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Smarter Risk Taking

GUEST POST from Janet Sernack

After founding ImagineNation™ in Israel, I invested a year of my time and considerable money in taking what I thought were smart risks to invent an experiential business game. This involved collaborating with one of the top game design companies to co-create a live business simulation incorporating innovative gamification elements intending to teach corporations how to be innovative.

To my shock and surprise at the time, my invention initially failed!

Despite being an adult and experiential learning specialist and having designed and facilitated hundreds of corporate learning games for some of Australia’s top 100 companies over twenty-five years. It felt really horrible, and it was a visceral, heartbreaking, shameful and ego-destroying experience that I would not want anyone, anywhere, ever to experience.

Deep Learning Experience

Yet, it became a profound learning experience, enabling me to understand how:

My imposter syndrome played a significant self-sabotaging role. It did not set me up for success, nor did it set me up for maximising the importance of self-efficacy and self-mastery when on an innovation roller-coaster ride.
I had not undertaken sufficient research studies to determine if users wanted and were ready to accept such a radical innovation. Nor had I noticed how much the corporate learning market was being disrupted by technology, causing significant time and budget constraints, that I had neglected to address.
I had not paused long enough to consider, anticipate, plan and mitigate the risks involved in prototyping a viable minimal product in a new market.
I had not considered the risks involved with collaborating with a new consulting partner and co-facilitator, as well as with a new client. Nor anticipated how to resolve the values conflict that erupted when the project failed.
I had not fully understood the process involved in iterating and pivoting a new invention and the time it would take to produce a commercially viable product that the market would understand, be ready for, and respond to.

Finally, it seems that I had unconsciously fallen victim to the innovative start-up entrepreneur’s curse – falling in love with my product!

This was generated by my excitement, enthusiasm and energy of the possibilities rather than balancing these courageously and compassionately with the:

Harsh realities to be innovative.
Vital role of smart risk-taking and experimentation.
What ‘fails fast, to learn quickly’ really means at the heart (emotional), head (cognitive) and gut (visceral) levels.

Value of Failing Fast

They say that people need to teach what they need to learn themselves.

This valuable failure enabled me to invest the next ten years in learning to make sense of innovation and what it means to be innovative, including:

Helped me develop self-efficacy, trust my inner knowing and judgement, and make a stand for myself in the face of opposition and criticism I often received when presenting at a global conference on the people side of innovation, especially by process engineers.
Investing more attention, time in iterating and pivoting, testing and validating the two-day business simulation MVP to make it more tangible, simpler and teachable.
Acknowledging that technology had accelerated sufficiently to accept that the original creative idea of a simple hybrid board game was the most valuable commercial option that could make the difference I wanted to make in the world.
Becoming more patient, self-compassionate, and courageous in smart risk-taking and leading, coaching, and engaging in team innovation and continuous learning through various innovation, entrepreneurial and intrapreneurial learning initiatives.

Iterating and Pivoting

I iterated, pivoted, and refined my intellectual property by presenting and bespoking the Coach for Innovators, Leaders and Teams Certified Program™ for over twelve years to global change-makers.

Most importantly, I reined in my competitive, risky and restless saboteur and focused on doing just one thing, which has finally morphed into a book, supported by a board game to teach people how to be innovative and develop an innovation mindset.

Taking Risks

In the fog of a globalised, disrupted, unpredictable and increasingly uncertain world, no innovation can progress, and no one can be innovative without smart risk-taking.

No innovation can improve without rigorous experimentation, where learning mainly happens by doing things to explore, discover, and know what not to do.

Research has shown that most successful new business ventures abandoned their original business strategies when implementing their initial plans, learned what would and would not work in the market, and conserved sufficient resources to have a second or third stab at getting it right.

Trial and Error and Cause and Effect

Innovation is a never-ending, risky, adaptive process involving trial and error and understanding cause and effect.

Because people are fearful of making mistakes and the negative consequences of failure, innovation requires leadership to develop both foresight and prospection skills to:

Empower and enable them to paradoxically take both a strategic and systemic perspective and a human-centred approach.
Equip them to be innovative when designing business ventures and transformation initiatives that deliver commercially viable outcomes to successfully improve the quality of people’s lives that are appreciated and cherished.

