Meeting the Challenge of Data Conversion

One of the keys to a successful association management system implementation is data conversion. Simply put, data conversion entails moving all of the data that you’re tracking in your legacy systems into your new data management system. Sounds simple, doesn’t it?

Unfortunately, for many associations, data conversion quickly turns into a resource hog, taking up far more staff time and much more money than initially anticipated. While this happens for many reasons, there are three primary causes for lengthy and expensive data conversions:

  • Data is in multiple sources. With most AMS implementations, one of the goals is to get all of your data into one place, the new AMS. But it is also typical for associations to have multiple sources of data before moving to an AMS (e.g., a legacy AMS plus an events registration system plus a list of prospective members). Moving multiple sources of data to a single source of data requires de-duping and the establishment of specific business rules (e.g., setting the unique identifier is for each data source).
  • Staff turnover. Over time, staff changes. As a result, how the database (and the data) is used, also changes. This results in data inconsistencies (e.g., a field once used to track prospect type is now used to track speaker type). These data inconsistencies make for extremely difficult data conversions.
  • Business rules change. This is related to staff changes, but not completely. As in the example above, if a data field is being used for one thing at one point in time, and then the field is used for something else later, this leads to inconsistencies, making conversion of the data difficult, if not impossible. Other business rule changes are more legitimate, such as a change in membership structure. However, even legitimate business rule changes can create data conversion headaches.

So what can associations do to avoid these headaches?

First, document everything. Always. Document how you’re using each field in the database. Document new fields as they are added to the database. Document business rule changes as they occur. All of this documentation will be critical for establishing institutional knowledge during data conversion. Documentation will help you answer questions like “Why do we collect this data?,” “What is this data used for?” and “Do we need to keep this data in our new system?”

Second, use data conversion as an opportunity to do some serious spring cleaning. Use worst-case scenario decision making to answer the question “Should we convert this data element?” When asking that question, also ask “If we don’t convert this data, what’s the worst thing that can happen?” If the worst case is something like “We’ll look it up in the old system,” then it might be a good candidate for not converting.

Finally, document everything, again. Document what data was converted and why, and start documenting your new AMS immediately and consistently. There will be another data conversion in your future, you can bet on it. Start preparing for it now.

This article originally appeared in the July 13, 2007 issue of Association Trends. Reprinted with permission.


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