Data governance is how banks exercise authority, control and shared decision-making over one of their most precious assets — customer data.
It is how banks answer today's pressing questions: How do we sell to someone we don't know? Which customers do we cater to with limited resources? What service is a given customer most likely to need? How are we affecting our bottom line?
The absence of data governance reveals itself in many ways. Sending repeated home equity line offers to a customer who rents, for example. Sending duplicates to multiple variations of one customer's name. Not recognizing current customers who are employees of the bank's best corporate customer. Being slow to discern major changes in borrowers' incomes.
Years of neglect have a cost, and separate lines of business with inconsistent data practices are not harmonized overnight. But the following 10 steps are a proven path to profit-oriented data governance:
- Articulate the data governance mission. The more harmony with a bank's other objectives, the more harmoniously the program will operate. Be precise about goals: better data, better use of the data warehouse, customer expansion. Who are your key stakeholders, and what do they expect? Spell out mission, strategy and organization so all program members know what to expect.
- Secure an executive sponsor for the mission. The sponsoring executive brings leadership, and leadership is crucial for a program that is bound to run up against some organizational fences, resource constraints and business-line priorities. Make sure the executive sponsor is in a position to overcome these obstacles without spending too much energy and time.
- Invest in change management. Data governance must induce behavioral change among individuals, cultural change across the institution, organizational change in structure and jobs and procedural change in process and technology. That is a tall order for employees if they must wear two hats. Move as quickly as possible to dedicated staff. It is hard to regain credibility if an overstretched staff commits early missteps.
- Define scope and focus. It is common for data governance converts to seek to solve many issues under its umbrella. Better to be specific, relevant and achievable. Link the program to a high-profile strategy. Start with a high-priority slice, and expand according to strategic priorities.
- Define success. Specify and communicate outcomes for each objective. If marketing is contemplating gender-based campaigns, yet the gender part on forms is completed only half the time, will 80% be considered successful? Each customer account should include a social or tax id number, but only 80% do. Is 98% acceptable? For customer matching purposes, is it a match if Len Baker also refers to Leonard Baker and Len X. Baker?
- Establish policies, procedures and standards. No matter how much desire exists for data governance, a new enterprise will prompt control issues. Preempt them as much as possible by being specific about the program and by enlisting the executive sponsor to solicit support to prevent turf battles and silo building.
- Communicate. The more comprehensive the communication before and during the program, the better the reception and outcomes. Even if some business units are not participants in the early stages, keep them informed so that, when their turn comes, they will be ready.
- Create a tactical road map. Precisely what steps will lead to rapid success that can energize and secure commitment for the next steps? This is where many banks are tempted to start, but shortchanging earlier steps is courting failure. Only here is it time to document in relentless detail your planned activities.
- Assimilate. This is when you are ready to integrate data governance into the culture — to establish accountability for each aspect of it. If data governance is truly to be part of the culture, this should be evident in new-employee training, job descriptions and compensation policy. Can the people involved articulate what data governance means? Assimilation makes data governance intrinsic, not just another project.
- Audit and enforce. When it comes time to measure, record and report results, reward the good. Communicate how data governance is improving the bank's ability to achieve its business objectives. State results in terms of the bank's strategic objectives and the business units' objectives. If it is time to expand the scope, do it in the same methodical way, starting by reassessing your mission.
Today it is not unusual to see banks spending millions of dollars on campaigns and customer initiatives that are inadvertently premised on weak or incomplete data. Changing this picture is the role of data governance. A methodical approach tied to the right objectives will quickly begin yielding powerful results.