Risk-taking is a Choice

In most businesses and organizations, innovation involves taking considerable risks, especially if seeking to enter a new market with a new product. It is compounded and resisted by many people in organizations because they are too focused on personal survival, personal gain, short-term gain and shareholder return.

Unfortunately, many organizations end up, paradoxically, undermining their organization’s capacity to be innovative, adapt, innovate and grow. Mainly due to their people being disengaged, resistant to change, lacking agency and being held back by bureaucracy and hierarchy that is averse to smart risk-taking and experimentation.

The Future is Permissionless

Because most people generally do not have permission, and are not allowed to make mistakes. They are not encouraged to try new things, so they become risk-averse, avoidant, oppositional and conventional, and don’t feel safe in deviating from the accepted way of doing things.

This is commonly known as the ‘status quo’ and drives people to comply with ‘what is’ (even when it no longer matters) and not apply their human ingenuity, be innovative and create new inventions from ‘what could be’ possible and through smart risk-taking to partner with AI in delivering innovative solutions in a disruptive world of complexity and unknowns.

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Is Disruption About to Claim a New Victim?

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Kodak. Blockbuster. Google?

GUEST POST from Robyn Bolton

You know the stories. Kodak developed a digital camera in the 1970s, but its images weren’t as good as film images, so it ended the project. Decades later, that decision ended Kodak. Blockbuster was given the chance to buy Netflix but declined due to its paltry library of titles (and the absence of late fees). A few years later, that decision led to Blockbuster’s decline and demise. Now, in the age of AI, disruption may be about to claim another victim – Google.

A very brief history of Google’s AI efforts

In 2017, Google Research invented Transformer, a neural network architecture that could be trained to read sentences and paragraphs, pay attention to how the words relate to each other, and predict the words that would come next.

In 2020, Google developed LaMDA, or Language Model for Dialogue Applications, using Transformer-based models trained on dialogue and able to chat.

Three years later, Google began developing its own conversational AI using its LaMDA system. The only wrinkle is that OpenAI launched ChatGPT in November 2022.

Now to The Financial Times for the current state of things

“In early 2023, months after the launch of OpenAI’s groundbreaking ChatGPT, Google was gearing up to launch its competitor to the model that underpinned the chatbot.

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The search company had been testing generative AI software internally for several months by then. But as the company rallied its resources, multiple competing models emerged from different divisions within Google, vying for internal attention.”

That last sentence is worrying. Competition in the early days of innovation can be great because it pushes people to think differently, ask tough questions, and take risks. But, eventually, one solution should emerge as superior to the others so you can focus your scarce resources on refining, launching, and scaling it. Multiple models “vying for internal attention” so close to launch indicate that something isn’t right and about to go very wrong.

“None was considered good enough to launch as the singular competitor to OpenAI’s model, known as ChatGPT-4. The company was forced to postpone its plans while it tried to sort through the scramble of research projects. Meanwhile, it pushed out a chatbot, Bard, that was widely viewed to be far less sophisticated than ChatGPT.”

Nothing signals the threat of disruption more than “good enough.” If Google, like most incumbent companies, defined “good enough” as “better than the best thing out there,” then it’s no surprise that they wouldn’t want to launch anything.

What’s weird is that instead of launching one of the “not good enough” models, they launched Bard, an obviously inferior product. Either the other models were terrible (or non-functional), or different people were making different decisions to achieve different definitions of success. Neither is a good sign.

“When Google’s finished product, Gemini, was finally ready nearly a year later, it came with flaws in image generation that CEO Sundar Pichai called ‘completely unacceptable’ – a let-down for what was meant to be a demonstration of Google’s lead in a key new technology.”

“A let-down” is an understatement. You don’t have to be first. You don’t have to be the best. But you also shouldn’t embarrass yourself. And you definitely shouldn’t launch things that are “completely unacceptable.”

What happens next?

Disruption takes a long time and doesn’t always mean death. Blackberry still exists, and integrated steel mills, one of Clayton Christensen’s original examples of disruption, still operate.

AI, LLMs, and LaMDAs are still in their infancy, so it’s too early to declare a winner. Market creation and consumer behavior change take time, and Google certainly has the knowledge and resources to stage a comeback.

