You are a natural-born problem solver. From the moment you were born, you’ve solved problems. Hungry? Start crying. Learning to walk? Stand up, take a step, fall over, repeat. Want to grow your business? Fall in love with a problem, then solve it more delightfully than anyone else.
Did you notice the slight shift in how you solve problems?
Initially, you solved problems on your own. As communication became easier, you started working with others. Now, you instinctively collaborate to solve complex problems, assembling teams to tackle challenges together.
But research indicates your instincts are wrong. In fact, while collaboration can be beneficial for gathering information, it hinders the process of developing innovative solutions. This counterintuitive finding has significant implications for how teams approach problem-solving.
What a Terrorism Study Reveals About Your Team
In a 2015 study, researchers used a simulation developed by the U.S. Department of Defense to examine how collaboration impacts the problem-solving process. 417 undergrads were randomly assigned to 16-person teams with varying levels of “interconnectedness” (clarity in their team structure and information-sharing permissions) and asked to solve aspects of an imaginary terrorist attack scenario, such as identifying the perpetrators and target. Teams had 25 minutes to tackle the problem, with monetary incentives for solving it quickly.
Highly interconnected teams “gathered 5 percent more information than the least-clustered groups because clustering prevented network members from unknowingly conducting duplicative searches. ‘By being in a cluster, individuals tended to contribute more to the collective exploration through information space—not from more search but rather by being more coordinated in their search,’”
The Least Interconnected teams developed 17.5% more theories and solutions and were more likely to develop the correct solution because they were less likely to “copy an incorrect theory from a neighbor.”
How You Can Help Your Team Create More Successful Solutions
You and your team rarely face problems as dire as terrorist attacks, but you can use these results to adapt your problem-solving practices and improve results.
Work together to gather and share information. This goes beyond emailing around research reports, interview summaries, and meeting notes. “Working together” requires your team to take action, like conducting interviews or writing surveys, with one another in real-time (not asynchronously through email, text, or “collaboration” platforms).
Start solving the problem alone. For example, at the start of every ideation session, I ask people to spend 5 minutes privately jotting down their ideas before group brainstorming. This prevents copying others’ theories and ensures all voices are heard. (not just the loudest or most senior)
Invite the “Unusual Suspects” into the process. Most executives know that diversity amplifies creativity, so they invite a mix of genders, ages, races, ethnicities, tenures, and industry experiences to brainstorming sessions. While that’s great, it also results in the same people being invited to every brainstorm and, ultimately, creating a highly interconnected group. So, mix it up even more. Invite people never before invited to brainstorming into the process. Instead of spending a day brainstorming, break it up into one-hour bursts at different times of the day.
Are You Willing to Take the Risk?
For most of your working life, collaboration has been the default approach to problem-solving. However, this research suggests that rethinking when and how to leverage collaboration can lead to greater success.
Making such a change isn’t easy – it invites skepticism and judgment as it deviates from the proven “status quo” process.
Are you willing to take that risk, separating information gathering from solution development, for the potential of achieving better, more innovative outcomes? Or will you remain content with “good enough” solutions from conventional methods?
“Time is a flat circle. Everything we have done or will do we will do over and over and over and over again – forever.”
– Rusty Cohle, played by Matthew McConaughey, in True Detective
For the whole of human existence, we have created new things with no idea if, when, or how they will affect humanity, society, or business. New things can be a distraction, sucking up time and money and offering nothing in return. Or they can be a bridge to a better future.
As a leader, it’s your job to figure out which things are a bridge (i.e., innovation) and which things suck (i.e., shiny objects).
Innovation is a flat circle
The concept of eternal recurrence, that time repeats itself in an infinite loop, was first taught by Pythagoras (of Pythagorean theorem fame) in the 6th century BC. It remerged (thereby proving its own truth) in Friedreich Nietzsche’s writings in the 19th century, then again in 2014’s first season of True Detective, and then again on Monday in Jamie Dimon’s Annual Letter to Shareholders.
