Making data personal
Are you a people person or a numbers guy? This question has been around for a long time and it has been used as a way to classify people into a stereotypical perspective that for the most part, makes it easy to know HOW to relate to that person.
What if you're both? What if you're that person that can play in both sandboxes so that you can speak the numbers language, but also make it relatable and inspiring and easy and fun and...well, you get the picture.
Making data personal is not that difficult. It's all about finding relationships within the numbers and understanding why someone should care about those relationships. For instance, let's take two numbers like a monthly budget and the actual expense. The easiest way to understand this relationship is typically the variance between the two, usually shown as a percentage. Not really that difficult, but why does someone care about the variance? Well, if the variance is up or down over time by a certain percent the person responsible will likely need to explain why to their boss. And by having to explain it to their boss the person is probably wondering how their boss will react to it. This is where it gets interesting.
The numbers guy would simply look at the variance and say, "it is what it is". The people person would look at this and say something like, "we had to hire more people to service our customers and it's the numbers guy fault for not seeing this in their crystal ball". The person that can do both would say that yes we had to hire more people and while it was not factored into the budget, the impact to our business (NPS, CSAT, Service Level) is improved causing x amount of additional revenue that will offset the variance which is the right thing for the company and also for our customer. This is WHY we should CARE about this relationship and it makes it relatable to others.
Making data personal is about understanding the perspectives of those that use it. The value-add proposition is to show others these different perspectives so that it makes it easy for them to care. But how do you do it? Well, first you must be willing to ask questions that sometimes can be tough.
- Ask clarifying questions that peel back the layers of the issue
- Ask questions that probe assumptions, reasons, and evidence
- Ask questions that probe implications and consequence
- Ask questions about questions
Getting the answers to these questions will make it easy to understand a perspective, which in turn makes it easier to know why that person cares. Knowing why someone cares about the data makes it easy to talk about the relationships of the numbers, ultimately leading to insight. And that insight is really what it's all about. To take action, make decisions or simply be able to explain it to others in a way that they can understand.
Make your data personal. Make it relatable. Make it be inspiring!