Here’s an interesting question: How do you create a successful data governance strategy across a large organization?
The International Association for Information and Data Quality recently published a lengthy piece that explains how you can coordinate such a data governance and master data management strategy by using a very specific tool: an alignment workshop.
Kelle O’Neal founded the MDM and customer data integration consultancy First San Francisco Partners, but she’s also worked for Siperian, GoldenGate Software, Oracle and Siebel Systems.
“Alignment is a key first step in any change management initiative and is especially important to an organization that is trying to better govern and manage data,” writes O’Neal. “Many organizations struggle with launching and sustaining a data program because of a lack of initial alignment.”
Kelle suggests the “Alignment Workshop” as a proactive approach to the problem.
As you might imagine, it involves bringing everyone together – the lines of business, IT and various stakeholders. Kelle writes that the benefits to such a meeting are two-fold:
- You can educate everyone about data quality, MDM and data governance from the get-go.
- It supports buy-in and helps maintain long-term interest.
That part about “maintain long-term interests” should be your first clue that this is NOT a one-time event. In fact, she describes it as five components, each building upon the previous components.
In brief, the five components are:
1. Confirm the value of the data initiative to IT and the business/operational groups — separately. Everybody lists what they see as the benefits, and then you prioritize and map these values. She includes a “value-mapping matrix” to help you visualize this process, but the gist is that you’re pairing up what matters to IT with the business’ values.
So, for instance, an IT value might be to create a single data brokerage architecture, but that’s tied to the business values of focusing on value-added activities, creating consistency in reporting, adhering to regulations and more efficient support processes.
“This serves to identify, illustrate and confirm the overlap between what is important to the business and what is important to IT,” Kelle writes.
2. Identify the stakeholders’ goals. You might assume that the stakeholders’ goals would either align with IT or business/operations. That’s not necessarily true. Even if the end goals are the same, it doesn’t mean the stakeholder will share your priorities or have the same concerns about the project.
So, this is your chance to hear from the people who really will be handling the day in, day out management of any governance or MDM project. Part of this process is also clearly defining what the consequences are if the goals are not achieved.
Personally, I love this kind of if-then logic, because I think it makes it very clear why individual employees should support concepts that can often seem overly vague – like data governance.
3. Create linkages between the delivery of the solution and what’s important to individual stakeholders. Here, you’re really drilling down and assigning tasks to individuals, and explaining how those tasks relate to the broader goals. The top data program deliverables are identified for each stakeholder and mapped to their goals.
“Stakeholders can now clearly see and articulate how those deliverables can help them achieve their business goals ,” Kelle writes.
Again, she offers a sample chart if you’re having trouble visualizing what that means.
4. Determine success criteria and metrics. We all know the maxim about what gets measured gets done, but this brings it a step closer to home by setting targets for specific stakeholders so they can measure and monitor their own progress.
5. Establish a communication plan. She goes into some detail about this, but, basically, this translates into documenting what’s been said, as well as how progress should be reported and to whom.
As I said, it’s very detailed and lengthy, but it addresses a complex, difficult issue: aligning IT and business around a central data management plan.
