What Stops Groups from Working Together Effectively – Overcoming Bias

Reading Time: 6 minutes

This is a follow up to an earlier post on The Role of Diversity in Knowledge Management. The focus of that post was directed more towards knowledge management but it was also a post about how groups collaboratively make decisions or find innovative solutions.  This is a continuation of that post.

Inhibiting Factors

An effective route to any kind of organizational initiative can be found in the application of a Force Field Analysis (FFA); a tool for systematically analyzing factors found in complex problems. The method used in FFA includes identifying the “restraining forces” or inhibiting factors preventing an initiative from moving forward. The theory is that by identifying and then systematically removing those factors or barriers to success the initiative can proceed successfully. Below are the inhibiting factors that relate to work groups or teams. By looking at each and systematically identifying and looking for ways to removing the barrier we might be able to increase the effectiveness of group decision making and solution finding.

Bias

The primary limiting factor is bias. There are many types of bias and all relate to how an individual views or perceives the world. The following list, presented as problems and solutions, includes types of bias and how to remove or prevent them from impacting the effectiveness of CI.

Problem: In-group bias – Group members favour and support the ideas presented by their own group members.

Solution: Shield group members from knowing the identity of others in the group. This is especially important at the thought generation stage where in-group bias can influence the ideas generated. In addition organizations can use technologies that allow for the inclusion of those not in the in-group.

Problem: Out-group homogeneity – We tend to view people not in our in-group as being all alike. We stereotype and think that “They are all like that”. This tendency we all have towards seeing people not like us as holding similar views can cause problems in diverse groups. Group members can unconsciously negatively or positively stereotype other group members which can influence their own ideas and alignment with others ideas. Both in-group and out-group bias relate to representativeness bias which is a heuristic (mental shortcut) we often use to place people and things into groups. The downside of these kinds of mental leaps is that grouping can prevent us from seeing unique qualities in people and the potential of their ideas.

Solution: Online groups can be diverse without triggering our out-group homogeneity by keeping the identity of group members anonymous.

Problem: Groupthink – We have a tendency toward doing what others do. This is often called the bandwagon or herd effect. This is the best case against traditional brainstorming and collective decision making in a face to face environment.

Solution: Use technology to mask the herd by eliciting thoughts and ideas without exposing participants to others thoughts or ideas.

Problem: Social Loafing – The larger the number of individuals whose work is combined on a group task, the smaller is each individuals contribution. In short we contribute less when we are working together as a group. This is true in a tug of war and studies suggest it is also true in some kinds of team work.

Solution: People are more motivated and tend to contribute more when they believe that their work is identifiable and separable from the work of others. This may seem like a bit of a conundrum. Shielded surveys works because it can make participants anonymous yet that very thing may reduce individual contribution.  There are several ways to address this. One way is to keep group input anonymous for the “brainstorm” section only. After that responses can be attributed thereby motivating people to contribute their unique and uninfluenced ideas knowing that their contributions will eventually be seen by the entire group. This option works best with groups comprised of individuals who are confident and where trust has been established. Another option is to use a facilitator role as the group eyes. Even though the entire group may not know how much each individual contributed, the facilitator will, and that can help the activity be seen as identifiable and separate.

Problem: Social Facilitation – This theory suggests that we do better at some things when we are, or believe that we are, being watched. Conversely, on tasks that are new or that we are challenged by performance gets worse when watched. Both of these situations can negatively impact participation in face to face sessions. People will tend to over participate in generating common knowledge and under participate in generating new knowledge or presenting novel ideas.

Solution: Help participants find the balance between being “watched” by a supportive facilitator and being able to struggle invisibly. This combination can support out-of-the-box and professionally riskier ideas and potential solutions.

Problem: Group Polarization – When brought together to discuss a problem or possible decisions some groups can end up taking more extreme positions than they had begun with. People often dig in on a stance and any discussion just causes them to dig in more or become more supportive of one idea over another. Believing in one view over another in not in itself a problem; the problem occurs when it causes people to become so fixed that they become blind to other perspectives. Part of the reason for this is that when people have to verbally defend a position the act of defending causes them to believe even more strongly in that position. In effect they are convincing themselves as they try to convince others. Another related problem with this is that some people are perceived as more knowledgeable or more powerful or they may be more charismatic and have expert communication skills. None of these attributes ensure that the idea they are presenting is the best one. Indeed the best solution or idea may be held by someone who does not have the capacity in a face to face group to push their agenda forward. The net result of group polarization can be a decision that is riskier than hoped for or needed.

Solution: Take steps to manage discussion by using a neutral facilitator and with groups where there is a history or concern that polarization will occur make the process anonymous and/or allow discussion to take place asynchronously greatly lessening the likelihood of polarization. In addition facilitators can level the field by reframing individuals thoughts and ideas into one voice (theme the individual responses into groups of responses) so that it is the thought, the idea, that is judged and not the strength of the person advocating for it.

