Q 239. Sir Francis Galton, in 1906, took more than 700 guesses from fair visitors about the weight of an Ox and the average value from guesses was found to be precise. 
 

Sometimes surveying for guessed values makes a lot of sense because the average obtained through crowd intelligence is better than individual assessments. At other times crowds provide values that are completely off the mark.
 

What are the elements to be considered before we think about relying on wisdom of the crowds? Are there any practical applications of this theory today? 

 

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1)The target crowd must have some relevance towards the  topic

2)public survey can be the tool for the same

The best example for practical application of  this is "Exit poll" results and actual results 

 

one more practice approach is Stock pricing and moment of stock direction (expert advice on stock pre-market time)

 

The exit poll is again a survey of known population /unknown population. 

but matters a lot different  when it comes to total population 

the results on whole may be wrong but trends lead to results 

 

Similarly Stock pricing opinion during pre-hours  looks like a guided projectile to movers and shakers of Stock market,

but when it comes to actual stock price the market may gain or collapse based on crowds guided decision to pull on the famous quote" buy when everyone buys and sell when everyone" sells

 

 The things to be considered when taking Wisdom of crowds are 

1) large diversity of opinion rather than fixed elements of yes, no, can't  say

2) independent opinion solution 

3) Across the population rather than concentrated crowds

4) gathering individual opinion into diversified baskets 

 

Additional to this 

 collection to be made impartially and there should be no common guided opinion like "person A say so what will you say regarding the same" it should be not guided 

With reference to Weight of Ox, Galton discovered that average guess was awfully close to the actual weight. Sporadically, it makes sense to go with guess from crowd intelligence, specifically when there is no scale, or when the measurement is expensive or when it is time-consuming for accurate measurement.

 

Few considerations and points to be factored before we rely on this method would include the below pointers:

• Diversity of opinion
• Independence of opinion
• Trusting the group to be fair in terms of giving the opinion
• Should be cautious of Groupthink
• Consideration on activity time
• Distribution of expert panel is important to avoid dominance and skewness
• Diffusion of responsibility 

We still use similar versions of Wisdom of Crowds in organizations.
 

Ref 1: When we do Story Point Estimation in Agile development
During development, it is critical and vital to plan budget, time and resource required to complete the module in every sprint. Entire project is broken into different levels and function point analysis and story points is assigned to each user stories.
Story point estimation gives rough estimation (more like a guess) for the product backlog items with relative sizing. This is a comparative analysis. Key estimators include developers, testers, scrum master, product owner and other related stake holders.

 

Some of the common estimating methods are

• T – shirt Sizing
• Using Fibonacci Series
• Animal Sizing

Typical measures used in T – shirt sizing comprise XS, S, M, L, XL, XXL; In Fibonacci sequence measures includes numerical 1,2,3,5,8,13,21,34,55, etc.; In Animal Sizing team uses Ant, bee, cat, dog, lion, horse, elephant, etc. It’s fun to use animals instead of numbers
Based on the efforts required, points are assigned for the stories during planning.
Quick and effective way of using crowd intelligence while doing story point estimation.

 

Ref 2: Delphi interview technique
This method relies on expert panels decision, considering opinion from experts more like that of getting crowd intelligence in wisdom of crowd

 

Ref 3: Group Decision Support System (GDSS)
Many organizations use this method for idea generation, to select optimal solution, for voting and so on. By using this technique, it easy to arrive at solution for complex problems

 

Other effective methods and applications includes below,

• Brain storming
• Nominal group technique
• Devil’s advocacy
• Fish bowling
• Didactic interaction 

Closing quotes to go with Wisdom of Crowd.

Quote

None of us is as smart as all of us - Ken Blanchard

 

The Wisdom of Crowds implies the  amalgamation of information/ideas/guesses in groups, that are regarded as better, compared to that could have been put forward by any particular member belonging to that group. The theory came into existence with Francis Galton’s discovery that a crowd of a particular country together  did  a much better guess of the weight of an ox, when their guesses were averaged, in comparison to the guess of all the members taken individually

 The advantages of wisdom of crowd is attributed to be due to following factors:

Cognition: Individual thinking and opining are much faster compared to the contemplation of  experts or expert committees, which offer many a times biased decision, out of each other’s influence or under external influence.

Diversity of opinion

Independent opinions: Not influenced by other’s opinion

Decentralisation:  drawing opinion on local knowledge

Aggregation: Assembling all individual decisions and leading to a collective decision

Trust: Every person has a trust on collective  group and respects  it's decision.

 

 The reasons  for failure of  wisdom of crowd and strategies to combat:

 

1.  Homogeneity/Lack of diversity: There has to be enough diversity to generate much of variance in thought process and private information

2.     Centralization: The opinion must be derived from local knowledge, rather than a centralized controlling factor.

3.     Division/Lack of dissemination of information: There needs to be free flow of information from one subdivision to another, lack of which can lead to failures, such as in 9/11 attack, lack of information from one to another subdivision led to failure of intelligence in prevention of such attacks.  On the contrary, free flow of research information on SARS virus and its isolation, without any  central control led to better curb on viral infection.

4.     Imitation: The focus should be to make right  decisions  based on the current choices, rather than looking for any similar kind of decisions in the past and  imitating it.

5.     Emotionality: Emotional factors , such as togetherness can lead to peer pressure  and members get influenced by each other and create collective hysteria. So the members should be divergent, without significant peer pressure.

 Application of Wisdom of Crowd in real world:

Prediction markets: one of the most common application is that of prediction market, which creates speculative or betting markets, based on common questions, such as “who  do you think, will win the polls’’. The current market values are indicators of probability of the event. The best example is Betfair, which is world’s biggest prediction exchange, with a very high trade volume, based on collective prediction. Many web based quasi-prediction market companies make use of this phenomenon to offer predictions based on things like  sporting events, stock market etc. Prediction marketing  principle is also  being used in project management software to enable the team members to predict it’s real time deadline and probable budget.

Delphi methods: The Delphi method  is a kind of  planned and  interactive decision, based on a panel of independent experts. The selected  experts , answers  questionnaires in few rounds.   After each round, a  moderator provides summary of all the expert opinions. The participants are encouraged to modify their answers, in light of other answers. The range of answers decrease in the process and lead to convergence towards correct  and better answer compared to individual answers.

Human Swarming: It is enabled using software such as  UNU collective intelligence platforms, in which groups of networked users can collectively respond to questions, generate ideas and make collective predictions. Studies have shown that human  swarms perform better than individuals across a number of real-world predictions. 

 Stock Markets:  Wisdom of crowd aspect of stock markets enables decision makers (e.g. firms’ managers, capital providers, regulators, or central bankers)  to use stock markets and their own information for a large  scale predictive market. 

 

While all published answers are appropriate, the two winners for today are Shashikant Adlakha and Mohamed Asif as both have provided very good examples.