Jury of executive opinion

Jury of executive opinion

A method of forecasting using a composite forecast prepared by a number of individual experts. The experts form their own opinions initially from the data given, and revise their opinions according to the others' opinions. Finally, the individuals' final opinions are combined.

Jury of Executive Opinion

A way to forecast future trends in which one gathers the opinions of a number of known experts on a security or other matter at hand. The members of the jury perform their initial assessments on their own, then review each other's work, revising their own estimates as needed. The jury of executive opinion is useful because it provides a sort of peer review to point out errors in a non-adversarial way. See also: Consensus opinion.
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Additionally, the present study revealed that the Jury of Executive Opinion, the Naive method, ARIMA, the Delphi method and Text Mining are the five least important methods for job applicants to know.
Deviation t-ratio Moving Average (**) 4.20 .866 18.39 Linear Regression Trends (**) 4.07 .971 14.64 How to Combine Forecasts (**) 4.06 .973 14.49 Simple Exponential Smoothing (**) 3.88 .954 12.20 Data Mining (**) 3.87 .938 12.29 Time Series Decomposition (**) 3.66 1.098 7.89 Causal Multiple Regression (**) 3.64 1.027 8.22 Holt's Exponential Smoothing (**) 3.49 1.060 6.03 Sales Force Composite (**) 3.44 .972 5.84 Winters' Exponential Smoothing (**) 3.43 1.111 5.09 Jury of Executive Opinion (**) 3.34 .991 4.40 Naive Method (**) 3.33 1.062 4.03 ARIMA (**) 3.16 1.036 2.07 Delphi 3.07 .899 0.95 Text Mining 2.91 .987 -1.18 (*) Scale 1 to 5 with higher values representing greater importance.
Nevertheless, how important is it for job applicants to know each of the following forecasting techniques (scaling from "very unimportant" to "very important" on a 5-point scale)?: ARIMA (Box Jenkins) (1) Causal Multiple Regression (2) Data Mining (3) Delphi method (4) Holt's exponential smoothing (5) How to combine forecasts (6) Jury of executive opinions (7) Linear regression trends (8) Moving averages (9) Naive method (10) Sales force composite (11) Simple exponential smoothing (12) Text Mining (13) Time series decomposition (14) Winters' exponential smoothing (15) Other: (16)
Q21 Given the menu of forecasting techniques below, how knowledgeable are you about each technique (scaling from "not at all knowledgeable (1)" to "very knowledgeable (5)" on a 5-point scale)?: ARIMA (Box Jenkins) (1) Causal Multiple Regression (2) Data Mining (3) Delphi method (4) Holt's exponential smoothing (5) How to combine forecasts (6) Jury of executive opinions (7) Linear regression trends (8) Moving averages (9) Naive method (10) Sales force composite (11) Simple exponential smoothing (12) Text Mining (13) Time series decomposition (14) Winters' exponential smoothing (15) Other: (16)
He begins with discussion of process and structure issues of new product forecasting and then moves on to chapters describing managerial judgment forecasting techniques, including jury of executive opinion and Markov process models; customer/market research techniques such as concept tests and conjoint analysis; time series data analysis on company data; and regression analysis from simple linear regression to logistic regression.
Those techniques include jury of executive opinion, sales force composite, customer expectations, decomposition, exponential smoothing, moving average, regression analysis, simulation, straight-line projection, Box-Jenkins time series models, expert systems, neural networks, trend line analysis, and life cycle analysis.
The bankers commonly used the following six forecasting techniques on a regular basis for generating demand deposit forecasts: in descending order of frequency, jury of executive opinion (70.6%), straight line projection (43.1%), sales force composite (37.3%), decomposition (27.5%), simulation (23.5%), and moving average (21.6%).
It is evident that the jury of executive opinion is the most popular forecasting technique with the highest satisfaction level (88.6%).
Large banks most often deployed, in descending order of frequency, jury of executive opinion (61.1%), sales force composite (39.9), decomposition (38.9%), straight line projection (38.9%), and simulation (27.8%), whereas small banks predominantly employed jury of executive opinion (75.8%), followed by straight line projection (45.5%), sales force composite (36.4%), moving average (24.2%), decomposition (21.2%), and simulation (21.2%) (see Table 6).