Lessons Learned from an Unexpected Candidate Placement: Part 1

Five years ago I was in the process of helping a client locate an exceptional sales leader for a high-profile global account position within their organization. I had arranged for the VP of Sales to meet with a very well qualified, proven group of five individuals – all of whom would undoubtedly represent the company with great aplomb and, most importantly, greatly improve customer relations and rapidly increase revenues generated from all pertinent accounts.

The interviews had been set up to take place in successive order over a period of five hours. The hiring manager and I had agreed to dissect the discussions immediately after all had been completed. Unbeknownst to me, one of the account executives (let’s call him Mark) had spoken with an associate at another company about his candidacy for the position and, upon further discussion, both had apparently decided that our new player (designated Steve) would be a better match for this specific role. Subsequently, they devised a plan to have Steve show up for the meeting and hope that it lasted long enough for him to avoid bodily damage.

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Motion Chart of U.S. Venture Funded IPO’s from 1998-2008

Given the events of 2008,  it seemed like now would be a good time to take a look at the U.S. IPO market for venture funded enterprises and see how it has fluctuated during the past 10 years.  One of the most effective means to illustrate movement of this type is the motion chart option offered by Google.  It provides a truly unique method of observing change over time.

The categories selected for this particular examination are City, Number of Companies,  Amount Raised, and Total Valuation.

The data used to construct the charts is derived from the always useful Moneytree Report along with 2008 data from Hoovers IPO Central and pertinent corporate releases.

Regions assigned to each metropolitan area are designations that I have often used for my own personal items and are provided as a means to allow the user to readily identify all cities in each particular realm if so desired.

Feel free to adjust the tracking speed with the arrow next to the play button.   I’ve also found that changing the ‘Lin’ setting to Logarithmic on both axes provides a much better visual perspective on the data. Individual metro areas can also be isolated either by clicking on the corresponding dot or checking any of them in the appropriate box on the right side of the form.

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