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.
The Unfair Comparison Problem
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.
The Prestige Factor: Transportation as Status Symbol
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.
The Economics of Self-Containment
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.
The Hidden Costs of Private Vehicle Dependence
Bengaluru’s 73% private vehicle usage rate comes with hidden costs that don’t appear in simple comparisons:
Environmental impact: More vehicles mean more emissions and pollution
Infrastructure strain: Roads designed for thousands now serve millions
Economic inefficiency: Individuals bearing the full cost of transportation instead of sharing it
Social segregation: Different economic classes using different transport modes
What This Means for Indian Cities
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:
1. Redefining Success
Moving away from private vehicle ownership as a status symbol requires cultural change, not just infrastructure investment.
2. Quality Over Quantity
Building public transport that’s so efficient and comfortable that choosing it becomes a matter of preference, not necessity.
3. Integrated Planning
Tokyo’s success comes from decades of coordinated urban planning where transportation, housing, and commercial development work in harmony.
The Path Forward
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:
Investing in Bus Rapid Transit systems that are more feasible than extensive metro networks
Creating integrated mobility solutions that combine multiple transport modes
Most importantly, fostering a cultural shift where using public transport is seen as civic responsibility rather than economic compromise
Conclusion
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.
The 4S Framework Explained
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.
1. Simplify: The Power of Reduction
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.
2. Small: Starting with Minimal Viable Actions
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.
3. Slow: The Paradox of Patient Progress
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.
4. Short: Bite-Sized Learning Sessions
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 Compound Effect: How 4S Creates Mastery
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.
Practical Applications for Your Business
For Entrepreneurs:
Simplify your business model to one clear value proposition
Start with a small, well-defined target market
Move slowly enough to gather meaningful customer feedback
Set short weekly goals rather than only focusing on yearly objectives
For Teams:
Simplify project scope to essential features
Break large initiatives into small, manageable components
Allow time for thorough planning and execution
Work in short sprints with regular review cycles
For Personal Development:
Simplify skill development to one core competency at a time
Start with small daily practices
Progress slowly enough to build solid foundations
Commit to short, consistent learning sessions over sporadic marathons
The Origami Mindset in Leadership
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.
Conclusion: The Art of Disciplined Progress
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.
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.
The Core Message: Achievement Is a Learnable Skill
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.
Three Game-Changing Takeaways
1. Your Perspective Creates Your Reality
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.
2. Reasons Are Just Sophisticated Excuses
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.
3. Doing Beats Trying Every Time
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.
Why This Book needs recommendation?
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 Bottom Line
“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.
Ready infographics
1. Non-Response Bias
The Silent Distorter of Data
When certain groups don’t respond to surveys, the resulting data can misrepresent the whole.
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.
What Exactly Is Non-Response Bias?
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.
Real-World Examples of Non-Response Bias
The Literary Digest Poll of 1936
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.
Modern Health Surveys
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.
Employee Satisfaction Surveys
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.
Online Product Reviews
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.
Why Does Non-Response Bias Occur?
Several factors contribute to non-response bias:
Accessibility Issues
Some potential respondents simply cannot be reached or face barriers to participation:
Lack of internet access for online surveys
Language barriers
Physical or cognitive disabilities that make participation difficult
Technological literacy limitations
Time constraints due to work or family responsibilities
Topic Sensitivity
The subject matter itself can influence who responds:
People may avoid surveys on stigmatized topics (mental health, financial struggles, etc.)
Those with strong opinions on a topic are more likely to participate
Surveys on specialized topics may only draw responses from those with relevant experience
Survey Fatigue
As people are increasingly bombarded with requests for feedback:
Response rates have declined across virtually all survey methods
Those who do respond may be unusual in their willingness to complete surveys
Longer surveys tend to have higher abandonment rates, creating another layer of bias
Trust and Privacy Concerns
In an era of data breaches and privacy concerns:
People may distrust how their information will be used
Certain demographic groups may have historical reasons to distrust researchers
Questions perceived as too personal may be skipped or cause survey abandonment
Detecting Non-Response Bias
How can researchers determine if non-response bias is affecting their results? Several approaches can help:
Compare Respondents to Known Population Characteristics
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.
