Analyzing Economic Impact of Exhibitions
By Doug Ducate
For the last 15 years the exhibition industry has pursued the goal of identifying economic impact of our events with the same fervor that Percival exhibited in his quest for the Holy Grail … and unfortunately with the same frustrating ending. But it hasn’t always been that way.
From the early 1970s to the end of the 1990s, economic impact was the product of IACVB (now DMAI). The process was simple. Organizers would provide the local CVB with a list of attendees. The CVB would mail them a survey form that identified the amount they spent while at the event. Good sampling and follow-up with non-respondent techniques were followed to insure a reliable outcome within a reasonable standard deviation. Local economists would then apply acceptable multipliers for the destination and multiply that times the total number of visitors and the result was economic impact of that event.
The advent of the Internet in 1994 made the process easier and less expensive but also doomed it. Instead of street addresses, organizers provided email addresses and the resulting wave of emails that inundated everyone led to filters and other techniques to stop unwanted email. Security concerns along with the volume issue resulted in organizers no longer giving out email or street addresses. With no way to collect direct spend data, there is no scientific way to calculate economic impact.
The convention industry problem was further exacerbated by the rise of special events such as the Super Bowl, the NBA All Star game and the Final Four. A recently completed study reported in The Dallas Morning News (29 October 2013) stated that “fans and workers are expected to spend $276 million at the 2014 Final Four” that is being played in the Dallas area. It goes on to say “that is slightly more than the record setting NBA All-Star game hosted in Dallas in 2010, but less than half the estimated spending for Super Bowl XLV hosted in 2011.” A typical economic multiplier to calculate economic impact is around six or seven times the direct spend so you can do the arithmetic.
Dallas was never able to verify direct spend numbers for the Super Bowl or NBA All-Star game that came anywhere near these estimates, and it is unlikely any other destination has either. The reality is these events brought visitors to the area that spent money then left. They have a significant economic impact on each destination that hosts them even if it cannot be quantified.
This is true for meetings and exhibitions too. IACVB got so good at these calculations when they had the direct spend numbers that they could distinguish a difference in the impact of a meeting with an exhibition versus one without an exhibition, and it was confirmed those events with exhibitions had a greater impact than those without. If a destination doesn’t have a facility and infrastructure needed to meet the needs of these events, they don’t come, and that economic impact can be calculated with certainty as it is zero.
Since the direct spend data flow ended about the time the dot com bubble burst, various industry groups have spent more than a million dollars with well known brands trying to identify the economic impact of our events. One of the latest done by CIC soon to be updated by them pegged the industry at $120 billion. Models attempting to bring that down to individual events have been labeled as “flawed” and of “marginal value.” But even if some day we have precision, we can’t compete with “estimates” for major events like the Super Bowl.
All this doesn’t mean the industry should stop trying. To the contrary each organizer should be able to make a case with a destination on the benefit their event will bring to the destination. Some of that to be sure is economic impact, but there are other benefits as well including bragging rights. Why else would a destination pursue such expensive ventures as the Super Bowl and the national political conventions?
Maybe someday we will find a way to gather direct spend information to provide a reliable direct spend total number that can be translated into an economic impact number for any destination. If we do, hopefully there will be enough money available to then build an economic model that economists and statisticians can accept as a reliable methodology for the next 10 or 15 years until the next direct spend data is needed.
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