What's the best way to show data governance metrics to different stakeholders?

Data governance starts with defining their purposes through: - readiness assessments and business alignment. - touch points and operational framework. - Goals, principles, and policies. - data management projects - change and issue management - reglutory compliance - standards and procedures sponsorship - business glossary - architecture reviews - data asset valuation It is the engine of all data management activities and initiatives.

One important thing to remember with data governance is that just doing this work because it's important is a bad strategy. What needs to be at the center of the strategy is solving a real business problem. Start there and get something done that helps add value to the people in your organization, and you'll gain credibility and be enabled to do more. One clarification on this - don't pick a real problem that isn't a priority for the organization. You may solve it, but if it wasn't one your key leaders care enough about then you are not showing the value of your work.

Data governance should be closely aligned with your organization's strategic objectives, whether its reducing cost, ensuring data is fit purpose, or reducing risk. Data governance managers should prioritize the establishment of data governance metrics that are reported to the board and group executive. This approach ensures that data governance receives the necessary visibility and attention across the entire organization

The primary goals of Data Governance are to: a) Improve the agility of data-driven business decisions. b) Seamlessly share knowledge across the organization. c) Eliminate uncertainty and instill trust in data. d) Drive value through collaboration in current workflows. e) Make security and privacy compliance effortless

Usually a whole governance group is involved in goal development. You are not alone. Ensure that the group contains diverse stakeholders from various functional units. Then work together to determine the common governance goals that cross all your needs.

You want to ensure you tell your stakeholders a story with meaningful business outcomes. What is the data telling us? How does this data story translate into a business ROI that the stakeholders care about? When you can answer these two questions you can deliver the needed information to peak interest and engagement.

The most effective data governance metrics illustrate the tangible benefits that data governance initiatives bring to the organization. These benefits could encompass improvements in data quality, trustworthiness, cost reduction, increased efficiency for data users, or reduced risk. It is imperative for data governance initiatives to deliver value and therefore have metrics that can demonstrate this to senior executives.

This is why I like to define layers of metrics: 1) executive KPIs: top level metrics that's give an overall status of an initiative. Something that can be quickly looked at by senior leadership and understood as red, yellow, or green with monitoring and alerting implemented. 2) operational metrics: more tactical and detailed metrics that are generally inputs to the executive layer. They don't just show you the what, but help explain the why and how to address issues (i.e. lead measures). These are for the stakeholder group responsible for moving the needle on an initiative. Monitoring, alerting, and forecasting is critical here as well. Metrics trees are very useful tools to map all KPIs out and then decide what goes on which dashboard.

Absolutely, tailoring data governance metrics to specific stakeholders' needs ensures that the metrics resonate with their interests and priorities. Executives may value ROI-focused metrics, data owners need quality and accuracy metrics, data users look for accessibility and usability indicators, while regulators require compliance and accountability metrics. This customized approach not only enhances the relevance of the metrics but also strengthens engagement and support from various stakeholders, ultimately contributing to the success of the data governance initiative. This is why I am strongly in favor of pushing data to the front front line and giving members all the ability to be expose to a product's datasets ( all within reason)

Always remember there is no such template that can serve all purposes and at the same time be equally effective. We have to tailor it based on the audience we are dealing with and have to see things from the lens of the consumers.

Present data governance metrics in the form of a narrative or story to engage your audience. This can involve using real-life examples, case studies, or anecdotes to highlight the impact and importance of data governance.

Data Culture matters. Creating excitement about #Data matters. Telling compelling #DataStories matter. I don't like data governance metrics. I don't even like the word governance being attached to data. I prefer data stewardship. I prefer stories about outcomes. Do I care if my Vendor data is at 87.4% quality and we have harmonized 57% of our top spend vendors, both 15% improved since last quarter? Meh. Am I excited if we increased our direct margins by 3% representing $400M in increased working capital due to renegotiating of enterprise vendor agreements that recognized purchasing power due to improvements in vendor data quality and harmonization? And ~$1.5B of additional savings to go if we can finish this? Heck ya! #LeadWithOutcomes

Yes, I prefer this way. Data is the company asset that need to manage clear and effective. Their statements should be reported and reviewed as financial statement as well.

The purpose of metrics delivery is to ensure understanding. Package ONLY what your audience needs to know. You may be monitoring 10,000 things. But your audience only needs to know four. Well, present those four, and provide additional detail if your stakeholders ask.

Not all metrics that are in data governance are necessary for every stakeholders. So choosing the appropriate content for the audience will be the primary step. Develop the story with the simple and elegant data visualization presentation would be required. If we could sequence the story with impact on trailing lines of business, would be interesting.

In a corporate setting, showcasing the impact of robust data governance became a priority. The team crafted comprehensive metrics—data quality, compliance adherence, and access controls. Regular, digestible reports were shared with stakeholders, illustrating tangible improvements. This transparency not only instilled confidence but also encouraged collaboration in upholding data standards. The story underlines the significance of presenting data governance metrics to all stakeholders, fostering a collective commitment to data excellence and integrity.