Analyze Early vs. Late Responders
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.
Conduct Non-Response Follow-Up Studies
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.
Wave Analysis
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.
Strategies to Minimize Non-Response Bias
While it’s impossible to eliminate non-response bias entirely, several strategies can help mitigate its effects:
Design User-Friendly Surveys
Keep surveys concise and focused
Use clear, simple language
Ensure accessibility across devices and for people with disabilities
Provide support for multiple languages when appropriate
Offer Multiple Response Channels
Combine online, phone, mail, and in-person collection methods
Allow respondents to choose their preferred contact method
Implement methods appropriate for the specific population being studied
Use Incentives Strategically
Offer appropriate compensation for participation time
Consider non-monetary incentives like donation to charity
Be careful that incentives don’t introduce their own biases
Implement Persistent Follow-Up
Send reminders through multiple channels
Schedule follow-ups at different times and days
Use increasingly strong incentives for hard-to-reach participants
Build Trust with Potential Respondents
Clearly explain how data will be used and protected
Partner with trusted community organizations
Provide examples of how previous survey results led to positive changes
Statistical Adjustments
Use weighting techniques to adjust for known demographic differences
Apply propensity score adjustments based on response patterns
Implement multiple imputation for missing data when appropriate
The Ethics of Pursuing Non-Respondents
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:
Respecting the right to decline participation
Setting appropriate limits on follow-up attempts
Ensuring incentives are not exploitative of vulnerable populations
Being transparent about potential non-response limitations when reporting results
Case Study: Non-Response in COVID-19 Research
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:
Those too ill to participate
Communities with limited internet access
People working essential jobs without time to participate
Those with language barriers or technology limitations
Individuals distrustful of medical research
Some research teams addressed these issues by:
Combining multiple data sources (administrative, clinical, and survey data)
Using community health workers to reach underrepresented groups
Implementing targeted sampling in areas with known low response rates
Working with trusted community organizations as intermediaries
These efforts revealed important disparities in COVID-19’s impact that might have been missed with conventional approaches.
Implications for Data Consumers
For those who use data rather than collect it, awareness of non-response bias is equally important:
Ask Critical Questions
When presented with survey results, ask:
What was the response rate?
Who might be missing from this data?
How might the conclusions change if non-respondents were included?
What steps were taken to address potential non-response bias?
Look for Transparency
Quality research will acknowledge limitations and potential biases. Be skeptical of results that claim perfect representativeness with low response rates.
Consider Multiple Data Sources
No single data source is perfect. Triangulate information from different sources with different methodological strengths and weaknesses.
Be Wary of Extreme Claims
If survey results seem dramatically different from expectations or other data sources, non-response bias may be a factor worth considering.
Conclusion: Embracing the Challenge
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.
Looking beyond what survived to understand the complete picture
Introduction
When we study history, we naturally focus on what remains: the buildings still standing, the books preserved through centuries, the businesses that thrived, the medical treatments that worked. This tendency creates what statisticians call “survival bias” – a logical error where we concentrate on people or things that made it past some selection process while overlooking those that did not, leading to false conclusions and distorted perspectives.
While the bullet-hole-riddled WWII aircraft example is perhaps the most famous illustration of survival bias, history offers us countless other illuminating cases that reveal how this cognitive error shapes our understanding of the past and influences our decisions today.
The Healthy Worker Effect: Industrial Revolution’s Hidden Truth
During the Industrial Revolution and early 20th century, medical researchers made a puzzling discovery: factory workers, despite laboring in what we now know were often hazardous conditions, frequently appeared healthier in statistical studies than the general population.
This counterintuitive finding, known as “the healthy worker effect,” represented a classic case of survival bias. Only individuals with robust constitutions could endure the punishing physical demands of factory work. Those who became ill simply disappeared from the workforce—and consequently from the studies—creating a false impression about working conditions.
The healthiest workers remained visible in the data, while those whose health deteriorated became invisible. This statistical illusion delayed necessary workplace safety reforms and obscured the true human cost of industrialization for decades. Only when researchers began tracking workers longitudinally and accounting for those who left the workforce did the actual health impacts become apparent.
The Deceptive Durability of Ancient Architecture
We marvel at structures like the Roman Pantheon, with its magnificent unreinforced concrete dome that has stood for nearly two millennia, while modern concrete often deteriorates within decades. This observation has led many to conclude that ancient Roman engineers possessed superior construction knowledge that was somehow “lost” to history.
However, this represents a classic survival bias. What we see today are only the most exceptional examples of Roman architecture—the statistical outliers that survived earthquakes, wars, and the relentless erosion of time. For every Pantheon or Colosseum that remains, thousands of ordinary Roman structures collapsed long ago and were forgotten.
Recent archaeological work has revealed that Roman concrete wasn’t universally superior—many structures failed quickly, but these failures don’t remain for us to observe. The structures that survived often did so because they were built in geologically stable areas, constructed with extraordinary resources by the empire’s finest engineers, or continuously maintained and restored throughout history.
When we consider only the survivors, we mischaracterize the typical Roman building experience and create false narratives about “lost knowledge,” when in fact modern materials science has produced far more reliable and consistently durable building materials.
Medieval Knowledge: The Monastery Filter
Our understanding of medieval thought and culture is profoundly shaped by survival bias. The vast majority of surviving manuscripts from the Middle Ages come from monasteries and religious institutions—texts deemed worthy of careful preservation and painstaking reproduction by scribes.
This creates a fundamentally skewed historical record. Religious perspectives, classical works approved by the Church, and writings by social elites are dramatically overrepresented, while secular literature, folk traditions, dissenting religious views, and the perspectives of ordinary people were far less likely to be preserved.
Historians estimate that less than 1% of all medieval manuscripts survived to the modern era. This tiny fraction profoundly shapes our perception of medieval society, making it appear more uniformly religious and intellectually constrained than it likely was. Recent archaeological finds, like the Novgorod birch bark documents in Russia—everyday letters written by ordinary citizens—suggest a much more diverse intellectual landscape than surviving formal manuscripts indicate.
The “Spanish” Flu Misnomer
The deadly influenza pandemic of 1918-1919 became known as the “Spanish Flu” not because it originated in Spain or because Spain suffered more severely, but because of a quirk of information survival. As a neutral country during World War I, Spain had no wartime press censorship, unlike most other affected nations.
While countries like the United States, Britain, France, and Germany suppressed news about the outbreak to maintain wartime morale, Spanish newspapers reported freely on the disease, including the illness of their king, Alfonso XIII. This created the false impression that Spain was uniquely affected when the pandemic was truly global in scope.
Modern research suggests the virus likely originated in the United States or China, but the survival bias in public information—with Spanish reports “surviving” censorship while others didn’t—created a historical distortion that persists in the pandemic’s name over a century later.
Literary Canons: The Survival of the “Greatest”
When we study literature from past centuries, we focus on what literary scholar Franco Moretti calls “the canonical 1%”—the tiny fraction of published works that have been preserved, anthologized, and continuously read. This creates the illusion that past eras produced mostly masterpieces, unlike our own time with its mix of great, good, and forgettable works.
In reality, Sturgeon’s Law—the principle that “90% of everything is crud”—applied just as much to Victorian novels or Renaissance plays as to modern literature. For every Shakespeare, there were dozens of forgotten playwrights; for every Jane Austen, hundreds of forgotten novelists whose works didn’t survive the ruthless filter of time.
This survival bias distorts our perception of literary history and creates unrealistic standards for contemporary writers. It also means our understanding of past literary cultures is based almost entirely on exceptional outliers rather than typical works.
