The Pursuit of Perfect Data
If you are leading a marketing team through a major structural shift, like building out new CRM workflows or centralizing a complex portfolio, you have likely hit a familiar wall. The launch stalls because the team is trying to account for every possible data gap, edge case, and hypothetical future scenario. We often paralyze our own operations chasing a pristine ecosystem that simply does not exist in reality.
The Fixation on Perfection
Over my career navigating complex marketing infrastructures, I have found that the roadblock is rarely the technology itself. The bottleneck is usually our own ambition to account for everything at once.
When I look under the hood of an institution's marketing infrastructure, the most common operational mess is a fixation on creating perfect processes to make imperfect data and future ad hoc situations fit in. It is nearly impossible, and honestly, it is a flaw to even think of it. Instead of engineering for the unknown, we have to build modular frameworks using the two or three data points we actually trust.
Building Scalable Frameworks
If you have the system run correctly by the best professionals, you should be able to enable marketing to run a highly personalized operation. You should use the available data to the best of how it might let you personalize.
Do not set expectations for the system or process that are so lofty and complicated that they cannot actually be met. Get the foundation running, learn from actual user engagement, and pace your ambition. Be realistic about what can happen with the data, and remember that whatever you cannot do today can be spread to tomorrow.
You “Ken” Quote Me on That
From working in this industry for more than 20 years, I’ve collected countless notes, ideas, and scribbled thoughts along the way. That archive is what led me to create this blog. Here are a few of my own original quotes from that treasure trove that inspired this article:
"Don’t fixate on creating perfect processes for imperfect data."
"Systems should be small, scalable, and adaptable."
"Don't set an expectation of the system or process before knowing what inputs you need to meet the outcomes.”