If you’re going to embark on a business intelligence initiative, you ought to have these five items in place before you do.
One of my least favorite questions on the ASAE listserver is when an association membership professional says something to the effect of: “My membership retention rate is 75%. How does that compare to your association?”
As I’ve written before, this question frustrates me because comparing retention rates, without context, provides absolutely no information as to whether 75% is good or bad. It is somewhat analogous to the question “My most recent mailing had a 3% response rate. Is that good or bad?”
Well, if you were giving away $500 gift certificates with no strings attached, then I’d say 3% is pretty bad. If you were selling $100,000 cars, I’d say 3% is pretty good. But again, without context, the 3% number is meaningless.
And so it goes with retention rates. Retention rates are important relative to your organization’s structure and needs. For example, one association I’m familiar with has nearly 100% retention. Why? Because every membership is a lifetime membership. That is, after the member joins and is accepted into membership, their membership is good for life.
Another association I’ve worked with has retention below 50%. Why? Because their primary benefit is for traveling college students, and once they leave college, they have little need for the membership.
Now, is the first association doing better than the second? And does knowing the first association’s retention rate help the second association at all? The answer, of course, is “no” to both questions.
Like most metrics within our association, the metrics are only important in context to our desired business objectives. In the case of the second association, if the objective is to expose as many college students to travel as possible, then having a high churn rate (i.e., a low retention) is not necessarily bad.
So before you ask “Is my retention rate good?” be sure you understand your business objectives. And be sure I’m not standing in the room with you.
Here’s a brief podcast (about three minutes) on my definition of business intelligence.
I’ve written in the past about the need for conducting a public relations campaign for your database. You can read that here and here.
One of the reasons a PR campaign is so critical is the anchoring effect. The anchoring effect is a pyschology term that essentially says that we “anchor” on one piece of information to make decisions. Or to put it another way, we tend to generalize from a specific, based on the “anchor” we’ve got.
In the database world, this means that once we discover some data is bad (e.g., an email address for one of our members is incorrect), then that means all the data in the database is bad.
Anyone who has had responsibility for data integrity in their organization’s database knows exactly what I mean. It usually goes something like this: A list of members is pulled. Some of the information on the list is incorrect. Fixes are made, but when the next list is pulled, other errors are discovered. Very quickly, the entire staff is talking about how bad the data in the database is. This based on one or two events. The “anchor” has been dropped.
This is why PR campaigns are so critical. Trust degrades quickly and once that trust is gone it’s difficult to get back. PR campaigns can help make deposits in the trust bank that you’re sure to need to draw on later, especially if anchors have been dropped in the past.
Did you ever notice that it’s easier to find information simply using Google than it is to find information in your database?
Why is that?
Compare these two processes and see what you come up with: Count the number of clicks it takes for you to look up a name in your database until you can see that person’s address. Now Google that person’s name with “address” in the google search, and see what you get. Which was easier? Google won’t always provide you with the correct answer, but it does an awful lot of the time.
Why isn’t searching your own database as easy (if not easier) than using Google?
I’ve posted a new article on my website, entitled “Healthcare and Your Database.”
Of course, if you’re already on my announcements list, you would have received notice of this new article right in your email box.
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I’m working on a research project to identify the factors that contribute most to the long-term success of an association management system (AMS). To that end I am going to interview several associations that I consider to have highly successful AMS implementations.
My request is a simple one. If you know of an association (even your own) that you believe uses its AMS very successfully, please click the link below and answer the three brief questions.
Thanks for your input.
I spoke recently for the Association Forum of Chicagoland on Business Intelligence. Afterwords I sat for a short interview on the topic of Business Intelligence.
As I watch the world financial crisis unfold, one contributing factor that has arisen is that there is a “lack of trust” among and between banks. In other words, because Bank A can’t trust what Bank B says about its solvency, Bank A won’t loan Bank B money. As a result, banks have stopped lending money to each other. And thus we have a credit crisis.
It struck me that this is a very good analogue to trust in your organization’s database. Many, many times, when I meet with clients or potential clients, one of the core challenges being faced is that of trust. Or more to the point, lack of trust in the database and the data it contains.
Recently I met with a mid-sized association (~30 staff) that is having some major challenges with their database. In the course of our discussions, it became clear that no one on staff really trusts any of the data in the database. Finance does not believe the numbers coming from membership. The events department has moved to a separate event registration system. The foundation went off and purchased its own database, even though the primary database could probably do everything they needed.
All because of a lack of trust.
And as a result, the organization is completely ineffective with their data management. Staff is frustrated, the executive director if frustrated, and nothing is improving.
I’ve written all over my blog and in articles about the need for business rules, documentation, and good training. All of these tools are a foundation for building trust in the database. Once you’ve lost that trust, it’s extremely difficult to get it back.
When discussing data management issues with clients I often hear “We want to be more efficient.”
Of course, we all want to be more efficient, but efficiency as a goal implies that you’re doing the right thing, just not in the right way. I would suggest that, quite often, we’re actually not doing the right things. Thus, doing the wrong things more efficiently won’t help us become more effective, just faster at doing the wrong things. Or as a friend of mine put it so indelicately, being more efficient with the wrong processes just means you’ll “suck faster.”
What we really want to focus on is effectiveness, not just efficiency. So whever you hear someone say “We want to be more efficient,” your first response should be “Do you really want to be more efficient, or do you want to be more effective?”
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