Medical Treatments: History’s Selective Memory
Medical history provides particularly consequential examples of survival bias. Before the advent of rigorous clinical trials, doctors primarily recorded and passed down treatments that seemed to work, creating a body of medical literature rife with survival bias.
When patients recovered after a particular treatment, the treatment received credit—regardless of whether recovery might have happened anyway. Treatments that failed were less likely to be documented or, if documented, less likely to be repeatedly cited in medical texts.
This created a medical canon filled with ineffective or even harmful treatments that persisted for centuries. Bloodletting, for instance, remained a standard medical practice for over 2,000 years despite causing more harm than good in most cases. It survived because doctors noticed and remembered the subset of patients who improved after bloodletting (often despite the treatment, not because of it), while minimizing or forgetting the many who deteriorated.
Only with the development of controlled trials in the 20th century, explicitly designed to counter survival bias by tracking all outcomes, did medicine begin to systematically separate truly effective treatments from those that merely appeared effective due to selective observation.
Business Advice: Survivor Stories
Management literature is notorious for survival bias. Books analyzing “great companies” often study only businesses that succeeded, drawing conclusions about their practices without examining whether failed companies followed the same practices.
A famous example comes from Jim Collins’ business bestseller “Good to Great,” which analyzed companies that transformed from average to exceptional performers. Several companies praised in the book, including Circuit City and Fannie Mae, subsequently collapsed or required government bailouts, raising questions about the methodology’s validity.
By studying only “survivors,” such analyses often mistake luck for skill and correlation for causation. They identify practices that might be common among successful companies but fail to note these same practices may be equally common among failed ones.
Napoleon’s Russian Campaign: The Frozen Evidence
When Napoleon invaded Russia in 1812, he began with approximately 450,000 soldiers. Only about 10,000 returned. Historical accounts of the campaign often focus disproportionately on these survivors’ experiences, creating a narrative heavily weighted toward the experiences of those who endured the entire ordeal.
The famous winter retreat from Moscow features prominently in these accounts, with harrowing descriptions of extreme cold and starvation. While these conditions were certainly devastating, survival bias obscures the fact that more of Napoleon’s troops died during the summer advance than during the winter retreat. Disease, heat exhaustion, and Russian guerrilla tactics decimated the Grande Armée before winter arrived.
By focusing primarily on winter survivors’ accounts, historical narratives overemphasized cold as the decisive factor while underrepresenting the many who perished from other causes earlier in the campaign.
Challenging Our Historical Understanding
These examples reveal how survival bias fundamentally shapes our understanding of history. To counter this bias, historians increasingly employ methodologies that actively search for what hasn’t survived, using archaeological evidence, statistical modeling, and cross-cultural comparisons to fill in historical blind spots.
As consumers of history, we should approach historical narratives with healthy skepticism, always asking: What might be missing from this picture? Whose voices weren’t preserved? What failures disappeared from the record?
Conclusion: The Value of Failure
Acknowledging survival bias doesn’t just give us a more accurate view of history—it offers practical wisdom. When we recognize that failure is underrepresented in our understanding of the past, we gain valuable perspective on our own setbacks and the statistical nature of success.
The real lesson of survival bias is that failure is both common and instructive. By seeking out and studying failures rather than focusing exclusively on survivors, we gain insights that would otherwise remain hidden. In business, science, medicine, and personal development, understanding what doesn’t work can be just as valuable as knowing what does.
History’s greatest progress often comes not from replicating past successes, but from analyzing past failures—the very data points that survival bias tends to erase. By actively countering this bias, we develop a richer, more accurate understanding of both history and the present.
As the philosopher George Santayana famously observed, “Those who cannot remember the past are condemned to repeat it.” To that, we might add: “Those who remember only the surviving parts of the past are condemned to misunderstand it.”
