Operations management by stevenson 9th student slides chapter 3

Chapter 3: Learning Objectives• You should be able to: – List the elements of a good forecast – Outline the steps in the forecasting process – Describe qualitative forecasting techniques

Chapter 3

Forecasting

Chapter 3: Learning Objectives

• You should be able to:

– List the elements of a good forecast

– Outline the steps in the forecasting process

– Describe qualitative forecasting techniques and their advantages and disadvantages

– Compare and contrast qualitative and quantitative approaches to forecasting – Briefly describe averaging techniques, trend and seasonal techniques, and regression analysis, and solve typical problems

– Describe three measures of forecast accuracy

– Describe two ways of evaluating and controlling forecasts

– Identify the major factors to consider when choosing a forecasting technique

of a variable of interest

demand, and resource availability

informed decisions

An Important Input to Decision Making

• The primary goal operations and supply chain

management is to match supply to demand

much supply will be needed to match demand:

• Budget preparation

• Capacity decisions (e.g., staff and equipment)

• Purchasing decisions

Forecast Uses

• Plan the system

– Generally involves long-range plans related to:

• Types of products and services to offer

• Facility and equipment levels

• Facility location

• Plan the use of the system

– Generally involves short- and medium-range plans related to:

• Inventory management

• Workforce levels

• Purchasing

• Budgeting

Elements of a Good Forecast

The forecast

Steps in the Forecasting Process

1 Determine the purpose of the forecast

2 Establish a time horizon

3 Select a forecasting technique

4 Obtain, clean, and analyze appropriate data

5 Make the forecast

6 Monitor the forecast

Forecasting Approaches

• Qualitative Forecasting

– Qualitative techniques permit the inclusion of soft information such as:

• Human factors

• Personal opinions

• Hunches

– These factors are difficult, or impossible, to quantify

• Quantitative Forecasting

– Quantitative techniques involve either the projection of historical data or

the development of associative methods that attempt to use causal

variables to make a forecast

– These techniques rely on hard data

Time-Series Behaviors

Time-Series Forecasting - Averaging

• These Techniques work best when a series

tends to vary about an average

the level of a series

• Moving average

• Weighted moving average

• Exponential smoothing

Simple Linear Regression

set of data points

regression that involves a linear relationship between two variables

• The object of simple linear regression is to obtain an

equation of a straight line that minimizes the sum of

squared vertical deviations from the line (i.e., the least squares criterion)

Monitoring the Forecast

• Tracking forecast errors and analyzing them can provide useful

insight into whether forecasts are performing satisfactorily

• Sources of forecast errors

– The model may be inadequate

– Irregular variations may have occurred

– The forecasting technique has been incorrectly applied

– Random error

• Control charts are useful for identifying the presence of

non-random error in forecasts

• Tracking signals can be used to detect forecast bias

Choosing a Forecasting Technique

• Factors to consider

– Cost

a forecast

Using Forecast Information

– View forecasts as probable future demand

– React to meet that demand

– Seeks to actively influence demand

• Advertising

• Pricing

• Product/service modifications

– Generally requires either and explanatory model or a subjective assessment of the influence on demand

Operations Strategy

• The better forecasts are, the more able organizations will be to take advantage of future opportunities and reduce potential risks

– A worthwhile strategy is to work to improve short-term forecasts

• Accurate up-to-date information can have a significant effect on forecast

accuracy:

– Reduce the time horizon forecasts have to cover

– Sharing forecasts or demand data through the

supply chain can improve forecast quality