What types of operational decisions would be affected by a seasonal approach for
ID: 382684 • Letter: W
Question
What types of operational decisions would be affected by a seasonal approach forecast? What would be the consequence of an inaccurate forecast?
Month Year
1
2
3
January
99
147
140
February
123
122
132
March
144
113
135
April
127
124
156
May
128
156
157
June
188
199
223
July
146
162
169
August
155
156
154
September
134
134
153
October
129
144
154
November
130
132
161
December
143
155
165
Month Year
1
2
3
January
99
147
140
February
123
122
132
March
144
113
135
April
127
124
156
May
128
156
157
June
188
199
223
July
146
162
169
August
155
156
154
September
134
134
153
October
129
144
154
November
130
132
161
December
143
155
165
Explanation / Answer
What types of operational decisions would be affected by a seasonal approach forecast?
The seasonal forecast is extremely important in predicting the resource requirement over a period of time corresponding to a particular S&OP planning. For example, in a season where the manpower requirement is low, the contract with the contractor who provides contractual workforce can be made accordingly. This will reduce the additional cost incurred by having the excess manpower. If seasonality is considered in the forecast, operations planning becomes easier form the point of view of plant and equipment maintenance as well. For example, factories can be planned to remain shut down in a particular season of low demand leading to scope to maintain the equipment in a preventive manner. This improves quality, productivity, and reliability of the products leading to competitive advantage.
What would be the consequence of an inaccurate forecast?
Seasonal forecasting, however, is only good when the forecaster is able to technically predict a seasonal trend with his/ her domain knowledge. Without domain knowledge, considering seasonality means leading to more inaccurate forecast. An inaccurate forecast will either lead the company go out of capacity due to improper resource planning or will lead to excess capacity and higher cost. Both the extremes will result in the erosion of competitive advantage by making the customers dissatisfied. Inaccurate forecasts will generally drive the companies to keep excess backups in terms of inventory or additional capacities.
Note: I don't understand why the numerical data is given along with these questions. The questions are theoretical in nature.
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