This is a broad question for what may be an even broader audience given the wide breadth covered by associations in our economy. Still, I think one issue looms large for any association — society or trade — in the coming year, especially considering the economy facing all association sectors. That dominant issue is the value proposition for members.
I can’t think of a study that examines how associations respond to economic shifts. There are plenty of anecdotal reports, but nothing rigorous. Yet, what association veterans have observed over the years is that association tend to lag markets by 12 to 18 months. On the face of it this makes sense. Association memberships are typically paid a year in advance. Therefore, it’s typical for members who view belonging to an association as a non-critical cost to let an existing membership stand and not renew if a downturn in their market or profession persists when the next renewal period arrives. An organization’s activities may slow down within a bad year, but the membership picture may not change until renewals are due.
The feature article in the January 2011 issue of Associations Now, ASAE’s monthly magazine, is entitled: “How much risk is right?”. It contained a few useful points, but overall it was disappointing. It would have been more useful if the author had recommended a general framework to making decisions involving risk.
What I liked about it includes learning about author and consultant David Ropeik and his book “How Risky Is It, Really?” and referencing Paul Wehking’s observation that ‘continuing the status quo might actually bring more risk to an organization than making a change, which may or may not involve doing something new.’ That was the only value for anyone with any direct management experience.
No, I’m not looking for academic coursework on the subject from Associations Now, but it would be helpful to lift their aim a bit higher and make their articles more than thinly veiled ‘infomercials by vendor members’. Suggesting even one framework for working through strategic decisions involving risk would have been nice. For example…
Michael LoBue writes: Earlier this year the 13th Edition of the Operating Ratio Report (ORR) was released by ASAE. This edition is a solid improvement over earlier editions. The ORR is an important, no make that an essential, benchmark report for AMCs of any size.
Included in the improvements in the 13th Edition is the reporting of medians, in addition to the usual averages. For those who took “Stat 101” too long ago to remember, median is that value in a range of numbers that is exactly in the middle of the distribution — half of the values are above that median and half are below. So, if the median is greater than the average (aka: mean) it means that the range of numbers contains “values below the median that are pulling down the average”. The opposite is true if the median value is less than the average. Thus, including medians gives us more information about the total distribution of values than the average alone provides. It also includes key performance ratios by organization types — these ratios are:
Productivity & Efficiency
Revenue & Expense Management
All this is good! But, we’re still lacking important data in the ORR that will give association managers a much better sense of how our organizations compare to like organizations. For example, it is misleading to compare a single organization to the ORR by revenue class and draw any useful conclusions, or even inferences, about how well our organization may be performing relative to the industry.
Chances are, any organization we compare the ORR metrics will be above or below the average and median. If our subject organization is below, does this mean it is leaving revenue on the table, or under-investing on the expense side? Presumably, deeper comparisons to the Key Performance Ratio will give us a better handle in comparing our organization. But, there is a missing metric that must exist in the data sets that would answer a key question. That question is: “How does my organization compare to the surveyed organizations that occupy the same point on the distribution?” To answer this question we need the “missing metric” and associated data from the organizations corresponding to the metric:
incremental data points – either standard deviation values or quartile values; and
demographic characteristics of the organizations at each incremental marker.
For example, if your subject organization is “some-number” in percentage points above the mean (and median), wouldn’t it be more valid to compare your subject organization to the organizations in the ORR that are at or near 8 percentage points above the mean?
Take the following model distribution curve… all the response form the “bell curve” distribution, where 68% of the responses (value) are 1 standard deviation above and below the mean value and 95% of all values in the distribution are between 2 standard deviations above and below the mean value. Assume your subject organization is somewhere between +1 and +2 standard deviations (see red X inside red oval below — wouldn’t it be more useful to compare your subject organizations to organizations in the distribution that were near the position of your subject organization (within red oval) than the general mean for the entire distribution? After all, isn’t the mean the best of the worst and worst of the best — that’s no target to shoot for!
The following list of comparisons should be available from the existing ORR dataset:
number of members
age of organization
scope (e.g., local, state, national or international)
line of business or profession
revenue source ratios
In conclusion, this should not be a difficult threshold to reach for the professional management of associations. After all, it’s being taught these days in high school!