Mr. Dimon, the CEO and Chairman of JPMorgan Chase & Co, first mentioned AI in his 2017 Letter to Shareholders. So, it wasn’t the mention of AI that was newsworthy. It was how it was mentioned. Before mentioning geopolitical risks, regulatory issues, or the recent acquisition of First Republic, Mr. Dimon spends nineparagraphs talking about AI, its impact on banking, and how JPMorgan Chase is responding.
Here’s a screenshot of the first two paragraphs:
He’s right. We don’t know “the full effect or the precise rate at which AI will change our business—or how it will affect society at large.” We were similarly clueless in 1436 (when the printing press was invented), 1712 (when the first commercially successful steam engine was invented), 1882 (when electricity was first commercially distributed), and 1993 (when the World Wide Web was released to the public).
Innovation, it seems, is also a flat circle.
Our response doesn’t have to be.
Historically, people responded to innovation in one of two ways: panic because it’s a sign of the apocalypse or rejoice because it will be our salvation. And those reactions aren’t confined to just “transformational” innovations. In 2015, a visiting professor at Kings College London declared that the humble eraser (1770) was “an instrument of the devil” because it creates “a culture of shame about error. It’s a way of lying to the world, which says, ‘I didn’t make a mistake. I got it right the first time.’”
Neither reaction is true. Fortunately, as time passes, more people recognize that the truth is somewhere between the apocalypse and salvation and that we can influence what that “between” place is through intentional experimentation and learning.
JPMorgan started experimenting with AI over a decade ago, well before most of its competitors. As a result, they “now have over 400 use cases in production in areas such as marketing, fraud, and risk” that are producing quantifiable financial value for the company.
It’s not just JPMorgan. Organizations as varied as John Deere, BMW, Amazon, the US Department of Energy, Vanguard, and Johns Hopkins Hospital have been experimenting with AI for years, trying to understand if and how it could improve their operations and enable them to serve customers better. Some experiments worked. Some didn’t. But every company brave enough to try learned something and, as a result, got smarter and more confident about “the full effect or the precise rate at which AI will change our business.”
You have free will. Use it to learn.
Cynics believe that time is a flat circle. Leaders believe it is an ever-ascending spiral, one in which we can learn, evolve, and influence what’s next. They also have the courage to act on (and invest in) that belief.
What do you believe? More importantly, what are you doing about it?
AI is NOT a substitute for person-to-person discovery conversations or Jobs to be Done interviews.
But it is a freakin’ fantastic place to start…if you do the work before you start.
Get smart about what’s possible
When ChatGPT debuted, I had a lot of fun playing with it, but never once worried that it would replace qualitative research. Deep insights, social and emotional Jobs to be Done, and game-changing surprises only ever emerge through personal conversation. No matter how good the Large Language Model (LLM) is, it can’t tell you how feelings, aspirations, and motivations drive their decisions.
Then I watched JTBD Untangled’s video with Evan Shore, WalMart’s Senior Director of Product for Health & Wellness, sharing the tests, prompts, and results his team used to compare insights from AI and traditional research approaches.
In a few hours, he generated 80% of the insights that took nine months to gather using traditional methods.
Get clear about what you want and need.
Before getting sucked into the latest shiny AI tools, get clear about what you expect the tool to do for you. For example:
Provide a starting point for research: I used the free version of ChatGPT to build JTBD Canvas 2.0 for four distinct consumer personas. The results weren’t great, but they provided a helpful starting point. I also like Perplexity because even the free version links to sources.
Conduct qualitative research for me: I haven’t used it yet, but a trusted colleague recommended Outset.ai, a service that promises to get to the Why behind the What because of its ability to “conduct and synthesize video, audio, and text conversations.”
Synthesize my research and identify insights: An AI platform built explicitly for Jobs to be Done Research? Yes, please! That’s precisely what JobLens claims to be, and while I haven’t used it in a live research project, I’ve been impressed by the results of my experiments. For non-JTBD research, Otter.ai is the original and still my favorite tool for recording, live transcription, and AI-generated summaries and key takeaways.