Except that that knowledge may be their undoing. Companies aren’t disrupted because their executives are idiots. They’re disrupted because their executives focus on extending existing technologies and business models to better serve their best customers with higher-profit offerings. In fact, Professor Christensen often warned that one of the first signs of disruption was a year of record profits.

In 2021, Google posted a profit of $76.033 billion. An 88.81% increase from the previous year.

2022 and 2023 profits have both been lower.

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How Eavesdropping Can Unlocked Exponential Growth

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How Eavesdropping Can Unlocked Exponential Growth

GUEST POST from Robyn Bolton

It’s easy to get caught up in the hunt for unique insights that will transform your business, conquer your competition, and put you on an ever-accelerating path to growth. But sometimes, the most valuable insights can come from listening to customers in their natural environment. That’s precisely what happened when I eavesdropped on a conversation at a local pizza joint. What I learned could be worth millions to your business.

A guy walked into a pizza place.

Last Wednesday, I met a friend for lunch. As usual, I was unreasonably early to the local wood-fired pizza joint, so I settled into my chair, content to spend time engaged in one of my favorite activities – watching people and eavesdropping on their conversations.

Although the restaurant is on the main street of one of the wealthier Boston suburbs, it draws an eclectic crowd, so I was surprised when a rather burly man in a paint-stained hoodie flung open the front door. As he stomped to the take-out order window, dust fell from his shoes, and you could hear the clanging of tools in his tool belt. He placed his order and thumped down at the table next to me.

A Multi-Million Dollar Chat

He pulled out his cell phone and made a call. “Hey, yeah, I’m at the pizza place, and they need your help. Yeah, they hate their current system, but they don’t have the time to figure out a new one or how to convert. Yeah, ok, I’ll get his number. Ok if I give him yours. Great. Thanks.”

A few minutes later, his order was ready, and the manager walked over with his pizza.

Hoodie-guy: “Hey, do you have a card?”

Manager: “No, I don’t. Something I can help you with?”

H: “I just called a friend of mine. He runs an IT shop, and I told him you’re using the RST restaurant management system, and you hate it…”

M: “I hate it so much…”

H: “So my buddy’s business can help you change it. He’s helped other restaurants convert away from RST, and he’d love to talk to you or the owner.”

M: “I’m one of the co-owners, and I’d love to stop using RST, but we use it for everything – our website, online ordering, managing our books, everything. I can’t risk changing.”

H: “That’s the thing, my friend does it all for you. He’ll help you pick the new system, set it up, migrate you from the other system, and ensure everything runs smoothly. You have nothing to worry about.”

M: “That would be amazing. Here’s my direct line. Have him give me a call. And if he’s good, I can guarantee you that every other restaurant on this street will change, too. We all use RST, and we all hate it. We even talked about working together to find something better, but no one had time to figure everything out.”

They exchanged numbers, and the hoodie guy walked out with his pizza. The manager/owner walked back to the open kitchen, told his staff about the conversation, and they cheered. Cheered!

Are You Listening?

In just a few minutes of eavesdropping, I uncovered a potential goldmine for a B2B business – 15 frustrated customers, all desperate to switch from a system they hate but unable to do so due to time and resource constraints. The implications are staggering – an entire local market worth tens of millions of dollars ripe for the taking simply by being willing to listen and offer a solution.

As a B2B leader, the question is: are you truly tapping into the insights right in front of you? When was the last time you left your desk, observed your customers in their natural habitat, and listened to their unvarnished feedback? If you’re not doing that, you’re missing out on opportunities that could transform your business.

The choice is yours. Will you stay in your office and rely on well-worn tools, or venture into the wild and listen to your customers? Your answer could be worth millions.

Image credit: Pixabay

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Learning to Innovate

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Learning to Innovate

GUEST POST from Janet Sernack

One of my coaching clients shared with me recently how she was feeling insecure in her job role and lacking motivation. The company she works for is acknowledged as an entrepreneurial industry leader. Because it is currently being challenged by poor sales performance, it has hunkered down and frozen any change initiatives, learning programs or new projects until mid-2025. My client is in a substantial Research and Development function, crucial to innovation, so we aimed to explore new ways of helping the company use their existing equipment (capital investments) and resources (people and expertise) to design and deliver low-cost and sustainable innovations to the market. To create a focused, meaningful, purposeful role and a values-based motivating opportunity for my client to be proactive, that impacts the company by adding value to the bottom line by improving productivity and cost efficiency because anyone can learn to innovate.