You know that moment in a business review where someone says, “We’ll definitely hit the target. It’s only September.” That’s optimism bias. It’s not just a mindset—it’s a recurring guest star in strategy decks, project timelines, and sales forecasts.
What Is Optimism Bias?
Optimism bias is the human tendency to believe that we’re less likely to encounter negative outcomes and more likely to succeed, even when evidence suggests otherwise. It’s why launch dates look like fairy tales and why budgets are often as tight as that last seat on a budget airline.
In business, it shows up with a suit and a smile:
“This will only take two weeks.” (Famous last words.) “The client will definitely sign this order.” (Spoiler: They won’t.) “We can absorb this scope change without affecting delivery.” (Said no Gantt chart ever.)
Where It Hides in Plain Sight
Project Timelines: Always on time, until they’re not. Gantt charts get high on hope. Sales Forecasts: Every lead is “hot.” But apparently, half are in Antarctica. Product Launches: MVPs become FOMOs (Fear Of Missing Out), loaded with “just one more feature.” Change Management: “People will adapt quickly.” Right after they stop resisting it entirely.
Why we fall for it?
We’re wired for progress and positivity. In fact, leaders often need to be optimistic to inspire teams and investors. But unchecked optimism can become a strategic liability, leading to budget overruns, missed milestones, and serious trust erosion.
The Optimism Balanced
Despite these cautions, some optimism remains valuable. As research psychologist Tali Sharot notes, “Optimism pushes us to take risks and attempt difficult things.” The goal isn’t eliminating optimism, but tempering it with reality. The next time you’re planning an office move, renovation, or technology implementation, ask: 1. What’s our historical accuracy on similar projects? 2. What specific complications might we face that aren’t in our current plan? 3. What would more experienced outsiders estimate for this project? 4. Have we built meaningful contingencies for time, budget, and resources? By acknowledging optimism bias, we can harness its motivational benefits while avoiding its planning pitfalls. The result? Office changes that actually meet expectations—perhaps the most optimistic outcome of all.
The Optimism Audit (A Survival Kit)
Here’s how to stay hopeful without losing your head (or your quarterly bonus):
Run Pre-Mortems: Before the kickoff, imagine it all went sideways. What caused it? Fix those now. Use RYB Indicators: Red-Yellow-Green status makes optimism earn its stripes. Build Buffers (Secretly): Be the realist who adds padding to timelines—but doesn’t advertise it. Listen to the Skeptics: That person always raising risks? Give them a doughnut. Then listen. Measure Backlog, Not Just Velocity: “Hope is not a strategy.” Data is.
In Summary: Optimism Is a Leadership Asset, When Balanced
Optimism bias isn’t the enemy. It’s your over-caffeinated cousin, fun to have around, but don’t let it drive. Combine its energy with critical thinking, and you’ve got a solid business partner.
Final Thought:
If your project plan reads like a wish list to Santa, it’s time for a reality check. Stay positive—but don’t forget to pack an umbrella.
Have you ever wondered why a team keeps hiring people who look remarkably similar? Or why certain clients receive faster responses than others, despite no official prioritization policy? These situations often stem from implicit bias—the unconscious attitudes and stereotypes that affect our understanding, actions, and decisions without our awareness.
What is Implicit Bias?
Implicit bias refers to attitudes or stereotypes that operate outside our conscious awareness. Unlike explicit bias (which reflects beliefs we acknowledge), implicit bias operates automatically, unintentionally influencing our behaviors and decisions despite our conscious values.
The Interview Room Reality
At one well known tech solutions company, the hiring team prided themselves on their objective assessment methods. Yet when analyzing two years of hiring data, they made a startling discovery: candidates with names suggesting certain cultural backgrounds were 35% less likely to advance past initial interviews, despite identical qualifications.
“We were shocked because we genuinely believed we were making purely merit-based decisions,” explains Rakesh Kumar, HR Director. “After implementing blind resume reviews, removing names and addresses in initial screenings, we saw a dramatic shift in our candidate pool diversity.”
