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How accurate is that membership database query?

Written by Ray van Hilst on . Posted in Association, Association Best Practices

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Here’s a quick query most associations run at some point in their membership database:

Find all members with between 10 and 15 years experience.

Sounds simple, right?  But…

What fields are you querying and what data is in those fields?

Was it a check-box on the initial membership form? (e.g. Please tell us how many years you have been working: 1-5, 5-10, etc.).  Still sounds simple, right?

Now, what about any records created by new members 5+ years ago?  They probably checked “1 to 5 years experience” when they filled out their new member form.  So when you run this query, how many records and members did you just exclude?

This example highlights the need for data quality and data integrity management?

It is typically assumed that data integrity is a problem for the database team or IT to take care of.  But the lack of clean data is something that affects all departments.

Using the above example, if the membership department is planning an upgrade campaign for young members, the query will return seasoned professionals who don’t qualify.  If you are segmenting a compensation study based on years experience, your results will show that junior members are making much more money than the industry standard.

This is why data integrity in your association management software is an issue for all staff members using the member database in any function.  So what can you do about it?

When doing your association management software implementation make sure to include input from all departments as to what types of queries they will use?  Include that feedback as you set-up your data tables.

  • Regularly review your database and make sure that fields and labels still make sense for your association’s business?
  • Look for opportunities to roll any extraneous databases in use by other departments into the main database
  • Look for opportunities to optimize your database by either purging irrelevant data or appending with new important data.

At the end of the day — clean, accurate data is the lifeblood of effective membership management.  It requires detailed, up-front identification of future data needs and a process that includes all departments for regular cleaning and verifying of the member data.

Because while you may blame the IT or database department for the bad data – it’s ultimately your program or initiative that will suffer.

For more information on how Avectra can help you improve your member database and optimize for these issues, feel free to sign up for a demo or contact one of their sales representatives.

 

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