Don't manage to the exception!
One of the universal truths about data management is, wherever possible, avoid managing to the exception. What I mean by this is to avoid developing any process that is designed to catch some arcane or unusual circumstance. Instead, the process should capture what happens the vast majority of the time, and then let staff manage the exceptions manually.
One of my favorite examples came from a client who had designed their membership join process to include a step for approving membership, and then once membership was approved, an invoice was sent. They had added this step because, in some instances, new members would join and pay their dues, and then it would turn out the individual was not actually eligible for membership in the association. So staff would have to cancel the membership and provide a refund. Staff didn't want to have to cancel and refund, but as a result, their current process meant that membership joins often took 60 or more days to complete!
But the reality was this: Of the hundreds of new joins this association received each year, only two or three were from individuals who were not eligible for membership. Their process for membership joins had been built around the exception, not what most commonly happened.
It's too easy to fall into the trap of designing our processes to address every possible contingency or possibility. But more often than not, managing to the exception creates more problems than it solves.
So take a look at all of your processes and ask yourself: Was this designed to address the majority of cases, or the exceptional ones?
Wes's Wednesday Wisdom Archives
Once you know, what will you do?
Once you know, what will you do? I’ve yet to meet a client who didn’t […]
If it’s not in your AMS, why not?
If it’s not in your AMS, why not? I like to tell my clients they’ll […]
Why checkboxes and tags are awesome and dangerous
Why checkboxes and tags are awesome and dangerous One of the most common functions in […]
Don’t miss obvious engagement data
Don’t miss obvious engagement data What I’ve experienced with my clients over the years is […]
All data requires active management
All data requires active management It’s a simple fact of data management that is often […]
Documentation is critical for consistency
Documentation is critical for consistency There are so many reasons why documenting your data management […]
Consumer demands change and technology changes
Consumer demands change and technology changes When I work with clients on the selection of […]
Why I write
Why I write Thirty years ago, I started a new job as director of membership […]
DAN – The Data Analytics Network
DAN – The Data Analytics Network I’m a huge fan of users groups (both internal […]
Process before technology
Process before technology In a conversation with a client recently, I was reminded (yet again) […]