Judgmental Forecasts

Judgmental forecasting methods incorporate intuitive judgments, opinions and subjective probability estimates.

Personal Insight

This type of forecast is created by taking an industry expert’s opinion relying solely on their opinion, bias, mood and personal judgment. Although this method is very flexible and widely used, it is unreliable.

Panel Consensus

Forecast is formed from taking the opinions of several industry experts through an open panel discussion. Although this method is a bit more reliable since it involves a group of experts but there are still some things to beware of. In some cases, some panels may not work well together due to personality traits. There may be difficulty in getting the panel to discuss openly and combine their different views into a non-bias, non-partial consensus so you should be cautious when you use this method.

Market Surveys

Survey methodology studies the sampling of individual units from a population and the associated survey data collection techniques, such as questionnaire construction and methods for improving the number and accuracy of responses to surveys.

Forecast based on data collected from a representative sample of your customers or potential customers through analysis of their views. This tends to get good results but is time consuming and expensive. However, there are still instances when a poorly conducted market survey causes poor results due to failing of accurate customers sample, poorly worded questions, and inaccurate analysis of the data and / or invalid conclusions.

Statistical surveys are undertaken with a view towards making statistical inferences about the population being studied, and this depends strongly on the survey questions used. Polls about public opinion, public health surveys, market research surveys, government surveys and censuses are all examples of quantitative research that use contemporary survey methodology to answer questions about a population. Although censuses do not include a “sample”, they do include other aspects of survey methodology, like questionnaires, interviewers, and nonresponse follow-up techniques. Surveys provide important information for all kinds of public information and research fields, e.g., marketing research, psychology, health professionals and sociology.

Scenario Analysis

Scenario analysis is a process of analyzing possible future events by considering alternative possible outcomes (sometimes called “alternative worlds”). Thus, the scenario analysis, which is a main method of projections, does not try to show one exact picture of the future. Instead, it presents consciously several alternative future developments. Consequently, a scope of possible future outcomes is observable. Not only are the outcomes observable, also the development paths leading to the outcomes. In contrast to prognoses, the scenario analysis is not using extrapolation of the past. It does not rely on historical data and does not expect past observations to be still valid in the future. Instead, it tries to consider possible developments and turning points, which may only be connected to the past. In short, several scenarios are demonstrated in a scenario analysis to show possible future outcomes. It is useful to generate a combination of an optimistic, a pessimistic, and a most likely scenario. Although highly discussed, experience has shown that around three scenarios are most appropriate for further discussion and selection. More scenarios could make the analysis unclear.

Forecast by Analogy or Historical Analogy

Forecast based on analyzing the product life cycle and the demands of similar past products with the assumption that it follows similar patterns. It is often difficult to locate recently introduced products that share similar product life-cycle traits and characters.

Forecast by analogy is a forecasting method that assumes that two different kinds of phenomena share the same model of behaviour. For example, one way to predict the sales of a new product is to choose an existing product which “looks like” the new product in terms of the expected demand pattern for sales of the product.

Used with care, an analogy is a form of scientific model that can be used to analyze and explain the behavior of other phenomena. According some experts, research has shown that the careful application of analogies improves the accuracy of the forecast.

Delphi Method

The Delphi method is a structured communication technique, originally developed as a systematic, interactive forecasting method which relies on a panel of experts. The experts answer questionnaires in two or more rounds. After each round, a facilitator provides an anonymous summary of the experts’ forecasts from the previous round as well as the reasons they provided for their judgments. Thus, experts are encouraged to revise their earlier answers in light of the replies of other members of their panel. It is believed that during this process the range of the answers will decrease and the group will converge towards the “correct” answer. Finally, the process is stopped after a pre-defined stop criterion (e.g. number of rounds, achievement of consensus, stability of results) and the mean or median scores of the final rounds determine the results.

The anonymous aggregated responses are shared after each round to allow them to adjust their answers in subsequent rounds until they are able to reach their final response through consensus. As in most judgmental forecasting, the Delphi method also has it difficulties. The time required to complete this method is long and finding the right mix of industry experts and keeping them involved throughout the product life-cycle is hard.

Delphi is based on the principle that forecasts (or decisions) from a structured group of individuals are more accurate than those from unstructured groups. The technique can also be adapted for use in face-to-face meetings, and is then called mini-Delphi or Estimate-Talk-Estimate (ETE). Delphi has been widely used for business forecasting and has certain advantages over another structured forecasting approach, prediction markets.

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The Delphi Method communication structure

Key characteristics – The following key characteristics of the Delphi method help the participants to focus on the issues at hand and separate Delphi from other methodologies

  • Anonymity of the participants – Usually all participants remains anonymous. Their identity is not revealed, even after the completion of the final report. This prevents the authority, personality, or reputation of some participants from dominating others in the process. Arguably, it also frees participants (to some extent) from their personal biases, minimizes the “bandwagon effect” or “halo effect”, allows free expression of opinions, encourages open critique, and facilitates admission of errors when revising earlier judgments.
  • Structuring of information flow – The initial contributions from the experts are collected in the form of answers to questionnaires and their comments to these answers. The panel director controls the interactions among the participants by processing the information and filtering out irrelevant content. This avoids the negative effects of face-to-face panel discussions and solves the usual problems of group dynamics.
  • Regular feedback – Participants comment on their own forecasts, the responses of others and on the progress of the panel as a whole. At any moment they can revise their earlier statements. While in regular group meetings participants tend to stick to previously stated opinions and often conform too much to the group leader; the Delphi method prevents it.
  • Role of the facilitator – The person coordinating the Delphi method is usually known as a facilitator or Leader, and facilitates the responses of their panel of experts, who are selected for a reason, usually that they hold knowledge on an opinion or view. The facilitator sends out questionnaires, surveys etc. and if the panel of experts accept, they follow instructions and present their views. Responses are collected and analyzed, then common and conflicting viewpoints are identified. If consensus is not reached, the process continues through thesis and antithesis, to gradually work towards synthesis, and building consensus.
Methods of Forecasting
Time Series

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