It seems to be popular these days amongst industry pundits to recommend that organizations add a new Cxx role: the Chief Data Officer (CDO). The arguments in favor of this move are exactly what you'd think: the rapidly accelerating importance of information in the enterprise, and, as important, the heightened perception of the importance of information by business executives. The attention on information comes from all the rich new data that simply didn't exist before: sensor data from the Internet Of Things, social media, process data -- really just the enormous volume of data resulting from the digitization of everything. Add to all that: new technology to handle big data in a reasonable time frame, user-friendly mobile computing in the form of tablets, data virtualization software and data warehouse appliances that significantly accelerate the process of getting at the information for analysis, and the promise of predictive analytics, and there's plenty of cause for an information management rennaisance out there. With a little luck, the activity it catalyzes will also improve enterprises' ability to manage the data and content that's not so new but also very important that we've been struggling with for the last decade or so.
The only argument against creating this role that I've run across is that if CIOs and CTOs did their jobs right, we wouldn't need this new role. That's pretty feeble since we're not just talking about IT's history of relative ineffectiveness in managing information outside of application silos (and don't get me started about content management) -- we're adding to that a significant increase in the value of information and a significant increase in the amount of available information. And then there's the fact that the data could be in the cloud and not managed by IT, and there's also a changing picture regarding risk that suggests a new approach.
I was talking with a client the other day about the reporting structure of her applications organization. The group had a single leader, but underneath, it was subdivided into groups that were a combination of technology (website, data analytics, intranet), business unit (four major ones), and IT processes (QA). The leader of this group knew that every organization is different based on the culture, size, maturity of managers and a dozen other factors. However, she was seeing a lot of friction between groups and wanted to know what structural changes other organizations had made and what the tradeoffs were.
We started by talking about the direction of the organization. In particular, she needed to determine if the business units were moving to greater integration of their data and processes or whether the business silos formed were just fine. Though most organizations are moving to greater integration, this is not an obvious answer, as some companies have run-off business areas that are in maintenance mode and may be kept separate. For this call, she asked that we assume the company needed greater integration. There were other drivers around growth and cost containment that we discussed as well.
Hello, everyone. As a new analyst on Forrester's Customer Intelligence team, I'm taking over coverage of enterprise marketing platforms. I'll range everywhere from cross-channel campaign management to interaction management to analytics and optimization tools.
I'm thrilled to join Forrester. We live in a time of extraordinary change in the way we conduct marketing. Businesses succeed and fail on how they bring the Customer Intelligence role to bear. I have the enviable task of following Suresh Vittal — who's since taken over the leadership of the CI role — as well as Dave Frankland, Zach Hofer-Shall, Fatemeh Khatibloo, Srividya Sridharan, and Joe Stanhope. As an aside, if we meet up, be sure to ask me the story of how Joe lured me to Forrester.
Extraordinary times imply that extraordinary challenges lurk underneath. CI professionals face the test of integrating data into a holistic view of customers. Recently in my report "CI Teams: Blocking and Tackling Is Not Enough," I dug into why data integration is such an omnipresent issue. As you might expect, a number of factors -- the explosion of touch points, the staggering amounts of data generated, budget, and skills -- contribute to the problem.