One of my favorite bloggers/data-geniuses, Kevin MacDonell, wrote a nice post on which I wanted to comment. Unfortunately he turned off comments on his blog (I can’t say I blame him), so I’ll write a post of my own in response.
There are two concepts in Kevin’s post I wanted to respond to:
- Becoming a data driven organization is a journey, not a destination
- Those of us who are already bought in to the data-driven mentality need to speak the language our bosses respond to.
Point 1: Becoming a data-driven organization is a journey, not a destination
I couldn’t agree more with this concept. It’s not enough to just hire a smart data analyst; start generating more reports; create new ways of scoring and analyzing our prospects; send out charts and graphs; etc. These are all tools that help move us in the right direction, but the real impact of a data-driven way of operating is in how we use all of that information to change behavior. What do those reports and charts and graphs show us that presents new opportunities? How do they inform us about our progress and what adjustments we might need to make in light of that progress?
In fact, I would say that being a data-driven organization is not so much about journeying as it is about completely changing how you think about, manage, and do your work. Moving in that direction is indeed a continual journey, and the end result is a rich, pervasive integration of a data-driven mentality.
Point 2: We need to speak the language that others respond to.
Again – agreed. Kevin’s big point is that if we want to convince others of the value of a data-driven mentality, we need to stop trying to get others to learn the language of data and analytics, and start putting data and analytics into their language, particularly for “bosses” and those leading the organization. I would say we need to make this shift in all settings where we are talking about (and using) data.
It seems that every organization has that brilliant data analyst who can go miles deep with his or her knowledge and analyses, and quickly lose the end users in highly technical language. This person is a huge asset with the potential to add tremendous value, but there’s a missed opportunity if we can’t take their good work and make it understandable and immediately relevant.
To be clear, this absolutely is not an issue of end-users being dumb or needing additional education. People simply think in different ways and they value different things. If I’m presenting new information or analysis to someone, and I don’t tailor my message to fit in with how they think and what they think about, far less of my message will resonate. If I’m lucky they’ll ask good questions that force me to reconfigure what I’m saying so they can take in more of it. But more likely a large portion of what I have to say will simply be ignored.
If we want smart data usage to become a regular part of how we do business, it needs to fit with how we all talk about our work, from the top of the organization to the bottom.