The intention to measure forecast accuracy – a relatively objective value – has a dual purpose: forecast accuracy influences various operating costs and customer satisfaction. In the same way, the very appearance of an effectiveness control function reveals the potential that salespeople have as agents that generate information – which feeds back to the forecasting system – and, at the same time, raises the need for good forecast management to be rewarded (“what is measured is rewarded and what is rewarded is done”).

One of the derivations of the importance of forecast accuracy is related to its effect on the so-called operating costs, which include the generation and management of the forecast management system itself. One way to mitigate or minimize this management is to examine only products for which an acceptable degree of precision has not been achieved, or to work on products that require higher levels of service. Within the process of generating forecasts, the existence of a “forecast champion”, with the consequent cost that this generates, and the training derivations that it entails – for the various functional lines – are aspects to be considered. Those who use forecasts need training on how they were developed, their limitations, and how they should be applied to planning.

Among the derived operating costs, we can mention those of operation (logistics production), marketing (promotions, advertising, sales quotas, product development, price). These arise, in the case of operations, due to inventory costs, product errors, changes in programs, erroneous shipments that increase inventory costs, transportation, etc.

Among the costs derived in the case of marketing would be ineffective costs in advertising, development of new products without adequate demand, prices that do not maximize the contribution, inappropriate sales quotas. It is important to consider how strange forecast patterns can arise, which may be caused by inappropriate incentives (a system of sanctions for those who exceed the sales quota, for example). It is always important to assess the benefits that the forecasting system can bring. They do not always exceed the costs of developing a more complex system.

A final aspect to consider regarding the accuracy of forecasts is their implementation with customer satisfaction and dissatisfaction. The measurement of this dissatisfaction reaches several facets:

• - Design and produce products that customers want.

• - Do not design or manufacture products that you do want.

• - Not having the products desired by customers in the desired places and quantities.

Quantitative methods

• - Analysis of market factors: The demand for a product is always related to the behavior of certain market factors. This being true, we can determine a sales estimate by studying factors related to the product.

• - Analysis of historical sales and trend: It consists of forecasting taking into account past sales and demand, considering current factors. The prognosis is not necessarily positive.

Where:.

• - Market Tests: A company sells a specific product in a restricted area as a pilot or experiment and measures its results. Sales and potential demand are projected.

• - Forecasts are almost always wrong. The important thing is to focus on the expected error of each forecast.

• - Forecasts are more accurate for groups or families of items. It is almost always easier to develop a good forecast for a product line than for an individual product, since errors tend to cancel each other out as they are grouped together.

• - Forecasts are not a substitute for calculated demand. If you have information on real demand, there is no point in obtaining forecasts.

• - They are trends provided on the basis of historical data, with the purpose of having certainty in future growth according to a methodology.

Qualitative methods

Forecasts generated from information that does not contain a well-defined analytical structure. This type of forecast is quite useful when historical information is not available (for example, a new product).

• - Survey of buyer intentions: It consists of a survey of opinions of desires or expectations regarding the purchase of a product. This will include items such as expected price, quality, packaging, etc. Its limitation is given because the purchase intention is one thing and the purchase itself is another.

• - Participation of the sales force: It consists of forecasting sales with the estimates of the sales force (salespeople, distributors, sales managers, etc.). This method can generate very accurate forecasts if the sellers are competent people since the direct link with the market makes them key people suitable for making said forecast. The limitation is that generally the sales force does not master statistical tools, methods, etc.

• - Executive Judgment: Like the previous method, it can be accurate if the executives have been competent, but it is usually more guesswork. One way to reduce the margin of error is to apply the Delphi method: A group of experts is taken and they anonymously give their opinion, then the estimates are summarized and these estimates are subsequently made known to the entire group and they are asked to make a new prediction, this can be repeated several times. This method prevents powerful people from influencing others or from “coupling” several opinions around a single judgment for the mere fact of having an opinion like “the other” or “not disagreeing.”

• - Judgment of expert consultants:.

It is a set of opinions that expert professionals in an industry or discipline can provide, related to the project being executed.

Several consultations are made, which is favorable for investigations.

This type of information can be obtained inside or outside the organization, free of charge or through a contract, in professional associations, chambers of commerce, government institutions, universities.

Throughout the project, expert judgment is used in:.

• - The integration of the project.

• - Integrated change control.

• - Administrative closure and closing of contracts.

• - Planning and definition of the scope.

• - The definition of the project activities.

• - Estimates of activities, resources and costs.

• - Risk analysis.

• - Planning of purchases and acquisitions.

• - The forecast is based on personal judgment or some external qualitative information.

• - The prognosis is subjective. It is biased depending on the optimistic or pessimistic perspective that people have.

• - Allows you to obtain some results quite quickly.

• - Sometimes it is the only method.

• - They are usually used for individual products, or families of products but rarely for entire markets.

• - Market study.

• - Law of inverse benefits.

• - Market (marketing) "Market (marketing)").

• - Business model.

• - Business plan.

• - Stanton WJ, Etzel MJ, Walker BJ. Fundamentals of marketing. McGraw-Hill; 2004.

• - Carranza O, Sabrià F. Logistics, best practices in Latin America. Mexico: Thompson; 2005. p.28-34.

• - Chase R, Jacobs R, Aquilano N. Operations management. Production and supply chain. Mexico: McGraw Hill Editorial. ISBN 978-970-10-7027-7.

