DELPHI  METHOD

 

      The Delphi method is a structured communication technique, originally developed as

1.      a systematic,

2.      Interactive

3.      forecasting method

which relies on a panel of experts.

        In the standard version, 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 and the mean or median scores of the final rounds determine the results.

        Other versions, such as the Policy Delphi, have been designed for normative and explorative use, particularly in the area of social policy and public health.

        In Europe, more recent web-based experiments have used the Delphi method as a communication technique for interactive decision-making and e-democracy.

        Delphi is based on the principle that forecasts (or decisions) from a structured group of individuals are more accurate than those from unstructured groups. This has been indicated with the term "collective intelligence". 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.

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:

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 group leader, the Delphi method prevents it.

Anonymity of the participants

Usually all participants remain 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 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.

Role of the facilitator

The person coordinating the Delphi method can be known as a facilitator, 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.

Use in forecasting

First applications of the Delphi method were in the field of science and technology forecasting. The objective of the method was to combine expert opinions on likelihood and expected development time, of the particular technology, in a single indicator.

One of the first such reports, prepared in 1964 by Gordon and Helmer, assessed the direction of long-term trends in science and technology development, covering such topics as scientific breakthroughs,

1.      Population control,

2.      Automation,

3.      Space progress,

4.      War prevention and

5.      Weapon systems.

Other forecasts of technology were dealing with

1.      Vehicle-highway systems,

2.      Industrial robots,

3.      Intelligent internet,

4.      Broadband connections, and

5.      Technology in education.

        Later the Delphi method was applied in other areas, especially those related to public policy issues, such as economic trends, health and education.

        It was also applied successfully and with high accuracy in business forecasting. For example, in one case reported by Basu and Schroeder (1977), the Delphi method predicted the sales of a new product during the first two years with inaccuracy of 3–4% compared with actual sales. Quantitative methods produced errors of 10–15%, and traditional unstructured forecast methods had errors of about 20%.

        The Delphi method has also been used as a tool to implement multi-stakeholder approaches for participative policy-making in developing countries.

        The governments of Latin America and the Caribbean have successfully used the Delphi method as an open-ended public-private sector approach to identify the most urgent challenges for their regional ICT-for-development eLAC Action Plans.

        As a result, governments have widely acknowledged the value of collective intelligence from

1.      Civil society,

2.      Academic sector participants of the Delphi and

3.      Private sector participants of the Delphi, especially in a field of

4.      Rapid change, such as technology policies.

        In this sense, the Delphi method can contribute to a general appreciation of participative policy-making.

Acceptance

        Overall the track record of the Delphi method is mixed. There have been many cases when the method produced poor results. Still, some authors attribute this to poor application of the method and not to the weaknesses of the method itself.

        It must also be realized that in areas such as science and technology forecasting the degree of uncertainty is so great that exact and always correct predictions are impossible, so a high degree of error is to be expected.

        Another particular weakness of the Delphi method is that future developments are not always predicted correctly by consensus of experts. Firstly, the issue of ignorance is important. If panelists are misinformed about a topic, the use of Delphi may only add confidence to their ignorance. Secondly, sometimes unconventional thinking of amateur outsiders may be superior to expert thinking.

        One of the initial problems of the method was its inability to make complex forecasts with multiple factors.

        Potential future outcomes were usually considered as if they had no effect on each other. Later on, several extensions to the Delphi method were developed to address this problem, such as cross impact analysis, that takes into consideration the possibility that the occurrence of one event may change probabilities of other events covered in the survey.

        Still the Delphi method can be used most successfully in forecasting single scalar indicators.

        Despite these shortcomings, today the Delphi method is a widely accepted forecasting tool and has been used successfully for thousands of studies in areas varying from technology forecasting to drug abuse.

Use in policy-making

        From the 1970's, the use of the Delphi technique in public policy-making introduces a number of methodological innovations. In particular:

the need to examine several types of items

1.      forecasting items but, typically,

2.      issue items,

3.      goal items, and

4.      option items

 lead to introducing different evaluation scales which are not used in the standard Delphi.

