Demand Forecasting in Supply Chain

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Demand Forecasting in a Supply Chain
Demand forecasts form the basis of all supply chain Planning.

Forecasts are always wrong. Forecasts can’t match the exact demand. So, it should include the expected value of forecast and a measure of forecast error(demand uncertainty). Short-term forecasts are more accurate than long-term forecasts. Forecast of 1 weeks demand is likely to be more accurate than forecast of a particular day’s demand. Aggregate forecasts are more accurate than disaggregate forecasts. It is easy to forecast the GDP of a country is less than 2% error, but it is much more difficult to forecast yearly revenue of a company. The farther up the supply chain a company is, the greater is the distortion of information it receives. The farther the order come from the end customer, the larger the forecasting error is. Importance of measuring forecast error:

Managers use error analysis to determine whether the current forecasting method is predicting the systematic components of demand accurately. All contingency plans must account for forecast error.

Forecast error for period t ,Et = Ft (Forecast for period t)- Dt (Actual demand for period t) The role of IT in forecasting
In forecasting large amount of data is involved. Getting the highest-quality results possible is very important in forecasting. So, there is a natural role of IT in forecasting .
The forecasting module within a supply chain IT system is often called Demand Planning Module. Pros:
Demand Planning Module provides more accurate forecast than general package like Excel. A good forecasting package provides forecast across a wide range of products that are updated in real time.
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