Five low-budget ways to boost your data quality culture


We need data tailored to our needs to support our services, policies and decisions. The same dataset can be used in different ways in the public, private and third sectors. The assessment of the quality of this data will vary depending on how it is used.

It is not easy to know the quality of the data or to ensure that the data is fit for purpose. There is no shortcut to having good quality data and making improvements can take time. But making those changes is easier when people have the right attitude and approach to data quality. As a senior manager, you can have a huge impact on the culture of quality within your organization and lead to positive change.

Here are some simple steps you can take to put your organization on the path to better data quality.

1. Be curious about the quality

If you receive a report or other information – perhaps to make a decision – ask about the quality of the data entered in it. Sometimes we have to use data that has quality issues because it is always the best source we have, but if we know about these issues we can take them into account.

Unknown quality is a greater risk than known poor quality. If the data quality is poor, but known, we can communicate and be transparent about its limitations. By considering the uses of the data, we can adjust our approach accordingly, while also being aware of the consequences when making decisions based on the data.

2. Find out who is responsible for quality

Everyone involved in data has a responsibility to maintain quality, but there should be people specifically responsible or responsible for quality. Different organizations do things differently, but someone should always be responsible for evaluating and managing the quality of the data.

If your organization has not defined who should be responsible for quality, there is a risk that no one is managing quality well. You should be able to find an appointed person responsible for the quality of your data. If you aren’t successful, it may just be a matter of coordinating responsibilities between teams, which can reduce duplication and fill in process gaps. Identifying this person and talking to them about their role helps promote good data quality management at a higher level.

While one or more people may be responsible for the overall data quality, it is important to understand that each has a role in maintaining and improving data quality. As a senior manager, you need to engage with them to understand the challenges they face and the impact that could have on your business goals.

3. Understand how the data gets to you

Where does your data come from? How did he get into your organization? What has been done to verify that it is suitable for the intended use? Understanding how data flows throughout its lifecycle is one of the most powerful steps in understanding the quality of that data.

Every time data is changed or moved, there is a chance that the quality will change. It could be improved, or it could get worse. By understanding the flow of data, you can help others recognize how important the quality of this data is to all who use it.

4. Challenge the quality

If you come across data that may not be suitable for your purpose, speak to the data owner. They may not be aware that the problem exists, or they may need more evidence to make changes to their data. Often, data owners are unaware of how their data is being used across different teams and organizations. Therefore, making these links can have benefits beyond quality improvements. Creators, managers and users of data must work closely together for data to reach its full potential.

By asking yourself questions about data quality, you can help others understand that it is important and that there is no need to hide quality issues. This is a crucial step in building a good culture of data quality.

5. Defend data quality in your organization

Everyone manages data in one form or another. This may include recording time, budget information and expenses; or it can be high level operational data that supports frontline services. Whatever the data, it must be fit for purpose if we are to use it in our work.

Lead by example by starting a conversation about the quality of your data. Check the quality of the data you are processing and tell others why it is important. As a senior manager, you need to be able to understand, challenge, and promote data quality within your organization, and encourage others to do the same. The Government Data Quality Hub has released the Government Data Quality Framework, which can help promote a common understanding of data quality.

These steps are just the start, but they help promote the importance of data quality in your organization. We can all lead by example by requesting and maintaining good quality data.

The Government Data Quality Hub (DQHub) develops tools, advice and training to help you with your data quality initiatives. Please visit our website for articles, tools and case studies.

We also provide personalized government-wide advice and support. Contact us by sending an email to [email protected]


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