Utilizing prediction markets in an executive search process

As the leader of English at Large's Search Committee for a new Executive Director in early 2009 we were facing several critical issues. We needed to hire a new Executive Director as quickly as possible. It was also critically important that the entire Board be engaged in the hiring process. To accommodate a large pool of candidates and enable a geographically distributed Board to participate an online prediction market was established with each candidate representing a market choice. Resumes and cover letters were distributed electronically to board members prior to the start of the market and the market was opened for approximately 10 days. The market proved extremely effective in sorting the candidates and allowing rapid execution against a tight deadline. A small pool of prospective hires were identified via this process who were then telephoned screened and interviewed per traditional methods. A new Executive Director was identified and hired in record time through this effort.

Difficult to create a news brand via prediction markets

The inability of hubdub.com (the news prediction game) and The Industry Standard to successfully leverage prediction markets into a new form of media brand demonstrates the difficulty of using this technology for this purpose.

Who is using prediction markets

A non-exhaustive search of published reports list the following companies as users of prediction markets: Eli Lilly (A. Bingham), Best Buy (J. Severts), Google (B. Cowgill), Harrahs (F. Keeton), Ingenix (T. Brown Stevenson), GE Research (C. LaComb), Headwall Photonics (D. Bannon), Corning, Qualcomm, Microsoft, and HP. Best buy, Google, Harrahs, Microsoft, and HP were using the approach for sales forecasting and Eli Lilly, GE Research, and Headwall Photonics were using the approach for new product development. I'm uncertain what the applications were at Corning, Qualcomm, and Ingenix.

Virtual Groups - planning for success

Research on virtual groups indicates the importance of initial communications to set the proper behavior norms for group participants. Interestingly the active behavior of a small number of individuals in virtual groups is also noted as driving overall behavior norms. Speculation for this is that the dearth of social cues in the available media enhances those cues that are available and increases their impact (this also relates to the importance of careful up-front communication). The beneficial impact of well orchestrated and clearly defined virtual group norms is well documented and managing this process carefully when establishing a virtual group is critical.

Leveraging Science to Optimize Sales

Steve Diamond, Managing Director at BitInsight, and Malcolm Rees, Global Head of Sales for DHL Express, recently published an article in the magazine SellingPower called A Scientific Approach to Managing the Salesforce at DHL Express. The article notes that to be effective it is important to tie your sales management and productivity tools to your company's strategy, to benchmark a small number of high leverage key performance indicators (KPIs) for sales team tracking, to evaluate behaviors as well as results, and to fully engage the organization in this effort.

The article emphasizes that effective use of sales force management tools requires generating timely, accurate data and using this data to drive decisions. Critical to this effort is knowing what metrics to track and knowing what tracking data results are optimal. This article provides insight into how DHL Express addresses these two critical points via benchmarking and gap analysis.

Semantics

In the technology realm one constantly sees references to knowledge management, business intelligence, data mining, artificial intelligence, collective wisdom, collective insight, etc. While this nomenclature typically refers to specific actions or tools, the implied meanings derived from the separate elements of these combined words must be considered carefully, especially when this implied meaning drives expectations of the benefit derived from implementing technologies in these respective areas.

To clarify this potential semantic ‘confusion’ a quick search of definitions at dictionary.com can prove helpful. The complete definition is available via the link however critical elements of the definition are listed below:

• Data: facts; statistics; information
• Intelligence: capacity; aptitude
• Knowledge: personal knowledge; result of study or experience; facts, truths, principles
• Wisdom: knowledge of what is true or right; judgment
• Insight: instance; apprehending the true nature.

Classification of the various actions and tools under these categories does not necessarily imply definitional accuracy. Careful consideration should always be given to what is really being delivered versus being swayed by the nomenclature’s ‘semantic lens.’

Better Choices

The Chief Security Officer of Siemens gave an excellent talk at a recent Infragard meeting discussing success. Referencing a Conference Board report he noted two facts:

• Most people are within 10% of each other in terms of IQ
• Most people work the same number of hours/days per year.

As we all know however not everyone is equally successful at what they do so what drives this difference? The premise presented is ‘choice’ where making and repeating good choices is what truly drives the majority of difference in performance.

Successful people were noted as ones that make choices that ‘others don’t like to make’ and good choices were identified as those that are:

• Fact based
• Relationship based
• Drive follow thought
• Receive long term commitment.

If one accepts this premise, assisting employees in making better choices could have a dramatic impact on a company’s performance! Is a culture and infrastructure that supports better choice what drives much of the difference in company performance within a given industry?