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Last updated on 2024年4月29日

What do you do if your stakeholders are not understanding data quality metrics and measurements?

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Data quality metrics and measurements are essential for ensuring the accuracy, completeness, consistency, timeliness, and validity of your data. However, not all stakeholders may be familiar with or appreciate the value of these indicators. How can you communicate effectively with them and demonstrate the impact of data quality on your projects and goals? Here are some tips to help you bridge the gap and gain their support.

本文章的要点总结

Understand stakeholder priorities:

Tailor data quality metrics to align with their specific needs and objectives. This approach ensures they see the direct impact on their goals, fostering appreciation and support.### *Simplify technical language:Use clear, relatable analogies and visuals to explain complex metrics. This helps stakeholders grasp the importance of data quality without feeling overwhelmed by jargon.

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Yawa Christine AGBOTSE GBONFOUN

Statisticienne économiste, chargée…

1 Understand their needs

Before you present your data quality metrics and measurements, you need to understand what your stakeholders care about and what their expectations are. What are their pain points, challenges, objectives, and priorities? How do they use data in their decision-making and operations? What are the benefits and risks of data quality for them? By aligning your metrics and measurements with their needs, you can show them how data quality matters to them and their outcomes.

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Yawa Christine AGBOTSE GBONFOUN

Statisticienne économiste, chargée Suivi et Evaluation à la GIZ et experte data
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De mon expérience, je souligne l'importance d'organiser des séances de brainstorming avec les parties prenantes afin de parvenir à une compréhension commune des effets et résultats attendus du projet. Une fois que ces produits et effets sont bien compris, il devient plus aisé d'identifier les indicateurs pertinents et d'expliquer à travers un schéma comment ils peuvent être mesurés. La dernière étape est d'effectuer un exercice avec les parties prenantes où on leur demande à quelle niveau elles interviennent dans la mesure de l'indicateurs.

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Karima Makrof, MBA

Ask me about Running, Data, Governance - I am passionate about them all! Welcoming discussions about new opportunities too ?? #opentowork
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To get your stakeholders to understand the data quality metrics, have them defining and owning them. All good to highlight the process to get there (painpoints, challenges, etc), but once again, those metrics should be THEIR metrics. By having them owning it, it is difficult to get afterwards "I do not understand this dashboard and metrics or whatever is shown here, therefore I am not doing anything about the red figures (or alike)" (true strory...).

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2 Simplify your language

Data quality metrics and measurements can be complex and technical, especially if you use acronyms, jargon, formulas, or standards. To avoid confusion and frustration, you need to simplify your language and explain your terms in a clear and concise way. Use analogies, examples, stories, or visuals to illustrate your points and make them more relatable. Avoid overwhelming your stakeholders with too many details or numbers, and focus on the key messages and insights.

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Yawa Christine AGBOTSE GBONFOUN

Statisticienne économiste, chargée Suivi et Evaluation à la GIZ et experte data
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Non seulement cela mais la visualisation qui suit la langue. Parfois, un visuel explique mieux qu'un texte. Il est donc important de se mettre à la place de la personne qui re?oit et de se poser la question si la communication optée est efficace.

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3 Highlight the value

Data quality metrics and measurements are not just numbers, they are indicators of the value and quality of your data. To communicate effectively with your stakeholders, you need to highlight the value of your metrics and measurements, not just the data itself. How do they help you identify and solve data quality issues? How do they improve your data governance, security, and compliance? How do they enable you to leverage your data for analytics, insights, and innovation? By showing the value of your metrics and measurements, you can demonstrate your credibility and expertise, and build trust and confidence with your stakeholders.

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4 Provide feedback and recommendations

Data quality metrics and measurements are not static, they are dynamic and evolving. To communicate effectively with your stakeholders, you need to provide feedback and recommendations based on your metrics and measurements, not just report them. How do your metrics and measurements compare to your benchmarks, goals, or industry standards? What are the strengths and weaknesses of your data quality? What are the opportunities and threats for your data quality? What are the actions and improvements you suggest or implement to enhance your data quality? By providing feedback and recommendations, you can show your stakeholders that you are proactive and responsive, and that you value their input and collaboration.

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Karima Makrof, MBA

Ask me about Running, Data, Governance - I am passionate about them all! Welcoming discussions about new opportunities too ?? #opentowork
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Nothing more boring and annoying than a dashboard with plenty of metrics, KPIs, and other measurements, without any narrative to it. I understand this is not always possible to provide (as everyone seems to want having all "at their fingertips"). But having a narrative is often what will get the attention to the stakeholders (even when they own and define the metrics). Spend time explaining, and when possible, suggesting action. Note that this might be done by different people, but still. Make the data talk...

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5 Follow up and measure progress

Data quality metrics and measurements are not one-time, they are ongoing and continuous. To communicate effectively with your stakeholders, you need to follow up and measure progress based on your metrics and measurements, not just share them. How do you track and monitor your data quality over time? How do you report and communicate your results and achievements? How do you evaluate and adjust your metrics and measurements as your data changes and grows? By following up and measuring progress, you can show your stakeholders that you are committed and accountable, and that you deliver on your promises and expectations.

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Karima Makrof, MBA

Ask me about Running, Data, Governance - I am passionate about them all! Welcoming discussions about new opportunities too ?? #opentowork
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Based on experience, having seen a data quality dashboard showing figures that no one really understood, and where no one felt very enthusiastic about it. Having red or green figure does not mean a thing really, when it is not clear what (for example) the threshold for colouring is. Having a total lack of interest for this dashboard is a real pain (and pity). It does cost a lot to maintain, update. So back to basic: who needs to see what and for which purpose. Get the stakeholders engaged. And if it means having only 3 out of 10 of the top management committed, it is better than none interested. Get the dashboard useful for those stakeholders, and the other ones will follow. (And if they don't, that is a pity for them... Will miss a lot!)

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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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Stefan Vermeulen

I have 25+ years experience in Marketing-, Product-, Project- and Change management. I deliver results by taking action, using new technologies, implementing improved processes and leveraging team power.
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Educate. We should not forget that we are transforming to a data rich business environment, but that many people either grew up in a "data poor, belly decision making first" era. Also, other colleagues simply might not have a (professional) background on data. So, when stakeholders are not understanding data quality metrics and measurements: start from the bottom and educate them bit by bit.

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What do you do if your stakeholders are not understanding data quality metrics and measurements?

1

2

3

4

5

6

1 Understand their needs

2 Simplify your language

3 Highlight the value

4 Provide feedback and recommendations

5 Follow up and measure progress

6 Here’s what else to consider

Data Management

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What do you do if your stakeholders are not understanding data quality metrics and measurements?

1

2

3

4

5

6

1 Understand their needs

2 Simplify your language

3 Highlight the value

4 Provide feedback and recommendations

5 Follow up and measure progress

6 Here’s what else to consider

Data Management

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