A leading Indian automotive company wished to overcome production and distribution planning challenges. The company approached IGSA to optimize product allocation on the assembly lines and dispatch allocation from plants to stockyards for SKU variants of one of their flagship products.  Previously the process and method deployed for production, sales and dispatch planning were ad-hoc. The monthly plans were made by individual executives on Excel sheets, relying on thumb rules and their operational experience. This led to sub-optimal plans. The planning team was not even aware of the potential by which the plans could be improved to enhance the company’s contribution margin. In addition, as the planning process was manual and involved iterative trial and error approach, it consumed previous executive time which could otherwise be spent on valuable managerial analysis and decision making  Based on the client’s requirement, IGSA implemented network allocation planning & design solution to optimize their production and dispatch planning. In the business analysis phase, it was decided to build and deploy the solution in two separate but interactive modules. The objective of the first module (production planning) was to maximize the company’s contribution at plants by employing the most optimal production mix, considering SKU wise demand, assembly line capacities and other operational constraints and costs. The objective of the second module (plant to stockyard dispatch planning) was to minimize the company’s cost of transportation with due consideration to demands of SKUs in various markets, freight costs, taxes and logistics constraints. The production mix and pant-to-stockyard logistics allocation were simultaneously optimized. IGSA’s network planning solution has a built-in OR model (developed in GAMS/CPLEX) that was tailored to the client’s requirement.  Significant shifts occurred in production mix at plants and plant-to-stockyard logistics allocation plans owing to optimization. The major benefits were:- Simultaneous maximization of contribution at plants through optimal production mix of SKUs on assembly lines and minimization of outbound logistics cost through optimal dispatch plan between plants and stockyards, resulting in an increase in company’s contribution margin by about 4 million USD every year.-  Automation of the monthly production and logistics planning process, resulting in saving of managerial time for value-added analysis.  

Enhancing contribution by improving the production and logistics planning.

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Network footprint Fig: Network Planning Model

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