My new book is called Big Data @ Work (get it?—the @ sign means the Internet and all that digital stuff), and it describes how large and small companies can get business advantage from big data. It’s got lots of examples of how companies are already moving out with this incredibly important business resource.
But every movement has leaders and laggards, and today I want to focus on the laggards—the big data underachievers. These are the companies that have had a lot of data for a long time, but haven’t done much with it. They had big data before big data was big, but for various reasons they simply didn’t use it to improve their business.
At the top of my underachiever list is the cable telecom industry. I have already written a bit on Comcast, but I thought about them again in terms of analytics when they announced they were going to acquire Time Warner Cable. The TWC acquisition, should it be successfully consummated, will certainly bring Comcast more data — not to mention more customers, revenue, and power. But will it bring better analytics? I doubt it—at least not anytime soon. One of the problems of the cable industry is that it’s been consolidating for a couple of decades, and instead of finding ways to use its existing data, it simply acquires more. Each acquisition brings in multiple different data formats and standards, and different processes for managing it. More data, less analytics.
As a result, the industry — and Comcast in particular, since I know them well as a customer — is unable to do basic analytics that other companies undertake on their customer data. They can’t seem to identify their best customers, and to give them better treatment. They don’t seem to know which of their most profitable customers are likely to leave them. Their marketing offers are targeted only in the most rudimentary fashion. These are the companies that ask for your phone or account number several different times during a customer service interaction, so it’s not surprising that they can’t use customer data in analytical business processes. I know that Comcast, Cox, TWC and other cable companies have hired some analytics talent, and I am sure they are capable people. But I have yet to see any indication that their work is paying off.
I mention several other underachieving industries in the book. They include:
Media and entertainment firms, who underachieved despite massive amounts of data on viewing behaviors. Why? Because they have long had decision cultures based on intuition and gut feel, and they didn’t know how or care to assess whether people were engaging with their content or not (in premium TV, think HBO and Showtime, as opposed to Netflix and Amazon);
Retailers had great data from point-of-sale systems, but most have underachieved with it until recently. Point of sale devices and most retail loyalty programs generate lots of data that is rarely used effectively. Tesco and to some degree WalMart and Target have been higher achievers;
Consumer banks have massive amounts of data on the money we spend and save, but for the most part they have been underachievers in helping us make sense of our financial situations, and presenting desirable targeted marketing offers to us (this is starting to change, as I argued in a previous post http://blogs.wsj.com/cio/2014/01/03/the-data-product-era-begins-in-financial-services/), and they do better at fraud prevention;
Electric utilities have been talking about the “smart grid” for a while, but we are still a long way from it. Apart from some limited rollouts of smart metering devices and time-of-day pricing, the US grid is still pretty dumb.
I make a distinction in the book between underachievers, who have lots of data but don’t use it, and the analytically disadvantaged, who just haven’t had good data. I’d put health care providers in that camp (though health insurers border on underachievement), and B-to-B firms that just don’t have much customer data.
Today, however, almost any firm can take advantage of big data if it puts its mind to it. If companies can’t get enough good internal transaction data, they can augment it with all sorts of external data sources. They can pop sensors into their supply chains and products and learn about how things flow and are used. They can monitor the behaviors of customers and non-customers, competitors, supply chain partners, and even employees. There is no limit to the opportunities, but unfortunately there usually is a limit to management awareness and desire to make use of big data. That’s the limiting factor these days.
Originally published in WSJ’s CIO Journal.