Visualize insights:Mural, Miro, and FigJam are the most widely known and used collaborative whiteboards, all offering hundreds of pre-formatted templates for personas, journey maps, and other consumer research templates. Another colleague recently sang the praises of theydo, an AI tool designed specifically for customer journey mapping.
Practice your prompts
“Garbage in. Garbage out.” Has never been truer than with AI. Your prompts determine the accuracy and richness of the insights you’ll get, so don’t wait until you’ve started researching to hone them. If you want to start from scratch, you can learn how to write super-effective prompts here and here. If you’d rather build on someone else’s work, Brian at JobsLens has great prompt resources.
Spend time testing and refining your prompts by using a previous project as a starting point. Because you know what the output should be (or at least the output you got), you can keep refining until you get a prompt that returns what you expect. It can take hours, days, or even weeks to craft effective prompts, but once you have them, you can re-use them for future projects.
Defend your budget
Using AI for customer research will save you time and money, but it is not free. It’s also not just the cost of the subscription or license for your chosen tool(s).
Remember the 80% of insights that AI surfaced in the JTBD Untangled video? The other 20% of insights came solely from in-person conversations but comprised almost 100% of the insights that inspired innovative products and services.
AI can only tell you what everyone already knows. You need to discover what no one knows, but everyone feels. That still takes time, money, and the ability to connect with humans.
Run small experiments before making big promises
People react to change differently. Some will love the idea of using AI for customer research, while others will resist with. Everyone, however, will pounce on any evidence that they’re right. So be prepared. Take advantage of free trials to play with tools. Test tools on friends, family, and colleagues. Then underpromise and overdeliver.
AI is a starting point. It is not the ending point.
I’m curious, have you tried using AI for customer research? What tools have you tried? Which ones do you recommend?
Unintended consequences often catch us off guard despite their predictability. The moment they occur, we gasp in shock, shake our heads, and look at each other in wide-eyed horror at this thing that just happened that we could never ever ever have anticipated.
Yet, when (if) we do an After-Action Review, we often realize that these consequences were not entirely unforeseeable. In fact, had we anticipated them, we might have made different decisions.
The Unintended Consequences of Spreadsheets
In 1800 BCE, ancient Babylonians started recording data by scratching grids and columns onto clay tablets, and the spreadsheet was born. Over the millennia, we went from clay tablets to papyrus to parchment and then paper.
Fast forward to 1963 when R. Brian Walsh of Marquette University ported the Business Computer Language (BCL) program to an IBM 7040, and electronic spreadsheets became a reality. The introduction of VisiCalc by Apple in 1979 revolutionized spreadsheet capabilities, followed by Lotus 123 and Microsoft Excel. Today, spreadsheets are ubiquitous in education, business operations, financial markets, budgeting, and even personal inventories.
Unintended yet predictable consequences
While spreadsheets have undoubtedly enhanced efficiency and accuracy compared to traditional methods like clay tablets or hand-drawn tables on parchment, their ease of use has inadvertently led to complacency.
We stopped engaging in a multi-millennial habit of discussing, debating, and deciding before making a spreadsheet. We started flippantly asking people to create spreadsheets and providing little, if any, guidance because “it’s easy to make changes and run scenarios.”
This shift resulted in a reliance on automated models and a lack of shared assumptions or analytical rigor in decision-making processes.
Of course, these behaviors were never intended. They were, however, very predictable.
Research spanning disciplines as varied as network scientists, anthropology, neuropsychology, and paleontology shines a light on how truly predictable we are.
Emotions before Reason: Ask someone if they make decisions based on their motivations, aspirations, and fears and use data to justify the decisions, and they’ll tell you no. Ask them the last time someone else made a decision that “made no sense,” and you’ll listen to a long list of examples.
Small gains now are better than big gains later: Thoughtfully planning before using solutions like spreadsheets, word processing, email, and instant messaging could save us time at work and help us get home 30 minutes earlier or work a few hours less on the weekend. But saving a few seconds now by brain-dumping into Word, setting up a “flexible” spreadsheet, and firing off a text feels much better.
