Rahul Kapoor is a Professor at the Wharton School of Business at the University of Pennsylvania. He is working in collaboration with Professor John Paul MacDuffie to study the disruption in the automotive ecosystem, to which he asks for your participation.
News headlines have recently been emphasizing companies like Tesla and Uber, technologies like self-driving cars, and a greener, more sustainable future through electric vehicles. It’s no secret that the auto industry is in the midst of a dramatic transformation. We’re seeing a changing dynamic from total reliance on internal combustion engines to growing acceptance of electric and hybrid electric vehicles; from driven to driverless cars; from vehicle ownership to vehicle sharing and pay-for-usage ride-hailing — and everything in between. I’ve been fascinated by these changes and am curious how these emerging trends will play out in the next year or so. But I’ve found that it’s even more fascinating to predict the trajectory of these emerging trends by harnessing the wisdom of the crowd. That is, getting people like you – auto enthusiasts who are passionate and eager to learn – to predict industry disruption.
So, my colleague John Paul MacDuffie and I started a forecasting challenge for autonomous and electric vehicles that ran from April to December 2016. We had incredible engagement from the forecasting community – from experienced forecasters to those who are just interested in the mobility space – and we had 1,530 forecasters make over 9,500 predications on 13 questions. The concept of using a forecasting challenge to predict these trends is a new approach in the world of forecasting. Originally, forecasting solely used subject matter experts, and this method was fraught with individual biases and little accountability. Forecasting tournaments (aka challenges) minimize such biases and increases accountability. Now, you may be thinking, what exactly is a forecasting challenge? Forecasting is simply the activity of judging what is likely to happen in the future, based on the information you have now (Cambridge Dictionary). So, in a forecasting challenge like ours, specific questions are asked and answers are predicted by a crowd of forecasters (i.e. you). Answers are judgments that are then translated into probabilities and tracked for accuracy.
Our first forecasting challenge found our forecasters to be highly accurate in their predictions. For electric vehicles, we found that 2016 was far from being a “tipping point” year. There were disappointing sales figures and lack of legislative action in the U.S. However, we saw a positive trend for EVs in that battery costs were dropping relatively quickly. In contrast, with autonomous vehicles, we saw progress – all major players in the space were making significant advances. And policymakers in the US are starting to allow AVs to operate on public roads. More than just accuracy in predictions, forecasters formed a strong community and had extensive interactions on the changing dynamic of the auto industry.
Due to the success of our last challenge, we have recently launched a second challenge to continue studying this exciting space. Like last year’s challenge, we will track developments in technology, automaker strategies, the competitive landscape and the regulatory environment; you will be able to collaborate with the global forecasting community to anticipate the trajectory of an industry in upheaval. We want to encourage you – as an auto enthusiast – to participate in the forecasting challenge. No prior forecasting experience is required and you have the ability to forecast for as many or as few questions as you’d like between now and July 1, 2018. Winners from the challenge will receive a special mention and “badge.” I’m excited to witness the disruption in the auto industry and learn alongside you!
You can join the forecasting challenge here: https://www.gjopen.com/challenges/18-2017-2018-vehicle-innovations-challenge