Problems without solutions are not problems, they are facts of life “Problems without solutions are not problems, they are facts of life.” A form of this quote is attributed to James Burnham, a philosopher and political scientist. I’ve always loved this quote because there are so many “problems” in the world of data management. One that […]
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Perfect is not possible We’ve all heard the phrase “Perfect is the enemy of good” and I like to think that most of us believe it. But oddly enough, this phrase tends to get ignored when it comes to data management. In my experience, too often associations believe that if they discover anyerrors in their data
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“Different” isn’t necessarily better or worse. One of the biggest challenges I face when working with my clients is getting them to think differently about things. Whether it’s a wholesale change of systems (e.g., a new AMS) or a change in how data is processed within an existing system, thinking about things differently is difficult.
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The Rule of 100 and 1,000 and automation I originally coined the rule of 100 and 1,000 in relationship to data conversion (here and here). I extended that rule to ongoing data management here. The rule of 100 and 1,000 can also be applied to automation. Simply put, if you’re managing fewer than 100 records
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Once you know, what will you do? I’ve yet to meet a client who didn’t require, in some form or another, some way to analyze their data. Whether it was simple queries or reports, or more advanced dashboards or analytics, everyone wants to be able to analyze their data. And that’s a good thing. But
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If it’s not in your AMS, why not? I like to tell my clients they’ll know they’ve reached data management nirvana when the answer to any question about data is “It’s in the database.” And I don’t mean the obvious questions like “How many members do we have?” or “Who has registered for next week’s event?”
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Why checkboxes and tags are awesome and dangerous One of the most common functions in an AMS is the concept of checkboxes and/or tags (your system may have both!). With checkboxes and tags we can easily “group” otherwise disparate data sets together. For example, need to create a VIP list of people to invite to
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Don’t miss obvious engagement data What I’ve experienced with my clients over the years is that too many associations are not very conscientious about tracking all of their volunteer engagement in a centralized manner. (Because I’m a volunteer myself, I find this particular issue rather grating.) Take the tracking of authors (i.e., anyone who has written
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All data requires active management It’s a simple fact of data management that is often overlooked: Any data that is not actively managed will eventually become useless. And it’s truer now than ever. If you take a moment to think about your members, whether they are individuals or organizations, every point of data that you
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Documentation is critical for consistency There are so many reasons why documenting your data management processes are so critical to long-term success, but one of the most important reasons is to ensure we process data consistently over time. This is especially true for processes that occur repeatedly but very infrequently. For example, a client of
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