I’m very often asked by my clients What can we do to improve our data management situation? My response is always the same: What does it look like now? What do your current benchmarks look like?
Frequently, they have no answer. They’ve set no benchmarks. They know they have a problem and they want to improve how they’re managing their data. But the problem is, if no benchmarks have been set its difficult, if not impossible to measure what progress, if any, has been made.
So what are some standard data management benchmarks? Here are just a couple of benchmarks to consider:
- Bouncebacks. Whether its snail-mail or email, are you measuring your bounceback rate (i.e., the amount of mail that is returned undeliverable)? I worked with one association that had been so diligent with their data cleanup that their snail-mail bounceback rate had been reduced to less than 0.5%. For a typical mailing of 3,000 pieces, they would get fewer than 15 returns.
- Percentage of members updating census Many associations collect demographic data from their members. Very often, this data needs to be updated on an annual basis. One benchmark that many of my clients use is the percentage of members who update their demographic data each year (or whatever period is designated).
- Ease and speed of reporting Many organizations struggle with getting data out of the database. There can be a variety of reasons for this, including poor technology or insufficient training. But accuracy in the data can also be an issue. Measuring how long it takes to create and execute reports can be a good benchmark when looking to improve data management.
- Amount of time required to process new memberships I worked with one association whose average time for processing a membership application was six weeks! That is, when a membership application was received by the organization, it was six weeks before that individual received their membership card and information. By changing processes and technology, that turnaround time went from six weeks to 48 hours.
In order for benchmarks to be effective in measuring success, you need to know how you’re measuring the benchmark, what the measurement is now, and what it is after you’ve implemented your data management changes. Then you’ll know if you’ve been successful or not.
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