Learning to innovate

As a result of our short time together, my client felt confident and empowered, motivated and energized, to invest time in learning how to apply her current skills and strengths, focus and attention to connect with key people and resources, explore options globally for identifying new business development opportunities, and in developing her technical skillset.

My client enrolled in an online innovation learning program to learn to innovate by acquiring the fundamentals of mindset and behavior changes to shift their thinking and act differently.

The innovation imperative has shifted

Productivity growth needs to accelerate

According to McKinsey and Co, in the article “Investing in Productivity Growth” it’s not only time to raise investment and catch the next productivity wave; the world needs to and can accelerate productivity growth.

“Productivity growth means getting more from our work and our investments. It is especially needed now as the world faces the many challenges of a new geo-economic era. Productivity growth is the best antidote to the asset price inflation of the past two decades, which has created about $160 trillion in “paper wealth” and even larger amounts of new debt”.

Adapting to the new net zero reality

The world is currently not on track to meet net-zero targets, yet many opportunities are available to accelerate efforts and help meet de-carbonization goals. Whilst some progress has been made to reduce global carbon emissions, under the current trajectory, the world won’t achieve net-zero emissions even during this century. Again, according to McKinsey and Co., in an article “Adapting to the new net-zero reality”, mitigation efforts alone are no longer sufficient – the world will need to adapt as well by going green, ramping up technologies and increasing investments.

Improving cost efficiencies

According to new BCG research, corporate leaders are making better cost management a priority as a hedge against ongoing economic, financial, and political uncertainties, stating that:

“Wholesale cuts are one way to manage costs. However, drastic measures such as sudden workforce reductions may lead to unintended consequences because they fail to address the root causes of inefficiencies. Nor do they position an organization for future success”.

Generative Ai is a critical enabler of innovation

Whether the organization focuses on developing new products, services, processes, or business models, Generative AI (GenAI) can enhance and challenge the work of leaders and teams across all phases of the innovation cycle and process.

By learning to innovate through knowing how to generatively question and listen, reveal and challenge operating beliefs and test assumptions to enable them to emerge, diverge, converge and prioritize high-quality creative ideas for change.

According to BCG in a recent article, “To Drive Innovation with GenAI, Start by Questioning Your Assumptions.”

“GenAI’s most prominent contribution is in idea generation and validation—innovation’s divergence and convergence phases. Yet, it can play an even more critical role in helping leaders confront and update the strategic assumptions at the foundation of their business and innovation strategies: the doubt phase of the cycle. Organizations that regularly question their beliefs are more resilient because they are more likely to see and position themselves to benefit from the shifts on which competitive advantage turns”.

The innovation imperative is paradoxical.

Suppose we combine the contradictory features or qualities of developing productivity growth while adapting to the new net zero reality and improving cost efficiencies. In that case, many organizations have reverted to their conventional, business-as-usual focus, relying on Generative Ai to solve their problems.

This demonstrates a typically faddish response to a revolutionary, transformative new invention whilst being avoidant and resisting the urgent need to change by building the fundamental foundations in learning to innovate.

Thinking and acting differently

Anyone can learn to innovate, and it starts with allowing, accepting and acknowledging that a business-as-usual focus, avoiding risk, making the tough decisions and resisting change are no longer effective, profitable, or sustainable because:

We all know that doing the same thing and expecting a different result is the definition of insanity.
We can no longer afford to keep producing the same results that no one wants.
We can’t solve the problem with the same thinking that created it; we have to learn how to be, think and act differently to deliver the sustainable and innovative solution we want to have.

Learning to innovate requires a radical strategic shift

Harnessing collective intelligence

Anyone can learn to innovate; it’s simply a matter of knowing, combining, leveraging and scaling people’s multiple and collective intelligence – heads/cognition, hearts/emotions and hands/actions.

Revealing and closing knowing-doing gaps

Then, we should align these to close the significant knowing-doing gap or disconnect between what people know and what people do.

