DEMAND FORECASTING

DEMAND FORECASTING

Introduction:

›Demand is dependent on many factors like market trend, competition, business environment. We cant predict exact demand. But using statistical tools, we can estimate demand, which can help us in production planning.

Objectives:

Long term objectives of demand forecasting are strategic planning, product planning, capacity and expansion planning, facility location and planning for research and development.

Medium term objectives are production and layout planning, aggregate planning, sales and marketing plans, annual, quarterly or half-yearly cash budgeting and working and operating plans.

Short term objectives are purchase planning, inventory plan, job scheduling, work force and employee planning.

Forecasting techniques:

  • ›Delphi
  • ›Nominal group technique
  • ›opinion poll
  • ›Moving average method
  • ›Trend analysis
  • ›Time series analysis

Delphi method:

The features are it is an attempt to develop forecasts through “group consensus”. The group size generally range from 7 to 10.

Nominal group technique:

›It is similar to Delphi, but here we ask experts to sit together and explain their perspective to others so that others can also give their opinion. ›People frame their estimates individually, but thereafter they give justification for their opinion.

Opinion poll:

›We collect information about the issue from people using opinion poll. ›We may take interview, we may collect data using questionnaire, or we may organize meeting / conference to find opinion of people. ›Variants of opinion poll are : focus group discussion which is used in marketing to know about consumer opinions.

Moving average method:

›Here we take moving average of either 3 days or 5 days or 7 days and try to forecast using this moving average. ›We may also use smoothing to remove exceptional fluctuations Moving average is a case where data can be used to forecast on the basis of past trend.

Trend Analysis:

›1. secular trend

› 2. cyclical fluctuation

seasonal fluctuation

random / irregular variations

Time series Analysis:

›In this method, we are using time as an independent variable and predict demand using this variable

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