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Blind to Data, Blinded by Data: Better Decision Making Using the FAIRE Model

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A few days ago I came across this Dilbert comic making its way around Facebook, and being pointed out as “sad but true” by those in my network.


Being a data enthusiast myself (not sure if I have quite enough street cred to earn the title of data “geek”), my knee-jerk reaction was to respond with something along the lines of “ZOMG SO TRUE! THOSE IDIOTS!”

But if there’s one thing I’ve learned in my time on the Operations side of a business, it’s that big decisions are rarely that simple. If data was all that mattered, choices as basic as hiring decisions would be based solely on the person with the best cost/qualification ratio. Can’t stand working with them? Suspect they’re better on paper than in person? If data were the end-all, be-all that us analytical folks would love to tout as the answer to the world’s problems, then those factors – important considerations – wouldn’t matter, but they do.

Therefore, my fellow decision makers and decision drivers, instead of being blind to data or being blinded by data, allow me to present an alternative.

The FAIRE Model

I’d like to say that the model I’m about to show you was the culmination of months of study and peer-reviewed research, but to be honest it was one of those ideas that popped into my brain in the shower. That’s right, folks, I thought this up while naked.

FAIRE is an acronym for five factors I look at when I need to evaluate either one thing or compare several things.






Facts & Figures What does the data show?What does evidence prove?What are the factual elements of the scenario? Costs, Defined Processes, Who’s involved, Basic Requirements, What happened


Attitudes & Assumptions What are your gut reactions? What are your instincts telling you? Like? Dislike? Why?


If/Then Scenarios & Ideas What are some possible ways this may play out? How could this evolve? What are some potential risks and rewards? Short-term play out, long term play out, what happens if it goes wrong?


Related & Relevant What are some other factors that may influence this? Competition, Seasonality, Positioning, Politics, Branding, Strategy, Experience, Geography, Demographics, Psychology, Morale, Relationships, History


End Result What happens now? What’s the next step? Go, No Go, How Go

The weight of those components will vary from person to person. By using this model, you eliminate (or reduce) blind spots and biases and make more thorough decisions.

FAIRE in Action

While it’s pretty easy to see how you may use this in a comparative decision like hiring, or process/tool evaluations, let’s apply it to something a bit more challenging. Rather than a comparative model, we’ll use this to get a comprehensive view of a single scenario in order to understand it and determine potential courses of action.


Joe Blow, the contact for Client X, having no experience in digital marketing, misinterprets some data in their AdWords account, and freaks out. What’s the situation, and how do we triage?


Account is performing at $70 CPA, down from $100 before we began managing. Target CPA is $70, so we are 100% to goal, which shows that has hit optimal balances between efficiency and volume. We also have 100% impression share. Joe’s background is in traditional media. He has no experience with AdWords but now has access to the account.


Joe believes Paid Search is simplistic, and that changing keyword positions are the only lever that affects his program. He also came from an agency that did Paid Search as a small part of their overall business, thus believes he has an elite understanding of managing a PPC program. In practice, this has not proven to be true.


If Joe assumes program is under-performing, agency needs to respond. If we don’t correct interpretations, Joe escalates to management. The further it escalates, the harder it is to triage, and it becomes harder to discuss, because the more stakeholders involved, the harder it is to explain to all relevant parties. Ultimately ends with us losing the client. If, however, we are able to triage and correct his understanding, we reiterate to Joe and company exactly how well we understand digital and why they have us managing their program in the first place This could lead to a greater trust level, and eventually, additional business.


This is actually not the first time Joe has misinterpreted data. In that scenario, it escalated to management, but we were able to show that Joe’s fears were misdirected. So, Joe has damaged the relationship between himself and his management, as well as between himself and the agency. So any triage that we propose can’t be worse Joe’s relationship with management, as that is already on shaky ground.


The end result is that we need to reiterate to Joe the complexities of search, and our understanding of them. We also need to illustrate that escalation-without-understanding on Joe’s part has cost both sides time, money, and trust, and should not be the first approach taken in the future if Joe has concerns.

Not the easiest scenario to address, but if it were an easy scenario, you wouldn’t need to use a framework to process the information through.

So there you have it. The FAIRE model. How would you use it?

What’s YOUR take?

In the end, this is a model that works for me and the scenarios and decisions I encounter (at work or otherwise). Can you see it working for you? Try it, and let me know if it helps give you a clearer view on your next strategic decision.