This blog recaps an ASUG Data Governance SIG webcast, led by Tina Rosario.
Setting the stage
The main objectives and outcomes of information governance are below. Maturity assessments should help provide deliverables and action plants to help you with that. Understand, Engage, and Identify are really the assessment phase, while Prioritize and Empower are the action plans going forward.
How do we do that? There is work to be done to set up the assessment approach, as well as the actual execution.
Depending on where you are in your journey, it should be 2 – 4 weeks for project setup and execution of the assessment itself. For a quick and easy assessment, you shouldn’t cover a significant volume of fields. Instead, focus on where the business has the largest set of priorities enabling key business processes. If you haven’t done defined that key set of fields already, make sure to include it here (this step may take the most time).
Once you get the right folks in the room and the right scope set, you just need to conduct the discussions with the data and process managers. As an outcome of that, you end up with the Maturity Execution column.
How do we define this vision at SAP? Creating end-to-end data management capabilities that deliver high data quality master data reliably, timely, and efficiently. This vision is supported by these key dimensions: Organization and Governance, Ongoing Data Maintenance, Process Re-engineering, and Tools/Systems. These capabilities span the lines of business and domains.
Targeting the maturity assessment
With hundreds of key fields across many domains, there needed to be some prioritization. SAP looked at within the key business priorities, which specific fields are required to support those key processes. In SAP’s case, we looked at Idea to Market and Demand to Cash.
Maturity Assessment baselined current capabilities for critical data fields for those two business processes.
SAP uses the Process Maturity Index (PMI), and wanted the information governance maturity assessment to synch up the scales and the questions in the assessments. Read the capability scale from 0 to 4, where 0 is no capability, and 4 is optimized excellence. Each of the scores gradually amps up toward continuous improvement.
Master Data Leads (Data Stewards) were to provide the critical fields, support the Business Owners in the LOBs, and then help interpret the results and actions up through each LOB. This couldn’t just be a one-time effort. Instead, the scores should be goals for improvement that the business sponsors and that the COO supports.
The actual assessment is in a Word document. Here are some sample questions:
Providing examples for each of the key capabilities and levels achieved was key in helping the business understand how to score themselves. Business then provides a score for each row, and the average of all of those scores becomes the baseline.
A new core capability is having a Center of Excellence for Mergers and Acquisitions, especially focusing on data migration. These data migration capabilities were added, as the framework should change over time to reflect changes in the business.
Results
SAP’s goal was to reach Level 2 by the end of the year. In order to help, the group defined what Level 2 would look like across the key dimensions (Organization and Governance, Data Maintenance and Cleansing, and CRUD Process Enablement).
With the target in place, SAP then defined which projects needed to be in place to reach Level 2. For example, perhaps most of the activities needed to be around data cleansing instead of CRUD processing. These results could vary according to domain.
Domains align nicely with the LOBs, which makes the results easier to digest, too. The results highlighted that we needed to work on accountability and further automation (specifically around on-going data quality maintenance without a lot of manual intervention). We used the slides to show COOs where we needed their project support, too.
Here’s an example of a mid-year checkpoint. We have to show that we are making progress with the projects in place.
Notice that specific KPIs and metrics were targeted for success, and TIED to business value. The results help highlight where executive support is going to be critical to get a project back on-track. Maturity assessment can’t be a one-time, early in the year activity. It has to be an ongoing objective for the Master Data Leaders. In SAP’s case, the assessment was also completed mid-year to highlight where additional support was necessary.
Today
Data Leads have gone back and assessed where SAP is with specific fields and the maturity assessment. The Data Leads also used this opportunity to check if additional fields should be included.
The program has worked very well, so now additional fields are being included. Will also be adding additional domains and processes (Procure to Pay). The lighter shade indicates the baseline score, and the darker score is current score. In some cases, the score didn’t move (Employee, for example).
The slide is a great report-out to executives, to show the impact of their support.
This will be an on-going process, including mid-year assessments and end-of-year assessment. However, the first step is to define an acceptable target. Should every domain be a Level 3? Or should the fields and processes be expanded?
Related blogs on SAP's Data Governance program:
Information Governance Maturity Models: Quick and Easy
Using the Program Management Office to help your initiative
Information Governance Tips + Tricks from a Practitioner
Walking the Walk: SAP and Information Governance
Information Steward 4.2 in Practice: How SAP's Data Management Organization Uses Information Steward
SAP’s Internal Information Governance Program: Business Value Metrics Framework
Thank you, Tina for this great webcast on quick ways to measure your organization’s data management maturity levels. Tina’s contact information is tina.rosario@sap.com.