Interpreting Retail POS Data
By Jim Lewis, CEO Enhanced Retail Solutions LLC
At a retail conference in 2019 (remember those days?), I got to see a lot of statistics, market share information, industry trends and the latest generation of gizmos that will continue to transform the retail world. That macro level information is always insightful and gets you thinking. It’s great directional information for participants who are retail executives. But talk at my table was about what to do with massive amounts of data they are currently spending a fortune on collecting. What to do on a micro level. All the executives I talked to expressed concern over the cost of collecting and organizing data and the systems required to do it. Some have hired data scientists to help them make use of the data, but they aren’t getting any great benefit.
Finding out what the numbers mean seems to be alluding them. I believe there’s two reasons for this. One is that many data scientists are experts on handling the data rather than having the specific industry retail or wholesale expertise to interpret it. For example, they aren’t providing actionable data that fixes an item’s inventory problem. There’s a difference between nice to know info, and info that can be brought to the planning team and acted on. The second problem is how the interpretation of the data is communicated to different levels throughout an organization. A list of algorithms means nothing to someone who is just trying to balance their inventory or improve the assortment. They need to see it in simple, clear terms. Better yet, just the answer to their most commonly asked questions provided in a way that it can be implemented.
The most important step to putting data to use is defining the goals and most common pain points. This includes both customer-facing and back end planning. For example, if overbuying is a common issue, data can be put to work to help determine thresholds, quantities by store/web and smarter allocations. Models can be built based on history and current trends. The key is to mix the expertise with data handling skills.
We’ve long believed in the Discipline of Planning- our e-books and posters shout that from the rooftops. Implementing it has never been easier because more data is easily accessible now. The discipline is a strategy that ties reports and data to each step in the planning process like prioritizing SKUs that need attention, calculating lost sales or recommending a new allocation for high weeks on hand items. It breaks downs activities weekly, monthly, quarterly and fits in with seasonal pre, in-season and post planning cadences.
In terms of systems, there are many on the market, most requiring a fair amount of training. We market several good ones, but our latest tools focus on the best and worst of items and their inventory positions. Instead of having to log-in and learn a system, a link is emailed to the user with their respective data. These types of tools, including our RetailNarrative software, have already done the interpretation of data, providing the most succinct and actionable data. It works for brick & mortar, multi-channel and digitally native retailers.