Thinking back to those times when someone had a significant impact on my life, it almost always started with some sort of relationship first. Maybe it was a deep relationship where after many conversations a friend earned the right to speak directly about personal things. Or maybe it was an opportunity where someone invested in a temporal way, and I could see their kindness and trust their advice. I often think BI works the same way.
If you are working with someone new to analytics, it is good if you can relate to them with their business-speak and understanding of the data first. Use their terminology and try to communicate analytical concepts in ways they can clearly understand. Avoid the techno-jargon that you think makes you look cool. It doesn’t and will not support the business the best in the long run. Use your visual tools to describe the data in a way that you earn the right to speak further about their data. You may feel that this is extra work, and it is. But it will help establish a level of trust and build a data relationship that will allow you to innovate with them and their data.
Sometimes you will work with someone in the organization who knows a little business intelligence. Maybe they had some analytics training while working on their business administration degree. They may even prefer to do analytics themselves, which is great. Be careful in how you offer improvements or corrections to their analytical approach. Because we are BI professionals and are immersed in it constantly staying current on the latest approaches, we will often know better and/or more accurate ways of finding insights. I have found one way to help offer advice is to build visuals using both their approach and my approach. We then sit down and look at the resulting insights together to see how one may be more accurate than another. You can use the data itself to reveal insights to show the differences and provide a great constructive learning experience.
To go a little deeper into this. I was working on a project where a business unit was predicting sales data and deriving multiple layers of calculations and insights from that prediction. They felt the prediction was a small piece of the puzzle and used a more manual approach. It was not very accurate. Instead of debating the method used, it was more effective to offer an alternate prediction and show the impact it had on the many resulting insights – which was significant. The business unit was able to see how important the prediction itself was and we were able to demonstrate a more accurate method of prediction by testing the results on historical data and showing our findings using visuals.
When doing business intelligence, relate first, then innovate. Relate to the business through understanding their perspective and then offer suggestions. Relate to the data through descriptive visuals and then pursue diagnostic analysis. And if a business user has taken the brave step of doing their own diagnostic analysis, commend their effort and provide a parallel evaluation to help deepen their understanding. Relationship is the key to collaborative innovation.
