This document discusses qualitative forecasting techniques, including when to use them, methods like expert opinion, the Delphi method, and scenario writing. It also covers challenges like judgment biases and conventional wisdom that can impact qualitative forecasts. When presenting forecasts to management, it recommends including the forecasting model, choices made, error terms, and conclusions with caveats.

1. QUALITATIVE FORECASTING
TECHNIQUES
DR. ROHIT VISHAL KUMAR
INTERNATIONAL MANAGEMENT INSTITUTE
BHUBANESWAR

2. WHEN TO APPLY QUALITATIVE FORECASTING TECHNIQUES?
• Data as a historical series is not available or is not relevant to the future
• An unusual product / project is being planned [Never Done Before]
• There are numerous variables which will affect the project
• The life of the project is longer than safe exploration of the time series
• Experts are available and consultable

3. FORECAST FROM EXPERT OPINION
• Creation of “Reference Population” or “Survey Group”
• Data can be gathered by phone or in writing.
• Data comes in three categories:
• Highly valuable
• Absolutely essential
• Supporting material
• The data collected is passed on to the “Jury Group”

4. FORECAST FROM EXPERT OPINION
• Jury of executive opinion:
• Consist of people who are experts and will be using the data in some way or the other
• Experts debate the data
• They draw upon their collective wisdom to map out future events
• These discussions are carried out in open meeting
• May be subject to the drawbacks of group think and personality dominance.

5. FORECAST FROM DELPHI METHOD
• Used to overcome the demerits of group think and personality dominance
• It has four key features
• Anonymity
• Iteration
• Controlled Feedback
• Aggregation
• Multiple Group evaluation stages:
• Round 1: Experts reply in writing to the questions posed by the investigating team
• Round 2: The investigating team summarizes comments of the participants and then mails them back to
the experts
• Round 3: Participants read the reactions of the others and either defend their original view or modify their
point of view based on the feedback
• The process continues till a consensus emerges

6. FORECAST FROM DELPHI METHOD
• The first round of the Delphi process are mostly unstructured
• This allows the experts to freely identify and comment on the issues that they see important
• The investigating team then tries to put the issues in a structured set of questions
• Initially in qualitative manner
• Subsequently in quantitative manner
• Different challenge methods can be used:
• The Nominal Group Technique is a face to face Delphi method, allowing group discussion.
• The Devils Advocate method poses sub-groups to question the group’s findings.
• The Dialectical Inquiry method poses sub-groups to challenge the group’s findings with alternative
scenarios.
• It has been seen that accuracy tends to increase over successive iterations
• Accuracy also depends on various factors
• Initial set of questions asked
• The Experts selected

7. FORECAST FROM SCENARIO WRITING
• Scenario Writing involves defining the particulars of an uncertain future by writing a “script”
for the environment of an organisation over many years in the future
• New Technology, Population Shifts and Changing consumer demands are among the factors that are
considered and woven into this specialization to provoke thinking of top management
• The most likely scenario is usually written down
• Can also be followed by a discussion phase

8. CHALLENGES: JUDGEMENT BIAS
• Inconsistency:
• Being unable to employ the same decision criteria in similar situation
• Conservatism:
• Failing to change (or change slowly) one’s own mind in light of new evidence
• Recency:
• Having the most recent effect dominate the effects of the past
• Availability:
• Relying upon specific events easily recalled from memory to the exclusion of other pertinent information
• Anchoring:
• Being unduly influenced by initial information which is given more weight in forecasting process
• Illusory Correlation:
• Believing that patterns are evident or causal relation exist when it does not

9. CHALLENGES: JUDGEMENT BIAS
• Search for Supportive Evidence:
• Gathering facts which lead to certain conclusion and disregarding others
• Regression Effect:
• Failing back to average
• Attribution of Success or Failure:
• Believing that success is a result of one’s skills and failure is due to bad luck
• Optimistic Thinking:
• If people think good things will happen to them they tend to give above average estimates
• Underestimating Uncertainty:
• Thinking that past bad performance was a one-off process
• Selective Perception:
• Seeing problems in terms of one owns background and experience

10. CHALLENGES: CONVENTIONAL WISDOM
• The more information we have; the more accurate the decision
• We can distinguish between useful and irrelevant information
• The more confident we are about the correctness of our decisions; the more accurate will
our results be
• We can take decisions rationally
• Monetary rewards and punishments contribute to better performance
• We can assess our chances of success and failure reasonably well
• Experience or Expertise increases the accuracy of the decision
• We know what we want – our preferences are stable

11. PRESENTING FORECAST TO MANAGEMENT
• Why is the forecast needed?
• Who will use the forecast?
• What is the goal that is being achieved by using this forecast?
• What is the management perspective?
• While preparing a report it is always a good practice to report the following:
• The model in the simplified form
• The rational for the choice of the model
• The Error Terms (One Absolute and One Relative)
• Thiel's’ U [if possible] and it’s interpretation
• R2, AIC, BIC and their interpretation
• The forecasted value and the prediction interval [ 𝐹𝑡+1 ± 1.96 𝑀𝑆𝐸 ]
• Conclusions and Caveats

12. THANK YOU
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