Why This Book Exists
Kristen Cox and Yishai Ashlag wrote The World of Decorating the Fish because they kept seeing the same pattern everywhere: smart organizations investing massive resources into initiatives that produced marginal improvements. Busy teams. Impressive presentations. Negligible results.
Their central metaphor is perfect: we’re decorating raw fish instead of cooking it. We’re making things look better without making them be better.
I’ve read Drucker, Collins, Sinek, Clear, and a dozen other management thinkers. They all circle the same problem from different angles. Cox and Ashlag name it directly and give you a diagnostic framework to spot it in your own organization.
Here’s what they taught me.
The Diagnostic: Are You Decorating the Fish?
Cox and Ashlag give you clear signals. If any of these sound familiar, you’re decorating:
“It’s complicated”

If you or your team respond to questions with “it’s complicated,” you’re decorating the fish. Complexity is often a smoke screen for unclear thinking. Real clarity is simple enough that anyone can understand it.
Chasing technology for technology’s sake
“If you believe that rushing to embrace technological trends is innovative, you are decorating the fish.”

I see this constantly. Organizations adopt AI, cloud, or the latest platform without asking: What customer limitation does this remove? New technology with old practices doesn’t create breakthroughs. It creates expensive chaos.
They’re blunt: “Technology frequently brings the promise of increased productivity and efficiency, but it can also introduce complexity into processes and compound problems… It can also make the workflow invisible, which hides the source of backlogs, quality issues and needless tasks.”
Targeting measures you can’t control
“The more removed an organization is from the goal it pursues, the lower the impact it will have. If your organization is targeting measures it cannot directly impact, then it is likely decorating the fish.”
How many times have I seen teams measured on outcomes they can’t influence? You’re measured on “customer satisfaction” but have no control over pricing, product features, or support staffing. That’s not accountability. That’s theater.
Living on lag indicators
“If your organization is focused on lag indicators that do not provide real-time feedback, it is likely decorating the fish.”
Lag indicators tell you what happened. They’re autopsies. By the time you see the number, it’s too late to fix it. You need lead measures—the daily or weekly actions that predict the outcome.
Massive investment, marginal improvement
“If your organization is making significant investments of either time or money into an initiative but is getting marginal improvements, then it is likely decorating the fish and not addressing the core problem.”

This one hits hard. We launch a six-month organisation wide initiative. Spent serious budget. Got a 3% improvement. We decorated the fish beautifully, but we never addressed the real constraint.
The Three Classic Traps
1. No Clear Goal
Cox and Ashlag are ruthless here:
“If you have to try to explain what your goal means, you are fish decorating. If you have no way to determine if you are making progress towards the goal, you are fish decorating. If your strategy is your goal you are decorating the fish.”
They give you the test for a real goal. It must have four elements:
Most organizational goals fail at least two of these. “Be the market leader in customer experience.” Sounds great. Means nothing. What does success look like Tuesday? No one knows.
2. Confusing Strategy with Goals
This is everywhere. Teams present their strategy, “we’ll implement agile, adopt AI, restructure the team” and call it a goal.
Strategy is how. Goals are what. If your goal is your strategy, you have no goal.
3. Solutions That Mirror Problems
“When the solution mirrors the problem, you are likely decorating the fish. For example, we fight addiction with another form of addiction, or respond to cost-cutting with more cost-cutting, or try to solve a lack of jobs with incentivizing jobs. Trying to get what we lack is not the solution.”
This is subtle but devastating. We’re behind schedule, so we add more meetings to coordinate. We have quality issues, so we add more inspection steps. We’re moving slowly, so we add more process to “ensure rigor.”
The solution looks like the problem. We’re adding complexity to solve complexity.
What Actually Works
Start with the customer’s primary need
Cox and Ashlag insist: “Distinguish between the customer’s primary and secondary needs using their perspective.”
Not what you think they need. Not what’s easy to measure. What they actually need, in their language, from their perspective.
This forces clarity. Your customer doesn’t need “a robust ticketing system with AI-powered routing.” They need “my problem solved in under four hours.”
Set ambitious targets
“Setting ambitious targets and going after big improvements will force you to redefine the problem.”
Small targets let you optimize current processes. Big targets force you to question whether you’re solving the right problem at all.
If you’re trying to reduce support tickets by 5%, you’ll optimize your current system. If you’re trying to reduce them by 50%, you have to ask: Why are people filing tickets in the first place?
Focus on what you can directly impact
Measure things your team can actually change through their daily work. If you can’t draw a straight line from their actions to the measure, pick a different measure.
Find the real constraint
Stop decorating. Find the one thing that, if removed, would unlock disproportionate improvement. That’s where your energy goes. Everything else is decoration.
Why This Book Matters Now
I’ve read the management classics. Drucker taught me about objectives and results. Collins taught me about clarity and understanding. Clear taught me about systems. Sinek taught me about infinite games.
Cox and Ashlag gave me the diagnostic.
