1. Assign Report Owners.
Partner with the person who understands the report’s purpose, data and calculations and implement controls to improve data quality.
2. Ask users what question they want answered, not what data they want.
Help ensure people have the right data for the right purpose while quality improves.
3. Use business translators.
Use business translators to expediate communication and literacy between the business and technical / data teams.
4. Prioritise fixing issues.
Build trust with users by fixing their quality issues as they arise.
5. Expose the data.
There may be reluctance by decision makers to open up their data for scrutiny, but the only way to make the data better is to see it, compare it and fix it – not hide it Compare the conflicting data sets in use. Highlight the different decisions and results it could lead to.
6. Empower and reward data producers.
Fully train frontline data producers and reward good practices. Communicate the impact of their work has on downstream processes.
7. Partner with HR to raise awareness of responsibilities to data.
Ensure all job descriptions reflect data-related duties required to fully enable digital transformation across the company.