Unlocking Cost Efficiency in Mobility Plan Optimizations with Integer Programming

In the United States, carriers often offer a variety of mobility plans at different price points, each with varying data usage bandwidth. Enterprise customers have the option to pool and share devices across individual plans.

The primary objective is to reduce the total cost of these plans while minimizing the risk of incurring overage charges. Large carriers like AT&T Mobility and Verizon Wireless provide the flexibility for enterprises to modify individual plans before the end of the usage period, with the revised plan retroactively applied from the beginning of the period. This feature potentially avoids additional charges that would have been incurred if an optimal plan had been selected earlier to minimize expenses.

Attempting to optimize mobility plans manually, say through a spreadsheet, can be time-consuming, error-prone, and may yield sub-optimal savings. Many individuals continue to employ incorrect approaches to optimizing mobility plans, either leaving money on the table or overspending in the process. Moreover, many enterprises cannot afford the lengthy analysis required to determine optimal plans. They seek prompt solutions to present to mobility carriers and realize savings.

This optimization process can be streamlined using algorithms such as integer programming. This algorithm is well-suited for mobility optimization tasks, capable of identifying the minimum cost based on individual usage, cost, and pooling ceiling constraints to ascertain how best to assign optimal plans for individual accounts. Remarkably, these calculations can be completed within seconds. Therefore, if you have a pooling plan with a large number of devices, you won't need to allocate significant resources to optimize the model. You can also enhance this model by incorporating additional decision points, like removing individual device users from the pooling plan to further minimize costs.

I am a proponent of an incremental approach, which allows for continual improvement of the model. While integrating what-if analysis or superior forecasting models in conjunction with integer programming could be beneficial, introducing integer programming into the management of mobility plans can yield immediate savings. There's no reason to delay automating this aspect of your business process.