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 the last month we’ve had two potential clients, after receiving proposals from us for projects, say they needed to step back and start the projects very differently than what we had originally discussed. They just weren't ready yet, they acknowledged...
I've been watching for the last few years the announcement, long delay, then recent launch of Augur, the decentralized, blockchain-based prediction market. First off, despite it taking a long time to launch, Augur finally did, and kudos to them for doing so. Building a prediction market from scratch is not easy, building a prediction market on top of immature technology is harder, and building a prediction market to be completely decentralized with smart contracts is downright scary.
We're pairing up with Lending Club to sponsor a monthly event where
cybersecurity startups pitch their companies, and the audience gets to make
predictions on our prediction market about how they're going to do in the
next year in terms of fundraising, hiring, etc.
Everyone who has worked in corporate America has seen or used it. The traffic light metaphor for status. Red, there’s significant problems with a project. Yellow, there are some issues, but we’re going to make it. Green, all is good. Unfortunately, this system is a disaster for decision making.
We're excited to be working with Idealantis, a startup based in Hyderabad, India on a prediction market pilot about the upcoming Gujarat state elections. Working with research organization People's Pulse, Idealantis has launched this test as a precursor to a country-wide effort for the general elections coming in 2019.
Cultivate Labs CEO, Adam Siegel, recently spoke at the Institute for Business Forecasting and Planning and spent time hearing directly form attendees about the challenges they face. He shares lessons learned about the challenges sales and operations planners face in their roles, and how crowdsourced forecasting can alleviate them and improve their forecast accuracy and efficiency.
Real-money prediction markets are illegal in the U.S., but blockchain technology is giving rise to several digital currency based prediction markets based on Ethereum. Cultivate Labs defines common terminology associated with blockchain-based prediction markets.
Joining a prediction market or prediction pool can be intimidating. You may feel like you've plunged into a world of impossible questions, ongoing arguments, and have no idea where to start. You might think there's no way you could possibly add anything, or that your forecasts couldn't possible be better than anyone else's. But prediction markets don't have to be intimidating - here are four tips to get started.
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.
The future of work is changing, and your car's gas gauge is an indicator of how. In a future that will be increasingly measured, acquiring, understanding, and leveraging data in a timely fashion will determine who sinks and who swims.
The ousting of Uber CEO Travis Kalanick on Tuesday is hardly surprising, though perhaps a bit out of step for both the revered ‘boys club’ who traditionally protect their own and the Silicon Valley culture that worships individuals who can, at all costs, create 10x returns on investment. But he should’ve seen it coming a long time ago, he brought it on himself after all...
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.
As a small bootstrapped company, we're constantly worrying about our next stage of growth. And of course start up orthodoxy says any size business should have a few key performance metrics they track to be aware of how you're doing in the things that influence revenue, profit, and the culture you want to cultivate. But as we've learned, it's not enough to just track your KPI's, you need to forecast how you're going to do on them weeks and months ahead of time.
With an election coming next month in the Netherlands, Marco van Schaardenburgh has successfully launched Prendid, a “voorspellingsmarkt” (prediction market) where players are predicting the outcome of the parliamentary elections. Joining is free and available to anyone globally.
Broadspectrum, whose parent organization is Ferrovial, is an Australian company that operates in the Defence, Property, Social, Infrastructure, Resources and Industrial sectors, and provide Logistics, Facilities Management, Consulting, Construction, Care, Welfare, Operations, Maintenance, Well Servicing, and Business Support services. We recently completed a pilot project in their Defence line of business...
I enjoyed John Horgan's piece on Bayes Theorem for Scientific American. Bayes Theorem and Bayesian reasoning are highly applicable when thinking about forecasting and prediction markets; indeed, one prediction market built a Bayes Net into its platform. In this post I'll explain what Bayesian reasoning is, why it matters to prediction markets, and give a concrete (but semi-fictitious) example of how it's applied.
Our sites use a popular prediction market algorithm called LMSR to determine how markets adjust when someone makes a forecast, and how user scores are affected by making correct and incorrect forecasts.
I've been trying to pick NFL game winners. I'm not using any complex analytical model; rather, I'm making decisions the way most sports bettors do--I watch some games, read the news, and use my judgment. I make each of my picks on SportsCast, which allows me to track my performance, interact with other forecasters, and track the performance of the prediction market--that is, the collective performance of all the forecasters on SportsCast.