Why Associations Struggle with Business Intelligence
For over five years, I have been writing about the benefits of business intelligence for associations. And for five years I’ve been waiting to see signs of more associations adopting a business intelligence approach to using data. I’ve been waiting patiently for case studies of associations using business intelligence to advance their organization’s mission.
But alas, I continue to wait.
I’ve been imploring my clients and other association professionals that their data has tremendous value. Even a simple business intelligence program would help them leverage that data for improved communications, better marketing, and advancement of their mission.
So I have to ask: Why do associations struggle so much with business intelligence? In short, the reason is fear: fear of not knowing how to do it “right,” fear of finding out things that contradict conventional wisdom, and fear of having to do things differently as a result of what the business intelligence is telling them.
For this discussion, I’ll use the calculation of lifetime value (LTV) as a simple business intelligence metric that many associations struggle with. Calculating lifetime value is relatively easy. The only two numbers you need are your retention rate and the “average annual spend” by a member. The retention rate tells you how long the average member stays, and your “average annual spend” is how much an average member spends each year. Click here to learn how to calculate lifetime value.
Fear of not doing it right
When I ask association executives if they’ve calculated the lifetime value of their members, far too often, the answer is “no.” When I ask why they haven’t done it, they say something along the lines of “Because I’m not certain our data is correct. I’m not sure of our retention rate or our average annual spend.”
This is fear.
The thing is, an LTV calculation that’s close to correct is far more useful than not knowing your LTV at all. Suppose your retention rate is actually 80% and you think it’s 70%. And suppose the annual spend is $400 instead of the $450 you estimate and your estimated LTV is ~$1,500. The actual LTV is $2,000. Will that $500 difference really cause such a dramatic change in behavior that it’s better to NOT know what your LTV is? No!
This is the first fear that holds associations back from doing even broader business intelligence. The fear that somehow they’re not analyzing the data correctly. But the reality is that even if they’re not using all the data, or they’re not analyzing it perfectly, the likelihood is that the intelligence they DO gather is more useful than having no business intelligence at all.
Fear of what you’ll learn contradicts conventional wisdom
The second fear of business intelligence is that the new information will contradict conventional wisdom, and that in turn will force you to confront some unpleasant truths. With no LTV calculation at all, the conventional wisdom might be that members stay longer than five years. Or that they spend a lot less each year than they really spend. Or (as I see far too often), that the amount you spend on membership acquisition should never exceed the amount of first year’s dues, e.g., if dues are $75 annually, you should not spend more than $75 to acquire a new member.
Going deeper into business intelligence may shed light on some other unpleasant truths. For example, you may find that programs that have been “sacred cows” for years are actually costing a lot more to produce than they return. And that they’re not reaching nearly as many members as you think.
But having data that answers these questions, and contradicts the generally accepted truths at your association, can be very uncomfortable and may lead to very difficult conversations.
Fear of having to change your behavior
The third fear is related to the second, in that if what you learn contradicts conventional wisdom, this will require you to change how you do things at your association. Again, using the example above, if you’ve always budgeted less than $75 per new member for acquisition costs, but learn that LTV is $2,000, then you have to have a more difficult discussion about how much you really should spend on new member acquisition. And if you decide that spending $150, or $500, or even $1,000 is worth bringing on a member with an LTV of $2,000, then you’re going to have to change how you do member acquisition.
Real data that suggests how you’re doing things is not as effective as it could be is discomforting. Taking on the change of behavior this new information requires is even more discomforting. But it’s absolutely essential, if the data is telling you that your current actions aren’t ideal.
To be sure, there are other reasons that associations are not adopting business intelligence programs as rapidly as they should be. But overcoming the initial fears around the process is the first step in reaping the benefits that business intelligence has to offer.
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