Demand forecasting in textile industry -a case study

Abstract

Forecasts are usually made to help and guide decision making. Good forecasts are preconditions for good, informed decisions. These decisions may vary from a financial market bet on interest rate changes to the policy decision on how to structure a country's pension system. Ideally, decision-makers should be as well prepared as possible for the future, which would allow them to act appropriately. To detect challenges and opportunities in a timely manner decision-makers require a good forecasting framework. Given the role governments, companies and individuals play, knowledge about the drivers and linkages that determine the future will allow these players to actually shape the future themselves. Decision makers need forecasts only if there is uncertainty about the future. Thus, we have no need to forecast whether the sun will rise tomorrow. There is also no uncertainty when events can be controlled. Many decisions, however, involve uncertainty, and in these cases, formal forecasting procedures can be useful. There are alternatives to forecasting. A decision maker can buy insurance, hedge, or use ―just-in-time‖ systems. Another possibility is to be flexible about decisions. Forecasting is often confused with planning. Planning concerns what the world should look like, while forecasting is about what it will look like. Planners can use forecasting methods to predict the outcomes for alternative plans. If the forecasted outcomes are not satisfactory, they can revise the plans, and then obtain new forecasts, repeating the process until the forecasted outcomes are satisfactory. They can then implement and monitor the actual outcomes to use in planning the next period. This process might seem obvious. However, in practice, many organizations revise their forecasts, not their plans. They believe that changing the forecasts will change behavior. Forecasting serves many needs. It can help people and organizations to plan for the future and to make rational decisions. It can help in deliberations about policy variables.