The VP from our group sent me the announcement of a webinar organised by The Conference Board of Canada with Tom Malone as speaker on October 27th with the question if I was interested. Absolutely! So that’s what I did last week: I listened to the webinar (although I missed the first 12 minutes due to technical issues). I read Malone’s “The Future of Work” long time ago, but this presentation was based on a new study about Collective Intelligence.
Malone studied the building blocks of Collective Intelligence. He calls them “genes”, which sounded awkward because I missed the introduction of the presentation and thus the explanation of the use of “gene”. I needed the slides, sent afterwards, to fill in the gaps from the introduction.
- What is being done? (Strategy)
- Who is doing it? (Staffing)
- Why are they doing it? (Incentives)
- How is it being done? (Structure, Process)
What? There are two genes here: create and decide. Creation of a Wikipedia entry, software code (Linus), t-shirt design (Threadless) and decide means the evaluation and selection among alternatives, like which t-shirt will be produced in Threadless.
Who? The staffing of the activities can be categorized into two genes: hierarchy and crowd. Linux, for example has Linus Torvalds and a few others who makes decisions. In the crowd mode it can be done by anybody involved, as is the case with voting and submitting reviews on Amazon.
Why? The motivation of why people participate can be divided into three genes: money, love and glory. Money can be a motivator, obviously, but more often there is no money involved (or even available). Love means being motivated because it gives opportunities to socialize, or comes from enjoyment of the activity (someone is intrinsically motivated) or to contribute to a larger cause. Glory or recognition is the third motivator and comes from the desire to be recognized by peers. Interesting quote: “Failure to get motivational factors right is probably the single greatest cause of failure in collective intelligence experiments”.
How? Here a matrix of four cells is created with the “what” genes (create or decide) and the way the crowd operates (dependent or independent): collection, collaboration, individual decision, group decision. Collection works when activities can be broken down and worked on independently. Contest is a subset of collection, when there is a winner involved and works when only one solution is needed. Collaboration is a good choice when pieces are being created that have importance dependencies to a larger whole. Group decisions can be split into three subsets: voting, consensus and prediction markets. The examples in this case reminded me of “The wisdom of crowds” by James Surowiecki where the collective wisdom outperforms the decisions of individuals. The last gene is individual decision. Members of the crowd make decisions that are individual, with information from the crowd. Amazon’s individual buyers decide to buy a certain book, based on customers’ reviews. It’s their own choice to buy or not. Two subsets here: markets and social networks. In markets there is money involved in decision making. Amazon and eBay are examples. Social networks give people who are related in some form of network, information and opinions that they can use for their individual decisions. Blogs are an example here.
So, what does this mean for managers? Innovations in the coming decade, according to Malone will not come from technologies. New ways of organizing work are needed, which are made possible by new technologies. Managers need to prepare for this and the framework presented in this webinar can help.
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