·         What influences demand?

o   General economic and business conditions

o   Competition

o   Market trends

o   Plans made by your firm

·         Examples of demand sources?

o   Customers

o   Spare parts

o   Promotions

o   Intracompany

·         Demand Characteristics

o   Trend

o   Seasonality:  variation in demand based on the season – doesn’t refer only to variation over the course of a year, can also be weekly (weekend retail shopping) or even daily (lunch/dinner time at restaurants).

o   Random variation

o   Cyclical variation

·         Demand Patterns

o   Stable vs Dynamic

§  Stable:  less variation, small standard deviation and demand stays relatively close to the mean

§  Dynamic:  high variation, large standard deviation, erratic

o   Independent vs Dependent

§  Independent:  demand for the finished product sold to a customer, only this type of demand should be forecasted

§  Dependent:  demand for the components used to produced a finished good, this demand is NOT forecasted, but instead calculated based on the demand for the finished good, or independent demand.

·         Forecasting Principles

o   Rarely 100% accurate over time

o   Should include an estimate of error

o    More accurate for product lines/families and nearer time periods

·         Data Collection and Preparation

o   Data should be in terms needed for the forecast

§  Remember to record actual DEMAND, not shipments (the customer may have wanted more parts that we couldn’t fill at the time)

§  Use the same time intervals used in planning

§  Forecast items controlled by manufacturing

o   Circumstances relating to the data should be recorded:  for example, marketing promotions – demand should be increased during promotion, then reduced.

o   Record demand separately for different customer groups

·         Forecasting Techniques

o   Qualitative: 

§  Based on informed opinion and intuition about the product and market

§  Subjective

§  Used for business forecasting and planning for new products

§  Medium to long term forecasting

o   Quantitative:

§  Based on historical demand data available to the company

§  Assumes future will repeat the past

o   Extrinsic:

§  Based on cause and effect

§  For example:  Electric Cars.  I sell Batteries for electric cars.  The demand for my product group correlates to this indicator (demand for electric cars), so I can use that indicator to forecast.

·         Seasonality

o   Measures amount of seasonal variation of demand for a product

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·         Monitoring the forecast

o   Measure actual demand and compare it to what was forecasted

o   Why?

§  To plan around the error in the future

§  To improve forecasting methods

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