A business intelligence department lives on it's credibility. Yet that same credibility can be undermined very quickly when the rest of the organisation is not engaged.
Business intelligence is often seen as a bit of a 'black box' by other parts of the organisation, which can lead to misunderstandings. These lead to credibility issues. Before long, you have a long list of unwarranted queries about your reports. Credibility takes time to win and can be lost very quickly.
Here are my 5 steps to building business intelligence credibility.
1. Definitions, definitions, definitions..
Write thorough, unambiguous, verbose business definitions with your customer and sign them off before developing. This ensures that the customer knows exactly what they are getting, the developers have a more focused set of requirements, and expectations are managed. Involving them in decision making and making the development process more visible are sure ways of building credibility. Establish a rule that all definitions are to be completed and signed off before development begins. Don't break that rule.
2. Visibility of lineage...
Publish your business definitions in a solution that integrates them with a metadata dictionary, so that there is complete visibility of the data lineage from user keystrokes to report. Make sure everyone knows about it. Visibility of data lineage informs people of the implications of their actions.
3. Profile your source data before you start building
Profile the data that you are reading in. Take the results to your customer and discuss any finer points about the measure. Make it known that your area is merely reading data that other areas are manufacturing (lineage). Communicate any problems you encounter with this data and engage your Data Quality department/team.
4. Automated data quality measures
Arrange for your BI processes to be regularly profiled and have a data quality scorecard running on the same schedule as the finished report.
5. Visibility of testing
Involve your customer in user-acceptance-testing activities. Even if it's just signing off the approach and the final report. This will give them visibility of the whole project life cycle.
When customers are aware of the definitions, development and data lineage, they understand that you are building the very best report you can. Giving them visibility of any data quality scorecard will highlight the steps you are going through to mitigate the risk that other areas pose to the accuracy of your report.
These are just some of the practical ways that good data governance and quality initiatives can improve the credibility of a business intelligence department.