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Does your organization have a Data Governance benefits realization model that helps you answer the value question? Whoever speaks to me within the organization or in the industry, often would want me to help them understand, “How data governance brings value to them?” Sometimes, they assume that “building value from data” is similar to “getting the right data fit for purpose”. Though, the latter can be quoted as a necessity to build value from data. Leaders in the industry could with ease state the value of data governance. You might ask me this question – What is the difference in the way I view these benefits after reading this article? There is quite a change needed in your perspective of viewing value from data governance.

I like this common description of benefit – “An outcome of change which is seen positive by a stakeholder”. Realizing the value from an outcome is in fact making it objective and converting it into actuality. Let’s move forward from having to describe an outcome as value and realizing the tangible value associated with an outcome. Often, coming up with outcomes like “Making data fit for purpose” or intangible value like “increased awareness” is not the ask by mature data governance divisions.

Let’s look at an analogy; Think of a cook who prepares your meals as providing you a service. The value from this service is not just to satisfy your hunger but also to provide you with high nutrition, on time, while also keeping you away from the risk of food poisoning. Value according to me is realizable only when it is monitored and measured. In the above analogy, you can convert nutrition to daily required limit in mg; “poison free” is nothing but mitigating risk which can be measured by number of incidents; apart from missed instances of timeliness in serving your food to get your enzymes right.

The lack of focus is common in data governance divisions across industries and is constantly effecting how people think of data governance activities. There are immediate and cumulative benefits from governance dimensions either metadata management or data quality. But, you need “The framework” to realize the benefits from these services.

Some data governance divisions kick-start their initiatives with valuable business cases that rightly overcome organization challenges, these business cases should clearly articulate tangible benefits of using the services. In other organizations, benefits would be monitored and measured on a continuous basis in accordance with an assessment plan. Most organizations are not orchestrating governance activities as initiatives but rather as continuous push/pull based services. It is strongly recommended that one have a performance assessment plan before starting a data governance service be it data quality or metadata management. This plan should bring out the approach to monitor and measure the value of orchestration over specific timelines.

Think of every data governance service/activity in your organization as governance enabler. An enabler, in simple sense, is a new or an improved capability made available by your governance division. These enablers can be further classified into Business, Process and Technology enablers. For example, “Policy making” is a business enabler, “Metadata service management” is a process enabler while “Data profiling” is a technology enabler.

A common roadblock that a CDO faces is having these divisions to own the metrics that monitor the value of governance activities. While there are common enterprise benefits like reduced operational costs and risk, there are benefits that weigh in directly with the value chains of the divisions like client service effectiveness. My initial recommendations are outlined below –

• Every Governance enabler should have a metric associated for measurement like person hours spent on Metadata management or number of business terms included in the glossary.
• The data stewards then, within each division, should get to understand the divisional business and data value chains.
• The stewards along with divisions discover the success factors and metrics used to measure the commercial success of the division like time to service, customer service effectiveness, cross sell ratio and many more.
• Then, establish a trace between governance enablers and the divisional value chains.
• Get the divisions to agree on these metrics and have them own the metrics.

This is what creates dialogue and awareness in the divisions where you would want to have governance to seep in. The framework as I said earlier should clearly outlay the traceability between governance enablers – Technology and process impact – Business impact and value.

For example, metadata capture and data mapping are governance enablers – which lead to reduction in person hours spent on data analysis – which further reduces the requirements turnaround time – finally, puts you in a competitive position in the market with product or service time to market.

Quoting a second example; what does a 10% increase in the accuracy of the leads dataset mean to your marketing division and organization? It directly impacts the ROI. The division efficiently utilizes the budget allocated to the campaign and also embraces high conversion rate which leads to revenue increase.

And a third example as well; what does de-duplication of the customer primary accounts mean to the organization? Less time is spent by the service executive on call with customer to get to the right customer account by not having to struggle with duplicate accounts. This directly impacts your customer satisfaction score, cross sell ratio while also reducing operating costs with maintaining duplicate accounts and time spent in getting the right account.