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JERSEY CITY, N.J. — Convenience store retailers can use a wide variety of data to optimize their business practices and improve sales, but only if they know how. A good place to start is by understanding point-of-sale (POS) data, according to a June 21 webcast titled "Harness Your Data: Drive Profits to Your Bottom Line," presented by Convenience Store News.
Advanced Digital Data Systems (ADD) sponsored the webcast, which was moderated by CSNews Editorial Director Don Longo. ADD's Chris Kiernan, director of retail applications, and Rich Hathaway, director of business intelligence, served as panelists.
Although people hear about data all the time and many systems exist to collect it, data is not the same as information, according to Hathaway. Excessive time is spent gathering data and inputting it into vast, complicated spreadsheets, but this alone does not help people.
"Data loves to pretend that it's information and many people are fooled," Hathaway said. "Computers need data and humans need information."
Data serves as a building block to information, which provides meaning and context. From there, people can obtain knowledge and wisdom. Hathaway used the example of a simple tomato. Data is observing that a tomato is a small, round, red object. By moving up the pyramid and gathering information such as its nutritional content and how it tastes, people identify patterns and understand how a tomato can best be used in recipes.
This is essentially business intelligence: a set of processes and technologies that transform data into actionable information available to people at all levels of an organization.
Benefits of cultivating business intelligence include improved decision making; aligning the organization toward key objectives; identifying new business opportunities; identifying and improving inefficient business processes; data control; removing information gatekeepers; and enabling a culture of performance.
To achieve this, c-stores can harness their data by applying activity analysis such as customer accounting and traffic. By examining this concrete data, store operators can identify peak times for certain parts of the store and adjust tactics accordingly. For example, during the busiest parts of the morning daypart, appropriate staffing will allow employees to serve customers, brew fresh coffee and keep the coffee area clean. Staffing can then be reduced during slower periods.
Activity analysis can also be applied to aspects of the business that are less obvious, such as ranking sales data. By identifying the in-stock items that are not selling well and the out-of-stock items that need to be replenished, retailers can fine-tune their ordering process, the panelists explained.
ADD's system uses sales and inventory data to estimate the level of demand, the expected purchases and how much product should be ordered; it also helps identify which items work best for a particular demographic or at a particular time, and which ones might cannibalize sales of other products, according to Kiernan.
Retailers can also use data to identify trends and make week-to-week or year-over-year comparisons of margins. The system can identify cashiers' weak areas and potential violations, too.
"When you can see the performance all lined up against multiple days, suddenly you see patterns, and see who you need to coach and who you need to help pack their bags," said a representative of one Midwest c-store chain that worked with ADD.