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For decades, convenience store retailers have been collecting and analyzing point-of-sale data, pioneering the concept of “big data” well before it was a widely used term. Today, c-store operators are driven to reduce operational costs. This has led them to adapt their energy management systems in ways that focus on the generation of information concerning the operation of each store.
By analyzing reams of information including automated refrigeration temperatures, c-store managers are becoming more aware of the possibilities to use this data, lending to the growing trend of using big data in operations to drive efficiencies, measure return on investment and evaluate equipment performance. Below are insights and best practices for big data in operations, based on discussions with convenience store and other retail facility managers in 2013.
DATA, DATA EVERYWHERE
One key theme is that there is not a lack of data in retail operations — there is actually too much data. With more than enough data, the challenge becomes using data to create a more precise picture of the business and highlight factors that can drive action within the store.
Retailers admit that much of their time can be spent poring over data. But, once the value is extracted, data analytics allow them to improve energy efficiency, lower expenses to enhance ROI, reduce complexity and manage capacity. Often, the value of data collected can only be determined in the future — which is why many retailers choose to err on the side of collecting as many data points as possible. Energy efficiency is also a main focus for c-stores, and many retailers dedicate teams within their businesses to deal with the issue.
SHORT-TERM THINKING LIMITS OPPORTUNITIES
Big data in operations can expose scenarios where an initial investment can lead to savings, sometimes in ways that are counterintuitive. When analyzing data, c-store retailers have to realize that they often need to make tradeoffs to see the benefits. For example, retailers might want to cut costs when it comes to maintenance, but doing so can have an adverse affect on food quality, customer comfort or energy efficiency of their units. Conversely, if retailers are investing in maintenance, they can positively impact food safety as well as realize energy efficiency benefits. Several retailers have cited examples of using years of data analysis to make the case for investing in “pricey” equipment that ended up saving hundreds of thousands of dollars annually.
Managing and standardizing operations is an especially daunting task for retailers with more than 50 stores. Frozen and refrigerated products must be maintained at exact temperatures to ensure product safety and quality. For example, prior to utilizing the big data to automatically record case temperatures across all stores, store employees spent more than 70,000 hours each year performing manual temperature checks on refrigerated cases.
But now, the automated process is done by aggregating site data from on-site energy management systems into a secure, web-based interface. Today’s cloud-based systems also allow management to create standard enterprise schedules, broadcast setpoints and apply schedule changes to all stores simultaneously.
A robust solution enables true enterprise management through rigorous operational analysis.
Data can be easily organized and located via the robust search function. Temperature logs, equipment history and workflow status can be found and sorted in seconds, providing users with the ability to quickly analyze equipment and store efficiency. Visual analysis tools also enable retailers to use the abundance of data to graph enterprise energy data and identify underperforming stores. To ensure protection, make sure data is transferred via a private network that is separate from the point-of-sale connection, ensuring maximum data security and integrity.
PUTTING THE RIGHT PEOPLE IN THE RIGHT PLACE
One of the most surprising areas of the big data discussion lies with the issue of staffing. With all the data surrounding retail operations, there is a shift in the makeup of some retailers’ teams and knowledge of data is trumping backgrounds in facility maintenance. Many retailers, including c-stores, have started hiring people who are skilled in data analysis and interpreting unstructured, multi-dimensional data, which brought about a new discussion concerning how to collaborate with information technology teams.
Pressure is mounting on operations management professionals at leading c-store chains to wring costs from their systems while ensuring food safety and shopping comfort. Big data derived from operations is the solution to help retailers more effectively measure ever-increasing amounts of operational data and gain tangible insights to improve their facilities.
Editor's note: The opinions expressed in this column are the author's and do not necessarily reflect the views of Convenience Store News.