     These often include

1.      desirability,

2.      feasibility (technical and political) and

3.      probability,

which the analysts can use to outline different scenarios:

1.      the desired scenario (from desirability),

2.      the potential scenario (from feasibility) and

3.      the expected scenario (from probability);

the complexity of the issues posed in public policy-making leads to give more importance to the arguments supporting the evaluations of the panelists; so these are often invited to list arguments for and against each option item, and sometimes they are given the possibility to suggest new items to be submitted to the panel;

for the same reason, the scaling methods, which are used to measure panel evaluations, often include more sophisticated approaches such as multi-dimensional scaling.

        Further innovations come from the use of computer-based (and later web-based) Delphi conferences.

According to Turoff and Hiltz, in computer-based Delphis:

1] the iteration structure used in the paper Delphis, which is divided into three or more discrete rounds, can be replaced by a process of continuous (roundless) interaction, enabling panelists to change their evaluations at any time;

2] the statistical group response can be updated in real-time, and shown whenever a panelist provides a new evaluation.

According to Bolognini, web-based Delphis offer two further possibilities, relevant in the context of interactive policy-making and e-democracy. These are:

A web-based communication structure (Hyperdelphi).

the involvement of a large number of participants,

the use of two or more panels representing different groups

(such as policy-makers, experts, citizens), which the administrator can give tasks reflecting their diverse roles and expertise, and make them to interact within ad hoc communication structures.

For example, the policy community members (policy-makers and experts) may interact as part of the main conference panel, while they receive inputs from a virtual community (citizens, associations etc.) involved in a side conference.

These web-based variable communication structures, which he calls Hyperdelphi (HD), are designed to make Delphi conferences "more fluid and adapted to the hypertextual and interactive nature of digital communication".

Delphi applications not aiming at consensus

        Traditionally the Delphi method has aimed at a consensus of the most probable future by iteration.

        The Policy Delphi, launched by Murray Turoff, is instead a decision support method aiming at structuring and discussing the diverse views of the preferred future.

        The Argument Delphi, developed by Osmo Kuusi, focuses on ongoing discussion and finding relevant arguments rather than focusing on the output.

        The Disaggregative Policy Delphi, developed by Petri Tapio, uses cluster analysis as a systematic tool to construct various scenarios of the future in the latest Delphi round.

The respondent's view on the probable and the preferable future are dealt with as separate cases.

Delphi vs. prediction markets

        As can be seen from the Methodology Tree of Forecasting, Delphi has characteristics similar to prediction markets as both are structured approaches that aggregate diverse opinions from groups.

        Yet, there are differences that may be decisive for their relative applicability for different problems.

        Some advantages of prediction markets derive from the possibility to provide incentives for participation.

1.      They can motivate people to participate over a long period of time and to reveal their true beliefs.

2.      They aggregate information automatically and instantly incorporate new information in the forecast.

3.      Participants do not have to be selected and recruited manually by a facilitator. They themselves decide whether to participate if they think their private information is not yet incorporated in the forecast.

        Delphi seems to have these advantages over prediction markets:

1.      Potentially quicker forecasts if experts are readily available.

Online Delphi forecasting systems

        A number of Delphi forecasts are conducted using web sites that allow the process to be conducted in Real-time Delphi. For instance, the TechCast Project uses a panel of 100 experts worldwide to forecast breakthroughs in all fields of science and technology. Further examples are several studies conducted by the Center for Futures Studies and Knowledge Management that use an online-based Delphi method.

Differences Between Oral and Written Communication

 Differences Between

Oral and Written  Communication

 

Most of us intuitively understand that there are differences between oral and written language. 

All communication includes the transfer of information from one person to another, and while the transfer of information is only the first step in the process of understanding a complex Phenomenon, it is an important first step. 

Writing is a fairly static form of transfer.  

 Speaking is a dynamic transfer of information. 

To be an effective speaker, you must exploit the dynamism of oral communication, but also learn to work within its limitations. 

