At the Descartes User Conference last year, a leading food and beverage manufacturer spoke about its implementation of a Mobile Resource Management (MRM) solution from Descartes (an ARC client). At a high level, the manufacturer’s goal was to improve its merchandising and store delivery operations.
Like other CPG companies, this manufacturer employs merchandisers (about 10,000 US sales reps and full and part-time merchandisers) to make sure that its products are stocked and displayed properly on store shelves; ensure that displays are deployed; get new product introductions on the shelf in a timely manner; and other related activities. For direct store deliveries (DSD), the logistics and merchandising teams need to collaborate. When a pallet of goods is delivered to a store, it is the merchandiser’s job to meet the truck and get the goods to the front of the store.
This manufacturer’s history with Descartes dates back to 1999 when it implemented a routing and scheduling solution for its DSD fleet. Around that time, the company had also tested various GPS solutions to track its DSD fleet and vehicles used by retail operations, but none of them met its needs. In 2007, the company began a GPS retail pilot with Descartes on a limited basis. Sprint was the mobility partner for this project, and the solution was integrated with the company’s ADP payroll solution.
The company expanded the pilot in the first half of 2008, and the ROI it achieved justified rolling out the solution nationally. The company’s specific goals for this project were:
- To reduce the amount of paperwork its managers had to process and give them more time to spend in the field (about one more day per week) to interact with and train their merchandisers;
- To enhance productivity and improve the company’s ability to accurately track what its workforce was doing;
- To provide a platform the company could use in the future to build better route development, delivery scheduling, and workload modeling.
From an ROI perspective, more accurate labor reimbursements helped to pay for the project and support the goals that were more difficult to model from an ROI perspective. The company’s merchandisers were paid based on the hours they worked and reimbursed for the miles they drove. Prior to the implementation of the MRM solution, this was based on self-reported data–i.e., merchandisers would call into voice response units to report their hours. Not surprisingly, some exaggeration in reported work hours was occurring.
Although the company did not disclose specific savings, it did say that after implementing the solution in a particular region it experienced almost a double-digit percent reduction in hours reported (which implies close to a 10 percent reduction), and reported miles driven decreased by almost double that amount (i.e., an almost 20 percent reduction). In addition, the system provides supervisors with actionable data–i.e., they can see, for example, if a merchandiser stops for 20 minutes at a fast food restaurant at 10 am. Finally, this data allows the company to have much better operational data for ABC customer profitability analysis, workload modeling, and the creation of labor standards.
There is also something in it for the merchandisers. By logging into a web-based portal, they now have accurate visibility to what they will get paid.
Other MRM pilots had not been successful, but what made the difference in this case was the integration of the GPS data with payroll. Workers don’t get paid if they don’t activate the GPS tracking. The other critical success factor was making sure managers review the data (at least twice a week for a half hour) and act on it. In short, payroll automation was the ‘hook’ that drives usage, while the GPS data is the “truth serum” that provides accountability.