Problem: Risky Shift – Overall groups tend towards making riskier decisions. This is sometimes seen in mob behaviour where individuals often act of character doing things they would never consider doing as individuals. Some of the theories supporting this include the notion that individuals who tend toward risk taking are more persuasive and that there is cultural value in risk taking.

Solution: Minimize the influence risk takers have on a group by anonymous and/or asynchronous interactions. This may help Individuals from getting caught up in the moment and making decisions or choices too quickly. In short, give people time to think and reflect.

Problem: Common Knowledge Effect – This is more colloquially referred to as common sense. Common sense suggests that world is flat. Researchers have found that teams tend to focus on shared, “in common” information, when making decisions.  If most of the team members “know” something, that knowledge is seen as more valid than information or knowledge held by fewer group or team members. The result is that unique information is not shared and when it is it is often ignored. Social science research suggests that the reason for this is that sociality trumps effectiveness. As innately social creatures we actively and unconsciously seek similarities when we meet others. When we are first introduced to someone we usually try to find something that ties us together in a social bond. Once we find a common interest or viewpoint we tend to hold on to that as a way of cementing the relationship. This occurs more often when there is increased value in the maintaining the relationship.

Solution: The influences that cause group members to default to social beings invested in relationship building at the expense of critical decision making and solution finding can be minimized by using technology and facilitated processes so that uncommon knowledge can be shared on equal footing with common knowledge and the negative influences of social bonding can be separated from the process.

Of course I’m a fan of online technology like Thoughtexchange to accomplish reduce the bias that accompanies face-to-face engagement. The platform was developed with these biases in mind so it’s no accident that Tx effectively removes, or at least reduces, these kinds of barriers.

I’m also a huge fan of of well facilitated processes and spending the time to create a healthy team but realize that that is not always possible, especially if we’re trying to include more diversity but inviting in team members for specific issues and/or shorter time frames.

What are some other ideas about reducing bias in group or team environments? What have you found that works?

 

Facebooktwittergoogle_plusredditpinterestlinkedinmailby feather

The Role of Diversity in Knowledge Management

Reading Time: 6 minutes

How do we incorporate diversity into leadership and knowledge management practices?

What tools can we use and what do we need to believe, think and understand in order to include diverse knowledge?

I’ve been pondering question like this for quite a while. Here’s what I have found.

James Surowiecki’s book The Wisdom of Crowds (2004) talks about crowdsourcing and collective intelligence, terms that are becoming more common. Crowdsourcing is what you do to get the wisdom of crowds or collective intelligence of a group. So crowdsourcing is the action and collective intelligence is the outcome or product. In the book Surowiecki uses real life examples to present a case for using collective intelligence (CI), under certain conditions. It is these critical conditions that need to be addressed in Knowledge Management processes.

How do we optimize the affordances of CI while limiting the factors that inhibit positive CI outcomes?

Surowiecki focuses on three types of decision making problems that the use of CI can help solve. The first is what he calls cognition problems, defining these as “problems that have or will have definitive solutions” (p.XVII). The theory is that these types of problems are best answered by a diverse crowd rather than a group of experts.

Cognition problems

It’s important to repeat that the theory only applies if certain conditions are met. With cognition problems the conditions vary in importance based on the specific problem. For example if you were to crowdsource the answer to “Who will win the next local election?” you would want a diverse group of people who were also familiar with that locale. Increasing diversity by including people who lived elsewhere would not improve the likelihood of a better than average outcome and would most likely result in a response that was worse than a group of political experts.

Coordination problems

The second type of problem that can positively impacted by CI are coordination problems. Like the name implies, coordination problems involve attempts to coordinate behaviours. An example of coordination problem would be, “Where and when should we meet for coffee?”. Like cognition problems, conditions apply and ensuring a crowd with the right balance of local knowledge and diverse perspectives is key. In this case the ability to aggregate or pull together and sort the collective intelligence is also required. Technology can help with this.

Cooperation problems

The third type of problem is a cooperation problem. Cooperation involves organizing individuals’ self-interested action in a way that creates mutual advantage. Cooperation moves us from doing what is best for me as an individual entity to doing what is best for us. Examples of cooperation problems include “How can we get coffee exporters to move toward higher standards of worker treatment and pay?” or “How can we balance the need for safe neighbourhoods with the need for harm reduction measures?”.

Cooperation problems are often complex rather than complicated; complicated being something that has a right answer. Putting a car engine together is complicated while complexity involves multiple ways of putting things together with many potential workable outcomes. Cooperation problems are in essence what the Club of Rome identified decades ago as the types of problems that could be solved best by learning through innovation. In their second report No Limits to Learning they suggested that there are two ways we can learn –  by shock or by innovation. To learn by innovation requires anticipation of what might happen and participative solution finding.

Both of these are conditions that can be met through the use of crowdsourcing technology.

A key to solving cooperation problems involves establishing and communicating trust. As Surowiecki states, to solve cooperation problems, a group or society needs to

“be able to trust those around them, because in the absence of trust the pursuit of myopic self-interest is the only strategy that makes sense.”

Thus cooperation problems require groups to do more than in coordination problems.