Everyone knows that innovation is the most impactful lever to use to scale and leverage change, yet are primarily unwilling to pause, stop and take time to retreat from their short-term focus, pay attention and reflect on how to equip people with the innovation fundamentals by getting people’s:

Heads to make sense of innovation and what innovation means by defining and framing it in their organization’s unique context, setting a strategic focus, determining the level of risk involved in achieving it, and mitigating the roadblocks that may arise.
Hearts aligned to embody and enact what innovation means by setting and sharing a passionately purposeful reason for innovation, building change receptivity and readiness for designing and delivering a range of bespoke deep learning processes and equipping people to activate it.
Hands dirty by creating a safe environment where people are encouraged to emerge and share creative ideas and permission and be allowed to experiment by making small bets and mistakes and learning by doing to know what not to do.

Innovation requires a strategic and systemic focus

Innovation is subjective and contextual, so it must be defined and framed in an organization’s unique context. It requires a strategic and systemic focus, so an organization needs to agree on whether they will choose an incremental, sustainable or disruptive strategy and the level of risk.

The 21st century requires us to unlearn, learn, and relearn a different set of mindsets, behaviors, and skills, and anyone can learn to innovate.

Commitment and conviction to learn to innovate

It’s only through being committed and having the conviction that my coaching client now has – to explore new ways of helping their organizations use their existing capital investments, collective intelligence, people resources, and expertise, supported by Generative AI and deep learning processes, to design and deliver low-cost and sustainable innovations to the market.

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Nike Should Stop Blaming Working from Home for Their Innovation Struggles

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GUEST POST from Robyn Bolton

“But even more importantly, our employees were working from home for two and a half years. And in hindsight, it turns out, it’s really hard to do bold, disruptive innovation, to develop a boldly disruptive shoe on Zoom.” – John Donahoe, Nike CEO

I am so glad CNBC’s interview with Nike’s CEO didn’t hit my feed until Friday afternoon. It sent me into a rage spiral that I am just barely emerging from. Seriously, I think my neighbors heard the string of expletives I unleashed after reading that quote, and it wasn’t because it was a lovely day and the windows were open.

Blaming remote work for lack of innovation is cowardly. And factually wrong.

I’m not the only one giving Mr. Donahoe some side-eye for this comment. “There were a whole bunch of brands who really thrived during and post-pandemic even though they were working remotely,” Matt Powell, advisor for Spurwink River and a senior advisor at BCE Consulting, told Footwear News. “So I’m not sure that we that we can blame remote work here on Nike’s issues.”

There’s data to back that up.

In 2023, Mark (Shuai) Ma, an associate professor at the University of Pittsburgh, and Yuye Ding, a PhD student at the university’s Katz Graduate School of Business, set out to empirically determine the causes and effects of a firm’s decision to mandate a return to work (RTO). They collected RTO mandate data from over 100 firms in the S&P 500, worked backward to identify what drove the decision, and monitored and measured the firm’s results after employees returned to work.

Their findings are stark: no significant changes in financial performance for firm value after RTO mandates and significant declines in employee job satisfaction. As Ma told Fortune, “Overall, our results do not support these mandates to increase firm values. Instead, these findings are consistent with managers using RTO mandates to reassert control over employees and blame employees as a scapegoat for firm bad performance.”

Or to justify spending more than $1B to double the size of its Beaverton, OR campus.

When you start blaming employees, you stop being a leader.

CEOs make and approve big, impactful, complex, high-stakes decisions. That’s why they get paid the big bucks. It’s also why, as Harry Truman said, “The buck stops here.”

Let’s examine some of the decisions Mr. Donahue made or supported that maybe (definitely) had a more significant impact on innovation than working from home two days a week.

Ignoring customers, consumers, and the market: Nike has a swagger that occasionally strays into arrogance. They set trends, steer culture, and dictate the rules of the game. They also think that gives them the right to stop listening to athletes, retailers, and consumers, as evidenced by the recently revealed Team USA Track & Field uniforms, the decision to stop selling through major retailers like Macy’s and Olympia Sports, and invest more in “hype, limited releases, and old school retro drops” than the technology and community that has consumers flocking to smaller brands like Hoka and Brooks.

Laying off 2% of its workforce: Anyone who has ever been through a layoff senses it’s coming months before the announcement and the verdicts are rendered. Psychological safety, feeling safe in your environment, is a required element for risk-taking and innovation. It’s hard to feel safe when saying goodbye to 1500 colleagues (and wondering if/when you’ll join them).

