Jennifer Belissent and I just published a report on the role of the Chief Data Officer that we’re hearing so much about these days – Top Performers Appoint Chief Data Officers. To introduce the report, we sat down with our press team at Forrester to talk about the findings and about the implications for our clients.
It’s not news that business user self-service for access to information and analytics is hot. What might not be as obvious is the overhaul of information-related roles that is happening now as a result. What’s driving this? The hunger for data (big, fast, and otherwise) to feed insights, very popular data visualization tools, and new but rapidly spreading technology that puts sophisticated data exploration and manipulation tools in the hands of business users.
One impact is that classic tech management functions such as data modeling and data integration are moving into business-side roles. I can’t help but be reminded of Bill Murray’s apocalyptic vision from “Ghostbusters:” “Dogs and cats, living together… mass hysteria!” Is this the end of rational, orderly data management as we know it? Haven’t central tech management organizations always seen business-side tech decision-making (and purchasing, and implementation) as “rogue” behavior that needed to be governed out of existence? If organizations have trouble now keeping data for analytics at the right level of quality in data warehouses, won’t all this introduction of new data sources and data lakes and whatnot just make things worse?
Well, my answers are “no,” “yes,” and “no” in that order. The big changes that are afoot are not the end of order and even though “business empowerment” translates to “rogue IT” in some circles, data lakes/hubs and the infusion of 3rd party data have actually been delivering on their promise of faster, better business insights for the organizations doing it right.
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.