With the vast amount of data now available to organizations, data science offers significant opportunities to complement a company’s continuous improvement efforts.
Unfortunately, to quote business strategy and technology expert Geoffrey Moore, “Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway.”
A 2017 American Society for Quality case study by Sivaram Pandravada and Thimmiah Gurunatha illustrates how data analysis helped a grocery chain reduce inefficiencies in its retail inventory and ordering process.
The short shelf lives of fresh foods along with ever-changing consumer demand meant that the retail chain’s stores often had to hold clearance sales with zero or negative margins or write off inventory. Annually, the problem of shrinkage accounted for revenue losses of up to 20 percent.
Although the ordering process was automated, it was better suited for longer shelf-life items. As a result, managers would often override the system and order manually. There were no defined limits in place. The organization needed an approach for monitoring and controlling this waste.
Explorative data analysis and basic statistics helped the chain identify and reduce inefficiencies in its inventory and ordering process, minimizing the gap between quantities sold and quantities ordered.
For example, to reduce excess ordering, the warehouse used color coding to monitor and track inventory. The colors of tags on the shelves helped ensure that department managers would see indications of stock levels during daily physical inspections. Red tags indicated Stock Keeping Units (SKUs) with high shrinkage. Blue tags signaled SKUs with high stock levels.
Rainbow statistical process control (SPC) charts, a variation on traditional SPC, helped ensure ongoing monitoring of the stock-to-sales ratio and escalated corrective action in real time, bringing sustainable results within three months.
Once the chain saw the difference that the data-based approach made in targeting waste and inefficiency in one store, it successfully replicated its process improvements to increase profitability throughout the organization.
If you haven’t seen it, the case study is definitely worth the read. The project approach and lessons learned can also be applied in other retail settings.
How are you helping your employees to work smarter by reducing the amount of time they spend on non-productive activities and correcting errors? If your business processes need a “check-up,” please email me at michael@leadingchangeforgood.com! I’d love to help you get back to a healthy, productive workplace.
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