http://www.1000ventures.com/business_guide/innovation_system_metrics.html Return on Innovation Investment (R2I) …R2I also shows return on investment, but only from new product innovation investments, not all investments. It looks at the firm’s total profits from new products (cumulative new profits generated from new products launched) divided by its total expenditures for new products. This long-term ratio shows the firm’s total return from new products over a three- to five-year period. This number has two uses:1. Descriptive: to demonstrate the overall
Here are my notes on the paper, Prediction Markets, by Justin Wolfers and Eric Zitzewitz Accuracy Wolfers and Zitzewitz recently published Interpreting Prediction Market Prices as Probabilities that claims that “prediction market prices are usually close to the mean beliefs of traders” and concludes… with some guidance for practitioners. In most cases we find that prediction market prices aggregate beliefs very well. Thus, if traders are typically well-informed, prediction market prices will aggregate information into
Notes on DEMOCRATIZING INNOVATION- by Eric Von Hippel Why users innovate for themselves Users do it themselves rather than hiring a customizer because of agency costs (i.e., cost of monitoring the agent), because their needs are unique and they want to get precisely what they want, and also becuase they enjoy innovating. Because innovation by users is widely distributed, they need a way to leverage and combine their efforts and avoid more than one user developing
Here’s the closest thing I’ve found to an explanation of how to set up and conduct a prediction market. This paper, INFORMATION AGGREGATION MECHANISMS: CONCEPT, DESIGN AND IMPLEMENTATION FOR A SALES FORECASTING PROBLEM, by Charles R. Plott of CalTech and Kay-Yut Chen of Hewlett Packard Laboratories, describes how they set up a prediction market for sales forecasts at HP with the following results: · In 6 out of 8 events for which official forecasts were
Here’s the second part of my notes from the paper, INFORMATION AGGREGATION MECHANISMS: CONCEPT, DESIGN AND IMPLEMENTATION FOR A SALES FORECASTING PROBLEM, by Charles R. Plott of CalTech and Kay-Yut Chen of Hewlett Packard Laboratories,which describes how they set up a prediction market for sales forecasts at HP. Advantages of Prediction Market Over Other Forecasting Methods · The methodology is flexible. It can be used to aggregate any type of information possessed by different people.
Art Hutchinson pointed me to his blog, Mapping Strategy, and the collection of articles he’s been writing about prediction markets since last September. Here are my notes:”The strong consensus – supported by a compelling body of academic research – is that these mechanisms deliver uncannily accurate forecasts across a wide range of topics, time horizons, and approaches to participation. Even more interesting is that they appear to do so at a fraction of the cost
Here are my notes on The Wisdom of Crowds by James Surowiecki Overview Under the right circumstances, groups are smarter than the smartest people in them, even if the group doesn’t contain expert members. Experts are as likely to disagree as agree. Experts’ individual consistency is also 0.5. Experts overestimate the likelihood that they are correct – little correlation between self-assessment and performance. Therefore, however well informed and sophisticated and expert is, his advice should