They gave me language to spot the pattern in real time: “We’re decorating the fish.” They gave me questions to ask: “Can you directly impact that measure?” “Is this technology removing a customer limitation?” “Are we getting marginal returns on major investment?”
In an era of AI hype, digital transformation initiatives, and agile everything, this book is the necessary counterweight. Before you adopt the next technology, launch the next initiative, or restructure the team, ask:
Are we cooking the fish, or just making it prettier?
The Bottom Line
Most organizations are decorating. Impressive activity. Marginal results. Cox and Ashlag show you how to spot it, why it happens, and what to do instead.
The real question isn’t whether you’re busy.
It’s whether the fish is actually cooked.
Book Details:
The World of Decorating the Fish by Kristen Cox and Yishai Ashlag
As the year ends, 2025 was a year of profound learning. This year’s reading list provided a profound exploration of human behavior, societal structures, and personal effectiveness. The collective insights challenged me to rethink my own motivations (Drive, Flow) and irrationalities (Predictably Irrational), while exposing the hidden systems of power that shape our world (Caste, The World is Flat, Apple in China). A recurring theme in all my reads this year is the power of strategic focus and questioning assumptions, whether in personal growth (The Achievement Habit), innovation (Blitzscaling, Decorating the Fish), or simply in what we choose to care about (The Subtle Art of Not Giving a F*ck). From the vastness of space (Starry Messenger) to the intimacy of a mother’s love (Shyamchi Aai) and the resilience of the human spirit (The Martian, I Who Have Never Known Men), these books collectively serve as a guide to navigating my complex inner and outer worlds with more wisdom, purpose, and clarity.
Row 1
Never Be Sick Again (Raymond Francis)
The World of Decorating the Fish (Kristen Cox & Yishai Ashlag)
Drive (Daniel H. Pink)
Wise Animals (Tom Chatfield)
The Very Secret Society of Irregular Witches (Sangu Mandanna)
The Change Maker’s Playbook (Amy J. Radin)
Row 2
Dust (Hugh Howey)
Death of the Author (Roland Barthes)
Predictably Irrational (Dan Ariely)
Flow (Mihaly Csikszentmihalyi)
Games People Play (Eric Berne)
Caste (Isabel Wilkerson)
Row 3
Blitzscaling (Reid Hoffman)
Tiny Experiments (Anne-Laure Le Cunff)
The Achievement Habit (Bernard Roth)
The Practicing Mind (Thomas M. Sterner)
I’m Just Saying (Milan Kordestani)
The Martian (Andy Weir)
Row 4
The Hundred Years’ War on Palestine (Rashid I. Khalidi)
The Last Queen (Chitra Banerjee Divakaruni)
Butter (Asako Yuzuki)
The Subtle Art of Not Giving a F*ck (Mark Manson)
Useful, Not True (Derek Sivers)
I Who Have Never Known Men (Jacqueline Harpman)
Row 5
श्यामची आई (Shyamchi Aai) (Sane Guruji)
The Intelligent Investor (Benjamin Graham)
Kashmir: The Case for Freedom (Various Authors)
Lord of Light (Roger Zelazny)
A Minute to Think (Juliet Funt)
The Art of Laziness (Library Mindset)
Row 6
Apple in China (Wei-Ting Yen)
Change is the Only Constant (Ben Orlin)
Decisions Over Decimals (Christopher Frank, et al.)
Starry Messenger (Neil deGrasse Tyson)
The World Is Flat (Thomas L. Friedman)
The 9/11 Commission Report (National Commission on Terrorist Attacks)
though the year coming to end, the reading will continue, you can join me on Goodreads, to share your reading list as well as inspire me for more wisdom seeking reads.
https://www.goodreads.com/user/show/36302373-sumit

I couldn’t look away from the Titan documentary. As someone who’s spent years building teams and pushing technological boundaries, watching Stockton Rush’s (CEO OceanGate, died in his last submarine dive) journey felt uncomfortably familiar. The relentless drive, the impatience with bureaucracy, the absolute conviction that you’re revolutionizing an industry—I’ve been there. But somewhere in that familiar entrepreneurial passion, Rush crossed a line that cost five people their lives.
The Seductive Power of Visionary Thinking
Rush wasn’t a villain—he was a visionary who lost his way. His dream of democratizing deep-sea exploration was genuinely inspiring. For decades, only government-funded missions could reach the Titanic’s depth of 12,500 feet. Rush wanted to change that, making the impossible accessible to civilians willing to pay $250,000 for the experience.
The problem wasn’t his vision; it was how completely he became it.
The Data Tell the Story: According to maritime safety records, properly certified deep-sea vessels have a failure rate of less than 0.1%. Experimental, uncertified vessels? The numbers are staggeringly different—failure rates approach 15-20% in extreme depth applications. Rush knew these statistics but convinced himself his carbon fiber innovation would beat the odds.
This is what psychologists call “optimism bias”— (Read more) the tendency to overestimate positive outcomes while underestimating risks. Research by Nobel laureate Daniel Kahneman shows that entrepreneurs exhibit this bias at rates 3-4 times higher than the general population. It’s what makes us start companies against impossible odds, but it’s also what can make us ignore flashing red warning lights.
