Data Collection:
Gathered required data for modelling from multiple data sources.
Data on committed trainings to customers.
Consolidation report of all training deliveries reported by partners through YTD.
Data on multiple pricing brackets across geographies.
Logic Formulation:
Listed down all the scenarios for potential subsidy savings calculation such as all unutilized seats, % of unutilized seats and x number of days from creation date.
Devised a logic to calculate the subsidy based on countries where the committed trainings are scheduled.
Model Creation:
Created a dynamic model so that the potential subsidy exposure changes based on the inputted parameters.
Provided flexibility to client in trying out ‘n’ number of possible scenarios and take decisions accordingly.
Potential subsidy savings provided at region level and tier level eased the process of decision making.
Dynamic model based on multiple input parameters helped client to try out multiple possible scenarios.
Potential subsidy savings provided at region and pricing bracket level enabled client to take a decision to provide training to X% out of committed trainings.