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You should now read the introduction to Chapter 12 in Russell & Taylor (p. 496).

QUALITATIVE FORECASTING METHODS 

When there is no historical data available, only qualitative or judgmental forecasting is possible. For example, management, marketing and purchasing, and engineering are sources for internal qualitative forecasts (Russell & Taylor, 2009: 477). Additional information about several of these methods is provided below. 

Qualitative forecasting methods may also be used in combination with quantitative forecasting methods to adjust quantitative forecasts when their track record is poor, when the decision maker has important contextual knowledge or to compensate for specific events. 

You should now read the section 'Forecasting methods' on pp. 501–502 of Russell & Taylor for an introduction to forecasting.

Executive committee consensus 

This approach summarises the opinions of a group of executives. It may be used to modify an existing forecast to account for unusual circumstances. The disadvantages are that it consumes expensive time and that executives may independently modify forecasts based on individual opinion.

Delphi method

 The Delphi method is a process of gaining consensus from a group of experts while maintaining anonymity. Anonymity is important so that one expert doesn't dominate the results. For a broader explanation of the Delphi method, refer to p. 501 of Russell & Taylor.

 

There are six steps in the Delphi method: 

1.       Questions are sent to a number of experts in a given field.

 

2.       Each expert responds and provides a justification of their response.

 

3.       A report that summarises the responses is prepared.

 

4.       The report is returned to the experts.

 

5.       The experts modify or reassert their responses.

 

6.       The process may repeat several times to achieve some form of consensus. 

The Delphi method is useful for long-range forecasting and for predicting technological changes. It has the advantage of being less expensive than other methods, but it also has the following disadvantages: 

§    The process can take a long time. 

§    Anonymity may also produce irresponsible opinions. 

§    All forecasts (regardless of method) may be wrong. 

§    Results are sensitive to the questionnaire design. 

Survey of sales force 

Members of the sales force in each region provide personal estimates of future demand. The advantages of this method are that the sales force has good information about customers' purchasing plans, individual forecasts are made by district or region, and the forecasts can be easily aggregated into any combination required. The disadvantages are that forecasts may be biased, the sales force may not be able to tell the true intentions of their customers, and there is the potential for personnel to underestimate sales so that their performance looks good when it is reviewed. 

Market research 

This is a systematic approach to creating and testing hypotheses about the market by gathering data using a survey. The disadvantages are that accuracy decreases as projections increase into the long-term, there are likely to be numerous hedges and qualifications in the findings, there may be a low response rate to surveys, and respondents may not be representative of the market.

 

A C T I V I T Y  5 . 1 

Investigate the types of qualitative forecasting techniques used in your organisation. How do senior managers identify the appropriate forecasting technique to use in different circumstances? Do you think these techniques are used appropriately in your organisation?

QUANTITATIVE FORECASTING USING PATTERNS OF DEMAND

Sometimes it is possible to observe a pattern in levels of demand over time. This pattern is known as a 'time series'. There are five basic patterns of time series: 

§    Historical—This illustrates an average level of demand. 

§    Trend—A trend is represented by an upward or downward slope. 

§    Cyclical—Business cycles often span four-to-eight years, while life cycles vary widely in duration. It is difficult to quantitatively address this component because a sufficient data history is rarely available. 

§    Seasonal—This usually repeats annually, but could be based on a day, week or month. 

§    Random—The magnitude of this component means it cannot be precisely forecast at a given time. However, the significance of the random factor's size can be observed, and it may be possible to predict the bounds of the random factor, which can help to determine the reliability of a forecast.

 The quantitative forecasting methods we will discuss in this topic are time series and causal methods that are used in a variety of forecasting applications. More advanced techniques such as Fourier Analysis will not be discussed. 

Factors affecting demand 

Any forecast based on a pattern of demand relies on that pattern continuing in the future. When using such forecasts you should carefully identify the conditions that existed when the data were collected, and compare these against the conditions that now exist and those that are likely to exist in the future. This should become a part of your general approach to risk analysis. 

The factors that cause changes in the patterns of demand for a particular product or service over time can be divided into two categories—external and internal. 

The external factors are the ones management cannot directly control. Some economic factors, such as a booming economy, may influence demand, but their influence may not be equal for all products and services. Other factors may positively affect one product while reducing the demand for another. When interpreting statistical indicators it is useful to be able to distinguish between leading, coincident and lagging indicators. 

Internal factors are easier for management to control. Examples include advertising and promotions to encourage customers to make purchases during off-peak demand periods, and developing products that have different seasonal peak demands in order to level production resource requirements. 

The timing of demand is important for efficient use of resources and production capacity. In terms of services, schedules of available capacity should ideally be matched to demand for services. When demand exceeds capacity, the lead-time to access a service lengthens until customers baulk.



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