The Regulatory Rebellion: Understanding Both Sides
I get Rush’s frustration with certification bodies. I’ve watched brilliant innovations die slow deaths in regulatory purgatory. The FDA takes an average of 12 years to approve breakthrough medical devices. Aviation certification can stretch beyond a decade. When you’re burning through investor capital and your team is depending on you, these timelines feel like innovation killers.
Rush chose to operate in international waters specifically to avoid U.S. Coast Guard oversight. His argument? “Innovation doesn’t happen when you have to follow restrictive regulations.” On the surface, it’s compelling.
But here’s what the data actually show: Industries with robust safety regulations don’t just save lives—they often accelerate long-term innovation. The aviation industry, heavily regulated since the 1950s, has achieved remarkable safety improvements while continuously advancing technology. Commercial aviation fatality rates have dropped 95% since 1970, even as air travel increased 10-fold.
Companies like SpaceX prove you can work within regulatory frameworks while still pushing boundaries. SpaceX conducted over 50 successful launches before their first crewed mission, working closely with NASA throughout. Their approach: “Regulation as a design constraint, not a roadblock.”
When Expertise Becomes the Enemy
Perhaps the most troubling aspect of Rush’s story was his systematic dismissal of expert warnings. Multiple deep-sea engineers, including his own employees, raised concerns about the Titan’s carbon fiber hull design. Industry veterans warned that carbon fiber, unlike steel or titanium, doesn’t fail gradually—it fails catastrophically, with no warning.
Rush’s response? He fired critics and publicly stated that industry experts were “uninspiring” and stuck in old ways of thinking.
The Psychology Behind This: Research from Harvard Business School shows that as entrepreneurs become more successful, they increasingly discount external advice. It’s called “expert blindness”—the more passionate we become about our vision, the less we hear dissenting voices. In a study of 847 startup failures, 34% could be traced directly to founders ignoring critical technical feedback from domain experts.
This hits close to home for any leader who’s ever built something from scratch. You become so emotionally invested in your creation that criticism feels like personal attacks. But in safety-critical applications, this emotional attachment can literally be deadly.
The Success-Fame Convergence Trap
What struck me most about Rush’s interviews was how intertwined his personal identity had become with OceanGate’s success. He wasn’t just building a submersible company—he was becoming the visionary who would change deep-sea exploration forever. His LinkedIn described him as a “Innovator, explorer, and entrepreneur revolutionizing ocean access.”
The numbers paint a clear picture: According to venture capital data, founder-led companies where the CEO maintains more than 60% equity ownership have 40% higher failure rates in safety-critical industries. When personal wealth and reputation become completely tied to a single product’s success, rational risk assessment becomes nearly impossible.
Jeff Bezos spoke about this phenomenon at a leadership conference in 2019: “The moment you think you are your company, you stop making decisions in the company’s best interest. You start making decisions to protect your ego.”
Building Better Safety Cultures: What Actually Works
So how do we maintain entrepreneurial drive while protecting the people who trust us with their lives? I’ve seen effective approaches across multiple industries:
The Titan wasn’t just an engineering failure—it was a leadership failure that cost five lives. As entrepreneurs and executives, we must learn from Rush’s mistakes before we repeat them in our own domains. Because in the end, no innovation is worth destroying the trust people place in our judgment.
The next time you see a leader who is calm, steady, and quietly resilient, give them the ultimate compliment: call them a donkey.
Today, I visited a petting farm and learned about the characteristics of donkeys. Contrary to popular belief, which often associates the term “dumb” with donkeys, I discovered that they are not only hardworking but also possess exceptional intelligence and discipline. Donkeys are meticulous creatures who take pride in maintaining a clean and organized environment. They naturally assume the role of leaders within their families, providing protection and guidance to their loved ones. When engaged in their tasks, donkeys exhibit unwavering focus and dedication, demonstrating their remarkable capabilities. This made me curious about what I can learn from them.
While lions get the glory and eagles soar in leadership metaphors, the donkey, often mischaracterized as stubborn, embodies the most practical and effective leadership traits. This misunderstood animal demonstrates systematic thinking, unwavering focus, and methodical execution that modern CXOs and executives desperately need.
Donkeys never just charge forward. They pause, assess the terrain, calculate the load, and check if the path is safe. Once convinced, they move forward with calm assurance.
For leaders:
• Build decision frameworks instead of relying on gut calls.
• Use tools like pre-mortems and go/no-go gates before committing resources.
Once a donkey commits to a path, it doesn’t get distracted. No noise, no glamour—just step after step until the goal is reached.
For leaders:
• Set clear, measurable objectives each quarter.
• Use OKRs to keep teams aligned.
• Create “mission filters” so you only pursue what truly matters.
Donkeys don’t sprint. They move steadily, balancing energy and endurance. And because of that, they rarely burn out.
For leaders:
• Prioritize sustainable pace over short-lived bursts.
• Focus on compound growth, not just hockey-stick projections.
• Adopt Kanban or continuous delivery to encourage steady progress.