Confidence > Realism: We’ve all been in meetings where the loudest voice or the most senior person’s opinion carried the day. As we follow their lead, we ignore signs that we’re wrong and explain away unexpected and foreboding outcomes until we either wake up to our mistakes or adjust to our new circumstances.
Predict the 93%. Create for the 7%
Acknowledging the predictability of human behavior is not an endorsement of stereotypes but a recognition of our innate cognitive processes. By incorporating this understanding into design, innovation, and decision-making processes, we better anticipate potential outcomes and mitigate unintended consequences.
While 93% of human behavior may follow predictable patterns rooted in evolutionary instincts, focusing on the remaining 7% allows for the exploration of unique behaviors and novel solutions. By embracing both aspects of human nature, we can navigate challenges more effectively and anticipate a broader range of outcomes in our endeavors, leading to informed decision-making and value creation.
Now, if I could only get Excel to stop auto-converting numbers into date/time format.
You want to make life better for others. This desire is reflected in the optimism and positivity of your language – create value, love the problem, and delight the customer. But making life better requires change, and, as the adage goes, “People want change, but they don’t want to be changed.”
You are confident that the solution you created will make life better and that the change people need to make is quite small and painless, well worth the dramatic improvement you offer. Yet they resist. No amount of explaining, showing, convincing, or cajoling changes their mind. What else can you do?
To quote Darth Vader, “Give yourself to the Dark Side. It is the only way to save your friends.”
“If only you knew the power of the Dark Side…”
The Dark Side is populated by “negative” emotions like anger, fear, and frustration, which are incredibly powerful.
Consider that:
Negative events are remembered more accurately and in greater detail than positive events
Unfortunately, these are also some of the first emotions experienced when confronting change.
Change requires people to let go of what they know in exchange for the promise of something better. This immediately triggers Loss Aversion, the cognitive bias in which the pain of losing is psychologically twice as powerful as the pleasure of gaining.
As a result, people won’t let go of what they know until the pain of holding on becomes unbearable. When you point out the problems and pain of the current situation, you help people understand and experience the unbearableness of the current situation.
“Anger, fear, aggression; the Dark Side of the Force are they”
Not every “negative” emotion elicits the same behavior, so carefully choose the one to tap into.
Fear motivates people to seek safety, which can be good if your solution truly offers a safer alternative. It’s a motivator used well by companies such as Volvo, SimpliSafe, and Graco. But lean on it too much, and people may feel overwhelmed and remain frozen to the status quo.
Anger motivates people to take risks, which can be good when the change requires bold decisions and dogged persistence. It can be great when it bonds people together to achieve a shared goal or protect a common value. Apple used this emotion to brilliant effect in its famous “1984” commercial announcing the launch of Macintosh. But incite too much anger, and things can get broken and not in a helpful way like Apple’s ad.
Frustration, one of the emotions that often drives aggression, is anger’s polite little sister. When people feel frustrated, they’re likely to act, persistently pursue solutions, and creatively approach and overcome obstacles. But if the change is big, feels scary, and puts their sense of self at risk, frustration isn’t powerful enough to convince people to let go of the old and embrace the new.
“If you start down the dark path, forever will it dominate your destiny.”
Yoda is incredibly wise, but he gets this one wrong. Using the Dark Side to speak to people’s “negative” emotions doesn’t doom you to a life or career of fear-mongering or inciting violence. Start here, don’t stay here.
Multiple research studies show that positive emotions, like hope and joy, are more powerful than negative ones in maintaining motivation and even enable more creative thinking and problem-solving. By speaking to both negative and positive emotions, the Dark Side and the Light, you enable change by giving people a reason to let go of the past and a future worth reaching for.
When people stop resisting and start reaching to the future you’re offering, change happens, and you realize that Yoda was right, “Luminous beings are we, not this crude matter.”
Most customer research efforts waste time and money because they don’t produce insights that fuel innovation. Well-meaning businesspeople say they want to “learn what customers want,” yet they ask questions better suited to confirming their own ideas or settling internal debates. Meanwhile, eager consumers dutifully provide answers despite the nagging belief that they’re being asked the wrong questions.
