1. Operation Management Chapter 3
Ziad T. Al-Salim
Mohammad H. Al-Hashim
Abdulrahman A. Al-Naim
Abdullah E.Al-Khater

2. Outline Forecasting Approaches (Q.1). Sales and Demand terms (Q.13).
Weaknesses of some of the approaches (Q.3).
Contrast the use of MAD and MSE in evaluating forecasts.

3. Forecasting Approaches
Qualitative Forecasting
Qualitative techniques permit the inclusion of soft information such as:
Human factors
Personal opinions
Hunches
These factors are difficult, or impossible, to quantify
Quantitative Forecasting
Quantitative techniques involve either the projection of historical data or the development of associative methods that attempt to use causal variables to make a forecast
These techniques rely on hard data

4. Sales and demand terms Sales forecasting:
is the most straightforward: you take your sales history as input in order to produce a sales forecast. This is the bread and butter of most Lokad sales forecasting add-ons. For most retail products, this approach is already fairly efficient. Indeed, sales are the only reliable quantitative indicator available about the customer demand for products.

5. Sales and demand terms
If you want to produce a demand forecast, then you need to use the demand history as input. In practice, it means that you need to correct (probably manually) your sales history to reflect the demand.

6. Weaknesses of some of the approaches (Q.3)
1. Executive opinions: There is risk that the view of one person will prevail and the possibility that diffusing responsibility for the forecast over the entire group may result in less pressure to produce a good forecast.

7. Weaknesses of some of the approaches (Q.3).
2. Sale force opinions: Staff members may be unable to distinguish between what costumers would like to do and what they actually will do. Another is that these people are sometimes overly influenced by recent experiences

8. Weaknesses of some of the approaches (Q.3).
3. consumer surveys: Surveys can be expensive and time consuming .In addition, even under the best conditions, surveys of the general public must contend with the possibility of irrational behavior patterns.

9. Contrast the use of MAD and MSE in evaluating forecasts
Contrast the use of MAD and MSE in evaluating forecasts. The difference between these measures is that MAD weights all errors evenly, MSE weights errors according to their squared values. There is a common use of these measures is to compare the accuracy of alternative forecasting methods. Another use is to track error performance over time to decide is attention is needed and is error performance getting better or worse or staying about the same.

10. References
Operation Management: Theory and practice

11. Thanks for listening