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Chief Data Officer?
I’m looking for your insights and wisdom. The article below comes from a recent Harvard Business Review daily briefing. The authors advocate the creation of a new senior position in organizations – chief data officer.
I’ve spent several months wrestling with a number of the issues named in the article, plus an even more fundamental question specific to my University – identifying where the heck all the information resides! That in itself is a challenge in an environment whose culture embraces distributed functions and generally resists central coordination and control.
Are any of you affiliated with universities or colleges where a similar position is already in place? Are you seeing any trends or best practices in this area as you scan the national and international picture? What are the qualifications for a CDO? Thoughts, observations, advice from anyone would be welcome.
With regards – Bill
William F. Hogue
Vice President for Information Technology and CIO
University of South Carolina
In the closing decade of the twentieth century, Louis V. Gerstner, Jr. showed the world that elephants can dance by turning around IBM, a mammoth if ever there was one. Part of his winning formula was in functional centralization, appointing the company's first Chief Marketing Officer — in function if not in name. Two decades later, it's time for corporations to embrace a new functional member of the C-suite: the Chief Data Officer (CDO).
Big data is enjoying unprecedented attention, with more than $1 billion invested in it in the last year alone. Big names like Ford and Sears are setting up data labs in the Bay Area and we have just witnessed the launch of Data Collective, a data-only venture fund set up by some of Silicon Valley's leading lights. However, most enterprises grew up in an era before the importance of data was recognized, such that the part of a company responsible for collecting, storing, and extracting data is often separate from the part responsible for using the data. This structural separation makes it difficult to implement data solutions across an organization.
Enter the Chief Data Officer. Making the most of a company's data requires oversight and evangelism at the highest levels of management. The CDO would be responsible for:
Identifying how data can be used to support the company's most important priorities. Some data use cases are obvious. Others are less so. Companies don't necessarily realize, for example, that they can use cross-selling algorithms to increase customer depth, or lead-prioritization algorithms to increase sales conversion rates. When meeting companies for the first time, we've learned not to ask, "Which problems can we help you with?" but rather, "What are your most pressing business problems?" Nine times out of 10, data has something to say about those problems — it's just that the company doesn't realize it.
In fact, data can assist most business decision-making — from the tactical (Which items should I bundle?) to the strategic (Should I open a new store in this location?). In all likelihood, data can be used to enhance the functions most essential to a business, but it takes someone who understands both the power of data and the priorities of a business to figure out how.
The CDO's most important role would be to understand when business units should be looking for answers in the company's data. Then the process of extracting those answers begins.
Making sure the company is collecting the right data. A critical prerequisite to making data-driven decisions is collecting the right data. For the CDO, this would mean ensuring that processes are being instrumented and that all necessary data is being captured and stored.
This, however, is only the first step. In some cases, necessary data must be found through experimentation. A/B testing is very much part of the culture of Silicon Valley web start-ups, but hasn't yet made its way to corporate America. If you want to know
how sales decrease as prices rise, there's no better way than trialing different prices. These experiments can yield a wealth of data which can then be used profitably in the business. It would be up to the CDO to engender this culture of experimentation.
Ensuring the company is wired to make data-driven decisions. Data-driven decision-making requires a series of steps best referred to as the "data production line." Data must be collected, stored, cleaned, analyzed and in some cases, visualized. In many cases, this process will result in an algorithm which must be embedded in business processes. It would be the CDO's responsibility to create the data production line, allowing the company to move seamlessly from collection to insight.
This is easier said than done. It's rare to find a company using complementary technology across the entire data value chain. Moreover, data is often stored in different silos, making it difficult to exploit. Imagine you're a bank approached for a loan by an employee of AIG. It's likely that your corporate lending department has spent a great deal of time analyzing AIG, such analysis having bearing on the customer's prospects of getting a bonus, being promoted, or being terminated. It's also likely that such information is hidden from the retail lending division tasked with rating the customer. Too often, mismatched technologies force algorithms to fly half blind.
The age of big data is upon us, but realizing its potential will require input from both the innovators in Silicon Valley building data solutions and the enterprises standing to benefit from them. The most valuable thing enterprises can do now to realize the promise of big data is to appoint a CDO. With facts replacing hunches in more and more areas of business, data is the elephant that should be in the room.