Black Belts could use predictive analytics to transform the convenience store industry

Convenience stores are located on most street corners the world over. These small enterprises offer customers a wide variety of items and often have gas pumps outside as well. Considering how long convenience stores have been around and the quantity of items they carry, you’d expect them to use some type of software to keep track of all of their inventory. However, that’s not always the case.

Many of these stores use point-of-sales systems to ensure correct pricing for products sold and to track sales taxes, and provide end-of-day and monthly accounting reports. Often these systems are integrated with various payment modes. Larger stores also use their systems to track inventory and manage their respective supply chains. Why smaller convenience stores don’t do the same, given the declining cost of technology and the the availability of inexpensive data capture tools, is surprising.

Recently, I witnessed multiple owners doing manual inventory audits at their respective stores. They were making counts of inventory at hand, trying to figure out units sold since their last order, and deciding what, when, and how much to order next. One owner told me that during one of these audits, performed with one of his suppliers, he realized that he’d failed to display promotional product at the right time, thus losing potential sales. Manual audits might be executed in developing nations, but not in the United States.

Understanding the changing market dynamics, product mix, customer preferences, and impact of promotions and seasonality, provides a tremendous opportunity for these mom-and-pop store owners and their distributors. Larger retailers already use optimization solutions to identify the proper mix of product, pricing, and placement. This often involves demand cluster analysis to identify naturally occurring patterns in transactions across thousands of retail outlets. These retailers monitor layout configurations to understand customer behavior and convert browsers into purchasers. They use techniques such as point-of-placement analysis along with specific promotions to identify key factors that influence a potential customer’s purchasing behavior.

The retail distribution channel demands accurate supply-and-demand matching, faster time to market, minimal stockouts, and low inventory obsolescence. Given the competitive nature of the market today, larger stores use analytic tools to better predict demand, proactively manage inventory risk, and recommend promotions for margin improvement.

With the wider use and understanding of statistical models, there’s a tremendous opportunity for smaller and midsize manufacturers and retailers to work together not only to improve their supply chain management but also their respective margins. For all within the supply chain, predictive analytics can reduce markdown losses, improve ROI on marketing expenditures, limit inventory risk through line-of-sight into usage—all leading to increased profitability.  Such analytics could transform the way convenience stores operate, increasing customer satisfaction while creating a culture of informed, data-driven decision making.

What an opportunity this presents for the thousands of Six Sigma Black Belts working throughout different industries. Most have been working in manufacturing and have recently been migrating into the healthcare, financial, and insurance sectors. They always seem surprised when I present them with such an opportunity. As they do in most business sectors, Black Belts could look at:

Although these employers might not always be able to offer Black Belts the types of projects that make appropriate use of their skills, there are still many opportunities for them to extend their reach across their respective supply, input, process, output, customer (SIPOC) chains. Using analytics not only will help convenience stores and their distributors increase their profit but also provide new opportunities for quality professionals.