Demand forecasting

1. Demand Forecasting in a Supply
Chain
Chapter 7

2.  Understand the role of forecasting for both an
enterprise and a supply chain
 Identify the components of a demand forecast
 Forecast demand in a supply chain given historical
demand data using time-series methodologies
What we will learn in Chapter 7

3. Role of Forecasting in a Supply Chain
 Demand forecast form the basis of all supply chain planning.
 Remember Push/pull view of Supply chain?
 Mature products with stable demand are usually easiest to
forecast.
 Forecasting and the accompanying managerial decisions are
extremely difficult and complex when either the supply of raw
material or the demand of finished product is highly unpredictable.

4. Characteristics of forecasts
Forecasts are always wrong and should thus include both the
expected value of the forecast and a measure of forecast error
Long term forecast are usually less accurate than short-term
forecast
Aggregate forecast are usually more accurate than disaggregate
forecast
The farther up the supply chain a company is, the greater is the
distortion of information it receives.

5. Components of a forecast and forecasting methods
 Demand does not arise in vacuum. Rather customer demand is
influenced by a variety of factors and can be predicted, at least
with some probability, if a company can determine the relationship
between these factors and future demand.
 Companies must balance objective and subjective factors when
forecasting demand.
 A company must be knowledgeable about numerous factors which
includes:
- Past Demand - Lead time of product
- Planned advertising - State of the economy
- Planned price discounts - Actions that competitors have taken

6. Forecasting Methods
•These are subjective and rely on human judgement. These
are suitable when little historical data is available
Qualitative
•Time-series forecasting methods use historical demand to
make forecast. They assume that past demand history is a
good indicator of future demand
Time Series
•Causal forecasting methods assume that demand is highly
correlated with certain factors in environment, for example
product pricing is strongly correlated with demand
Causal
•Combination of time-series and causal methods to answer
questions like; what will be the impact of price promotion.
Simulation

7. Basic approach to demand forecasting
1. Understand the objective of forecasting
2. Integrate demand planning and forecasting throughout the supply
chain
3. Understand and identify customer segments
4. Identify major factors that influence the demand forecast (Demand
side, Supply side or product side)
5. Determine the appropriate forecasting technique
6. Establish performance and error measures for the forecast

8. Time-series Forecasting methods
--The goal of any forecasting method is to predict the systematic components
of demand and estimate the random component.
Systematic components of demand contains a level, trend and a seasonal
factor
 Multiplicative: Systematic components = level x trend x seasonal factor
 Additive = level + trend + seasonal factor
 Mixed = (level + trend) x seasonal factor
 Static Methods: Assume that estimate level, trend and seasonality within the
systematic components do no vary as new demand is observed.
 Adaptive Methods: Estimates of level, trend, and seasonality are updated after
each demand observation.

9. Measures of Forecast Error
--A good forecasting method should capture the systematic component of
demand but not the random component. It manifests it self in the form of a
forecast error which must be analyzed because of:
1. Managers use error analysis to determine whether the current
forecasting method is predicting the systematic component of demand
accurately.
2. All contingency plans must account for forecast error.

10. Role of IT in demand planning
--IT has a natural role in forecasting as it involves large amount of data
analysis, the frequency with which forecasting is performed, and the
importance of getting the highest-quality results possible.
Risk Management in Forecasting
--Risks associated with forecast error must be considered when planning for
future. Errors in forecasting can cause significant misallocation of resources in
inventory, facilities, transportation, sourcing, pricing and even information
management.