The Accelerated Analytics team spent a majority of the day to day reviewing retail point of sale data provided by a manufacturer client of ours. These are large reports with thousands of rows of data organized by UPC, reporting units sold, units on hand, forecast units, etc. This particular client sells to a ‘big box’ retailer, so each UPC is duplicated for over 2,000 stores. Not an easy task to review and draw out meaningful and actionable intelligence. It was clear as we reviewed the data that we needed to create a few top line key performance indicators to summarize what was happening. The natural choices were sell-thru, weeks supply on hand, and in-stock percentage. By calculating these metrics and then eliminating all the columns of units sold and units on hand, we were able to more quickly identify which products were performing well and which were not. This caused us to write up for this client a short summary on how to define effective key performance indicators to manage their business.
Effective key performance indicators are:
Context driven. Reporting units sold by UPC does not by itself yeild much information. On the other hand, units sold compared to forecast provides very useful context to the user because you can immediately judge the relative performance.
Actionable. If a report tells you UPC 384730384738 sold 374 units, what action can you take based on that knowledge? Not much. However if the report tells you the sell-thru percentage is 9% you immediately know action is required.
Gather together your top 3 reports and review them to see if the data summarized provides KPI’s or just data. Then work on creating KPI’s that provide context and actionable information. You will be surprised by how much more effective your analysis can be.