Our bread and butter working with clients is organizing their employees to participate in crowdsourcing exercises. Recently we have been approached more to help get forecasts from external crowds, either to support research projects, or to better understand what outside experts or customers think.
In more than 10 years of working with large companies on building prediction markets and other crowdsourced forecasting mechanisms, we’ve seen one common thread with the projects that are unsuccessful. Project owners overestimate the technology, and underestimate what it takes to engage people to make the technology successful. Avoid these 5 pitfalls to improve the success of your Cultivate Forecasts prediction market.
So, you asked a prediction market question, and the outcome is now known. The question has been resolved and winnings have been disbursed to the forecasters who held winning positions. Forecasters know how well they did based upon their profits in the question, and you know who your good forecasters were too. But how accurate was your organization at answering the question itself? There are several things to consider when thinking about accuracy of the prediction market:
A multinational energy company uses Cultivate Forecasts predict economic and geopolitical events that impact oil and gas prices. We find out why they decided to incorporate internal crowdsourcing within their business and how they have been so successful at engaging employee participation.
Two key take-aways from the emerging scandal surrounding Daily Fantasy sites: one, gambling data can be extremely valuable, and two: the only thing Americans love more than gambling is hating on gambling. Taken together, these findings illustrate why large-scale prediction markets present a path towards improving human knowledge in a wide range of topics.