The intention to measure forecast accuracy – a relatively objective value – has a dual purpose: forecast accuracy influences various operating costs and customer satisfaction. In the same way, the very appearance of an effectiveness control function reveals the potential that salespeople have as agents that generate information – which feeds back to the forecasting system – and, at the same time, raises the need for good forecast management to be rewarded (“what is measured is rewarded and what is rewarded is done”).

One of the derivations of the importance of forecast accuracy is related to its effect on the so-called operating costs, which include the generation and management of the forecast management system itself. One way to mitigate or minimize this management is to examine only products for which an acceptable degree of precision has not been achieved, or to work on products that require higher levels of service. Within the process of generating forecasts, the existence of a “forecast champion”, with the consequent cost that this generates, and the training derivations that it entails – for the various functional lines – are aspects to be considered. Those who use forecasts need training on how they were developed, their limitations, and how they should be applied to planning.

Among the derived operating costs, we can mention those of operation (logistics production), marketing (promotions, advertising, sales quotas, product development, price). These arise, in the case of operations, due to inventory costs, product errors, changes in programs, erroneous shipments that increase inventory costs, transportation, etc.

Among the costs derived in the case of marketing would be ineffective costs in advertising, development of new products without adequate demand, prices that do not maximize the contribution, inappropriate sales quotas. It is important to consider how strange forecast patterns can arise, which may be caused by inappropriate incentives (a system of sanctions for those who exceed the sales quota, for example). It is always important to assess the benefits that the forecasting system can bring. They do not always exceed the costs of developing a more complex system.

A final aspect to consider regarding the accuracy of forecasts is their implementation with customer satisfaction and dissatisfaction. The measurement of this dissatisfaction reaches several facets:

• - Design and produce products that customers want.

• - Do not design or manufacture products that you do want.

• - Not having the products desired by customers in the desired places and quantities.

Quantitative methods

• - Analysis of market factors: The demand for a product is always related to the behavior of certain market factors. This being true, we can determine a sales estimate by studying factors related to the product.

• - Analysis of historical sales and trend: It consists of forecasting taking into account past sales and demand, considering current factors. The prognosis is not necessarily positive.

Where:.

• - Market Tests: A company sells a specific product in a restricted area as a pilot or experiment and measures its results. Sales and potential demand are projected.

• - Forecasts are almost always wrong. The important thing is to focus on the expected error of each forecast.

• - Forecasts are more accurate for groups or families of items. It is almost always easier to develop a good forecast for a product line than for an individual product, since errors tend to cancel each other out as they are grouped together.

• - Forecasts are not a substitute for calculated demand. If you have information on real demand, there is no point in obtaining forecasts.

• - They are trends provided on the basis of historical data, with the purpose of having certainty in future growth according to a methodology.

Qualitative methods

Forecasts generated from information that does not contain a well-defined analytical structure. This type of forecast is quite useful when historical information is not available (for example, a new product).

• - Survey of buyer intentions: It consists of a survey of opinions of desires or expectations regarding the purchase of a product. This will include items such as expected price, quality, packaging, etc. Its limitation is given because the purchase intention is one thing and the purchase itself is another.

• - Participation of the sales force: It consists of forecasting sales with the estimates of the sales force (salespeople, distributors, sales managers, etc.). This method can generate very accurate forecasts if the sellers are competent people since the direct link with the market makes them key people suitable for making said forecast. The limitation is that generally the sales force does not master statistical tools, methods, etc.

• - Executive Judgment: Like the previous method, it can be accurate if the executives have been competent, but it is usually more guesswork. One way to reduce the margin of error is to apply the Delphi method: A group of experts is taken and they anonymously give their opinion, then the estimates are summarized and these estimates are subsequently made known to the entire group and they are asked to make a new prediction, this can be repeated several times. This method prevents powerful people from influencing others or from “coupling” several opinions around a single judgment for the mere fact of having an opinion like “the other” or “not disagreeing.”

• - Judgment of expert consultants:.

It is a set of opinions that expert professionals in an industry or discipline can provide, related to the project being executed.

Several consultations are made, which is favorable for investigations.

This type of information can be obtained inside or outside the organization, free of charge or through a contract, in professional associations, chambers of commerce, government institutions, universities.

Throughout the project, expert judgment is used in:.

• - The integration of the project.

• - Integrated change control.

• - Administrative closure and closing of contracts.

• - Planning and definition of the scope.

• - The definition of the project activities.

• - Estimates of activities, resources and costs.

• - Risk analysis.

• - Planning of purchases and acquisitions.

• - The forecast is based on personal judgment or some external qualitative information.

• - The prognosis is subjective. It is biased depending on the optimistic or pessimistic perspective that people have.

• - Allows you to obtain some results quite quickly.

• - Sometimes it is the only method.

• - They are usually used for individual products, or families of products but rarely for entire markets.

• - Market study.

• - Law of inverse benefits.

• - Market (marketing) "Market (marketing)").

• - Business model.

• - Business plan.

• - Stanton WJ, Etzel MJ, Walker BJ. Fundamentals of marketing. McGraw-Hill; 2004.

• - Carranza O, Sabrià F. Logistics, best practices in Latin America. Mexico: Thompson; 2005. p.28-34.

• - Chase R, Jacobs R, Aquilano N. Operations management. Production and supply chain. Mexico: McGraw Hill Editorial. ISBN 978-970-10-7027-7.