Investing too much in the core: Speaking of safety, in uncertain times, it’s tempting to pour every resource into the core business because the ROI is “known.” Nike gave in to that temptation, and consumers and analysts noticed. Despite recent new product announcements like the Air Max DN, Pegasus Premium, and Pegasus 41, “analysts point out these ‘new’ innovations rely too much on existing franchises.”

Innovation is a leadership problem that only leaders can solve

Being a CEO or any other senior executive is hard. The past four years have been anything but ordinary, and running a business while navigating a global pandemic, multiple societal upheavals, two wars, and an uncertain economy is almost impossible.

Bosses blame. Leaders inspire.

Mr. Donohue just showed us which one he is. Which one are you?

One MORE thing

This is a losing battle, but STOP USING “DISRUPTIVE” INCORRECTLY!!!! “Disruptive Innovation,” as defined by Clayton Christensen, who literally coined the phrase, is an innovation that appeals to non-consumers and is cheaper and often lower quality than existing competitors.

Nike is a premium brand that makes premium shoes for premium athletes. Employees could spend 24/7/365 in the office, and Nike would never develop and launch a “boldly disruptive shoe.”

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Time is a Flat Circle

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Jamie Dimon’s Comments on AI Just Proved It

Time is a Flat Circle

GUEST POST from Robyn Bolton

“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 6^th 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 nine paragraphs talking about AI, its impact on banking, and how JPMorgan Chase is responding.

Here’s a screenshot of the first two paragraphs:

JP Morgan Annual Letter 2017

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?

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Do You Find Growth By Searching, Seeking, or Stalking?

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GUEST POST from Robyn Bolton

Growth is the lifeblood of any organization, and the quest for growth opportunities is not just a strategic imperative. It is a fundamental necessity because the ability to identify and capitalize on opportunities is a game-changer for companies wanting to achieve sustainable success and stay ahead of the competition.

The challenge, however, is that not all opportunities are the same – some are head-smackingly obvious, while others are like trying to nail down JELL-O. Yet companies take a “one size fits all” approach to finding, developing, and capitalizing on them.

SEARCH when need to transform

What do you do when you need information but don’t know precisely what you need and certainly don’t know where to find it? You Google it or, in less-branded terms, you search for it.

When searching for growth opportunities, you’re looking for something but don’t know exactly what you need or where you’ll find it. Finding opportunities requires you to go beyond traditional market analysis and adopt a learner’s mindset to see ways to disrupt the status quo, challenge existing paradigms, and create new value propositions for your customers.

Searching is a creative process that entails investing in R&D, fostering a culture of intrapreneurship, and experimenting with new technologies. It requires a culture of creativity, experimentation, and agility to adapt to changing market dynamics. You have to be willing to be wrong on your way to being right, to move slowly so you can act quickly, and to throw out the timeline to harness the game-changing opportunity.

SEEK when you need to innovate

What do you do when you know what you need and generally where to find it? You seek it out – you go to where you think it will be, and, on the off-chance it’s not there, you pivot to Option B.

When you’re seeking growth opportunities, you have a target in mind but are not 100% sure how to hit it. Maybe you know you want to enter a new geography, but you need to figure out how to do it successfully and avoid the mistakes of previous entrants. Maybe it’s a new industry or category, but you must understand if and how to do it without disrupting your existing business model.

Seeking is both creative and analytical. You look for data and market intelligence, interview experts and individuals, analyze industry trends and explore untapped segments. It also requires you to stay open to surprises and new possibilities and take calculated risks to capitalize on emerging trends or consumer preferences. Like searching, it requires patience. Unlike searching, it respects a deadline.

STALK when you need to improve

Just like a lioness stalking a wildebeest, you do this when you see an opportunity and know exactly how to capture it. Yes, there will be zigs and zags along the way, and an unexpected competitor may pop up. But this is who you are and what you do.

When stalking opportunities, you bring the full value and power of your experience, expertise, resources, and capabilities to bear on an opportunity. This may happen when you’re operating and improving your core business. It may also occur after you’ve searched (and found) an opportunity, sought (and decided on) a strategy, and now you have the confidence to launch and scale.

Do Your Approaches Align with Your Goals?

Most companies say that they want to transform. Still, very few have the patience or intestinal fortitude to search because there is no Google for Transformation that produces the exact plan you need to transform successfully.

