Metric-Driven Information Governance
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How should you measure your information governance success?
So your enterprise has invested in a number of Information Governance roles, including a program manager and data stewards. More importantly, the Information Governance program also requires time commitments from senior leaders within IT and the business.
After having a couple of meetings, the next question will be: “So what have you done for me lately?” That is why it is important for the Information Governance program to agree on a set of business-driven metrics upfront in the process.
The light bulb went off for me when I attended the Information Governance meeting at one of our clients. This client had an Information Governance program that was a few years old but the perception was that they had very little to show for it.
The CIO walked into the room and said, “You have to develop an Information Governance scorecard to explain to all these business stakeholders how your program is making their jobs easier. Show them how you are making their information more trustworthy.”
The best practice around metrics is to develop a scorecard in conjunction with the business stakeholders. The scorecard should start out with not more than 10 metrics, though the number can grow over time. The Information Governance leader or the Lead Data Steward (if there is one) should be responsible for the overall scorecard and must report ongoing progress to the Information Governance Council.
Ideally, there should be a small set of metrics to measure the performance of each data steward.
For example, the customer data steward might be responsible for the percentage of null mailing addresses and null phone numbers. The vendor data steward might be responsible for the number of duplicate vendor names. And the materials data steward might be responsible for the percentage of null values within the material reorder level field.
The Information Governance metrics need to be specific to your industry and business functions that are stakeholders in your program. Let’s consider a few industry examples.
Credit Risk
The Credit Risk department in a bank needs to understand the overall risk exposure by industry. However, their analysis will be incorrect if the Standard Industry Classification (SIC) codes are null. Worse, the Credit Risk team might have to increase the level of loan loss provisions in situations where the SIC code is not available.
The Information Governance program can improve the level of trustworthiness of the data by measuring the percentage of customer records that have null SIC codes.
Health Insurance
Let’s take another example from the health insurance industry. The Medical Informatics team wants to ensure that 80% of patients with a chronic illness – such as diabetes or cancer – are within 5 miles of a patient-centered medical home (PCMH). Think of a PCMH as a group of providers (doctors) that provide comprehensive primary care.
Many health insurers find that their provider data is actually quite old. Providers move between practices, some are sanctioned and others become inactive over time. An appropriate Information Governance metric might be the percentage of provider ZIP codes that are inaccurate.
Obviously, it is not easy to determine the percentage of inaccurate ZIP codes, but it is something that needs to be done based on ongoing interactions with the provider network.
Hopefully, this post has given you enough context to start thinking about Information Governance metrics. Remember, if you cannot measure it then maybe you should not be doing it at all!
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