Donkeys carry impressive loads for their size—but they know their limits. If overloaded, they simply refuse to move. That’s not stubbornness; it’s wisdom.
For leaders:
• Protect your team from being overburdened.
• Define capacity clearly and say “no” when necessary.
• Delegate wisely instead of piling work on the same shoulders.
Leadership isn’t about charisma or brute force. It’s about focus, resilience, and knowing your limits. In other words, leading like a donkey.
Donkeys aren’t impulsive. They pause, assess the ground, and only move when it’s safe. They don’t burn themselves out sprinting, but they keep going, step after step—until the job is done. They carry heavy loads, but they also know when to stop and refuse more. That isn’t stubbornness; it’s wisdom about limits. And when they lead, it’s not through noise or force, but through presence, protection, and quiet guidance.
In a world where leaders often confuse speed for progress and noise for impact, we could use more donkey-like qualities: patience, focus, endurance, and balance.
So yes—when you meet a leader like that, don’t flatter them with the usual metaphors. Look them in the eye and give them the highest praise you can: “You lead like a donkey.”
The race to “solve all diseases” has begun, and AI is leading the charge.

Something remarkable is happening in pharmaceutical labs around the world. For the first time in history, drugs designed entirely by artificial intelligence are about to be tested in humans. Alphabet’s Isomorphic Labs will begin these groundbreaking trials in 2025, marking a potential turning point in how we discover new medicines.
Think about it: after decades of painstaking trial-and-error in drug discovery, we’re now watching AI systems design potential cures in a fraction of the time. Demis Hassabis, the Nobel Prize-winning CEO behind this breakthrough, believes we’re finally within reach of “solving all diseases.”
Here’s what traditional drug discovery looks like:
Imagine you’re searching for a needle in a haystack—except the haystack is the size of a football stadium, and you’re not even sure what the needle looks like. That’s essentially what pharmaceutical companies have been doing for decades.
The Traditional Timeline:
Now picture having a super-intelligent assistant that can scan the entire haystack in minutes, identify exactly what you’re looking for, and even suggest improvements. That’s what AI is doing for drug discovery.
Isomorphic Labs compressed this entire process to about four years—and they’re just getting started.
While Isomorphic Labs grabbed headlines, they’re not alone in this race. Other companies are achieving even more dramatic speed improvements:
The Speed Leaders:
What used to take nearly a decade now happens in 1-4 years. In some cases, it’s even faster. This isn’t just incremental improvement—it’s a complete transformation of how medicines are discovered.
The secret isn’t just faster computers—it’s smarter approaches. AI transforms drug discovery in three powerful ways:
1. Smart Target Hunting
Instead of researchers spending years in labs testing thousands of compounds, AI analyzes massive datasets to predict which molecules will work—often in just weeks.
2. Virtual Testing
Before expensive animal testing, AI can simulate how drugs will behave in the body. Think of it as a sophisticated video game that predicts real-world results.
3. Rapid Learning Cycles
Traditional research moves slowly: test, analyze, redesign, repeat. AI systems can run thousands of these cycles simultaneously, learning from each iteration.
This is how AlphaFold 3 and similar platforms are changing the game—they’re not just tools, they’re intelligent partners in the discovery process.
For Pharmaceutical Companies:
For Patients:
Before we get too excited, let’s address the elephant in the room. Despite these impressive timelines, some things simply can’t be rushed:
Regulatory Requirements Don’t Disappear
The FDA still requires extensive safety testing. Animal studies are mandatory. Long-term effects must be studied. No amount of AI can change these fundamental safety requirements.
Biology Is Still Complex
Cancer drugs, especially new ones, require extensive validation. The human body is incredibly complex, and AI is still learning to predict how drugs will actually behave in real patients.
Technology Is Still Maturing
These are first-generation AI platforms. They’re impressive, but they’re still evolving. Regulatory agencies are also still figuring out how to evaluate AI-designed drugs.
The good news? Even with these constraints, AI is already delivering meaningful speed improvements. As the technology matures, we can expect even better results.
For Technology Leaders:
The question isn’t whether to invest in AI drug discovery, it’s how fast you can move. This represents a fundamental platform shift, similar to how the internet transformed commerce. Early movers are building sustainable advantages.
For Business Strategy:
Watch the partnerships. Traditional pharma companies are racing to ally with AI-first companies. The successful combinations will likely dominate the next decade of drug discovery.
For Market Watchers:
Isomorphic Labs’ human trials in 2025 represent a crucial test case. Success could accelerate investment and regulatory acceptance. Failure might slow the entire field.
Isomorphic Labs’ upcoming human trials, mark more than just another drug study they represent a potential inflection point in medicine. While the company’s four-year timeline isn’t dramatically faster than optimized traditional development, it’s what comes next that matters.
As AI platforms mature and regulatory pathways streamline, we’ll likely see even more dramatic accelerations. The companies and countries that master this technology first will have enormous advantages in addressing humanity’s greatest health challenges.