It doesn’t have to be this way. In fact, you can get profound revelations into consumers’ psyche, motivations, and behaviors if you do one thing – channel your inner Elmo.
First, a confession
I find Elmo deeply annoying. I grew up watching Sesame Street, and I still get an astounding amount of joy watching Big Bird, Mr. Snuffleupagus, Cookie Monster, Bert and Ernie, Grover, and Oscar the Grouch (especially when Oscar channels his inner Taylor Swift).
Elmo moved to Sesame Street in 1985, and it hasn’t been the same since. He’s designed to reflect the mental, emotional, and intellectual capabilities of a 3.5-year-old, and, in that aspect, his creators were wildly successful. I fully acknowledge that Elmo plays a vital role in the mission of Sesame Street and that people of all ages love Elmo. But Elmo makes my ears bleed, and I will never be ok with the fact that Elmo refers to himself in the third person.
This is why my recommendation to channel your inner Elmo is shocking and extremely serious.
Next, an explanation
On Monday, Elmo posted on X (yes, the minimum age limit is 13, but his mom and dad help him run the account, so it’s apparently okay), “Elmo is just checking in! How is everybody doing?”
180 million views, 120,000 likes, and 13,000 comments later, it was clear that no one was okay.
And lest you think this was Gen Z trauma dumping on their ol’ pal Elmo, Dionne Warwick, T-Pain, and Today Show anchor Craig Melvin responded with their struggles. Comments ranged from, “Mondays are hard” to “Elmo I’m gonna be real I am at my f—ing limit,’ to “Elmo each day the abyss we stare into grows a unique horror. one that was previously unfathomable in nature. our inevitable doom which once accelerated in years, or months, now accelerates in hours, even minutes. however I did have a good grapefruit earlier, thank you for asking.”
Wow. Thank goodness for that grapefruit.
There are a lot of theories about why Elmo’s post touched a nerve – it’s January and we’re tired, it’s easier to share our struggles online than in person, or we still enjoy “that wholesome and sincere bond from childhood that makes us want to share.”
I’m sure all those are true, and I think it’s something more, something we can all learn and do.
Now, the secret
Elmo may be a red, hairy, 3.5-year-old muppet. Still, he nailed the behaviors required to get people to open up and share their inner worlds – the very thoughts, beliefs, and motivations that enable others to create and offer impactful and innovative solutions.
Here’s what Elmo did (and you should, too):
Show that you’re genuinely curious: Elmo didn’t open with the standard “How are you?” that if answered with anything other than the socially acceptable “Fine,” results in awkward silence and inner panic. Elmo opened by declaring his intent – checking in – and then asked a question. Because of that, we understood his motivation was genuine, and he wanted an honest answer.
Ask open-ended questions: Elmo didn’t ask a closed question that can be answered with yes or no. He asked a question that allowed people to share as much or as little as they wanted and that could act as a springboard to a deeper conversation.
Listen silently and without judgment: Elmo didn’t follow up his original tweet with options like “Are you doing ok, or not ok, or are you happy, or sad, or mad, or…” Elmo asked a question and then listened (read the responses) without jumping back into the conversation or firing off follow-up questions.
Acknowledge and thank the person sharing: On Tuesday, Elmo responded but not by skipping off to the next scheduled post. He acknowledged the response by opening with, “Wow! Elmo is glad he asked!” He didn’t share his opinion or immediately ask another question. Instead, he thanked people for sharing, acknowledged that he heard their responses, and was grateful.
Do something with what was shared: Even if you do #4, it’s tempting to move on to the next question. Don’t. Elmo didn’t. Instead, he wrote that he “learned that it is important to ask a friend how they are doing.” He also wrote that he “will check in again soon, friends! Elmo loves you.” You don’t have to profess your love but do respond with what you learned and what it makes you wonder.
People can’t tell you what to create because they don’t know what you know. But they can tell you the problems they have. If you’re willing to listen (just don’t talk about yourself in the third person, you’re not a muppet).
