Forecasting

1. INTRODUCTION

Forecasting is defined and described in many ways. Forecasting in lay man term is to predict a future event or data by taking account of current and past data or events. Prediction of data could be of business profits, estimated demand of produced product, estimated supply of raw material needs and the list goes on. People can’t run away from forecasting something in some way or other. The best example would be weather forecast. If it’s predicted to be rain tomorrow, convenience store will increase their supply of umbrella for the next day demand. Forecasting plays important roles in making future decisions especially involving business and national interest. It is most important in planning for the future by anticipating the outcome. For example, how many police officers needed to handle the public safety in a community? How many specialist doctor and general practitioner to be placed in a state general hospital?

Forecasting is done through two main approaches; qualitative and quantitative. There are varieties of forecasting technique which could be classified as judgemental forecasts, time-series forecast and associative forecast. Examples of methods in those categories are as per table 1 below:-

Forecasting Technique | Method |

Judgemental Forecast | Executive opinions, sales force opinion, consumer survey |

Time-series Forecast | Naïve methods, Moving average, exponential smoothing |

Associative Forecast | Simple linear regression |

In this given Operational Management Assignment, associative forecast technique will be used. Associative forecast identify related variables in order to predict necessary forecasts. Associative forecasting assumes that the variable being forecasted (the dependent variable) is related to other variables (independent variables). For example, the sales of type of car model (dependant) is depends on the individual monthly income level (independent). In other words, knowing an individual income we...