Field Service Optimization
Client is leading telecom player with 4000 field technicians deployed for installation, maintenance and network operations.
To design a planning optimizer for enhancing the productivity and utilization of technicians w.r.t. contractors by skill removals and efficiency changes on the basis of forecast demand and supply.
- A gradient boosting model was used to construct and confirm the input-output relationship between supply, demand, skill-mix, efficiencies and productivity
- A Bayesian optimization layer was used to solve the problem to generate optimized skill-mix based on efficiency changes and skill-removals
- More than 2000 engineered variables
- Contextual and agile modelling
- Optimized selection of skill-mix of technicians and contractors resulted in a 7% increase in productivity of technicians across 8 districts.
- Selective skill removals of contractual work force helped in better work allocation to technicians and enhanced utilization by reducing idle time by 30 mins in a day.