Don't be data driven
The subtle dangers of wrong turns
What does it mean to be data-driven? There is information in a chart, the chart says “go that-a way” and off we go.
What drives us if not data?
Purpose.
Hopefully.
Without purpose, we are Alice chatting with the cheshire cat.
Be wary of anyone overly reliant on data to make decisions.
Folks driven by data are indistinguishable from folks on a random walk. Reactiveness gets cloaked under the guise of being agile and we end up all over the place because we believe the data told us to.
The data did no such thing.
Our Purpose is what drives us. Data is what guides us along our own path.
We are not data driven.
Data driven means data dictates what to do.
Be data informed and be driven by your mission, your purpose.
We are led by what we believe to be right, and we seek out the paths to get there.
Feedback loops offer us guidance and navigation
Deep Insights gift us with sight into what is not observable
We form theories
We interpret within context
We use our knowledge and our ideas and let data inform and guide us
In the business world, this means doing right by your customers
Hopefully, you have a clear mission and values.
At least a north star, or an X on a map that draws you in like a siren.
You have a path to get there. The data will tell you how to adjust
Or you might get blocked along the way. Data will help you navigate and get you unstuck
But don't ever follow data blindly.
Know where you're going, and lean on the data to help guide you there.
Descriptive-Predictive-Prescriptive
A lot has been written and drawn about prescriptive analytics. "With enough data and the right models, the algorithm could spit out exactly what we should do!"
Today, in 2023, training the data science models to give the right answers is no longer a very difficult task. The machine learning part of this problem is solved.
What remains a challenge is providing the machine with the right context. We are climbing up ladders that are leaning against the wrong walls. We cannot provide the right context to our models, because often it is we ourselves who need it. We have to go out and gather it.
For those of us in the data industry, we know what it means to seek out context. We know what it's like to operate on data without the appropriate context (data reverse engineering, anyone?), and we know firsthand how much more effective data becomes when applied correctly and with context.
Data Product Managers are experts at applying data
Data Product Management has evolved out of this work to help folks solve the problem of how to apply data correctly. We cannot feed data into an algorithm and expect it to simply tell us where to go. We cannot plug data into dashboard and follow it.
We have to first understand why we are going. And then data will help us get there.
In future writings, I’ll share methods of uncovering our why and that of our customers’ (anyone other than us who relies on our work) and then how to help put it all together and lean into data’s purpose.
Hit the button below if that’s what you’re into.
-Ricky