Conclusion: A Decision is Not a Problem

Balancing Scale

In July of 2017 I wrote the third in a series of blog posts about cognitive bias (see Part 1 and Part 2). We had just worked through a long process of redesigning our product around cognitive bias in an effort to work more closely with our clients and to help them make better decisions.

That process grew out of the acknowledgment that what we do is complicated, and the data science underpinnings of our processes can be hard for non-advertising people to understand, almost entirely because they just don’t do it every day.

how do we Make it Better?

Before the overhaul, the first draft of our reporting process felt that way. We would present a sometimes overwhelming amount of data to our clients about campaign performance, and then ask them to make decisions based on that information. Those decisions always involve money. Many of our clients are small businesses and nonprofits, so it is easy to understand how these decisions about money can easily become emotionally charged.

The goal in redesigning our process was to empower our clients to make objective, smart decisions about how to spend their money — the allocation of resources in service of business goals. My intention, in July of 2017, was to write a final blog about our cognitive bias project which brought everything together. I am now writing that final blog post in November of 2018, about a year and a half into working through our new process with clients.

The good news: the transition has been largely successful. We redesigned our data and performance reporting to surface the information that is most relevant and useful to each client, and we did so in a format we can standardize at a baseline and then customize for each client’s needs and goals. This even informed how we pitch, and has positively influenced how we integrate creative work into a campaign structure. Our clients have given us overwhelmingly positive feedback about the main process outcome of the overhaul — the Co-Lab Session — which is the new structure of our campaign performance and measurement reporting in a regular monthly meeting format.

Now that the new process is well and firmly entrenched, I have been thinking about where we started. A creative business is just like any other small business, in that we often find ourselves building the plane on the way up. You design a process, see how it works, and try to improve it however you can, to whatever end you’re looking for. There’s no instruction manual, so with the best information you have at the time, you make decisions and solve problems. And in thinking about those two actions — making decisions and solving problems — I was able to see something a year and a half later I couldn’t see when we started our cognitive bias project.

Decisions Are Not Problems

People often conflate the concept of “decision” and the concept of “problem” and even use these words interchangeably. This is destructive if you are trying to establish an environment for objective decision-making, and I think this is emblematic of what was happening: we were presenting our clients with decisions to make, but we were presenting them in a context which made them seem like problems.

In a mathematical context, a problem is a challenge, a puzzle requiring skill, effort, and time to solve. Outside of math, a problem is “a matter or situation regarded as unwelcome or harmful and needing to be dealt with and overcome.” The design thinking of presenting a formidable amount of statistical information, and then expecting someone to be capable of making anything other than a value-laden, emotionally-charged decision, is inherently flawed. That decision will always feel like a problem, and that’s why the process had to change.

Problems involve decisions, but decisions do not have to be problems. If we isolate decisions from their intangible, psychological, cognitively-weighted environments, we can achieve a borderline Zen-like approach. Some problems melt away when you consider them objectively, or as a series of possibilities, capabilities, and resultant decisions.

For example:

  • If there is something I can do to solve a problem, then I can go ahead and make the decision to be proactive and do something.

  • If there’s nothing I can do to solve a problem, then I don’t have to make a decision.

In the moment of consideration about what’s possible, of considering a literal step into what can I do, we distance ourselves from the problem by actively seeking a decision opportunity. Then, once we have made the decision to do something, we weigh the options for action with all the considerations of risk and probability separated by at least one step from the emotional stress of the problem itself. Now we aren’t talking about the problem, we’re talking about what to do about the problem.


So, in redesigning a process to help our clients make better decisions, we actually provided them with the opportunity to make a decision at all, as opposed to presenting them with a problem to solve. I think that’s why it’s been a successful project.

I hope this opens a few cracks in your own problems, helps you break them down into decisions, and eases your path to action.