Category Archives: Entrepreneurship

Creating Value from Nothing

GUEST POST from Robyn Bolton

Doing nothing fuels creativity and innovation, but that fuel is wasted if you don’t put it to use. Idleness clears the mind, allowing fresh ideas to emerge, but those ideas must be acted upon to create value.

Why is doing something with that fuel so difficult?

Don’t blame the status quo.

The moment we get thrown back into the topsy-turvy, deadline-driven, politics-navigating, schedule-juggling humdrum of everyday life, we slide back into old habits and routines. The status quo is a well-known foe, so it’s tempting to blame it for our lack of action.

But it’s not stopping us from taking the first step.

We’re stopping ourselves.

Blame one (or more) of these.

Last week, I stumbled upon this image from the Near Future Laboratory, based on a theory from psychologist Mihaly Csikszentmihalyi’s book Flow:

There’s a lot going on here, but four things jumped out at me:

When we don’t have the skills needed to do something challenging, we feel anxiety
When we don’t feel challenged because our skills exceed the task, we feel boredom
When we don’t feel challenged and we don’t have the skills, we feel apathy
When we have the skills and feel challenged, we are in flow

Four different states. Only one of them is positive.

I don’t love those odds.

Yet we live them every day.

Every day, in every activity and interaction, we dance in and through these stages. Anxiety when given a new project and doubt that we have what it takes. Boredom when asked to explain something for the 82^nd time to a new colleague and nostalgia for when people stayed in jobs longer or spent time figuring things out for themselves. Sometimes, we get lucky and find ourselves in a Flow State, where our skills perfectly match the challenge, and we lose track of space and time as we explore and create. Sometimes, we are mired in apathy.

Round and round we go.

The same is true when we have a creative or innovative idea. We have creative thoughts, but the challenge seems too great, so we get nervous, doubt our abilities, and never speak up. We have an innovative idea, but we don’t think management will understand, let alone approve it, so we keep it to ourselves.

Anxiety. Boredom. Apathy.

One (or more) of these tells you that your creative thoughts are crazy and your innovative ideas are wild. They tell you that none of them are ready to be presented to your boss with a multi-million-dollar funding request. In fact, none of them should be shared with anyone, lest they think you, not your idea, is crazy.

Then overcome them

I’m not going to tell you not to feel anxiety, boredom, or apathy. I feel all three of those every day.

I am telling you not to get stuck there.

Yes, all the things anxiety, boredom, and apathy tell you about your crazy thoughts and innovative ideas may be true. AND it may also be true that there’s a spark of genius in your crazy thoughts and truly disruptive thinking in your innovative ideas. But you won’t know if you don’t act:

When you feel anxious, ask a friend, mentor, or trusted colleague if the challenge is as big as it seems or if you have the skills to take it on.
When you feel bored, find a new challenge
When you feel apathetic, change everything

Your thoughts and ideas are valuable. Without them, nothing changes, and nothing gets better.

You have the fuel. Now, need to be brave.

We need you to act.

Image credit: Pexels

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Smarter Risk Taking

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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.

.

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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The Surprising Downside of Collaboration in Problem-Solving

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The Surprising Downside of Collaboration in Problem-Solving

GUEST POST from Robyn Bolton

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?

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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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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?

Image credit: Pixabay

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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?

Image credit: Dall-E via Bing

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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?

Image credit: Unsplash

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Next Generation Leadership Traits and Characteristics

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Next Generation Leadership Traits and Characteristics

GUEST POST from Stefan Lindegaard

What are the traits and characteristics for a new generation of leaders, those who will shape the future in this sea of uncertainty?

To me, this is more about mindset than age. However, the mindset which I hint at below and that I believe we need more of reside well within the younger generation.

Thus, we could see a higher number of younger executives in the coming years even though they lack the leadership experience and skills that have been normal for leaders in their roles. They need to learn fast and hopefully do this while being surrounded with experiences in different ways.

I think this will be most prominent in Asia and even parts of Africa and South America where there is a stronger belief in the future compared to Europe and even the USA with its stronger sentiment of complacency as well as many overwhelming challenges.

Many current executives will of course also develop in good ways so I suggest we look for traits and characteristics in both groups such as:

Holistic point of view (intrapreneurial skills)
Understanding of psychological safety and the growth mindset (and ability to lead with and through this)
Ability to constructively handle conflict
Optimism, passion and drive
Curiosity and belief in change
Tolerance for / ability to deal with uncertainty
Adaptive fast learner with sense of urgency
Talent for networking / strategic influencing

The desired end-game? Leaders who are capable of the almost super-human task of both managing day-to-day activities and shaping the future.

Get the Right People on the Bus

By shaping the future, I mean the ability to thrive with transformation/change, apply new ways of working and improve collaboration capabilities while pursing new business opportunities and innovation.

