Reducing forecast error, reducing the need to forecast and avoiding the problems caused by inaccurate forecasts
Part 1. Why forecast, why forecasts are wrong, and why does that matter?
This article is part 1 of two articles on forecasting. This first article deals with the need to forecast, why forecasts are often wrong (contain errors), and the implications of forecast error. The second article (available on request) deals with improving the quality of forecasts, reducing the need to forecast, and reducing the impact of forecast error. This service is not available to consultants.
Links to More Best Practices and Training Below
Why do you need to forecast?
There are a number of reasons why you may need to forecast. Below are listed the ones we have encountered, together with their characteristics.
The following diagram (figure 1.) illustrates a product life cycle. It shows a growth in volume up to a peak. This peak which may be short lived is sometimes called "the novelty curve" then declines to a plateau of relatively stable demand and then a decline into obscurity. The scale of the curves and slope of the lines varies from product to product but the general shape is applicable to many if not most products.
Figure 1. Product life cycle
The volume and duration where the changes in slope are most significant are:
- The most important to forecast
- The most difficult to forecast
- The ones where people want to exert maximum influence
Together with economic prosperity and decline goes a cycle of what has come to be known as "the business cycle" (a period of slow or negative growth followed by the next period of rapid growth). It is also referred to as "boom and bust".
The impact of this on capacity and stock is shown in figure 2 below:
Figure 2. The business cycle
Again it is important to identify the next upturn or downturn accurately, or there will be the sort of implications shown in the diagram.
3. Supply chain lead-times greater than consumer required lead-time
Where there is uncertain demand and the supply chain lead-time is greater than the customer required lead-time, safety stock needs to be held in anticipation of an order. I.e. Items cannot be made to order.
4. To provide input into long term decisions such as capital investment.
Often major capital equipment or expansion plans have to be viewed against a forecast of what the demand will be.
5. Peak demand and average capacity
This is the problem caused when customers want things at a faster rate than your capacity allows. For a period of time the mismatch ((anticipated peak rate of demand - peak rate of supply) x lead-time) has to be made in advance to ensure that sales are made when required. It is not readily realised that in order to give consistently high service levels, peak demand has to be matched by peak capacity. This gives accountants concerns since the capacity is therefore under-utilised for the remaining time. Most management accounting systems and budgetary control systems are based on top down spreading of annual targets which has a smoothing (averaging) effect, rather than bottom up costing of timed causal relationships, for example, a sales campaign leading to increased costs at a particular time. This would not be a problem if these budgets were not then used indiscriminately to control expenditure rather than intelligently to explain necessary variances. This cost tension then starts to create the problems shown in figure 2. Extreme examples of this problem are in seasonal demand such as vehicle batteries, and garden equipment and success stories where products are selling better than expected but cost pressures prevent increasing capacity. Much worse however is where products are going rapidly into steep decline but backward looking management accounting systems do not exert cost pressures until too late.
6. Spares
Spares present two major problems:
- In early life the supply chain has to be primed on estimates of mean-time-between-failures based on small sample testing.
- In later life as the original equipment is taken out of production it is often necessary to estimate all-time spares requirements with little knowledge of the decline in usage of the product.
Mid life spares forecasting whilst still potentially problematic for long life components, is less troublesome, since after the novelty phase (see figure 1) demand is more stable.
Transport costs inhibit the supply-to-order situation, which is the ideal lean supply chain (See Designing Lean Supply Chains), forcing suppliers to "batch up" to reduce unit transport costs.
The old adage "cheaper by the dozen" is often used to justify large batches (See Participative Sales and Operations Planning), which then require a forecast to justify the stock holding costs and reduce the risk of obsolescence.
Which of the lines in figure 3 represents the best forecast after plot 3? There is a good argument for each.
Figure 3: Best-Fit Trend
There are a number of reasons for forecast error. We discuss the 59 we have encountered so far, under the following 10 general headings in our SSC05 Producing Accurate Forecasts training course:
What decisions need forecasting & which do not?
What data do you need and how far ahead should you look?
Data sources: Where to collect data from (& where not to)
Data collection processes
Induced changes
Customer’s inventory planners
Computer models
Interpretation and analysis
Not recognising natural variation & "the black swan" (when they are usually white)
The Mathematics of modelling (overview of SSC03 Advanced Forecasting and Inventory Modelling)
The implications of forecast error
The obvious implication of forecast error is an over or under reaction to the latest trend. This gives rise to the following risks:
Figure 4: The implications of Forecast Error
Shown in figure 4 is the fine balance between being right and wrong!
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More information is available in the following articles:
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From our archived best practices: - Best Practice of the Week B014 Effective Bill of Material Design - Best Practice of the Week B022 Change Control - Best Practice of the Week B029 Bin Discipline
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We cover this topic in the following training courses:
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SSC05 Producing Accurate Forecasts (Discusses the business processes required) |
SSC03 Advanced Forecasting & Inventory Modelling (Using Spreadsheets) (Discusses the maths) |
To discuss your consulting or training needs with one of our independent consultants or trainers please Contact Us.
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Summary: Best Practice Business Processes |
Ó SM Thacker & Associates February 2001 Version 3 November 2009
