Probabilistic Forecasting for Contractors

Kierulff, Herbert E.; Robison, D. E.

doi:10.1287/mnsc.17.12.b773

Management Science

1971

DOI: 10.1287/mnsc.17.12.b773

|View full text |Cite

Probabilistic Forecasting for Contractors

Herbert E. Kierulff¹,

D. E. Robison²

Abstract: Firms that perform work on contract to others often estimate their sales by assigning a probability of award to each potential contract, finding the expected value of each contract and then summing these expected values. Our methodology provides a complete probability distribution around the company sales forecast mean with no further data input than that required to obtain the expected value. The full distribution more realistically portrays business prospects, and allows planners and decision makers to engag… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

1972

1976

Publication Types

Select...

Article3

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Optimal Planning: The Use of Sales Forecasts

Childress

1973

Decision Sciences

View full text Add to dashboard Cite

Budgets are established and decisions in a firm are made on the basis of the sales forecast. In the majority of firms this forecast is a singlc value estimate of sales. The decisions made on the basis of the single value estimate frequently fall short of optimal strategies because of costs that occur when actual sales differ from forecast sales. These costs, measured in terms of opportunity losses, can be minimized when considered in conjunction with a probability distribution of sales.Three methods for determining the probability distribution of sales are considered in this paper. These are regression analysis Schlaifer's approach for establishing a subjective distribution, and Bayesian regression. The use of the distribution in conjunction with linear and quadratic loss functions is illustrated.

show abstract

Optimal Planning: The Use of Sales Forecasts

Childress

1973

Decision Sciences

View full text Add to dashboard Cite

show abstract

Fixed Sum Losses in Operational Forecasting

Willis

1976

Decision Sciences

View full text Add to dashboard Cite

In operational applications, forecasts .are normally adjusted by applying safety factors to allow for asymmetry in the underlying loss function. This paper considers an extension of the often used linear loss function to situations in which an error can also result in a fixed sum loss.The need for forecasts as inputs to planning and decision models is widely recognized. Forecasts range from subjective, qualitative predictions of the long range future to short range operational projections which are quantitative and highly structured. In the latter case historical statistics normally are available and form the basis for the projection as in sales forecasting for production and inventory control, cash flow forecasts, and forecasts of labor turnover. Analytic procedures include classical time series analysis, regression models, exponential smoothing, and other adaptive procedures, as well as subjective methods such as the use of executive or sales force opinions.It is generally accepted that forecasts can never be completely accurate. To the extent that the loss functions associated with forecast errors are explicitly considered, the usual assumption is that the loss function is symmetric and often that it is quadratic.' This leads to an emphasis on unbiased predictors. Alternatively, maximum likelihood procedures may be used, implying that a forecast should have a high probability of being (approximately) correct. In practice, the users of forecasts are seldom interested in either an unbiased or a most likely forecast. Instead, a correction usually is added to or subtracted from the forecast to implicitly allow for an intuitively felt asymmetry in the costs of positive and negative forecast errors. As planning and decision models have become more structured, it is frequently possible to objectively include these adjustments or safety factors in the model by formally introducing some measure of forecast uncertainty. Therefore, more and more forecasts are being given as probability distributions rather than as point predictions [4], [ 5 ] , [ 6 ] .In some cases, planning and decision models can directly incorporate these probability distributions by using payoff tables or decision trees. In other cases, the forecast variable is quantitative, and the asymmetric loss function can be made an integral part of the statistical analysis [l]. Since a substantial forecasting methodology already exists based on symmetric loss functions, it is far more practical to consider ways of adjusting these forecasts through correction For example see [7, p. 161. 425

show abstract

Best Estimate Forecasting—A Better Alternative

Kierulff¹

1972

California Management Review

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Probabilistic Forecasting for Contractors

Cited by 3 publications

References 0 publications

Optimal Planning: The Use of Sales Forecasts

Optimal Planning: The Use of Sales Forecasts

Fixed Sum Losses in Operational Forecasting

Best Estimate Forecasting—A Better Alternative

Contact Info

Product

Resources

About