Stuck in a Rut? Additional Analysis Can Possibly Break You Free
One of my major analysis challenges with average day-to-day work is avoiding the rut of routine. Establishing a routine and having a schedule is great for getting things done, but I find that, for someone in my role, it can stifle innovation.
How do I break out of that rut? Additional analysis.
We had just finished a project that had a report due each week. Each report covered a different market. Because of the frequency of the reports, they became routine. To ensure that we reported all of the important data points, the process allowed little flexibility. Although this served the client’s purposes well and was a useful tool for them to compare data across their markets, I felt as though I had underachieved. The reports looked essentially the same. They were routine.
One of my personal goals for 2016 is to avoid letting things like this happen in the future. I intend to set aside some time each week for “additional analysis review.” Each week I will pick one project that has a report coming due. I’ll spend one or two hours reviewing the data to determine if we are missing any relevant insights. This could happen either because we neglected to include a segment in our analysis, or because the insights require more advanced analysis (possibly an option not known by the reporting team).
My first look into a project was for a brand that was marketing a fairly new product. They were trying to discern where they stood in the marketplace. We ran some standard analysis to see whether the product was performing better with men or women, and for what ages the product was most successful. It was a health product, so we had some questions about how people eat and how that influenced their perceptions.
The comparisons gave consumer context with which the client could see the product from their perspective, but I believed that we could do better.
Typically, our clients provide their target demographic data, then we provide feedback based on that information. This was our opportunity to present the persona whom they ideally would be serving, defining their target demographic for them. We were able to pull the variables together and show the subset with which they were performing best. The client was pleased, and I felt that I had done a thorough job. It was a win-win situation.
The additional analysis was straightforward and productive. Targeting demographics is common in our work. Adding one was no big deal for me, and it was useful to our new client. The important takeaway is that, simply by slowing down and reviewing data a second or third time, I can improve the analysis. It is worth the effort.