Seasonal index is a method used to measure the variations that are experienced due to the change in seasonal demand. They are used in adjusting of the demand forecast by multiplying the product base forecast by the seasonal index. Holidays like Easter, seasons like summer time, and super bowl events are better serviced with the seasonal index. The problem with seasonality is that seasons always change and this variation may not coincide with the demand forecast calculated using the seasonal index (Sharma, 2012). Therefore, a business has to adjust accordingly to the current situation which may be costly and time consuming thus may lead to loss of money.
Seasonal index helps to forecast seasonal sales demand, but this may create inaccurate demand forecast for a given year. Sales data from previous years are used to find the base forecast; however, this number may be incorrect due to wrong information on sales history or right information generated at the wrong time (Wegner, 2007). The base number is multiplied by the seasonal index to get the demand forecast. Inaccurate demand forecast used will leads poor product forecasting, and will subsequently affect the business goals. These incidences associated with poor wrong demand forecasting will trigger lower sales and gross profit margin for the business.
Seasonality also impact to a product lead time. Product lead time is the time frame between the period a product order is placed and the time the product is picked, shipped or sold. Seasonal index may cause inaccurate product lead time, which may make a product to stay on the shelves longer than expected, thus the products may expire or decrease in quality.
In order to avoid difficulties and misleading information about seasonal index, business people should adjust their demand forecast to coincide with the present season in order to save the huge amounts of money that would have been lost due to incorrect seasonal forecast (Sharma, 2012).
References
Sharma, J. K. (2012). Business statistics. New Delhi: Dorling Kindersley.
Wegner, T. (2007). Applied business statistics: Methods and Excel-based applications. Cape Town: Juta.
