Albert Einstein once said, “imagination is more important than knowledge.” Really. He said it. I’ve found that Einstein belongs to a holy trinity of folks that tend to get all sorts of quotes misattributed to them, along with Mark Twain and Winston Churchill. But this one really was him.
I remember first hearing Dr. Einstein’s quote associated with some LEGO exhibit when I was a young boy. The context being: play and experimentation stimulate imagination, expanding our knowledge beyond what we thought possible. A recent experience surfaced this quote from the dusty recesses of my long-term memory. A corny twist on Dr. Einstein’s original line came to me: imagination is more important than data sources.
I was working with a team that wanted to modernize their approach to measurement through our Metrics Finder. As we typically do, we approached the engagement with a “sky’s-the-limit” mentality. After all, it’s our belief that you can measure anything, no matter how fuzzy or seemingly qualitative.
Related Reading: Yes, You Can Measure Anything
There was healthy skepticism on the part of the project sponsor, not because of a lack of faith in us or our approach, but rather what they believed were systemic impediments to innovation. Their specific concern was that we would come up with metrics that their applications were incapable of tracking. Should we establish guardrails based on those limitations ahead of time? We wouldn’t want our efforts to be wasted on impossible measurements.
I told them not to worry, because uncovering the right things to measure isn’t about your source data. It’s about imagination. Without boundaries, you can dream up the right things to measure, and then figure out how to collect, track, and report the data. The team took this to heart and stepped out of their comfort zone to great effect. Setting aside system limitations, they looked beyond the actions and behaviors they’re doing right now to focus on things they could be doing. The results featured a powerful blend of metrics that look at what they’re doing right now, along with measurable shifts in strategy that will bring them closer to achieving their goals.
By the time we were done, this team came to a realization that demystified measurement for them: some of the best metrics are just counts of actions you take that predict success, however you define it. That’s why we call them CAP metrics – they are Countable, Actionable, and Predictive. When you think of those as the criteria, it’s easy to see why we’re not worried about your current technology landscape.
Now, not all valuable metrics are so simple. Some do require advanced analytics approaches. If the data you are looking at are retrospective and longitudinal, or if you need to use historical data to train a machine learning model, then there is some legwork to be done and some new data to collect. However, there is always an opportunity to start simple. You can be innovative and buck tradition without being needlessly complex. Imaginative metrics are a great way to establish a quick win towards changing the organization’s culture around measurement to support those larger initiatives. And you don’t even need to overhaul any data sources to do it.
To learn more about our Metrics Finder methodology, designed to help you measure the immeasurable, click here.