Simply having Power BI isn’t enough. In fact, you may be asking yourself why your reporting is not all that it could be, even though you’ve adopted Power BI as your reporting tool. Below we offer three important, practical (but overlooked) steps to improve your reporting using Power BI (no matter if you are writing reports yourself or an executive trying to get more out of your data).
1. Recognize Who Needs a Report and Why
Different stakeholders need different reports. Moreover, they might need access to information at different time intervals and update frequencies. For the most part, executive leaders need aggregated dashboards updated on a weekly, monthly, and quarterly basis. Financial professionals, on the other hand, usually want to review operational data more frequently to track cash flow and see updated forecasting and budgeting data. The best practice is to start with a thorough understanding of who needs your report and why they need it. This drives everything else.
2. Understand What Your Stakeholders Want to Know
While it may sound simple, truly understanding what you or your stakeholders need to see (or rather know) from your data is half the battle. Most financial and operational executives tend to re-create the spreadsheets they have been using for years. Instead of focusing on old spreadsheets, start with a clean slate. What do you want to know? How do you want to see it? This process usually starts on a whiteboard (or electronic equivalent) so you can lay out the presentation layers the way they make sense to you. Don’t forget to think about how to slice and filter data…remember, you are not working with a spreadsheet anymore…don’t try to re-create it.
3. Organize (Model) Your Data
Having Power BI isn’t necessarily enough; to get timely, accurate reports, your data needs to be properly organized to provide you with the information you are looking for. The fancy way of saying this is to “Model” your data. This is especially true if you are pulling data from different systems. Different systems structure data in different ways. Simple things like naming conventions and units of measurement can easily trip you up when System A uses one convention and System B another. Once you understand what you need to know, figure out where the data resides (what system). Just remember that bringing data together means transforming it, so it does what you need it to do. It may need to be cleaned, normalized, and structured differently than in the source system. Again, how you transform your data depends on what you want to know and how your data needs to fit together to be useful. You can do all this in Power BI if you want to, but there may be better choices. It depends on how much data you are dealing with and how often your data changes.
Power BI is a fantastic tool and can deliver the answers that the business needs when it needs them. You just need to ensure you are helping Power BI do its job. In short, understanding the data itself is the most important thing you can do to get the most out of it.