1- You are following manual processes
Do not tell me you are copying and pasting data!
You need to steer away from manual processes such as long weekly or monthly reports that need a lot of manipulation or manual data inputs. You need to make sure that you are doing the least amount of manual work possible. It might take some time, but make sure you automate all your data processes.
Manual processing lead to mistakes and inaccurate reports.
Different studies report that 88% of all spreadsheets have substantial errors. Furthermore, most errors reported were caused by human mistakes, which could have been entirely avoidable.
2- You are not using the right tools
Special work requires special tools. I will not go through all the tools that you might need in this post, but basically, the right tools should allow you to:
- Validate data.
- Manipulate data.
- Create meaningful reports.
- Do it fast!! (No one wants to wait for 6 weeks for an analysis).
3- You are not quantifying the results of BI
It is usually believed that the role of the BI team is to produce reports!! BIG MISTAKE. The role of the BI team is to impact the bottom line of the business with data (to make money), and there is no other way to do that than quantifying your results. If you are going to spend a lot of time analyzing data, make sure you are adding value to the company.
4- You have broken connections
Another common thing within the BI teams is to find siloed or disconnected data. That happens often because you receive datasets from different sources, legacy systems, etc. You need to make sure that all the dots are connected.
Whether you need new ETL jobs or data integrations, that is up to you, but make sure that you can switch from one data source to the other smoothly and without compromising your analysis.
5- You Don’t Have a Goal
This is probably the biggest mistake made by BI teams but unfortunately, it is the one that is most frequently made across companies. BI teams usually get lost in trivial analysis and vanity metrics. 80% of the reports and analysis produced by BI teams never get actioned (this is my own benchmark based on years of producing reports and analysis).
Now, ask yourself why. Whenever are you requested to produce an analysis or a report just ask this simple question: What do you want to do with this data?
I created the GIDAR Analytics Framework (Goals, Information, Data, Analysis, Action, Result) precisely to ensure that every analysis produces a change.
Bonus: You are concealing data
Another common one that most of us have experienced. Example:
Your company just run a campaign and the Marketing team ask you for a report. You crunch the numbers, and you see that you have incremental revenue of 5000$ vs 1000$ in the previous period. However, they want the numbers to shine, and they propose to report on percentages rather than actual numbers. Using the numbers above will give you a 400% growth, which may look like a significant increment. But for large companies, in many cases, an increase of four thousand dollars will not impact the bottom line. Hence, misleading.
Give perspective and reality to your reports.