The race to “solve all diseases” isn’t just a bold vision anymore—it’s becoming a measurable reality. And AI is leading the charge.
A LinkedIn comparison sparked a deeper reflection on transportation, culture, and what it means to build sustainable cities.

A recent LinkedIn post comparing Tokyo and Bengaluru’s transportation systems has been making rounds, showing stark differences in their mass transit networks, ridership numbers, and private vehicle usage. While the data is factual, the comparison itself reveals something more profound about how we think about urban mobility and social development.
Comparing Bengaluru directly with Tokyo is like comparing a promising startup with a Fortune 500 company. Tokyo’s transportation system is the result of decades of systematic investment, urban planning, and cultural evolution. With over 150 years of railway history and post-war reconstruction that prioritized public transit, Tokyo’s current state represents generational thinking and investment.
A more apt comparison would be Mumbai with Tokyo – both are financial capitals with comparable population densities and similar economic pressures. Mumbai’s suburban rail network, though strained, serves millions daily and represents a more mature Indian transportation ecosystem.
But here’s where the comparison becomes truly interesting. In Bengaluru, and much of India, private vehicle ownership isn’t just about mobility – it’s about social signaling. The 1.1 crore private vehicles in Bengaluru represent more than transportation choices; they represent aspirations, status, and perceived success.
This stands in stark contrast to mature economies like Japan, where you’ll find CEOs and janitors sharing the same train compartment without a second thought. In Tokyo, the efficiency and reliability of public transport have made it the preferred choice across all economic strata. There’s no stigma attached to taking the train – if anything, it’s seen as the smart choice.
What Tokyo demonstrates beautifully is the concept of ikigai – finding purpose and contentment in life’s simple, efficient systems. The city’s transportation network embodies this philosophy: it’s not about showcasing wealth through individual car ownership, but about creating a system that serves everyone efficiently.
In mature economies, the wealthy don’t feel the need to differentiate themselves through transportation choices. They’ve moved beyond conspicuous consumption in basic utilities. A millionaire in Tokyo takes the same train as a student because both recognize it’s the most efficient way to navigate the city.
Bengaluru’s 73% private vehicle usage rate comes with hidden costs that don’t appear in simple comparisons:
The real lesson isn’t that Bengaluru should simply copy Tokyo’s model. Instead, it’s about understanding the deeper cultural and economic shifts required for sustainable urban mobility:
Moving away from private vehicle ownership as a status symbol requires cultural change, not just infrastructure investment.
Building public transport that’s so efficient and comfortable that choosing it becomes a matter of preference, not necessity.
Tokyo’s success comes from decades of coordinated urban planning where transportation, housing, and commercial development work in harmony.
Bengaluru and other Indian cities don’t need to replicate Tokyo exactly. They need to develop their own version of transportation ikigai – finding purpose and efficiency in shared mobility solutions that work for their unique context.
This might mean:
The Tokyo-Bengaluru comparison isn’t just about transportation – it’s a mirror reflecting our values, aspirations, and understanding of what makes a city truly livable. Until we address the prestige factor in transportation choices and embrace the efficiency of shared mobility, we’ll continue to build cities that serve vehicles rather than people.
The question isn’t whether Bengaluru can build Tokyo’s transportation system. The question is whether Bengaluru can build a transportation culture that serves its people as effectively as Tokyo serves its own.
What are your thoughts on transportation as a status symbol in Indian cities? How can we shift the conversation from ownership to access?
How the ancient art of paper folding teaches us Thomas Sterner‘s principles of discipline and focus

There’s something magical about watching a master origami artist transform a simple sheet of paper into an intricate crane, dragon, or flower. What starts as a flat, unremarkable square becomes something beautiful and complex through nothing more than strategic folds. This transformation embodies a profound truth about learning, growth, and achievement—one that Thomas M. Sterner captures brilliantly in his book “The Practicing Mind” through what I call the 4S Framework: Simplify, Small, Slow, and Short.
Sterner’s framework offers a counterintuitive approach to mastery in our fast-paced, instant-gratification world. Let’s explore each element through the lens of origami, then see how these principles revolutionize business thinking.
In origami, every complex creation begins with the same foundation: a single square of paper. No glue, no scissors, no elaborate tools—just paper and intention. The art lies not in adding complexity, but in finding the elegant simplicity within complexity.
Master origami artists don’t start by imagining the final crane; they focus on the next fold. Each fold is a simple action: valley fold, mountain fold, inside reverse fold. The complexity emerges from the accumulation of simple, deliberate actions.
The Business Connection: The most successful businesses often have the simplest core concepts. Amazon started with one idea: sell books online. Google began with one mission: organize the world’s information. Netflix simplified entertainment: movies by mail, then streaming. They didn’t launch with dozens of features—they perfected one simple value proposition first.
Every origami journey begins with a modest square of paper—often just 6 inches by 6 inches. You don’t need expensive materials or vast resources. The constraint of size actually enhances creativity and forces precision. Small paper means small mistakes, quick learning cycles, and lower stakes for experimentation.
