Some of which are well established, while others are in the early stages of development – When picking assessment tools to better inform decisions about future paths, managers are faced with a variety of options. The authors give an insider’s guide to prediction and recommendation techniques and technologies. They cover prediction tools including attributized Bayesian analysis, biological reactions, cluster analysis, collaborative filtering, content-based filtering / decision trees, … Read more »

Some of which are well established, while others are in the early stages of development – When picking assessment tools to better inform decisions about future paths, managers are faced with a variety of options. The authors give an insider’s guide to prediction and recommendation techniques and technologies. They cover prediction tools including attributized Bayesian analysis, biological reactions, cluster analysis, collaborative filtering, content-based filtering / decision trees, neural network analysis, prediction (or opinion) markets, regression analysis, social network-based recommendations and textual analysis. With every possible tool they describe briefly the technique that is used and for what purpose, its strengths and weaknesses, and its future prospects as a forecasting tool. Finally, the authors offer up a notice on the best time to begin the decision-making process with the tool.
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Thomas H. Davenport,
Jeanne G. Harris
Source: MIT Sloan Management Review
5 pages.
Release Date: 1 January 2009. Prod #: SMR299-PDF-ENG
The prediction of the beloved Handbook HBR case solution