 While there is a higher level of immediacy and a lower level of retention in the spoken word, a speaker has more ability to engage the audience psychologically and to use complex forms of non-verbal communication

The written language can be significantly more precise. 

Written words can be chosen with greater deliberation and thought, and a written argument can be extraordinarily sophisticated, intricate, and lengthy.  These attributes of writing are possible because the pace of involvement is controlled by both the writer and the reader. 

The writer can write and rewrite at great length, a span of time which in some cases can be measured in years.  Similarly, the reader can read quickly or slowly or even stop to think about what he or she has just read.  

More importantly, the reader always has the option of re-reading; even if that option is not exercised, its mere possibility has an effect upon a reader's understanding of a text. 

The written word appeals more to a contemplative, deliberative style.

Speeches can also be precise and indeed they ought to be. 

But precision in oral communication comes only with a great deal of preparation and compression. 

Once spoken, words cannot be retracted, although one can apologize for a mistake and improvise a clarification or qualification. 

One can read from a written text and achieve the same degree of verbal precision as written communication.  But word-for-word reading from a text is not speech-making, and in most circumstances audiences find speech-reading boring and retain very little of the information transmitted.

On the other hand, oral communication can be significantly more effective in expressing meaning to an audience. 

This distinction between precision and effectiveness is due to the extensive repertoire of signals available to the speaker: gestures, intonation, inflection, volume, pitch, pauses, movement, visual cues such as appearance, and a whole host of other ways to communicate meaning.

A speaker has significantly more control over what the listener will hear than the writer has over what the reader will read. 

For these techniques to be effective, however, the speaker needs to make sure that he or she has the audience's attention--audiences do not have the luxury of re-reading the words spoken. 

The speaker, therefore, must become a reader of the audience. 

Reading an audience is a systematic and cumulative endeavor unavailable to the writer. 

 As one speaks, the audience provides its own visual cues about whether it is finding the argument coherent, comprehensible, or interesting. 

Speakers should avoid focusing on single individuals within an audience. 

There are always some who scrunch up their faces when they disagree with a point; others will stare out the window; a few rude (but tired) persons will fall asleep.  These persons do not necessarily represent the views of the audience; much depends upon how many in the audience manifest these signals. 

By and large, one should take the head-nodders and the note-takers as signs that the audience is following one's argument. 

If these people seem to outnumber the people not paying attention, then the speech is being well-received. 

The single most important bit of evidence about the audience's attention, however, is eye contact.  If members of the audience will look back at you when you are speaking, then you have their attention.  If they look away, then your contact with the audience is probably fading.

Speeches probably cannot be sophisticated and intricate.  Few audiences have the listening ability or background to work through a difficult or complex argument, and speakers should not expect them to be able to do so. 

Many speakers fail to appreciate the difficulties of good listening, and most speakers worry about leaving out some important part of the argument.

One must be acutely aware of the tradeoff between comprehensiveness and comprehension.  Trying to put too much into a speech is probably the single most frequent error made by speakers.

This desire to "say everything" stems from the distinctive limitations of speeches:  after a speech, one cannot go back and correct errors or omissions, and such mistakes could potentially cripple the persuasiveness of a speech.

A speaker cannot allow himself or herself to fall into this mentality.  At the outset, a speaker must define an argument sharply and narrowly and must focus on only that argument.  

There are certainly implications of an argument that are important but cannot be developed within the speech. 

These aspects should be clearly acknowledged by the speaker, but deferred to a question-and-answer period, a future speech, or a reference to a work that the audience can follow-up on its own. 

Speakers must exercise tight and disciplined control over content.

As a rule of thumb, the audience will remember about one-half of what was said in a twenty-minute talk. 

After twenty-minutes, recall drops off precipitously. 

Oral arguments should therefore be parsed down as much as possible.  

There are very few circumstances in which an audience will recall a great deal of the information in a speech longer than twenty minutes.  Most evidence suggests that audience recall declines precipitously after 16 and one-half minutes.

Oral communication uses words with fewer syllables than the written language, the sentences are shorter, and self-referencing pronouns such as I are common.  

