Is Your Data-Driven Organization Heading into a Lake?

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​.office​quotes​.net/​n​o​4​-​0​2​.​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.