When learning origami, you don’t start with a 1,000-step dragon. You begin with a simple boat or paper airplane. These small projects build fundamental skills while providing immediate satisfaction and confidence.
The Business Connection: The startup world has embraced this through the Minimum Viable Product (MVP) concept. Instead of spending years building the perfect product, successful entrepreneurs start small. Facebook began as a simple directory for Harvard students. Airbnb started with air mattresses in the founders’ apartment. Twitter emerged from a simple question: “What are you doing?”
Small beginnings allow for rapid iteration, reduced financial risk, and faster market feedback. They also make the seemingly impossible feel achievable.
Here’s where origami reveals its deepest wisdom: going slow actually makes you faster. When you rush through folds, you create imprecision that compounds throughout the model. A valley fold that’s slightly off becomes a major structural problem twenty steps later. You end up starting over, taking much longer than if you’d been deliberate from the beginning.
Experienced origami artists move with methodical precision. They study the diagram, understand the intended result, make the fold carefully, and ensure it’s correct before proceeding. This “slow” approach leads to flawless execution and faster overall completion.
The Business Connection: In business, “slow” means taking time to understand your market, validate assumptions, and build solid foundations. Companies that rush to scale often collapse under their own weight. Those that move deliberately—like Patagonia’s careful expansion or In-N-Out Burger’s methodical geographic growth—build sustainable, lasting enterprises.
Slow also means giving your team time to understand strategy, your customers time to adopt your product, and yourself time to develop genuine expertise. The paradox is that this patient approach ultimately accelerates long-term success.
Origami mastery doesn’t come from marathon folding sessions that leave you frustrated and fatigued. It comes from consistent, short practice periods. Fifteen minutes of focused folding is more valuable than two hours of distracted attempts.
Short sessions maintain engagement, prevent mental fatigue, and allow for better retention. Each brief practice builds on the previous one, creating steady progress without burnout. You might learn one new fold per session, but those folds compound into increasingly sophisticated models over time.
The Business Connection: The most effective business development happens in short, focused sprints rather than endless work marathons. The Pomodoro Technique, agile development cycles, and regular brief check-ins all reflect this principle.
Short also applies to goal setting. Instead of aiming to “transform the industry,” successful businesses set short-term, achievable milestones. Weekly objectives, monthly targets, and quarterly goals create momentum and maintain motivation while building toward larger visions.
The magic happens when these four principles work together. In origami, you simplify complex forms into basic folds, start with small projects and small pieces of paper, work slowly and deliberately, and practice in short, focused sessions. This approach doesn’t just create paper art—it develops patience, precision, spatial intelligence, and the ability to see complex systems as sequences of simple steps.
The same compound effect occurs in business. Companies that simplify their core offering, start small with their market, move slowly enough to build solid foundations, and focus on short-term achievable goals often outperform those that try to do everything at once.
For Entrepreneurs:
For Teams:
For Personal Development:
Perhaps the most profound lesson from origami is about the nature of creation itself. Every fold matters. Every decision has consequences that ripple through the entire structure. There are no shortcuts, but there is elegance in the process when you embrace the 4S principles.
Great leaders, like master origami artists, understand that transformation happens one fold at a time. They resist the urge to force outcomes and instead focus on perfecting the process. They know that rushing leads to structural weaknesses, while patience creates strength.
In our age of instant everything, origami offers a different path—one that mirrors Sterner’s insights about developing a practicing mind. The art teaches us that complexity emerges from simplicity, that small beginnings enable great achievements, that slow progress is often the fastest route to mastery, and that short, focused efforts compound into extraordinary results.
Whether you’re building a business, developing a skill, or pursuing any meaningful goal, the 4S framework provides a sustainable path forward. Like the origami artist who transforms a simple square into something beautiful, you can transform your aspirations into reality—one deliberate fold at a time.
The next time you feel overwhelmed by the complexity of your goals, remember the origami master. Pick up that simple square of paper. Make one fold. Then another. Trust the process, embrace the principles, and watch as something extraordinary emerges from the most humble beginnings.
What will you create with your next fold?

Have you ever wondered why some people seem to effortlessly turn their dreams into reality while others remain perpetually stuck in the planning phase? Bernard Roth’s “The Achievement Habit: Stop Wishing, Start Doing, and Take Command of Your Life” offers a refreshingly honest answer: achievement isn’t about having the best ideas or the most talent, it’s about developing the right habits and taking consistent action.
Roth, a Stanford professor and co-founder of the renowned d.school, brings decades of design thinking expertise to personal development. His central thesis is revolutionary in its simplicity: achievement is a habit that can be learned, practiced, and strengthened like a muscle. Drawing from real student transformations in his Stanford class “The Designer in Society,” Roth demonstrates that the same design thinking principles used to solve complex organizational problems can redesign your entire life.
The book’s power lies in its practical approach. Rather than offering feel-good platitudes, Roth presents a systematic method for breaking through self-imposed limitations and creating lasting change.

One of the book’s most profound insights is that meaning is entirely subjective—we assign significance to everything in our lives, and these assignments shape our actions and outcomes. Roth argues that changing how you label and view situations can unlock creativity and positive transformation.