How Implicit Bias Quietly Shapes Business
Implicit bias manifests in workplace settings in several consequential ways:
Customer Service Disparities
A telecommunications company analyzed their customer service response times and discovered representatives unconsciously responded faster to emails from customers with male names and titles like “Director” or “VP.” Female customers and those without titles waited an average of 23 minutes longer for responses to identical queries.
Resource Allocation Skews
When a manufacturing firm evaluated project funding approvals, they found proposals from longer-tenured managers received 40% more budget allocation than those from newer managers—even when external evaluators rated the newer managers’ proposals as more innovative and potentially profitable.
Performance Evaluation Discrepancies
Research by a financial services firm revealed that performance reviews for women contained 2.5 times more language about communication style (“aggressive,” “abrasive”) while men’s reviews focused primarily on business outcomes and technical skills, despite similar performance metrics.
The Business Cost of Unconscious Assumptions
Implicit bias carries significant costs:
Innovation Limitations: When teams lack cognitive diversity due to implicit hiring biases, research shows they generate 15% fewer novel solutions to problems
Talent Loss: Organizations lose qualified candidates and employees when unconscious biases affect recruitment and advancement
Reputation Damage: Companies increasingly face public scrutiny when bias patterns become visible
Legal Vulnerability: Systematic bias, even if unconscious, can create legal exposure
Why Implicit Bias Is So Difficult to Address
Unlike other cognitive biases, implicit bias presents unique challenges:
It operates below conscious awareness
It often contradicts our explicit values
We tend to recognize it more easily in others than in ourselves
It can be activated situationally when we’re stressed, rushed, or cognitively taxed
Strategies for Minimizing Implicit Bias
Forward-thinking organizations are implementing effective countermeasures:
Structured Decision Processes
The procurement department at a global retailer implemented standardized evaluation criteria that must be completed before vendor selection. This structured approach reduced the influence of “gut feelings” that often harbor implicit biases.
Blind Review Mechanisms
A venture capital firm now removes founder demographics from initial pitch evaluations, focusing solely on business metrics and innovation potential. This resulted in a 28% increase in funding for ventures led by women and minorities.
Bias Interrupters
An advertising agency appointed “bias interrupters” in creative meetings—team members specifically tasked with questioning assumptions about target audiences. This simple practice led to campaigns reaching previously overlooked customer segments.
Data-Driven Awareness
A healthcare system began tracking physician referral patterns and discovered specialists were disproportionately referring complex cases to male colleagues. Simply making this pattern visible through monthly metrics resulted in a more equitable distribution without additional interventions.
The Path Forward: From Awareness to Action
While complete elimination of implicit bias may not be possible, awareness combined with structural changes can significantly reduce its impact:
Acknowledge Universality: Recognize that having implicit biases doesn’t make someone “bad”—these biases are universal human tendencies
Measure Impact: Use data to identify where bias might be influencing key decisions
Create Friction: Implement processes that slow down automatic thinking, creating space for more deliberate evaluation
Prioritize Diversity: Ensure diverse perspectives are present when making important decisions
As IBM’s former CEO Ginni Rometty noted, “Growth and comfort do not coexist.” Addressing implicit bias often feels uncomfortable precisely because it challenges our self-perception as fair and objective decision-makers.
The most successful organizations recognize that confronting implicit bias isn’t just about social responsibility—it’s about making better business decisions by ensuring all available talent, perspectives, and opportunities are fully considered.
What hidden patterns in your organization’s decisions might reveal implicit biases at work?
Have you ever found yourself endlessly researching before making a decision, only to feel more confused than when you started? Or spent hours gathering metrics that ultimately didn’t change your course of action? If so, you’ve experienced information bias—our tendency to seek additional information even when it won’t improve our decisions.
What is Information Bias?
Information bias is our natural tendency to believe that more information leads to better decisions, even when additional data is irrelevant or excessive. In today’s data-saturated business environment, this bias can lead to analysis paralysis, wasted resources, and delayed action.
