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10 Quick Tips for Managing Association Data (by Guest, Wes Trochlil)

By Rich Campbell

Wes Trochlil, president of association consulting firm, Effective Database Management, shares that data is an essential asset for any association. It’s what drives member engagement, increases member retention, creates additional revenue, and enhances marketing efforts. He notes that most associations are doing a better job than they think they are at managing data; however, there is always room for improvement.

Here Trochlil offers us his 10 tips for maintaining association data:

1. Create data entry and user guidelines (i.e. documenting processing). Data entry guidelines tell us what type of data is being entered into any given field (i.e., for an address, do you spell out “street” or abbreviate “St.”). User guidelines establish how we ‘re processing data for a given process (i.e., when a member joins, what happens?).

2. Training. Training must be made available to new staff and as a refresher later on; over-the-shoulder training is useless; and employees should be trained and/or tested in a sandbox, not in a live system. If trained in a live system, employees are more likely to react anxiously, worried that they may make a mistake that could be permanently damaging.

3. Eliminate shadow systems. A shadow system is any list of data being managed actively outside your primary system (Outlook list, spreadsheet, etc.). Every organization struggles with this, no matter how good.

4. Don’t manage to the exception. Many times, associations build processes for the exception rather than the rule. For example, an association of lawyers only wanted a certain type of lawyer as a member. Though 99% of the lawyers who applied made it through, their approval process took up 60 days. Since the 1% was the exception, it was more efficient to approve everyone quickly, then address the exceptions.

5. Capture all of your contacts in the primary system. Everyone should be doing business within the same system. Confusion can arise when there are multiple systems operating separate and independent of one another. In the case of third-party systems and managing data, data should be brought back to the primary system so that everyone in the organization can have access to the information if necessary.

6. Have processes for capturing non-financial, non-volunteer Interactions. Capturing contacts that have value outside of financial and volunteerism can be a huge opportunity. For example:

  • People who want to volunteer
  • People who give suggestions

7. Create data integrity reports. Such reports are designed to uncover whether you have erroneous data in your system. Think what types of queries and reports can point out bad data (i.e., a report searching for whether there are “@” symbols in the email list, if an email address is missing one, it’s obviously not a good address). Weeding out bad data is something that must be done frequently if you want it to be successful.

When auditing old data, a good rule of thumb is to get rid of data that is three years old or older, especially if there’s been no interaction with the subjects in that time.

8. Start an internal users group. Even the most well-intentioned people can work with blinders on, working on and creating shadow systems unknowingly. An internal user group helps open the lines of communication to make people aware of what’s going on outside of their personal silos and encouraging cooperation.

9. Practice database Public Relations. PR is about presenting the best face and the positive of a product or project. The reality of data management is that no one cares until they’re involved. Database PR is about putting over the process so that when something negative does happens people will still have faith that things can and do get better.

10. Pursue success, not perfection. Understand, as soon as data goes into your system it’s out of date. People die, lose jobs, and change addresses. So be comfortable knowing that your data is never going to be completely perfect and up to date.