How to pitch data governance

Data Governance won’t sell itself.

For those of us who’s work focus directly on data it's clear that data is a critical and strategic asset for any organization, that getting the right information at the right time to the right people is essential to gain the necessary edge when facing incredibly competitive markets.

We also know that assuring the quality and availability of data to feed the business decision processes, often in real time - is a priority, but also a critical challenge - as failure to deliver can develop into a disaster for decision making and implementing business strategies.

And data governance plays a critical role in all of this, although having a data governance framework in place will not have an immediate impact on the business, it will improve trust, transparency, and reliability when meeting customer and stakeholder expectations.

Although clear for some, pitching data governance to the decision-makers is a challenging task.

They see the world in a different perspective, either because daily priorities and short-term deadlines dictate their priorities, or even if data is one the priorities, data governance competes with analytics, AI, or other more data initiatives with faster returns for attention, ending up being seen as a nice to have – hardly ever a priority – mostly because it’s unclear how data governance will support their own priorities.

The case for data governance must be built around business value, arguments around managing data assets or optimising the value of data produce excellent training sessions but hardly demonstrate how value can be generated.

Always keep in mind that data’s purpose is to create value, business value, so the focus on business priorities and key business objectives is critical.

1. Talk business, don’t talk technical, it’s essential to create an understanding on what value data governance can bring on board, decision makers don’t want to hear about our solutions, they want to hear about their problems, and they want to hear it in their own language. Data governance is not an IT function, it is a business function, it is the business who better knows what their problems and objectives are.

2. Start with business areas than can clearly identify and measure the business impact of bad data on their processes - In every organization the opportunities to identify these cases are abundant. Across all the business areas there are pain points related with the quality of data and identifying them is not a challenge. These problems or needs are anchored on very clear business impacts: on how data impacts business performance, how it impacts customer and experience loyalty, how it impacts offer and innovation, how it impacts operation efficiency, how it impacts processes, creating inefficiencies and increasing costs, or how it impacts risk and compliance.

3. Build your business case with those willing to defend it - Once you’ve identified a critical pain point and a business objective, you’ll have the business stakeholder that can passionately and effectively articulate the impacts of poor data in their processes and that will be eager to defend the project. These will be the business cases for data governance (for effectiveness purposes, there should not be more than five use cases, all with clear, achievable objectives and stakeholders that are aware of the importance and impact of data).

4. Design and propose small, targeted initiatives, where the impact and value of data can be clearly identified and that can bring results in short time, with metrics that can directly linked to business objectives.

5. Create success stories, that even at a small scale will create the awareness and act as a motor to leverage the replication of that story in other business units.

We are not bringing anything new, every organization that uses data, is somehow already doing data governance, often in an ad-hoc way, inefficiently and reactively, the value proposition is to do it efficiently, proactively and in a structured way.