by Andrew White | August 14, 2017 | Comments Off on WebMD Shows Why Data Gravity Begets Business Process Gravity
You have probably read or heard about data gravity. I first learned about it a couple of years ago when my colleague, Alan Dayley, was explaining how amassing data to comply with retention policies was creating a self-feeding problem: the more you kept data around, the more data you collected. In other words as data collected, it would itself start to attract and collect other data because having it close by, in the same place, reduced the “friction” that would ensue if you had to connect to data across a wide number of sources.
It turns out that a notable collection of data may meet many uses, not just compliance. A data warehouse and nowadays a data lake is a sizable mass of data. But the improvement in analysis or machine learning processing is notable as that data mass increases. We may seek to increase its mass explicitly and actively collect more data. Data gravity implies that data mass will increase organically or on its own, indirectly, even if we did nothing explicitly. In other words it is a natural business phenomenon.
This morning I was reading an article in my US print edition of the Wall Street Journal, titled, “WebMD Looks Beyond Information“. This title intrigued me since I could not imagine what comes after data. But after reading the article it was obvious. The article explores an interview with Blake Desimone, CFO of WebMD.
The CFO explains how WebMD has been amassing data related to healthcare. In fact I have used WebMD in the past and it is clear that it has a vast treasure trove of useful information. But what is actually ‘beyond’ data? What can be beyond data, given the acquisitive efforts of other vendors (e.g. IBM, Oracle etc.) in securing access to data to power the algorithms of our digital future? I had concluded some time ago that business process (including apps), and analytics, are all held hostage to data, and so ownership of the (information) asset trumps ownership of the analysis or process. Mr. Desimone explains that given the dominant nature WebMD has with one of the largest medical data pools, it is a logical step to add the ability for a customer to take action. In other words, once you have enough data, it is more efficient and effective to move up the stack and add businesses and applications on top. The friction between the data is one thing, but this is closer to the Coase’s theory of the firm and transaction costs: there is much less friction across the stack (more data) as well as up the stack (to process). This is much less data gravity and more process gravity.
If you think about this, it is obvious. You are a sick person or someone interested in some medical data. You search and find the information you are looking for on WebMD. Your next task might be to schedule an appointment or call someone for additional context. Instead of WebMD pushing you (the customer) off to another website or service where the process/app has to collect the data (WebMD shared the data with an external service, or you re-key it), their plan is to extend their capabilities directly. The mass of data has grown so large that there is an ease, a natural progression, to overlay and add business processes and applications on top. This then disrupts what had been an established relationship between the healthcare organizations.
It is more effective and efficient to build across (more data) and up (more apps/processes) than building and maintaining apps elsewhere where you would need to transport the data. This is a great example of when collecting data provides better results than connecting to data. Data gravity drives the attraction to business process gravity. I thought that the WebMD was a nice example of this evolving theory.. It nicely exposes the role of information costs as part of the overall transaction costs that define the boundaries of an application, business process, or indeed a firm.
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