The Manufacturing Supply Chain Dilemma
Rajesh, a procurement manager at a medium-sized auto parts manufacturing company, is responsible for maintaining optimal inventory levels of critical components. For years, his ordering decisions have been effectively guided by three key metrics: current stock levels, production forecasts, and supplier lead times. Yet each month, his team spends nearly 40 hours gathering additional data: detailed breakdowns of stock movement by hour, historical pricing fluctuations over five years, weather patterns that might affect shipping routes, and extensive competitor intelligence reports. Despite this exhaustive research, Rajesh’s final ordering decisions consistently align with what the three primary metrics initially suggested. “I realized we were investing two full working days every month collecting information that wasn’t materially changing our procurement decisions,” Rajesh explains. “Now we focus on our core metrics and only dive deeper when there’s a specific supply chain disruption or market anomaly to address. Our decision quality remained the same, but we’ve reclaimed valuable time.”
When More Information Hurts Rather Than Helps
Information bias manifests in business settings in several costly ways:
Analysis Paralysis
The marketing team at a mid-sized e-commerce company spent six weeks gathering consumer data before launching a straightforward email campaign. By the time they felt they had “enough information,” their competitors had already captured the seasonal opportunity. What they didn’t realize: after the first week, additional research wasn’t reducing uncertainty in any meaningful way.
Illusion of Control
A regional sales manager requires his team to submit 15-page reports with dozens of metrics before their weekly meetings. When asked which data points actually influence his decisions, he could only identify three. The extensive reporting gives him a feeling of control without actually improving outcomes.
Decision Avoidance
“We need more data before deciding” often serves as a socially acceptable way to avoid making difficult choices. A product development team at a consumer goods company delayed sun protection product decisions for months by continuously requesting additional market research—ultimately missing their launch window despite having sufficient information early in the process.
Confirmation Seeking
Sometimes we seek additional information not to make better decisions, but to validate choices we’ve already made. A real estate developer continued requesting financial projections with slightly adjusted assumptions until the numbers supported her preferred property investment, rather than letting the initial valid data guide her decision.
Why We Fall Into The Information Trap
Our preference for unnecessary information stems from several factors:
Uncertainty Aversion: Humans naturally dislike uncertainty; gathering more data creates a comforting illusion of reduced ambiguity.
Decision Accountability: Additional information provides psychological protection—if criticized, we can point to our thorough research.
Corporate Culture: Many organizations reward “data-driven” approaches without distinguishing between valuable information and unnecessary details.
Technology Access: Modern business tools make it easy to generate endless reports and dashboards, whether useful or not.
Breaking Free From Information Bias
Smart business leaders are finding ways to combat information bias:
Define “Enough” in Advance
Before gathering data, ask: “What specific information would change my decision?” and “At what point would additional information no longer affect my choice?” A product manager at a software company sets specific thresholds: “If user testing shows satisfaction above 85%, we’ll proceed with the feature regardless of additional feedback.”
Implement Decision Rules
Establish clear rules for routine decisions to avoid information overload. A logistics company created a simple algorithm for delivery route planning rather than analyzing dozens of variables daily. The streamlined approach proved 95% as effective while saving hours of analysis.
Distinguish “Nice to Know” From “Need to Know”
A manufacturing supervisor was drowning in daily reports until she categorized metrics as either decision-critical or merely interesting. She discovered that 70% of the information she received didn’t influence any operational decisions.
Conduct Information Audits
Periodically review what data your team collects and uses. A financial services firm discovered that 40% of their weekly reports were either redundant or unused after conducting a simple audit asking managers to identify which information actually influenced their decisions.
The Decision Quality Test
When you find yourself seeking more information, ask these questions:
Would a reasonable decision be possible with what I already know?
What specific action would change based on this additional information?
Is gathering more data primarily providing decision value or psychological comfort?
Does the value of potentially better decisions outweigh the cost of delayed action?
