achieved by marketing activities. It has incorporated the data—and the results of its cross-media, cross-channel predictive analyses on it—into a product called MarketShare Planner. It allows marketers to develop scenarios addressing how much they should invest in different types of marketing initiatives (online and traditional advertising, search, mobile, social, etc.) and what the outcomes are likely to be. Companies that don’t have their own historical data can rely on the experience of others. This patented benchmarking technology is used by some of the world’s largest companies for new product launches, emerging markets where data can be challenging to collect, or for very quick resource allocation decisions.
Another company I advise, Medidata Solutions, is primarily in the business of supporting life science clinical research with cloud based software. They provide solutions and tools for the entire process of clinical trials, from design to assessing results. As a result, they know how pharma company sponsors and other players perform in the clinical trials process. They have captured clinical, operational, and financial data—again, aggregated and normalized to ensure anonymity—and make it available in a product called Insights. That offering lets pharma companies examine their own performance relative to other firms in the industry, and also evaluate the performance of contract research organizations they hire, or clinical trials research sites they work with. The data come from more than 6000 clinical studies from over 350 different sponsors. Not surprisingly, Medidata’s trial sponsor customers find that information quite useful. Medidata is working on making it even more useful, with predictive analytics and integration of the insights into the core systems for managing trials.
These two companies can offer new products based on their data exhaust 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 the anonymized data for these purposes. In addition, of course, they had to execute—they collected the data over time, ensured that it was cleaned and integrated, and developed analysis tools for customers around the data.
Providers of all types of software should ensure that they have the ability to use the information generated and captured by the software for analytical purposes. For that matter, providers of any product or service that involves data—and that is an increasing percentage of all products and services—should examine their agreements with customers to ensure that they can use it—and charge for offerings based on it.
To make this possible, corporate lawyers need to learn more about data and analytical products, and analysts and data scientists need to learn a little bit about the legal agreements behind the data they use. At a minimum, the two groups should be talking with each other. We’re likely to see lots more data products in the future, and owning the rights to your data exhaust is critical to developing and introducing them without lots of lawsuits.