In working through examples of each type of problem Surowiecki defines the overall conditions that must be met for collective intelligence to trump the decisions reached by expert groups and individuals. These condition are:

  1. diversity of opinion (each person should have some private information, even if it’s just an eccentric interpretation of the known facts).
  2. independence (people’s opinions are not determined by the opinions of those around them).
  3. decentralization (people are able to specialize and draw on local knowledge).
  4. aggregation (some mechanism exists for turning private judgments into collective decision).

In response to Surowiecki’s book, Harri Oinas-Kukkonen, Professor of information systems at the Department of Information Processing Science, University of Oulu, captures the Wisdom of Crowds approach with the following ideas:

  1. It is possible to describe how people in a group think as a whole.
  2. In some cases, groups are remarkably intelligent and are often smarter than the smartest people in them.
  3. The three conditions for a group to be intelligent are diversity, independence, and decentralization.
  4. The best decisions are a product of disagreement and contest.
  5. Too much communication can make the group as a whole less intelligent.
  6. Information aggregation functionality is needed.
  7. The right information needs to be delivered to the right people in the right place, at the right time, and in the right way.
  8. There is no need to chase the expert.

In addition to this MIT has collected a large body of research on Collective Intelligence that can be accesses via the MIT Center for Collective Intelligence. Their handbook, in wiki form, is itself an example of crowdsourcing at work. The wiki includes two areas that specifically list factors that facilitate CI and factors that inhibit CI. Let’s first take a closer look at the conditions needed for CI to be effective.

Facilitating Factors

Diversity

Scott E. Page  read Surowiecki’s book and Howard Reinhold‘s Smart Mobs and then went on to produce what some have called Wisdom of Crowds on steroids. In The Difference – How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies (2007) Page, a University of Michigan researcher in the field of complex adaptive systems, uses mathematical models, logic and frameworks to examine the power of diversity with scientific rigor. He created the Diversity Prediction Theorem presented in the MIT handbook. The theorem is:

Crowd Error = Average Individual Error – Diversity Among Individuals

Page presents sound arguments and scientific proof that “diversity trumps ability” under certain conditions and concludes that we should pay diversity equal attention. He suggests that to leverage diversity we need to apply the theoretical sciences of distributed and collective intelligence to the art and practice of distributed, decentralized organizations.

One of the focuses of his work is on distributed problem solving, the process of allowing a problem to be investigated by a group of people, with diverse experiential and cognitive tools, simultaneously. He suggests that distributed problem solving can be thought of as an innovation called distributed co-creation.

Page identifies the conditions that must be present within an organization so that distributed problem solving and innovation can take place.

  • There must be some sense that improvement is possible
  • The organization is currently stuck or locked into a few perspectives
  • They must believe that people with relevant perspectives and heuristics exist and
  • Those people can be accessed and encouraged to think about the organizations problem
  • The problem itself is quantifiable
  • There exists a fast, low cost way of comparing solutions
  • The act of stating the problem cannot give away valuable information including proprietary information, cost structures or other ideas that could limit ideas by priming

The bottom line on diversity, as presented by the Page, Surowiecki, and the MIT group, is:

  • Diversity trumps ability – Diverse groups with diverse tools consistently outperform groups made up of the best and brightest
  • There are times when crowds are smart and also times when crowds are not so smart
  • Individuals have particular perspectives on a problem, paying attention to some aspects and filtering out others

Specifically:

  • Learned perspectives may limit the search space any one individual uses to reach an answer, even for “smart” individuals
  • Multiple individuals with varying perspectives, experiences and cognitive tools expand the search space employed
  • A diverse crowd has more “tools” to apply

That said:

  • This is not to say that diversity does not have drawbacks
  • Diversity works if everyone has same goal of getting the answer right, and values this goal
  • If goal-related values of different groups are not shared, crowd may splinter into factions
  • A culture of collaboration and sharing increases the likelihood of successful co-creation

Edge and Ecosystem

Related to diversity but viewed through a slightly different lens are the Power of the Edge and the Power of an Ecosystem. Both describe the way in which bottom-up approaches have a positive impact on organizational decision making and innovation. The diagram below is a visual representation of how people within an organization view what’s going on outside, especially those events or shifts that may impact the organization.

Diagram

Leadership, in the middle, is often insulated by the management who may act as a filter. Staff members who exist closer to the edge of an organization can offer a perspective that is shielded and lacks clarity from a leadership perspective. Customers or clients can also offer an unobstructed view of how services or products could better meet their needs.

A perspective related to this can be found in Malcolm Gladwell’s book Outliers which features many stories of how the brilliant among us rose from a unique set of circumstances and how their unique perspectives help then rise above the crowd and how organizations can leverage that kind of talent.

Someone way smarter that me once said something about how important diversity is to the ecosystem. Biodiversity is critical in nature. I think diversity is important to all natural systems. What do you think?

Next post will be on Inhibiting Factors – What Stops Groups from Working Together Effectively

 

 

Facebooktwittergoogle_plusredditpinterestlinkedinmailby feather