Just a discussion starter. What do you think?

Image Credit: Pexels, Stefan Lindegaard

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3 Innovation Lessons from The Departed

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3 Innovation Lessons from The Departed

GUEST POST from Robyn Bolton

It’s award season, which means that, as a resident of Boston, I have the responsibility and privilege to talk about The Departed (pronounced: The Dep-ah-ted). The film won the Oscar for Best Picture in 2007 and earned Martin Scorsese his first, and to date only, Academy Award for Best Director. It is also chock-full of great lessons for corporate innovators.

Quick Synopsis

If you’ve seen The Departed, you can skip this part. If you haven’t, why not and read on.

The Departed is loosely based on notorious Boston crime boss Whitey Bulger and features three main characters:

Frank Costello (Jack Nicholson), a vicious and slightly unhinged Irish mob boss
Colin Sullivan (Matt Damon), a Massachusetts State Trooper in the Special Investigation Unit (SIU) formed to catch Costello, who, in his spare time, is a spy for Costello.
Billy Costigan (Leonardo DiCaprio), a police academy recruit who goes undercover to infiltrate Costello’s organization

But wait! There’s more. Alec Baldwin plays Colin’s SIU boss, George Ellerby. Martin Sheen and Mark Wahlberg (who received an Oscar nomination for this role) play Billy’s Mass State Police (MSP) bosses, Captain Queenan and Staff Sergeant Dignam, respectively. Completing the chaos is Vera Farmiga, who plays Madolyn Madden, Colin’s girlfriend and Billy’s court-ordered psychiatrist.

There’s a lot of other stuff going on, but that gives you enough context for the following quotes to hopefully make sense.

Listen to the words people use.

Colin (after Dignam refuses to hand over undercover files): I need those passwords.

Ellerby: No, you want those passwords

It’s not often that Ellerby says something useful, let alone wise, but he nails it with this one. Colin wants the passwords to Dignam’s files on undercover agents because it will make both Colin’s official job of finding Costello’s rat in the MSP and his unofficial job of finding the MSP officer in Costello’s crew easier. He doesn’t need the passwords, however, because, with enough time and effort, he can find the rats he’s looking for.

When we hear from customers that they want something, it’s tempting to run off and create it. But as Ellerby points out, wants and needs are different. Just because customers want something doesn’t mean they are willing to pay for or change their behavior to get and use it.

Figuring out what a customer needs is difficult because it requires them to trust you enough to admit they have a problem they can’t solve. It’s also difficult because most of us have access to solutions to our functional needs (think the bottom few layers of Maslow’s hierarchy). As a result, the needs consumers grapple with tend to be emotional and social, and it’s far more challenging to admit those to a stranger, especially in a focus group or product-focused interview.

How you feel impacts everyone around you

Madolyn (after a counseling session): Why is the last patient of the day always the hardest?

Billy: Because you’re tired, and you don’t give a sh*t. It’s not super-natural.

Billy and Madolyn get off to a rough start in their first counseling session, culminating in Billy asking for a prescription for Valium. Madolyn calls him out for “drug-seeking behavior” and throws two Valiums across the desk before Billy storms out. A few minutes later, Madolyn catches up with Billy, hands him a prescription for Valium, and asks the above question.

Being a corporate innovator can be difficult, sometimes soul-crushing work (ask the good people at Store 8). It can also be thrilling and inspiring. It can even be all those things in one day. That’s what makes it tiring, even when you give a sh*t.

Managing your energy and monitoring your behavior are leadership qualities we don’t discuss often enough. It’s okay to be exhausted after a day of facilitating ideation sessions or intense strategic meetings. It’s normal to be frustrated after a contentious conversation or demotivated when you get bad news. But leaders usually find a way to not take those emotions out on their teams. And, in the rare instance when they punish the team for someone else’s sin, they apologize and explain.

Your job is not your identity.

Billy: Look, I just want my identity back, all right? That’s all.

Colin: All right, I understand. You want to be a cop again.

Billy: No, no, being a cop’s not an identity. I want my identity back.

Towards the end of the film, Billy is tired of working undercover and reports to MSP headquarters to complete the paperwork required to expunge his criminal record and get his identity back. That’s when Colin makes the same mistake most of us make and confuses Billy’s job with his identity.

We spend so much time at work. We rely on our paychecks for so much. We even introduce ourselves to new people using our job titles. It’s easy for your job to feel like your identity, especially when your job aligns so closely with your deeply held beliefs and values. But your job is not your identity. You are still a Tempered Radical, even without your corporate title. You are still an optimistic problem-solver, even when it’s been months since your last brainstorming session.

You are an innovator, even if you don’t have a business card to prove it.

Image credit: RadioTimes.com

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