Demand Planning and ForecastingSession 5

Selecting and Monitoring a Forecast System

ByK. Sashi Rao

Management Teacher and Trainer

Choice of Forecasting MethodTime Span Purpose Forecasting

MethodLONG RANGE- 3 YEARS OR MORE

Capital BudgetingProduct SelectionPlant Selection

DelphiExpert JudgmentSales Force CompositeSurvey Methods

INTERMEDIATE- 1 TO 3 YEARS

Capacity PlanningSales Planning

RegressionTime Series Decomposition

SHORT RANGE- 1 YEAR OR LESS

Sales ForecastingOperational SchedulingInventory Control

Trend ProjectionsMoving AveragesExponential Smoothing

Key Methodology Issues

• Choice of method/model determined by forecast need and purpose

• Accuracy level required for predictions and trade-offs involved• Extent to which chosen model assumes past relationships and

patterns which are expected to remain so in future• Appropriate forecasting horizon that reflects current lead time

for capacity creation• Need to match existing business patterns( constant, trend,

seasonal et al) with selected forecasting model

Developing the Forecasting Logic

STARTSSTT Idnetify /////identify

Develop

TestSTOP

START

STOP

Identify PURPOSE-use -horizon-data needed

Identify TECHNIQUE-collect/analyze past data-select suitable model

Develop FORECASTING LOGIC-establish model parameters-build the model

Test MODEL ADEQUACY-test using historical data

MODEL SATISFACTORY ??

NO

YES

7-5

Basic Approach toForecasting

• Understand the objectives of forecasting• Integrate demand planning and forecasting• Identify major factors that influence the demand

forecast• Understand and identify customer segments• Determine the appropriate forecasting technique• Establish performance and error measures for the

forecast

Developing a Forecasting System

• Three step process involves:• Developing a forecasting logic by identifying the

purpose, data, models and methods to be used• Establishing a control mechanism to obtain reliable

forecasts• Incorporating managerial considerations in using the

forecasting system

Establishing a Forecast System

• Importing historical sales data• Creating statistical forecasts• Importing customer forecasts• Collaborating with customers• Managing forecasts• Building consensus forecasts• Supply and demand collaboration• Securing constrained forecasts• Confirmation with customers• Re-examining data and adjusting planning accordingly.

Features of a Good Forecast

• Accuracy- with small errors• Unbiased- so as not to overestimate or underestimate

demand• Responsiveness – to frequent changes in demand( high alpha

choice) • Stability- strike balance with responsiveness( low alpha choice) • Accommodative – of odd unusual figures• Timeliness – to meet its purpose• Cost-effective- forecasts benefits more than costs • Easiness - to understand and operate• Sustaining- useful for reasonable time before needed changes

Forecasting Principles

• Unless method is 100% accurate( very rarely so!), the chosen one should be simple to understand and use by all concerned at all levels

• Every forecast should state the estimate of likely error as +/- % error ( as measure of accuracy)

• Individual items best forecast for shorter periods with only as groups/families of items for longer periods

• Managerial judgments should be used, if necessary, over forecasts generated by any method

• Forecasts are not an end in themselves, but done for a purpose, and should finally be useful for decision-making

7-10

Forecasting in Practice

• Recognize that forecasting is an essential part of business planning

• Involve all those who can contribute to building good forecasts

• Actively collaborate with all above in building forecasts• The value of data depends on where you are in the supply

chain• Be sure to distinguish between demand and sales forecasting• Ensure that forecasting models are periodically reviewed for

their utility of purpose

Forecasting Issues in Small/New Ventures

• They also need forecasts to plan and run their businesses• But they don’t have data-rich environments• Forecasting for new/constantly evolving products more

challenging• There may not be much historical/time series data• They lack the resources and/or capability to develop and

use advanced forecasting techniques• Should make do with external data/forecasting resources• Will still have to develop own practical forecasting

solutions conscious of forecast inaccuracies

Managerial Issues in Forecasting

G

CH

COST D TIMTI

GETTING STARTED- Choice of model- Estimation of parameters

USING THE SYSTEM-how to incorporate external information-stability versus responsiveness

CHANGING THE SYSTEM-parameter re-estimation versus model change

COST-BENEFIT

DATAAVAILABILTY

TIME FRAMEKEY INFERENCES

NEW COMPETITION

SALES PROMOTION

FORECASTRELIABILITY

Some Last Words

• The future is not ‘knowable’ in the sense of exact predictions. Life is filled with surrealistic surprise. Even the seemingly ‘hardest ‘ models and data are frequently based on ‘soft’ assumptions – Alvin Toffler, Future Shock

• It is far better to foresee into the future without certainty than not to foresee at all- Henry Poincare

Thank you

All the very best