Whenever we are stuck with a difficult problem in school or at work, our common first reaction would be to ask a friend or colleague for help. When we do that, we are actually tapping on collective intelligence – the technical, economic, legal, and human enhancement of a universally distributed intelligence that will unleash a positive dynamic of recognition and skills mobilization (Levy, 1997) – to help us solve daily issues. This is in a way crowd sourcing at the most basic level.
The article “The Collective Intelligence Genome” (Malone, Laubacher and Dellarocas, 2010) propagates that to build exactly the kind of complex intelligence system that will accomplish an organization’s desired job, managers have to ask four main questions: “What? Who? Why? How?” The answers to these 4 questions will eventually define the “genes”, or the core building blocks of collective intelligence, and these genes when appropriately combined and recombined with one another under suitable conditions would then successfully and sustainably allow companies to design a system that will harness collective intelligence in a way that will meet their needs.
Another perspective on how companies can strategies their crowdsourcing efforts comes from the article “Which type of collaboration is right for you?” (Pisano and Verganti, 2008). By combining participation factors (open/closed) with governance factors (flat/hierarchical), the article presents four basic modes of collaboration and companies can figure out which mode is most appropriate by being focused on their organizational strategy and considering the trade-offs of each mode.
The last article “Prediction Markets: A new tool for strategic decision making” highlights how companies can leverage on the masses to achieve strategic decisions in times of uncertainty through an emerging tool called prediction markets. The article favors prediction markets over current practice due to its advantages in theoretical foundation, empirical evidence, and credibility/defensibility. However, it also highlights limitations that might arise through prediction markets such as predictive errors, manipulation and problematic long-term forecasting (Borison and Hamm, 2010).
One example of an organization from the private sector which has achieved the right permutation of “open, closed, flat, and hierarchical” (Pisano and Verganti, 2008) is Quirky – a New York City based invention company that crowdsources its product ideas from people all over the world before selling the winning products online or through partner retail stores like Target and Best Buy (Forbes, 2013). On the other hand, in the non-profit sector, we can see how crowdsourcing can also be a useful tool to aid in disaster relief. One example would be how volunteer organizations in Guinea and Sierra Leona have used open-mapping to help them efficiently locate Ebola-infected victims in rural areas (Reuters, 2014).
In conclusion, there is no doubt that there are many benefits to crowdsourcing such as reach, speed, low cost, flexibility and efficiency. Yet, organizations also need to be aware of the various limitations that come with this tool such as uncertainty, data inaccuracy, ethical issues and security threats, and understand when and how best to use it, so as to achieve the results they are looking for.
References:
Borison, A., and Hamm, G. 2010. Prediction markets: A new tool for strategic decision making. California Management Review 52(4) 125-141
“Can A Crowdsourcing Invention Company Become ‘The Best Retailer In The World?'” Forbes. Forbes Magazine, 27 May 2013. Web. 15 Oct. 2014.
Levy, P., 1997. Collective intelligence: mankind’s emerging world in cyberspace.
Malone, T.W., Laubacher, R., and Dellarocas, C. 2010. The collective intelligence genome. MIT Sloan Management Review 51(3) 21-31
“Online Volunteers Map Uncharted Ebola Zones to Help save Lives.” Trust.Org, 23 Sept. 2014. Web. 16 Oct. 2014.
Pisano, G.P., and Verganti, R. 2008. Which kind of collaboration is right for you? Harvard Business Review 86(12) 78-86
