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How do you set data governance metrics that balance quality, availability, and usability?

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Data governance is the process of managing the quality, availability, and usability of data across an organization. It involves defining policies, roles, standards, and metrics to ensure data is consistent, accurate, secure, and accessible. But how do you measure the effectiveness of your data governance strategy? How do you set data governance metrics that balance quality, availability, and usability? In this article, we will explore some key aspects of data governance metrics and how to align them with your business goals and user needs.

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Merrill Albert

Enterprise Data Leader, Data Governance Officer, Data Thought Leader, Chief Data Officer, Fractional Governance, Data…
Lukas Negrin

AI Enablement: Crafting and Executing Data Strategies, Governance, and Management
Naresh Gudla, PMP?,SAFe?,CSM?,ITIL?,SRE

2x Top Community Voice on LinkedIn 2023, Release/Change Management, Operational & Delivery Management using lean &…

1 Why data governance metrics matter

Data governance metrics are essential for monitoring and improving your data governance performance. They help you track the progress of your data governance initiatives, identify gaps and issues, and communicate the value and impact of data governance to your stakeholders. Data governance metrics also enable you to benchmark your data maturity, compare your data performance with industry standards, and demonstrate compliance with regulations and best practices. Without data governance metrics, you risk wasting resources, losing trust, and missing opportunities.

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Lukas Negrin

AI Enablement: Crafting and Executing Data Strategies, Governance, and Management
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Focus on what really matters and try to establish meaningful KPIs. Too often, motivated individuals come up with an abundance of KPIs that mean nothing to their stakeholders. Try to keep yourself honest and help yourself reflect on the progress achieved. Measure engagement and business impact, not the number of policies issued.

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2 What data governance metrics to choose

Data governance metrics vary depending on the objectives, scope, and maturity of your organization. However, some common categories of data governance metrics include data quality, data availability, and data usability. Data quality metrics measure accuracy, completeness, timeliness, validity, consistency, and relevance of your data. Examples include error rates, completeness ratios, duplication rates, or data lineage. Data availability metrics measure accessibility, reliability, and security of your data. Examples include uptime, downtime, recovery time, or access requests. Data usability metrics measure usability, usefulness, and satisfaction of your data for your users. Examples include adoption rates, usage frequency, feedback scores, or business outcomes.

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Merrill Albert

Enterprise Data Leader, Data Governance Officer, Data Thought Leader, Chief Data Officer, Fractional Governance, Data Evangelist, LinkedIn Top Data Governance Voice, creator of #CrimesAgainstData
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There are lots of metrics that can be helpful, but to be comprehensive, you really need to think of everything you can measure. For instance, data quality metrics are data quality metrics, not data governance metrics. If you want data governance metrics as well, think about what makes sense to measure, which could be attendance, documentation completion, issue resolution, etc.

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Lukas Negrin

AI Enablement: Crafting and Executing Data Strategies, Governance, and Management
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Find a balance between long-term goals you are trying to achieve and short actions that help you correct your path. The long term could be maturity, which you will measure yearly or even less frequent. The short term could be the time it takes to approve a data sharing request.

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3 How to align data governance metrics with business goals and user needs

Data governance metrics should not be separated from business goals and user needs. Instead, they should be in harmony with your strategic vision, mission, and values. To ensure alignment, you should involve your stakeholders in defining and prioritizing your data governance metrics. Ask them about their pain points, expectations, and requirements for data quality, availability, and usability. Additionally, link your data governance metrics to your business goals and key performance indicators (KPIs) so that you can show how improving data quality, availability, and usability can help you reach desired outcomes and benefits. Lastly, make sure to balance your metrics across quality, availability, and usability to gain a comprehensive view of your data governance performance.

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Naresh Gudla, PMP?,SAFe?,CSM?,ITIL?,SRE

2x Top Community Voice on LinkedIn 2023, Release/Change Management, Operational & Delivery Management using lean & Agile, Service Delivery (ITIL, SRE), Technical Program/Project Manager,Data Governance, Data Management
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Understanding the business goals/pain points/expectations by doing surveys, user interviews and focus groups helps to align the goals of Data governance metrics. Involving and communicating/collaborating the findings leads to better defining the metrics around quality, availability etc. Getting buy-in is critical for the success of any framework and helps to have a better feedback loop for continuous improvement.

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4 How to collect and report data governance metrics

Data governance metrics are only useful if they are collected and reported effectively. To ensure this, you should automate your metrics with tools and processes that save time, reduce errors, and ensure accuracy. Additionally, you should use dashboards, charts, graphs, and tables to visualize and communicate your data governance metrics. This can help to highlight trends, patterns, and insights, while making your metrics easy to understand and act on. Finally, it is important to review your metrics regularly to check if they are still relevant, accurate, and actionable. Make adjustments as needed to reflect changes in your data governance strategy, goals, or environment.

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Lukas Negrin

AI Enablement: Crafting and Executing Data Strategies, Governance, and Management
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KISS – Keep it super simple. Before you start investing in fully automated dashboards, figure out how to collect the data and if what you are measuring actually tells you what you hoped. For your key stakeholders data story telling more important than dashboards. For stewards, engagement in the form of a community is the answer. Regular surveys help you reflect and communicate results.

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5 How to improve your data governance metrics

Data governance metrics are not only for measuring and reporting, but also for improving and learning. You should use them to identify and address data governance issues, gaps, and opportunities. To ensure continuous improvement, you should set targets and thresholds to motivate and guide your data governance efforts and actions. Additionally, you should monitor and track your data governance metrics over time to measure your progress and performance. With this information, you can learn from your data governance metrics to identify root causes, risks, and areas for improvement. Finally, take corrective and preventive actions to resolve data governance issues and enhance data governance performance.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How do you set data governance metrics that balance quality, availability, and usability?

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6

1 Why data governance metrics matter

2 What data governance metrics to choose

3 How to align data governance metrics with business goals and user needs

4 How to collect and report data governance metrics

5 How to improve your data governance metrics

6 Here’s what else to consider

Data Governance

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How do you set data governance metrics that balance quality, availability, and usability?

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5

6

1 Why data governance metrics matter

2 What data governance metrics to choose

3 How to align data governance metrics with business goals and user needs

4 How to collect and report data governance metrics

5 How to improve your data governance metrics

6 Here’s what else to consider

Data Governance

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