In a recent post by Eric Peterson (Web Analytics Demystified), he brought up the interesting topic of what it means to be “data-driven” and proposed that the data-driven business is a myth. He actually went so far as to say, “A ‘data-driven business’ would be doomed to fail.” That’s a bold prediction, and a bit too ominous for me.

Before I get into the subtle semantic differences between being data-informed and data-driven, I’d like to start by focusing on the interpretation that a “data-driven” organization will blindly follow whatever its data tells it to do. In all my years in web analytics consulting, I’ve never run into an organization that is prepared to let the data control the decision making process. Influence – yes. Inform – yes. Inspire – yes. Control – no. It reminds me of an episode from the TV show, “The Office”, where Michael Scott and Dwight Schrute went out to win back lost clients with gift baskets. As they were trying to find a particular client using a GPS device, the following encounter happened between Michael Scott who was driving and his trusted “Assistant to the Regional Manager” Dwight:

GPS: Make a right turn.
Dwight: Wait, wait, wait! No, no, no! It means bear right, up there.
Michael: No, it said right. It said take a right.
Dwight: No, no, no. Look, it means go up to the right. Bear right over the bridge, and hook up with 307.
Michael: Maybe it’s a shortcut, Dwight. It said go to the right. [turns right]
Dwight: It can’t mean that! There’s a lake there!
Michael: The machine knows where it is going!
Dwight: This is the lake!
Michael: The machine knows— stop yelling at me!
Dwight: No, it’s— there’s no road here! [car drives into lake]

http://www.officequotes.net/no4-02.php

Data-driven organizations seek out relevant data to help inform and shape, not dictate or control, their key business decisions. They’re not going to drive into a proverbial lake because their web analytics GPS tells them to – at least not when their business sense or intuition disagrees with the decision. Both logic and intuition (common sense in the case of Michael Scott) are needed and equally important to the decision making process. They can act as valuable checks and balances to each other. Data can reveal when your gut feeling is far askew, and intuition can ground your high-flying calculations in relevant past experience. They work together and need to be balanced.

When I think of being “driven” in anything (family, work, values, etc.), I think of conviction and determination. Having a data-driven mindset is a commitment to ensuring all forms of data are actively contributing to making better business decisions. For me it’s about fixing and correcting an existing imbalance in order to find more equilibrium. Whether we like it or not, business decisions are still predominantly driven by intuition. Data hasn’t had an equal footing at the decision making table – since, well, the dawn of data. It’s still frequently viewed as a nice-to-have, not as a need-to-have. It’s welcomed with open arms when it supports a particular position but can be dismissed and belittled when it doesn’t. By encouraging individuals and organizations to be more data-driven (and accountable), I’m looking for that eye-of-the-tiger hunger for data and insights that still isn’t as prevalent as it should be in our data-rich digital age. By pushing for a data-driven mindset and approach, I’m advocating for data to receive the same level of consideration and appreciation as intuition already receives. It’s definitely not about replacing intuition with data (that’s a false dichotomy) but about getting data a chair at the big people table.

Whenever you have a conflict between the two sides of logic and intuition during decision making, you’d rationally expect people to reconcile the differences in their minds before acting. Regardless of the type of person you are – “data-driven” or “data-informed” – you’ll decide to gather more data if the data appears to be wrong or doesn’t agree with your intuition. On the flip side, a data-driven person will question their assumptions if their intuition feels way off base and the data looks sound. What will the data-informed person do? Probably still question the data if it doesn’t agree with their intuition. That’s the problem. Being data-informed is just too passive or weak. While some people struggle with the semantics of “data-driven”, I struggle with the semantics of “data-informed”. Is someone data-informed if they regularly receive a scheduled report in their Outlook inbox? Do we expect them to have at least looked at the report? Do we expect them to have properly interpreted and understood the report? Do we expect them to be open-minded about considering the data if it contradicts their established views? For me, data-informed creates a weaker standard than data-driven does. Rather than leaning into the data ready to pounce on an optimization opportunity (data-driven), I envision someone leaning back waiting for something obvious to hit them in the face (data-informed).

