Production Planning And Control : Hugo Costa Campbel Student Number

1495 Words Aug 24th, 2014 6 Pages
MANF 4615
PRODUCTION PLANNING & CONTROL

Student: Hugo Costa Campbel Student number: z5007692 Due date: 25/08/2014

Assignment 1

Question 1: The customer order decoupling point is described as the point at which demand changes from independent to dependant. What does this mean and why is this important to managers?

The demand can be divided in two different types:
- The independent demand depends on the market conditions and it is difficult to control and must be forecast. Even though the company can interfere or stimulate this demand through some events such as promotions or price reductions, the final amount will depend on the item demanded in the market. Thus, companies will have to supply the demand without having any
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Vollman et al. (2005) also point out that although a manager cannot be responsible for not getting a forecast right, he/she should be responsible for making their plans. Furthermore, he/she should change the plan and execute it when the conditions change. (Word count: 341 words)
Question 2: ME, MAPD, Cumulative Error – what do they tell us and why do we want to know?

Forecasting information comes from a variety of sources and incorporates different assumptions about the market. It can be used by managers to make decisions for the company and its quality is reflected in the quality of the decision based on the forecast. For Sales and Operations Planning (SOP), the forecasts provide the basis for plans. For Master Production Schedule (MPS), the flow of forecast information is frequent and detailed. Thus, control decisions must be made quickly and efficiently to keep the product moving to the customer.
It is important to evaluate forecasts in order to identify the value of the forecast for the decision from its production costs and match the nature of the forecast with the nature of the decision.

There are some different techniques to evaluate a forecast:

- Mean error (ME): it is used to measure bias. The forecast error in each period is the actual demand in each period minus forecasted demand for that period. A positive value indicates low bias, and a negative

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