How bad decisions get the green light
The dashboard on the wall of the conference room refreshed and as if on cue, my direct report and I exchanged a knowing glance. In an instant, we both realized that he was right. The decision I made amounted to a mess that now needed to be cleaned up, likely with my team having to work over the next few weekends.
Without exchanging a word, we had an entire conversation through eye contact:
Him: “I told you this would happen, why didn’t you believe me?”
Me: “I didn’t have enough information to take the risk”
Him: “Like I said, no one ever listens to me.”
Me: “We’ll talk about this at our next one on one.”
Having spent a fair amount of time as a leader in a startup environment, I’ve had more of these moments than I care to admit. So how does this happen?
Trading one problem for a worse one
As an operations director, I was responsible for costs associated with a portion of our contractor workforce, whom we collectively referred to as “pros.” Think payroll, performance incentives, and equipment. The last few P&Ls showed that costs in my department were rising, and I was beginning to feel the heat from the executives.
Our internal metrics made it clear that lowering our pay rates would be a quick fix, but anytime I brought up the subject with my team, I’d get immediate pushback. I had been on the job for about six months and I was new to this industry.
By contrast, nearly all of my direct reports had years of experience managing the pro workforce, and by the time I arrived, there were very few problems they hadn’t already seen.
The decision that blew up in my face came from trusting the spreadsheet over the experience of my team. I ended up lowering the rates, which promptly led to an exodus of gig workers from our platform, in one of our biggest markets.
The “told you so” look in my direct report’s eyes underscored how I had traded a problem of slowly rising costs for a much worse and more immediate problem: forfeiting revenue due to a lack of workers. The fact that he, and the rest of the team, had to cancel weekend plans to fix the supply problem only compounded their frustration with me.
If this was all so preventable though, why did I decide the way I did?
The doer/decider spectrum
All work, from submitting TPS reports to making the call to launch a new product, falls on what I call the doer/decider spectrum. Where you fall on the spectrum is usually a function of seniority. Executives spend most of their time making decisions while front line workers spend most of their time executing tasks. Middle managers fall in the middle, having to be equally good at both.
Regardless of where you fall on the doer/decider spectrum, being able to crisply state and support your views on the work you influence is key to being effective at your job.
Deciders
Not having enough information or context is a big reason why decision making is hard. While reviewing internal metrics and gathering input from others is a good starting point, arriving at a wise decision in a short amount of time often comes from uncovering options that aren’t immediately clear.
This fact explains why relevant prior experience is so crucial in hiring leaders, and why being oblivious to what you don’t know is so damaging. Sourcing good options can feel squishy and intuitive, but when you look under the hood, much of it comes down to understanding how the problem at hand resembles a problem you’ve engaged with before, and determining how a prior solution might shed light on a way forward today.
The QCE (question, claim, evidence) framework, which I referred to in prior posts as the knowledge architecture, strikes me as an ideal system for sourcing and considering options.
Within the parlance of the framework, the decision at hand can be thought of as a question, and the options up for consideration slot in as claims. Deciding which option to go with then becomes an exercise in assessing the volume and quality of evidence for, or against, each of the claims on deck.
Here’s how my situation would have looked through the QCE framework:
Question: How can I keep costs low while keeping pro satisfaction high?
Claim 1: Lowering pay rates will quickly reduce P&L costs.
Claim 2: Lowering pay rates negatively impact pro satisfaction.
Claim 3: Low pro satisfaction quickly leads to spikes in churn.
Claim 4: It’s less expensive to pay an existing pro more, than to recruit and onboard a new pro to replace them.
Out of the four claims on the table, only claim 1 would lead to any action. Claims 2-4 neatly sum up the push back I was getting from my team, but they also would result in my doing nothing in the eyes of my boss.
What I needed was another proactive option. It would take me an additional six months in the saddle to finally arrive at it:
Claim 5: Significant bottom line cost savings are often available by reducing rework and quality errors in upstream processes.
I discovered Claim 5 from an unrelated initiative having to do with pro onboarding. The executive team had made pro recruiting and enablement an OKR, and I was on the hook to deploy changes to our process.
Had claim 5 been on my mind six months earlier however, I would have seen that there was indeed a large amount of money I could have recovered without having to touch our compensation policy.
Having Claim 5 available would have relieved me from having to choose between two poor options.
Doers
If lack of claims (options) is what dogs the deciders, lack of evidence is what undermines the voice of people who do the actual work.
Going back to my example earlier, even though my team knew the dynamics of the pro workforce inside and out, the reason claims 2 through 4 didn’t persuade me was because there was no proof or examples offered to substantiate them.
Anytime a doer starts a sentence that begins with “I feel” or “this one time” or “that never works”, they’re already undermining their ability to persuade a decider. What we have is a situation where the doer is long on claims and short on evidence.
It’s especially tragic when the doer knows that they’re right, struggles to explain why, and is then instructed to carry out a solution they don’t agree with, only to be “proven right” later on. This is exactly what happened in my case.
The QCE framework offers a solution to this negative cycle. Because of the executional nature of their work, doers spend most of their day wading through a stream of evidence in the form of real world examples that can be used to form opinions (claims) that shed light on questions shared by decision makers.
By continuously gathering these first hand pieces of evidence, and contextualizing them against the dashboards and reports all managers pay attention to, a doer could form persuasive claims about how work ought to be performed and how common problems ought to be solved.
Nothing is better to a decider than a highly informed doer capable of articulating a crisp and well supported suggestion for improving performance.
Here’s how that could have looked in my earlier example:
Claim 2: Lowering pay rates negatively impact pro satisfaction.
Evidence: Pro satisfaction bar chart showing how a new, reduced, payout policy resulted in an immediate dip in NPS scores in the prior year.
Claim 3: Low pro satisfaction quickly leads to spikes in churn.
Evidence: Capacity utilization chart correlating the dip in pro platform availability with a dip in NPS scores.
Claim 4: It’s less expensive to pay an existing pro more, than to recruit and onboard a new pro to replace them.
Evidence: A post mortem illustrating how per-pro acquisition costs eclipse the comparatively modest increase in per-pro payouts.
All of these pieces of evidence were available at the time, but unless they’re gathered within the context of relevant claims, they’re doomed to hide in plain sight. Most doers either lack the training to think along these lines, or lack the systems to capture and catalog the evidence as it comes up.
With credibility built in, and armed with an abundance of relevant evidence, doers who can confidently substantiate their positions quickly stand out as the heroes of the organization. By distinguishing themselves, these doers can supercharge their careers by simply leveraging the information that they’re already interacting with day in and day out.
Conclusion
Regardless of where you fall on the doer/decider spectrum, getting clear on your positions using the QCE framework could lead to a step change in your career trajectory.
Whether it’s having a deep well of clear thinking and reference models to aid in making decisions, or it’s having the infrastructure in place to make your voice the most valuable in the room, growing your personal knowledge base of questions, claims, and evidence is worth the time and effort.
That’s my hypothesis anyway. I’m continuing to experiment with the tooling to make a working QCE system come to life. Be sure to subscribe to follow along as I post updates on how it’s going.
This post is the third in a series focused on how the QCE framework can aid us in the non-academic contexts of business and life. Here are links to the prior posts:
Post 1: Extending the zettelkasten beyond the ivory tower. An experiment.
Post 2: Highlighting too much? Try raising the standard.
Post 4: How an evidence hierarchy can inform your thinking
If you have any ideas, questions, or feedback, I’d love to hear from you. Please feel free to reach me at jon@fallingtosystems.com.