Logic faces a bigger uphill battle than intuition does in the decision-making process. Consider the metaphor of the Elephant and its Rider put forth by Chip and Dan Heath in their excellent book, “Switch“. Our emotional side is our Elephant and our rational side is our Rider. “Perched atop the Elephant, the Rider holds the reins and seems to be the leader. But the Rider’s control is precarious because the Rider is so small relative to the Elephant. Anytime the six-ton Elephant and the Rider disagree about which direction to go, the Rider is going to lose.”

If the Rider is reduced to being just a back-seat driver or an informed passenger to the Elephant, you know who is ultimately going to decide the path. At some point the Elephant may get impatient and will act without data. In my view, a data-driven approach needs to respect the strengths of the Elephant (speed, energy, creativity, and relevant experience) and be cautious of its weaknesses (biases, fears, simplistic heuristics, and mismatched experience). In most cases, the Elephant and the Rider want to get to the same destination; they just disagree on the route sometimes. Working together with a data-driven emphasis will ensure the Elephant’s intuition receives the proper rigor, scrutiny, and discipline from the Rider in order to safely and efficiently reach the final destination. Essentially, a rational “data-driven” approach can help to calibrate a decision maker’s intuition over time and increase awareness for when gut feelings should and shouldn’t be followed, increasing the likelihood of successful outcomes. The Elephant will walk all over a more passive, data-informed Rider.

For most companies, becoming more data-driven is a long-term goal, which requires focus on important key areas such as people, processes, and technology. Do we avoid data if it causes us to be paralyzed in our decision making? No, we figure out ways to maximize the benefits of data while minimizing its drawbacks. For many companies, data is a real competitive advantage that some firms are leveraging and others are not. I hope that by lowering the target from becoming data-driven to being satisfied with merely data-informed, organizations don’t lose momentum or fall short of their original vision for organizational success. Knowing Eric, I think he’s trying to make us think a little more rigorously about the phrases we use and the positions we take. In my mind, the data-controlled business is the real myth, while the data-driven organization is still a desirable standard.

3 comments
John Hunter
John Hunter

Data driven does not mean you remove judgement (though many act as it does). Data driven mean you use data and when you are making a judgement you use data (and notice when you are not doing so). It isn't as simple as just looking at a spreadsheet and acting based on what numbers you see. You have to understand what the numbers mean. You have to know how they were collected. You have to understand when the numbers seem to be wrong. As an example, when I was, first getting an organization to try and use data a supervisor gave me data on phone calls. The data was obviously wrong. It showed far more calls than I knew were handled in that office. A supervisor needs to know their business. But their reaction was that we were suppose to use data now, this is the data. Anyway I went and talked to the person collecting the data, they counted a phone call, then if another came in they put #1 on hold and counted the next one, put #2 on hold went back to #1 and counted it again (3 now), then another came put #1 on hold... The numbers were at least inflated by 200-300%. You must understand the data and make sure the data is telling you what you need to know to make decisions. Software often leads people to believe the numbers presented are somehow super valid as a computer gave the number. This is dangerous. People need to understand the data and far too often people don't. That is a serious problem.

Brent Dykes
Brent Dykes

Philip, I'm glad the post resonated with you. I agree with you that acting on the data can be a huge challenge for many companies. Being data-driven needs executive and company-wide commitment because data won't generate any value on its own if it's not acted upon. Cheers, Brent.

Philip
Philip

I agree wholeheartedly. Arguments about semantics just detract from more important conversations. There isn't a company out there that implements an analytics tool and then puts the business on autopilot. In fact, it seems to be quite the opposite. The biggest concern of many companies, when it comes to analytics, seems to be both getting and applying actionable data.