This isn’t just positive thinking; it’s strategic reframing. When you recognize that your interpretation of events—not the events themselves—determines your response, you gain tremendous power to change your experience. The practical exercise here is simple but transformative: regularly question your assumptions and consciously relabel familiar situations to open new possibilities.
Perhaps the book’s most controversial chapter tackles our relationship with excuses. Roth boldly states that most reasons we give for our actions are simply sophisticated excuses designed to protect our self-image. While this might sound harsh, it’s liberating once you embrace it.
The author isn’t advocating for social rudeness, externally, reasons may still be necessary. But internally, questioning every reason forces honest self-assessment. If something truly matters to you, your actions should reflect that priority without elaborate justification. This shift from explanation to action is where real change begins.
The distinction between “trying” and “doing” runs throughout the book like a golden thread. Roth emphasizes that real achievement comes only through committed action, not good intentions or endless discussions. There’s a fundamental difference between someone who says “I’ll try to exercise” and someone who simply exercises.
This connects to his advocacy for prototyping, taking small, experimental steps to build momentum. Rather than waiting for the perfect plan, start with imperfect action. Small wins build confidence and break the inertia that keeps most people stuck in perpetual preparation mode.
In our age of endless information and analysis paralysis, “The Achievement Habit” offers a refreshing antidote. Roth’s background in design thinking brings practical structure to personal development, moving beyond motivation to methodology. The book doesn’t just inspire—it instructs.
What makes this particularly relevant is how Roth addresses modern challenges like overthinking, perfectionism, and the tendency to substitute planning for action. His emphasis on collaboration and asking for help counters our increasingly isolated approach to personal growth.

“The Achievement Habit” succeeds because it treats personal development as a design problem rather than a motivation issue. Roth shows that achievement isn’t about having the right personality or waiting for inspiration, it’s about building systems and habits that consistently move you forward.
The book’s real strength lies in its integration of mindset shifts with practical action. It’s not enough to change how you think; you must change what you do. And it’s not enough to take random action; you must align that action with an empowering self-image and clear purpose.
If you’re tired of books that make you feel good but don’t create lasting change, “The Achievement Habit” offers something different: a proven framework for turning intentions into results. Roth’s message is both challenging and hopeful, you have more control over your outcomes than you think, but only if you’re willing to stop making excuses and start taking consistent action.
The question isn’t whether you can achieve more in your life. The question is whether you’re ready to make achievement a habit.
Cognitive biases subtly shape our perceptions and decisions, often without our awareness. Understanding these mental shortcuts is crucial for leaders aiming to make informed, rational choices. This guide distills insights from ten detailed explorations of prevalent biases, each accompanied by a link to delve deeper.

The Silent Distorter of Data
When certain groups don’t respond to surveys, the resulting data can misrepresent the whole.
Learning from History’s Hidden Failures
Focusing only on successes can lead to overestimating probabilities and ignoring critical lessons from failures.
Where Good Vibes Wreck Good Plans
Overestimating positive outcomes can result in inadequate preparation for potential challenges.
The Hidden Influence Shaping Our Business Decisions
Unconscious attitudes can affect decisions, leading to unintended discrimination or favoritism.
When More Data Clouds Better Decisions
Seeking excessive information can delay decisions and obscure key insights.
How First Numbers Shape Our Decisions
Initial information can disproportionately influence subsequent judgments and decisions.
When We Fail to Update Our Beliefs
A reluctance to revise beliefs in light of new evidence can hinder growth and adaptation.
Why You See Your New Car Everywhere
Focusing on specific stimuli can make them appear more prevalent, skewing perception.
When What Comes to Mind Isn’t What Matters
Recent or memorable events can disproportionately influence decision-making.
When Staying the Course Becomes Dangerous
Persisting with a plan despite new risks can lead to adverse outcomes.
Awareness is Crucial: Recognizing these biases is the first step toward mitigating their impact. Continuous Reflection: Regularly question assumptions and seek diverse perspectives. Informed Decision-Making: Integrate checks and balances to counteract potential biases.
For leaders and decision-makers, understanding and addressing cognitive biases is essential for effective strategy and operations. Explore each article to deepen your insight and enhance your decision-making acumen.
Feel free to share this guide with your network to promote awareness and understanding of cognitive biases in professional settings.
When we conduct surveys or studies or ask for feedback, we often focus on the responses we receive—analyzing patterns, drawing conclusions, and making decisions based on this data. However, what about the voices we never hear? The participants who decline to respond, hang up the phone, ignore the email, or simply cannot be reached? Their absence from our data can tell an important story of its own—one that might significantly alter our conclusions if we knew it.
This is the challenge of non-response bias, a systematic error that occurs when those who respond to a survey differ in meaningful ways from those who don’t respond. Unlike sampling error, which can be addressed through larger sample sizes, non-response bias can persist or even worsen as you collect more data if the underlying pattern of non-response remains consistent.

