As I see it, there are really only three types of data contained within a typical association management system: short-term data, long-term data, and useless data. Allow me to expand:
- Short-term data. This is typically transactional data. For example, during an event registration we will collect data on dietary needs of the attendee. This is short-term data (i.e., it’s only used for the event itself, and once the event is done, it won’t be used again). It’s important to collect but it has a short shelf-life.
- Long-term data. One of the best examples of this type of data is certification or accreditation data. While all certification programs are different, a typical certification program has a join and renew date, and requirements for attaining and retaining the certification. So there is data collected over a much longer period of time, all of which needs to be saved until at least the next renewal period, if not longer.
Another example is areas of interest or opt-ins/outs. These will change over time, but they are also used over the long-term.
- Useless data. Alas, too much of our databases are filled with truly useless data. One of the most common examples of this is demograhpic data. So many associations collect this data with the intent of using it (e.g., race, gender, age, in order to report on “makeup” of the association membership) but too often never do. How many times have you filled out a registration form that included ten questions about who you are, and as you answered the questions you thought to yourself “What are they going to DO with this data?!?”
So as you collect data on a day-to-day basis, ask yourself which category the data falls into. The 80/20 rule probably applies here; 80% of what you’re collecting needs to be collected (it’s short-term or long-term data). But what about that other 20%? And how much effort are you putting into collecting that 20%, which is ultimately useless data? Imagine the time savings that could be had!