ClearCOGS Named Finalist for Best Sustainability Program in 2026 Citizens Awards

CHICAGO, October 23, 2026 /CourierPR/ -- ClearCOGS, a decision intelligence company that turns restaurant data into daily operating guidance, has been named a finalist for the Best Sustainability Program in the 2026 Citizens Awards. The recognition highlights ClearCOGS's work to prevent food waste by helping restaurant teams decide what to prepare, how much to make, and when to make it.

The U.S. Chamber of Commerce Foundation selected ClearCOGS as one of four finalists in the category, alongside Allagash Brewing Company, Netafim North America, and U-Haul International. The winners will be announced during the Business Solves conference, which takes place from October 27-28 in Washington, D.C.

For restaurant operators, food waste often starts with a decision made hours before a guest arrives: how much bread to bake, meat to smoke, or produce to prepare. Making too much ties up labor and ingredients in food that may never sell. Making too little risks shortages and disappointed guests. ClearCOGS's decision intelligence platform combines data from restaurants' existing systems with AI-powered forecasts and restaurant-specific operating requirements. Its outputs include daily prep sheets, order guides, and labor plans.

Don W. Bradley, a Manhattan Bagel franchise owner and author of Don B From the Dish Pit, reported using ClearCOGS to plan production for a product that takes roughly 24 hours to make. He reduced bagel waste and saved about $4,000 per month in labor costs related to overproduction after tightening production quantities and adjusting baking shifts.

A 2024 report by McKenzie Huneke, completed during an Environmental Defense Fund Climate Corps fellowship at ClearCOGS, estimated that food waste prevention with ClearCOGS can avoid 2.90 to 4.48 tons of CO2-equivalent emissions per restaurant location each month, depending on ingredient types. The study also reported average monthly food waste prevention of 380 pounds per location across the customers analyzed. The estimates draw on customer data and emissions factors from ReFED, WRAP, and Hestia, and include both implementation results and modeled scenarios.