Five Models for Data Stewardship

GOVERN White Paper Five Models for Data Stewardship by Jill Dyché sponsored by: A Five Models for Data Stewardship 2| Baseline Consulting Contents O Introduction .....................................................................................................................................................4 O The Problem with Data Stewardship ..........................................................................4 O Gauging Data Stewardship Models ...............................................................................6 O Five Models for Data Stewardship ................................................................................6 O Model 1: Data Steward by Subject Area .................................................................................7 O Model 2: Data Steward by Function ............................................................................9 O Model 3: Data Steward by Business Process ....................................................11 O Model 4: Data Steward by Systems ..........................................................................13 O Model 5: Data Steward by Project .............................................................................15 O Conclusion 17 .................................................................................................................................... Five Models for Data Stewardship |3 A Five Models for Data Stewardship Introduction Former Intel CEO Andy Grove once coined the phrase, “Technology happens.” As true as Grove’s pat aphorism has become, it’s not always good news. Twenty years ago, no one ever got fired for buying IBM. In the heyday of customer relationship management (CRM), com- panies bought first and asked questions later. Nowadays, business intelligence, data quality and master data management (MDM) initiatives have opened companies’ eyes to the fact that—absent sustained processes and data-centric expertise—the tools themselves rarely solve the problem. A technology’s success or failure is not proportional to the existence of an executive spon- sor, solid requirements, or even a deliberately-crafted business case. Instead it depends on the existence of rigorous processes and dedicated skills to implement and maintain it. When it comes to the aforementioned solutions, data stewardship is seen as the glue that binds heterogeneous information—ensuring common, meaningful data across applications and systems. It seems obvious that data stewardship is important to the business. However, is it really a critical success factor? The Problem with Data Stewardship When clients talk to us about introducing the role of data steward in their organizations, the need for data stewardship often belies broader cultural and ownership issues. Here’s a synopsis of a conversation with the Director of Marketing Analytics at a consumer goods firm that illustrates this point. Baseline: “So can you describe the problems that are driving the need for data steward- ship?” Director: “Well, it’s pretty clear we’re at the point now where we need someone to own the data.” Baseline: “And what data is that?” Director: “All the marketing data.” Baseline: “What are the boundaries with the data?” Director: “Boundaries? All customers, all products and all financial data. Oh, and the stores, too, so location data. And five years of history.” Baseline: “Hmmm. You mention ownership. If you had a single data owner, how would that help?” Director: “He’d own the data so he could tell us what to do with it and the processes to put in place. He’d also define it all for us, and tell us where to keep it. We have no one to do that now.” Baseline: “And how do you see this new resource spending his time?” 4| Baseline Consulting Director: “Spending his time?” Baseline: “Yes. Tactically.” Director: “We’d need you guys to tell us that.” Baseline: “Okay. But would there be an initial project or data set that the data steward could focus on? So that we can design the role and the accompanying processes to prove value?” Director: “Yes. The project would be to socialize the understanding of data stewardship.” In chaotic environments with highly distributed systems and projects, data stewardship promises a central point of contact for increasingly complex and growing data volumes. In companies where roles are vague, data stewardship assigns decision rights around data – enforcing accountability. In very political environments, data stewardship holds the prom- ise of more turf ownership and more visibility. In these cases, data stewards are often assigned hastily without much vetting or focus, and are just as quickly rendered inert by organizational maneuvering and land-grabbing. Whether they exist in the business or in IT, data stewards become roving linebackers, going from meeting to meeting with no real authority to resolve data quality problems or enhance metadata management capabilities. Many data stewards are rendered mere figure- heads in their organizations, with few constituents understanding their responsibilities. The term “data steward” is eventually met with shrugs and rolled eyes and is all too often mar- ginalized as just another indistinct IT function. Indeed, the promise of data stewardship is the inherent problem with data stewardship: it’s not specific enough. In fact, the well-worn industry precepts for data stewardship have been largely to blame for the increasing disillusionment and confusion about the role. You’ve probably heard some of them: O Data stewardship is a business function, not an IT function In fact, the well-worn O Data stewardship requires enterprise data governance industry precepts for O Data stewards define and maintain data O Data stewards are subject area experts data stewardship have O Everybody is a data steward been largely to blame But we have clients where none of the above applies and yet their data stewardship efforts for the increasing have been wildly successful. How did they do it? disillusionment and confusion about the role. Five Models for Data Stewardship |5 A Five Models for Data Stewardship Gauging Data Stewardship Models In our work with clients to formalize the role of data steward, we’ve realized that there’s no such thing as “one-size-fits-all.” Indeed, some of the most effective data stewardship pro- grams we’ve seen have bucked popular dogma and started in IT. The truth is that how you begin data stewardship depends on where you are now. When considering launching data stewardship, companies should consider a range of fac- tors, including: O Existing data-centric skills. Are data skills tied to systems? Are they tied to individual implementation efforts? Are there data modelers or DBAs who know data and who are available to different projects? Answers to these questions can determine not only what the data steward initially does, but the reporting structure. O Company culture.