Master Operations Scheduling

Project : Case Write-Up on

Master Operations Scheduling (MOS) game

A report submitted to

Prof. Janat Shah

In partial fulfillment of the requirements of the course

Operations Management

By

  Chaitali Nemade     (166090)

  K V Sai Krishna      (166060)

   Lubhan Mahajan     (166072)

   Saradindu Naskar    (166151)

   Sunil Negi                (166178)

On

24-11-2016

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Master Operating Scheduling

Objective

Master Operations Scheduling (MOS) game is based on how, planning, forecasting the sales and marketing promotion effect the scheduling of production. We need to maximize the net operating contribution using the forecast data available and adjusting production and advertisement levels. One should keep into consideration the costs involved with inventories and backlogs. Based on production one needs to decide number of shifts and maximize contribution by reducing wage cost.

Strategy

The game was simply to meet the demand with the supply by keeping in mind the expected forecasts of demands for different periods in a year.  The one thing we kept in mind from the very start of our operating cycle for each period was to not have backlogs and not to keep excess inventory. Whenever we had the tradeoff whether to keep excess inventory or to have backlogs, we decided on keeping extra inventory as the price to keep inventory was less as compared to have backlogs from the previous period. We also had the option of meeting demands by making the workers work overtime or to either work in 2 shifts.  We as a team did the cost benefit analysis of both the approaches and find out that it was better to work in two shifts than doing work in overtime. We also decided not to change the shift in between periods as changing the shift would have cost us a huge amount of money which would have narrowed our contribution margin.  Also, we as a team didn’t find any advantage in incurring a cost for advertisement as the advertisement cost were not providing sufficient advantage to us. There were factory rate charges also, so we kept in mind to not have a huge difference in between the factory production rate so as to avoid extra cost. The delivery of factory output for a particular period in the future was always in our mind while we were setting the production capabilities for a particular period so as to meet the demand for that period in the future so as to avoid the backlog cost.

We started the game from period 2. As per the data from 1st period, we had a backlog of 4000 units. The forecasted demand for period 2 was 82000; we placed an order of 80000 to avoid inventory holding cost. But as total demand was greater, we incurred the cost of the backlog.

In the next period, i.e. three we had forecasted demand of 125000 but our production capacity was a maximum of 110000, so we gave an order of 110000. We already had a backlog of 7000; we got current demand of 119000 which increased backlog to 16000. Here we understood how to use the n+1 and n+2 sales alonwith forecasted demand to place production order.