Bringing judgment into combination forecasts

Abstract This research investigates the benefits in forecast accuracy by combining judgmental forecasts with those generated by statistical models. Our study differs from prior research efforts in this area along two important dimensions. First, two different types of judgmental forecasts are evaluated for combination with statistical forecasts — one based on contextual knowledge and one based on technical knowledge. Contextual knowledge is information gained through experience on the job with the specific time series and products being forecasted. Technical knowledge is information gained from education on formal forecasting models and data analysis. Second, we investigate the conditions under which adding judgment to combination forecasts helps the most. Specifically, we test the improvement as a function of time series variability. Our results show that judgmental forecasts based on contextual knowledge, rather than technical knowledge, are the better input into combination forecasts. Bringing judgmental forecasts based on contextual knowledge into combination forecast improves forecast accuracy over the individual statistical and judgmental forecasts. However, the benefit attained from including contextual knowledge in the combination depends on the amount of inherent variability in the time series being forecast. More contextual knowledge is needed for combination forecasts if a time series has more data variability. If the amount of variability is low, less emphasis should be given to contextual knowledge when making combination forecasts. In general, our findings suggest a linear relationship between the amount of contextual knowledge needed and data variability.

[1]  N. Sanders,et al.  Forecasting Practices in US Corporations: Survey Results , 1994 .

[2]  Robert E. Machol,et al.  Principles of Operations Research---9. The Hawthorne Effect , 1975 .

[3]  Steven P. Schnaars,et al.  The Accuracy of Business Week's Industry Outlook Survey , 1988 .

[4]  Fred Collopy,et al.  Rule-Based Forecasting: Development and Validation of an Expert Systems Approach to Combining Time Series Extrapolations , 1992 .

[5]  Larry P. Ritzman,et al.  Some Empirical Findings on Short-Term Forecasting: Technique Complexity and Combinations , 1989 .

[6]  Robert L. Winkler,et al.  The accuracy of extrapolation (time series) methods: Results of a forecasting competition , 1982 .

[7]  Larry P. Ritzman,et al.  The need for contextual and technical knowledge in judgmental forecasting , 1992 .

[8]  Ronald Dattero,et al.  Combining vector forecasts to predict thoroughbred horse race outcomes , 1992 .

[9]  R. L. Winkler,et al.  Averages of Forecasts: Some Empirical Results , 1983 .

[10]  Everett E. Adam,et al.  Forecasting error evaluation in material requirements planning (MRP) production-inventory systems , 1986 .

[11]  E. S. Gardner,et al.  FORECASTING WITH EXPONENTIAL SMOOTHING: SOME GUIDELINES FOR MODEL SELECTION , 1980 .

[12]  R. Clemen.  Combining forecasts: A review and annotated bibliography , 1989 .

[13]  J. Sparkes,et al.  Awareness and use of forecasting techniques in british industry , 1984 .

[14]  R. H. Edmundson,et al.  The accuracy of combining judgemental and statistical forecasts , 1986 .

[15]  D. Bunn,et al.  Interaction of judgemental and statistical forecasting methods: issues & , 1991 .

[16]  Pam Angus-Leppan,et al.  The Forecasting Accuracy of Trainee Accountants Using Judgemental and Statistical Techniques , 1986 .

[17]  Robert J. Genetski,et al.  Long-Range Forecasting: From Crystal Ball to Computer , 1981 .

[18]  Andrew Zardecki,et al.  Rule-Based Forecasting , 1996 .

[19]  Robert C. Blattberg,et al.  Database Models And Managerial Intuition: 50% Model + 50% Manager , 1990 .

[20]  Spyros Makridakis,et al.  Forecasting and Planning: An Evaluation , 1981 .

[21]  George Foster,et al.  Security analyst multi-year earnings forecasts and the capital market , 1985 .

[22]  Wilpen L. Gorr,et al.  ACCURACY OF JUDGMENTAL FORECASTING OF TIME SERIES , 1985 .

[23]  J. Armstrong.  Research Needs in Forecasting , 1988 .

[24]  John T. Mentzer,et al.  Familiarity, application, and performance of sales forecasting techniques , 1984 .

[25]  Marcus O'Connor,et al.  The use of non‐time series information in sales forecasting: A case study , 1988 .

[26]  Douglas J. Dalrymple.  Sales forecasting practices: Results from a United States survey , 1987 .

[27]  R. L. Winkler,et al.  The Combination of Forecasts , 1983 .

[28]  Marcus O'Connor,et al.  An examination of the accuracy of judgmental extrapolation of time series , 1985 .

[29]  C. B. Tilanus,et al.  Applied Economic Forecasting , 1966 .

[30]  Robert Carbone,et al.  Comparing for Different Time Series Methods the Value of Technical Expertise Individualized Analysis, and Judgmental Adjustment , 1983 .

[31]  Robert H. Ashton,et al.  Aggregating Subjective Forecasts: Some Empirical Results , 1985 .