The problem
Where the time was going
Reliable mail is something most people never think about, but behind it sits an enormous operation. This national postal service moves about fifteen billion pieces of mail a year for a country of thirty five million people and 1.3 million businesses and institutions, through 25 major processing plants, 24,000 outlets, and a fleet of 9,300 vehicles, with 62,000 employees keeping it all moving.
At one of those mail processing plants, the mail preparation work cell was not keeping up. Sorting and processing ran inefficiently, which pushed out delivery times and piled extra work onto staff. The plant needed to know whether it was staffing the work cell correctly and how to make the flow of mail move more smoothly, without guessing and disrupting live operations.
What we modeled
Mapping the process, then testing the fix
ProcessModel was already trusted elsewhere in the service, so the team used it to model the mail preparation work cell end to end. They fed in counter-service data to size manpower against demand and to test how the equipment was actually being used, then built each stage of the operation into the model.
The simulation followed the mail the way the floor did: collecting it from the dock, opening the bags, pulling out the non-machinable letters, and separating everything by its final destination. For the first time management could watch the whole flow of mail, beginning to end, on a single model, which is what won their go-ahead to act on it.
As a result of using ProcessModel simulation nationwide in 20 plants, we discovered that we could better organize staffing and scheduling. This was demonstrated when we were able to efficiently process the same amount of mail, while reducing work cells by 50 percent. This led to a savings of $4 million per year.
The result
The proof, and the payoff
The change was rolled out nationwide across 20 plants. With staffing and scheduling reorganized around what the model showed, the service processed the same volume of mail while cutting work cells by 50 percent, which saved about $4 million a year.
The existing mail-processing equipment was also used more effectively, lifting throughput and trimming work and overhead costs further. The project worked well enough that management began planning more simulations, for space, cycle time, and facility design.
- 50%
- fewer work cells
- $4M
- saved a year
- 20 plants
- rolled out nationwide
Part of our work in government.