It's always a surreal experience to sit in a meeting with people and their bosses and hear "we're on track, no issues, the new product launch is going to be great, we're going to sell a ton, etc. etc." and then have a private/informal meeting with the same people who will confide that the project/product/strategy is completely fucked and everyone thinks that. :)
I've noticed that in large organizations certain information are held by a small number of people who may be reluctant to share them for political reasons. Another challenge with internal prediction markets is the possibility that knowing the "probability" of an project-related outcome reduces morale and hence creates a self-fulfilling prophecy that further reduces the chance of success. Appreciate your insights.
Bottom line, these aren't for everyone. One of the first questions I ask when someone expresses interest is what their culture is like and how humble their leadership is. If they're ready for it, prediction market can be transformative. But if they're not, they can fail - and we've surely had plenty of those projects too!
The average project size we work with tends to be in the low hundreds of participants, with the biggest one being in the mid-thousands.
I want to to figure out if this would be a fit for one of my projects, but I don’t want to get a demo, talk to people, etc just to find out it’s an incompatible price.
In the past few years, many companies have experimented with prediction markets. In this
paper, we analyze the largest such experiment we are aware of. We find that prices in Google’s
markets closely approximated event probabilities, but did contain some biases, especially early
in our sample. The most interesting of these was an optimism bias, which was more
pronounced for subjects under the control of Google employees, such as would a project be
completed on time or would a particular office be opened. Optimism was more present in the
trading of newly hired employees, and was significantly more pronounced on and immediately
following days with Google stock price appreciation. Our optimism results are interesting given
the role that optimism is often thought to play in motivation and the success of entrepreneurial
firms. They raise the possibility of a “stock price‐optimism‐performance‐stock price” feedback
that may be worthy of further investigation.
We also examine how information and beliefs about prediction market topics move
around an organization. We find a significant role for micro‐geography. The trading of
physically proximate employees is correlated, and only becomes correlated after the employees
begin to sit near each other, suggesting a causal relationship. Work and social connections play
a detectable but significantly smaller role.
An important caveat to our results is that they tell us about information flows about
prediction market subjects, many of which are ancillary to employees’ main jobs. This may
explain why physical proximity matters so much more than work relationships – if prediction
market topics are lower‐priority subjects on which to exchange information, then information
exchange may require the opportunities for low‐opportunity‐cost communication created by
physical proximity. Of course, introspection suggests that genuinely creative ideas often arise
from such low‐opportunity‐cost communication. Google’s frequent office moves and emphasis
on product innovation may provide an ideal testing ground in which to better understand the