Scheduling and routing for commercial cleaning

The client is a leader in the janitorial services industry, with over 50 years of experience cleaning offices, industrial facilities, schools, medical facilities, and cleanrooms. The company built its reputation on employing the best people and the best technology to deliver consistent, high-quality outcomes for its clients.

The business relied on spreadsheets and loosely connected software to identify cleanable square footage, define service specs and schedules, and route staff through a facility. Estimating took real time and skill, and doing it by hand left room for the kind of inconsistencies that are hard to catch until a job is already underway: mismatched schedules, inaccurate estimates, uneven training, and little real oversight of how work was actually being planned. In an industry already burdened by high turnover, none of that was sustainable.

The company’s founder and CEO, Jim, was a well-known voice in the industry, a regular speaker at industry conferences on how commercial cleaning operations could run. He saw an opportunity to bring real structure and automation to a corner of the business that had stayed manual industry-wide.

Gavant conducted a collaborative review of the science and process behind the company’s cleaning system and built a software platform to model and automate the workflow. Users could upload and draw directly on floor plans to capture cleanable square footage automatically, then build cleaning specs, assign and schedule staff, and print job cards that gave front-line cleaners and specialists clear, consistent instructions.

The early version proved out the concept, automating scheduling and estimating behavior that had never been systematized before. As it became clear what the platform could do, both for internal operations and for how the company sold to prospective customers, Jim wanted to push further and add more advanced functionality. By then, the original technology stack was aging and its core framework was being phased out. The new functionality he wanted would have required significant rework of the existing system regardless, and building that rework on a sunsetting foundation made little sense for a system that had already proven itself mission-critical. Gavant rebuilt the platform on a modern stack built to support it for the long term.

Job cards alone cut training time for front-line cleaners by 40%, a meaningful number in an industry with this much turnover. The time needed to workload and estimate a space dropped by 50%, with far fewer of the inconsistencies that used to come with doing it by hand. Visibility improved across the organization too, with operations managers weighing in earlier in the process and automated approvals giving senior leadership real oversight and accountability.

The system also became something the company could point to competitively. “I am very pleased with the application we have currently, and feel very confident that a good push in the marketplace will bring dividends,” Jim said. Gavant took on ongoing support for the platform following the rebuild.