What is a data driven culture?
Data Driven Cultures
Carl Anderson, 2015 (Data Scientist at Warby Parker) describes a data driven culture as on that:
- Is continuously testing;
- Has a continuous improvement mindset;
- Is involved in predictive modeling and model improvement;
- Chooses among actions using a suite of weighted variables;
- Has a culture where decision makers take notice of key findings, trust them, and act upon them;
- Uses data to help inform and influence strategy.
This is a fine summary and worthy of unpacking.
The Big Why
Data driven cultures are likely to produce better, sustained, performance over time than the alternatives.
It’s not even worth considering the alternatives to a data driven culture.
How do you know if a strategy is working? Feeling?
How can you feel a cash flow statement? How can you feel conversions happening? How can you feel aggregate engagement on a mobile app?
You can’t feel these things on their own.
You can feel the results of decisions taken on those things. Growing cash flow may manifest itself in the form of more people around the office. More conversions on the website may translate to a happier set of people. But you can’t feel a balance sheet, cashflow statement, or the effectiveness of a website.
The digital world generates data, and it’s through data that we experience a lot of the world. What we choose to do with those experiences forms the basis of intelligence.
There are a lot of choices with respect to how people choose to experience data.
There’s 5.972 × 10^24 kg of data in support of the fact that the Earth is an oblate spheroid — a squashed sphere. You may feel as though the world is flat based on your personal experience. Now, if you choose to disregard the data that conflicts with your personal feelings, if that’s the way you turn data into knowledge, then that’s fine. To each their own. Live and let live. And what strategic difference does it make to a majority of people anyways? Does intelligence matter when it isn’t salient to a decision set?
The scientific method, at its best, is recursive and very effective at transforming data into intelligence. There is some literature about how social institutions slow it down (Kuhn), but by and large, its pretty effective.
Folks can feel otherwise all they want.
The data supports the effectiveness of the scientific method.
If data driven cultures are inherently scientific, as I will argue in this series, then why even consider anything less?
Posts in this series include: