Mar/Apr 2011

Decision-makers trying to understand ill-defined problems, in particular the assessment of likely competitors, are increasingly turning to an unusual tool in the analytics kit: wargaming. Strategic games are expanding from defense applications, where they have been widely used for years, into corporate strategy and security.

• Doug Samuelson

John Wanamaker, the father of modern advertising, famously stated in the early 20th century, “I know that half of my advertising dollars are wasted … I just don’t know which half.” Unfortunately, as marketing, advertising and media move at warp speed, the dilemma of this old adage has only gotten worse for even the most sophisticated advertisers.

• Eric Fischer
• Atanu Basu
• Joachim Hubele
• Eric Levine

With the proliferation of unstructured data, semantic applications have moved out of the laboratory and into enterprise contexts. 21st century knowledge organizations are learning that semantic technologies can be designed, configured and implemented to support a wide range of business processes. Semantic technologies go beyond simple data retrieval. Today’s semantic technologies, also known as text analytics, are smart, applying rigorous natural language processing (NLP) methods to model human decision-making processes, and – perhaps most importantly – they can integrate existing organizational knowledge.

• Denise Bedford

An earlier article [1] showed how a simple measure, Time To Payback (TTP), can be a major help in the definition of an optimization development project. One of the goals of any iteration is to deliver (financially) rewarding results to the client in line with the corresponding investment. The TTP rule of thumb: a specific investment should be less than six months for the project to be safely successful. This, or at least this way of thinking, should apply to every iteration.

• Maurice Schlumberger

In the coming year, executives will once again hear a lot about the value of analytics and its ability to convert corporate data and information from hindsight to insight and then, ideally, to valuable and actionable foresight. Generally, the two most common approaches to generating foresights are: 1. the use of statistics and mathematical models, and 2. the use of machine learning tools such as neural nets and genetic algorithms software to mine existing data and generate predictions. While we may explore these approaches and their business applications to finance in future articles, this one features an emerging third approach to generating predictions: the use of “social analytics” through prediction markets. Instead of fancy statistics and software, prediction markets tap into the “wisdom of crowds” and the capacity of markets to aggregate beliefs to generate predictions. This article explores how organizations can use prediction markets as part of their portfolio of analytics tools.

• Ajit Kambil

There are no sure things in an uncertain world, as the Seattle Seahawks dramatically demonstrated when they defeated the heavily favored New Orleans Saints during the recent NFL playoffs. At about the same time the 7-9 Seahawks knocked out the defending Super Bowl champ Saints, snow and ice surprisingly blanketed every state of the union except Florida.

• James J. Swain