Turn your maybe into might. The power of questionable thinking

Philosophy academy
Any organisation can be stymied by slack-jawed thinking reinforced by unblinking data. Introducing a different type of analytical thought leadership can reduce uncertainty, mitigate risk, and uncover opportunities in your brand strategy.

To be clear, when we say, “questionable thinking”, we are not talking about putting out controversial or problematic opinions into the world. Rather we’re talking about the kind of thinking that invites challenge, and indeed, thrives on being challenged. Our type of questionable thinking means interrogating long-accepted practices and reconsidering the usual methods of ideation.

Why is it important? In today’s information-rich age it can be difficult to adequately understand all the details on any given topic, and important decisions can be left to paralysis by analysis and decision by committee.

So too can organisational hierarchy and culture affect the ability to forge ahead. Be it the ‘illusion of confidence’, the ‘security of authority’ or, more bluntly, the ‘blanket of bullshittery’, there are many ways a project can be derailed by the pitfalls of a personality.

In our experience, questionable thinking creates the kind of space where the outside-the-box ideas, the zigs-to-everyone-else’s-zags, and all those other creative cliches can be found. Neurobiologists refer to it as ‘divergent thinking’ and it is a favourite tool of creative folks, whether their medium is music or marketing, pottery or poetry.

However, when applied beyond the pursuit of creative ideas, questionable thinking can also yield results in surprising areas. We considered how the approach can be applied to more procedural marketing and branding activities.

Let’s take research and analytics for instance, which is a space that can be so dry it’s almost desiccated. But it’s also one where a marketing team can turn a good question into a great source of strength for the organisation – where a new perspective can provide an effective alternative to “the computer says no”.

Bring questionable thinking into your analytics

Today’s information-rich digital environment has empowered marketing and advertising like never before. Data about customer behaviour and campaign performance can be sucked out from all platforms in the most granular of detail and reconstituted in an array of automated, shiny-looking graphs.

Shiny graph

While this deluge of data is obviously useful to marketers, it can also bog us down. How often do you find yourself trapped in the weeds of Time to Purchase stats and obscure corners of your site’s page reach numbers? By applying questionable thinking, marketers can parse all the relevant details on any given area of interest.

Be data-driven —but also be data sceptical

By all means, use the rich information gained through data analysis as a basis for marketing discussions. But remember, they’re just numbers. And while we humans have this innate desire to “see the raw figures” when we need to make a decision and like to reassure each other that the “numbers don’t lie”, hard numbers can be a lot softer than we realise.

In their book Calling Bullshit: The Art of Scepticism in a Data Driven World, Carl Bergstrom and Jevin West unpick the way numbers, despite their solidity and apparent objectivity, can be used to manipulate. They use a classic joke to illustrate:

A mathematician, an engineer, and an accountant are applying for a job. They are led to the interview room and given maths problems to solve. The first problem is a warm-up: What is 2 + 2? The mathematician rolls her eyes, writes the numeral 4, and moves on. The engineer pauses for a moment, then writes “Approximately 4.” The accountant looks around nervously, then gets out of his chair and walks over to the fellow administering the test. “Before I put anything in writing,” he says in a low whisper, “what do you want it to be?”

Calling bullshit 1
Source: Calling Bullshit: The Art of Skepticism (2020) https://www.callingbullshit.org/

Increasingly, marketing decisions can be made for us by the algorithms and the AI built into digital tools like email marketing services or online shopping platforms. That’s, if we let them.

Here it pays to remember that these tools were made by humans, with all their inherent biases and fallibility, and that the overall human experience is one of truly extraordinary possibility and potential. It’s also worth reminding ourselves that they want us to keep paying for the tools, so we can expect an element of selection bias to be at work, cherry-picking the most positive statistics to showcase.

So, while the hype around AI that broke in 2022 (and continues to grow as we experiment with AI-charged applications), remember there are some jobs that are best left to humans — particularly where judgement and discretion are required.

Be ruthlessly precise about what you want to know

After all, you’re the one who decides what information is worth paying attention to. Amongst the slew of percentages, numbers, red and green arrows; embedded in the filtering options and behind the automated suggestions for improving your ranking for this acronym or another, is what you actually want to know. This will most likely be linked to the goals set for the quarter, so narrow your focus accordingly.

Choose to look at the metrics that offer tangible evidence against the goals set. When interrogating results of a campaign or initiative, often the simple questions are the most revealing. It’s hard to lose with a question like, “to what extent did activity X contribute to goal Y?”

The questionable thinking here is deciding what to ask because, ultimately, where you look determines what you see. Take the time to be deliberate in choosing where to look.

Once a data set is selected and you’re about to dig in, it’s important to listen to your hunches. Perhaps you’re wondering what keeps long-term customers active and want to apply the findings to other groups. Or maybe a particular demographic didn’t respond to a campaign as expected and you suspect you know why. Try to articulate the hunch using the parameters of your measurement system.

Lastly, don’t forget the qual. Graphs, numbers and up-down arrows are all great, but qualitative data can flesh out the sketch drawn by your quantitative data analysis. For many people, a focus group or long-winded survey is what pops to mind when talking about qualitative research. Fortunately, there are now a myriad of ways to gather this information without the use of a clunky and time-consuming process.

Want to be challenged by some questionable thinking? We’re always keen to provide a new perspective. Get in touch.

More articles

Social gif
Article thumbnail v2
Thinking GIF