Building a business case for your governance program

Most data and IT leaders know that their organizations need data governance to stay afloat in the current market landscape. However, some struggle to communicate the value when it is not tied to a defensive need. In order to implement data governance, your organization needs to see that there is value in embarking on the journey. It’s up to data and IT leaders to build business cases, both defensive and offensive, to demonstrate how data governance is critical for transforming your organization into a Data Intelligent enterprise.

How to build a data governance business case

Building a business case may sound like a big effort. But, in reality, it can be quick and result in significant long term benefits for the data governance program. The data governance business case establishes the direction and priorities, as well as the benefits for the program. It should establish the high-level understanding and communications for the business benefits the governance program will seek to achieve (use cases), who will be involved (resource types), where governance disciplines will be applied (processes in the use cases), and the economic value for applying governance to achieve those outcomes.

1. Build your team

The first step is to put together a cross-functional team.

An effective team should be a mixture of executive, managers, and data analysts from across the organization. This will provide resources with the experience and understanding to create the business use cases. Ensure that you have experienced resources from finance as well. They will be invaluable in building the details for the financial cost and value template.

The team will help you solicit recommendations for:

  • The business use cases, priorities, and outcomes for data governance
  • The recommendations of processes and resources for each use case
  • Agreement to the risks, costs, and values
  • Organization communications and initial education for data governance

2. Clarify the business imperatives and use cases

This is perhaps the most important part of the process. Data governance programs gain the most traction when they are tied to specific business imperatives. These are typically high level goals that are priorities for the whole organization. Some examples are

  • Transform into a SaaS company
  • Become the #1 offering in your industry
  • Take your company public

Next you’ll have to determine the use case that data governance will help your organization address. Use cases should roll up to your business imperatives. There are three major categories of use cases:

  1. Grow the business (revenue focused)
  2. Run the business (cost focused)
  3. Protect the business (risk focused)

Common use cases:

Grow the business
(revenue focused)
Run the business
(cost focused)
Protect the business
(risk focused)
  • Identify new customers and market opportunities
  • Innovate product and service offerings
  • Increase customer lifetime value
  • Accelerate time to market
  • Optimize promotions and marketing campaigns
  • Reduce IT operations and maintenance costs
  • Eliminate duplicate data spend
  • Optimize supply chain operations
  • Optimize sales and marketing efficiency
  • Improve production inventory efficiency
  • Avoid regulatory fines and penalties
  • Streamline auditing and reporting
  • Protect against data breaches and other data incidents
  • Increase customer and investor trust

3. Identify your challenges

Once you understand your goals, consider what is stopping you from achieving those goals. Is it due to the people? Structure? Processes? Technology? Data? 

Often data challenges revolve around:

  • Difficulty finding data
  • Difficulty trusting data
  • Difficulty understanding data
  • Inconsistent and unclear KPIs, metrics, and definitions
  • Manual processes for remediating issues
  • Lack of visibility into how data is used and why
  • Slow response time to regulators

4. Determine the required capabilities

The last step for building the business case for data governance is identifying the required capabilities. These capabilities should all directly address the challenges that your organization is facing.

If your organization is going down the route of evaluating technology, best in class data governance platforms usually have features that align to the following capabilities

  • Embedded data governance and privacy by design to drive trust and compliance
  • Automated data curation and enrichment to build the active metadata graph
  • Seamless collaboration and consumption for smart decision making
  • Wide-ranging connectivity to streamline analytics 
  • Architected for secure, enterprise-wide adoption 

3 Building blocks of a governance use case

For each use case, the team needs to build a financial template containing the 3 building blocks of:

  • Business risk (for doing and not doing data governance)
    • Identify and prioritize the business risks (hint: often risk has the greatest weight)
    • Measured in aggregate as high, medium, low
  • Business value (benefits for data governance)
    • Identify the business value, tangible and intangible
    • This is often the most difficult for us to quantify, thus we have to identify assumptions that we have made to identify the benefits
  • Costs (current and future operational and capital costs for data governance)
    • We understand this component the best
    • Measure current state costs against future state costs
    • Financial templates that present value versus cost are the desired outcome

Deliverables of the business case

Your data governance business case may have three core deliverables:

  1. A document describing each business case, the business benefits for each, the processes and organizations impacted in each case, as well as the assumptions used to determine the benefits of each use case
  2. A financial template used to derive the benefits for risk, value, and cost of each use case
  3. A presentation for communications and education of the business case

Defining success

When building a data governance program, it’s important to track progress and measure success. The best way to demonstrate data governance effectiveness is to align the measurements to business value. Some areas to record are:

  • Productivity
  • Revenue
  • Cost
  • Data quality
  • Data protection
  • Availability to data documentation
  • Data standardization
  • Data understanding
  • Acceptance and adoption of the program

The list of KPIs for data governance is extensive, but measuring too many components can do more harm than good. Choose a few KPIs that are the most relevant to your business case.

Conclusion

Data governance is crucial to all data-driven organizations. It ensures trust and understanding in an organization’s data so that business analysts can confidently use this data to make informed business decisions. Although data governance is clearly an important component of a successful enterprise, many Chief Data Officers struggle to get by-in from executives, and therefore, never fulfill their data initiatives. With a solid data governance business case, however, Chief Data Officers are able to show the value of implementing data governance within their organization. With help from IT, organizations are able to build a solid data governance business case that demonstrates how data governance can help your organization achieve their key business objectives. 

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