Lew McCreary, writing on the Harvard Business Review Editors’ Blog, covers two of my favorite topics (prediction markets and nipping stupidity in the bud) with How to Kill Bad Projects:
Project owners creatively spun results for political reasons—mainly to prevent funding from being yanked. Consequently, there was a gaping disconnect between the project people down at ground level and the business leaders farther up the food chain when it came to understanding how projects were actually progressing. The leaders tended to think things were going much better than they actually were.
The problem of corrupted information flows stayed with Siegel and ultimately led him to found his current company, Inkling Markets, a software-as-service venture aimed at helping companies conduct successful prediction markets. What does a prediction market have to do with eliminating spin? Siegel sees an opportunity to produce higher quality decision support in businesses by tapping anonymous input “from people who aren’t normally asked their opinions, in samples large enough to filter out individual agendas.â€
In the case of an internal prediction market, employees might be asked to weigh in anonymously (wagering a sum of token currency) on a statement like this: “The Voldemort Project will meet all of its defined performance targets by the end of 2008.â€
Unfortunately, the post includes just a bit of its own stupidity (emphasis added):
While many are naturally captivated by the black-swan-finding potential of prediction markets, another sweet spot may be their use as a form of institutional lie detection—guaranteeing the integrity of internal reporting and keeping the progress of business initiatives transparent.
What the heck is he talking about? I have never heard of anyone claiming that a prediction market could find black swans — to the contrary, a black swan is almost by definition something a prediction market will fail to signal — the knowledge does not exist to be aggregated. Chris Masse quoting Nassim Taleb:
If, as Niall Ferguson showed, war bonds did not forecast the great war, it was a Black Swan
Now prediction markets and black swans both have something to do with prediction and probability, but they’re otherwise ships passing not in the night, but on opposite sides of the globe — with one in the night.
DRM strikes me as another example of people fooled by common interest, in this case of cryptography and censorshipcopyright enforcement. Both have something to do with preventing someone from getting access to information. That doesn’t make one a tool for the other (in either direction). Of course that knowledge was distributed, but apparently not visibly in the right places, resulting in lots of bad projects.