Companies also tend to stalk when they want to innovate, leaving opportunities to change the game and build sustainable competitive advantage on the sideline because they’re too uncertain or take too long.

Growth requires all three approaches – search, seek, and stalk – but only happens when your chosen approach aligns with your goals.

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Five Lessons from the Apple Car’s Demise

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Five Lessons from the Apple Car's Demise

GUEST POST from Robyn Bolton

In 2014, rumors started to circulate that Apple was developing a self-driving autonomous car to compete with Tesla. At the end of February 2024, rumors circulated that Apple was shutting down “Project Titan,” its car program. According to multiple media outlets, the only logical conclusion from the project’s death is that this decision signals the beginning of the end of Apple.

As much as I enjoy hyperbole and unnecessary drama, the truth is far more mundane.

The decision was just another day in the life of an innovation.

As always, there is a silver lining to this car-shaped cloud: the lessons we can learn from Apple’s efforts.

Lesson 1: Innovation isn’t all rainbows and unicorns

People think innovation is fun. It is. It is also gut-wrenching, frustrating, and infuriating. Doing something new requires taking risks, which is uncomfortable for most people. Even more challenging is that, more often than not, when you take a risk, you “fail.” (if you learned something, you didn’t fail, but that’s another article).

What you can do: Focus on the good stuff – moments of discovery, adventures when experimenting, signs that you’re making life better for others – but don’t forget that you’re defying the odds.

Lesson 2: More does not mean success

It’s been reported that Apple spent over ten billion dollars on Project Titan and that over 2000 people were working on it before it was canceled. With a market cap of over two trillion dollars, a billion dollars a year isn’t even a rounding error. But it’s still an eye-popping number, which makes Apple’s decision to cut its losses downright courageous.

What you can do: Be on guard for the sunk-cost fallacy. It’s easy to believe that you’ll eventually succeed if you keep working and pouring resources into a project. That’s not true, as Apple experienced. And in the rare cases when it is, executives are often left wondering if the success was worth the cost.

Lesson 3: Pivot based on data, not opinions

At least four different executives led Project Titan during its decade in development, and each leader brought their own vision for what the Apple Car should be. First, it was an electric vehicle with driver assistance that would compete with Tesla. Next, it was a self-driving car to compete with Google’s WayMo. Then, plans for fully autonomous driving were canceled. Finally, the team returned to its original target of matching Tesla’s Level 2 automation.

Changes in project objectives, strategies, and execution plans are necessary for innovation, so there’s nothing obviously wrong with these pivots. But the fact that they tended to happen when a new leader was appointed (and that Jony Ive caused an 18-month hiring freeze simply by expressing “displeasure”) makes me question how data-based these pivots actually were

What you can do: Be willing to change but have a high standard for what is required to cause a change. Data, even qualitative and anecdotal data, should be seriously considered. The opinion of a single executive, not so much.

Lesson 4: Dream big, build small

Apple certainly dreamed big with its aspirations to build a ~~fully~~ semi-autonomous vehicle and it poured billions into developing and testing the sensors, batteries, and partnership required to make it a reality. But it was never all-or-nothing in its pursuit of the automotive industry. Apple introduced CarPlay the same year it kicked off Project Titan, and it continues to offer regular updates to the system. Car Key was announced in 2020 and is now offered by BMW, Genesis, Hyundai, and Kia.

What you can do: Take a portfolio approach towards your overall innovation portfolio (Apple kept working on the iPhone, iPad, Apple Watch, and Vision Pro) and within each project. It’s not unusual that a part of the project turns out to be more valuable than the whole project.

Lesson 5: ___________________________

Yes, that is a fill-in-the-blank because I want to hear from you. What lesson are you taking away from Project Titan’s demise, and how will it make you a better innovator?

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How I Use AI to Understand Humans

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(and Cut Research Time by 80%)

How I Use AI to Understand Humans

GUEST POST from Robyn Bolton

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 under-promise and over-deliver.

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?

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Predicting Unintended Consequences

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The 93% Rule

Predicting Unintended Consequences

GUEST POST from Robyn Bolton

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.

93% of Human Behavior is predictable .

Research spanning disciplines as varied as network scientists, anthropology, neuropsychology, and paleontology shines a light on how truly predictable we are.

Here are some examples:

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.

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