Oral communication also allows incomplete sentences if delivered properly, and many sentences will begin with "and," "but," and "except."

The upshot of these differences is that one should not think about speeches as oral presentations of a written text. 

Speeches are genuinely different from written prose, and one should not use the logic of writing as a basis for writing a speech.

Written Communication :-                                                                

1.      It is accurate and precise.        

2.      It can be repeatedly referred to.

3.      It is permanent record.

4.      It is a legal document.

5.      It facilitates the assignation of responsibilities.

6.      It has wide access.

7.      It is suitable to transmit complex information

Oral communication limitations :- 1.      Not possible for distance comm. 2.      Unsuitable for lengthy messages 3.      Messages cannot be retained 4.      No legal validity 5.      Greater chances for misunderstanding 6.      Not easy to fix responsibility

and statistical data.

8.      It is formal and authoritative.

Oral communication :-                                                          

1.      It saves time.                           

2.      It saves money.

3.      More forceful.

4.      Conveys shades of meaning.

5.      Immediate feedback.

6.      Immediate clarification.

7.      Can be informal.

8.      Good for interpersonal relationships.

9.      More effective with groups.

THE  WISDOM  OF  CROWDS

 

Types of crowd wisdom

 

• Cognition

Thinking and information Processing

Market judgment, which can be much faster, more reliable, and less subject to political forces than the deliberations of experts or expert committees.

• Coordination

Coordination of behavior includes optimizing the utilization of a popular bar and not colliding in moving traffic flows.

• Cooperation

How groups of people can form networks of trust without a central system controlling their behavior or directly enforcing their compliance. This section is especially pro free market.

Four elements required to form a wise crowd

Not all crowds (groups) are wise. Consider, for example, mobs or crazed investors in a stock market bubble.

The key criteria separate wise crowds from irrational ones:

Criteria	Description
Diversity of opinion	Each person should have private information even if it's just an eccentric interpretation of the known facts.
Independence	People's opinions aren't determined by the opinions of those around them.
Decentralization	People are able to specialize and draw on local knowledge.
Aggregation	Some mechanism exists for turning private judgments into a collective decision.

 

Failures of crowd intelligence

The crowd produces very bad judgment, and argues that in these types of situations their cognition or cooperation fail because (in one way or another) the members of the crowd are too conscious of the opinions of others and begin to emulate each other and conform rather than think differently.

Although experimental details of crowds collectively swayed by a persuasive speaker, the main reason that groups of people intellectually conform is that the system for making decisions has a systematic flaw.

What happens when the decision making environment is not set up to accept the crowd, is that the benefits of individual judgments and private information are lost and that the crowd can only do as well as its smartest member, rather than perform better.

Detailed case histories of such failures include:

Extreme	Description
Homogeneity	The need for diversity within a crowd to ensure enough variance in approach, thought process, and private information.
Centralization	The Columbia shuttle disaster, on a hierarchical NASA management bureaucracy that was totally closed to the wisdom of low-level engineers.
Division	The United States Intelligence Community, the 9/11 Commission Report claims, failed to prevent the 11 September 2001 attacks partly because information held by one subdivision was not accessible by another. The crowds (of intelligence analysts in this case) work best when they choose for themselves what to work on and what information they need. The Office of the Director of National Intelligence and the CIA have created a Wikipedia-style information sharing network called Intellipedia that will help the free flow of information to prevent such failures again.
Imitation	Where choices are visible and made in sequence, an "information cascade" can form in which only the first few decision makers gain anything by contemplating the choices available: once past decisions have become sufficiently informative, it pays for later decision makers to simply copy those around them. This can lead to fragile social outcomes.
Emotionality	Emotional factors, such as a feeling of belonging, can lead to peer pressure, herd instinct, and in extreme cases collective hysteria.

 

Connection

The question for all of us is, how can you have interaction without information cascades, without losing the independence that’s such a key factor in group intelligence?

• Keep your ties loose.
• Keep yourself exposed to as many diverse sources of information as possible.
• Make groups that range across hierarchies.