Non-response bias occurs when people who don’t respond to surveys or studies have characteristics that differ from those who do respond, leading to skewed results that don’t accurately represent the target population. In statistical terms, it’s a type of selection bias where the selection process is driven by the subjects themselves rather than the researchers.
For example, imagine a university sending out a satisfaction survey to all its graduates. Those who had particularly positive or negative experiences might be more motivated to respond than those with moderate experiences. If the survey concludes that 40% of graduates were extremely satisfied and 30% extremely dissatisfied, this might represent a distorted picture compared to the true distribution.
Perhaps the most famous historical example of non-response bias occurred during the 1936 U.S. presidential election. The Literary Digest, a respected magazine, conducted what was then the largest political poll in history, mailing out surveys to over 10 million Americans. Based on the 2.4 million responses they received, they confidently predicted that Republican Alf Landon would defeat incumbent Democrat Franklin D. Roosevelt in a landslide.
Instead, Roosevelt won in one of the most lopsided victories in American electoral history, carrying 46 of 48 states.
What went wrong? The Literary Digest had compiled their mailing list from telephone directories, club memberships, and magazine subscriptions—all indicators of higher socioeconomic status during the Great Depression. Additionally, those who responded were more likely to be politically engaged and opposed to Roosevelt’s New Deal policies. The combined effect of this sampling bias and non-response bias led to a spectacular polling failure that effectively ended the magazine’s reputation.
Health surveys frequently suffer from non-response bias. People with serious health conditions may be too ill to participate in surveys, while those who are health-conscious might be overrepresented in responses. This can lead to underestimating disease prevalence and overestimating healthy behaviors in the general population.
A striking example comes from the Centers for Disease Control and Prevention’s (CDC) Behavioral Risk Factor Surveillance System (BRFSS), which has seen declining response rates over time. Research comparing early BRFSS data to subsequent health records found that respondents were generally healthier than non-respondents, leading to potentially optimistic assessments of population health.
Corporate employee satisfaction surveys often suffer from non-response bias. Employees who feel extremely negative about their workplace may fear retaliation despite promises of anonymity. Conversely, highly satisfied employees might not feel motivated to respond because they see no problems needing attention.
Additionally, the busiest and most overworked employees—whose feedback might be particularly valuable regarding workload issues—often don’t have time to complete voluntary surveys, creating a systematic gap in the data.
The dramatic bimodal distribution of online product reviews (many 5-star and 1-star reviews, fewer in the middle) is a classic example of non-response bias in everyday life. Customers with strong positive or negative experiences feel motivated to leave reviews, while those with average experiences typically don’t bother. This creates a “J-shaped” or “U-shaped” distribution that may not reflect the true customer experience.
Several factors contribute to non-response bias:
Some potential respondents simply cannot be reached or face barriers to participation:
The subject matter itself can influence who responds:
As people are increasingly bombarded with requests for feedback:
In an era of data breaches and privacy concerns:
How can researchers determine if non-response bias is affecting their results? Several approaches can help:
If demographic information about the target population is available from reliable sources (like census data), researchers can compare the demographic profile of respondents to that of the overall population. Significant differences may suggest non-response bias.
Research suggests that late responders often share characteristics with non-responders. By comparing those who responded immediately to those who only responded after multiple reminders, researchers can estimate the direction and magnitude of non-response bias.
The gold standard approach is to conduct intensive follow-up with a sample of non-respondents, using additional incentives or different contact methods to secure their participation. The responses from this group can then be compared to the original respondents to identify systematic differences.
By analyzing how survey results change as additional waves of responses come in (after reminders or follow-ups), researchers can extrapolate what the results might look like if everyone had responded.
While it’s impossible to eliminate non-response bias entirely, several strategies can help mitigate its effects:
While reducing non-response bias is important for research validity, there’s an ethical balance to strike. Persistent follow-up can cross the line into harassment, and excessive incentives may become coercive. Researchers must consider:
The COVID-19 pandemic created unique challenges for researchers studying the disease’s spread and impact. Early studies relied heavily on voluntary participation, potentially missing:
Some research teams addressed these issues by:
These efforts revealed important disparities in COVID-19’s impact that might have been missed with conventional approaches.
For those who use data rather than collect it, awareness of non-response bias is equally important:
When presented with survey results, ask:
Quality research will acknowledge limitations and potential biases. Be skeptical of results that claim perfect representativeness with low response rates.
No single data source is perfect. Triangulate information from different sources with different methodological strengths and weaknesses.
If survey results seem dramatically different from expectations or other data sources, non-response bias may be a factor worth considering.
Non-response bias represents one of the most persistent challenges in survey research, and its importance has grown as response rates have declined across countries and methods. Rather than seeing it as merely a methodological nuisance, we should view addressing non-response bias as an opportunity to hear diverse voices and understand the full spectrum of human experiences.
By acknowledging who might be missing from our data, implementing strategies to include them, and remaining humble about the limitations of our methods, we can work toward research that more accurately represents the populations we study.
The story told by silence—by those who don’t respond—can be as important as the story told by those who do. In the pursuit of truth and understanding, we must listen carefully to both.