As management expert Peter Drucker wisely noted: “The most common source of mistakes in management decisions is the emphasis on finding the right answer rather than the right question.”
In our information-rich business environment, the competitive advantage increasingly belongs not to those with the most data, but to those who best distinguish signal from noise—knowing when more information will improve decisions and when it simply wastes valuable time and resources.
The next time you find yourself saying “we need more data,” pause and ask whether you truly need more information to decide, or if you already know enough to act wisely.
What decisions might you be delaying in your business under the guise of needing more information?
Have you ever wondered why the first price you see for a product seems to determine what you consider “expensive” or “a good deal” afterward? Or why your initial impression of a job candidate’s resume might color your entire interview assessment? These are examples of anchor bias, a fascinating mental shortcut that profoundly affects our judgment, especially for those in leadership positions.
What is Anchor Bias?
Anchor bias occurs when we rely too heavily on the first piece of information we encounter (the “anchor”) when making decisions. This initial reference point creates a powerful psychological effect that influences subsequent judgments, even when the anchor is completely arbitrary or irrelevant.
The Daily Life of Anchor Bias
The Weekend Shopping Dilemma
Last Saturday, I walked into a IKEA store looking for a new work table. The first one I spotted had a price tag of ₹15,000. Throughout my shopping journey, I found myself mentally comparing every other table to this initial price, tables at ₹12,000 felt like “good deals” while those at ₹18,000 seemed “overpriced.” Only later did I realize my entire perception of “reasonable pricing” had been shaped by that first tag I happened to see, rather than any objective assessment of quality, materials, or craftsmanship.
The Restaurant Menu Strategy
Ever notice how many restaurants place an extremely expensive item at the top of their menu? That ₹2,500 lobster special isn’t necessarily there because they expect everyone to order it. Rather, it makes the ₹850 dish below it suddenly feel like a moderate, reasonable choice—even though you might have considered ₹850 quite expensive without that initial anchor.
How Anchor Bias Derails Leadership Decisions
Salary Negotiations Gone Wrong
Imagine you’re a manager who needs to hire a new team member. The first candidate mentions they earned ₹8 lakh annually in their previous role. Without realizing it, this number becomes your anchor. When the second candidate (who may actually be more qualified) asks for ₹10 lakh, you instinctively perceive this as “expensive,” even if market rate for the position is actually ₹12 lakh. The first number you heard has distorted your entire perception of fair compensation.
Budget Planning Limitations
A marketing director I know once shared how his team’s innovation was hampered by anchor bias. Each year’s budget discussions began with the statement, “Last year, we spent ₹50 lakh on digital marketing.” This anchor made any proposal for ₹75 lakh seem like a dramatic increase requiring extensive justification, even though market conditions and strategic priorities had completely changed. The previous budget had become an arbitrary anchor limiting strategic thinking.
Performance Review Distortions
Leaders often unintentionally create anchors during performance evaluations. If you begin by discussing one aspect of performance (either positive or negative), this initial focus can disproportionately influence your overall assessment. A manager who starts by praising a team member’s project management skills might subconsciously downplay significant communication issues later in the review.
Why Leaders Are Particularly Vulnerable
Leaders face unique challenges with anchor bias:
Decision Volume: Executives make numerous decisions daily, increasing reliance on mental shortcuts
Information Asymmetry: Often, the first person to speak in a meeting sets the anchor for everyone else
Precedent Power: In organizational cultures, “what we did before” creates powerful anchors
Status Effects: Numbers presented by high-status individuals create stronger anchors than the same figures presented by others
Breaking Free From Anchor Bias
Consider Multiple Reference Points
Smart leaders deliberately seek various data points before making judgments. When evaluating employee performance, review multiple projects rather than allowing the most recent one to serve as an anchor.
Reverse Your Thinking
Try approaching decisions from the opposite direction. If you’re negotiating and someone anchors at ₹10 lakh, mentally reset by asking, “What if they had started at ₹5 lakh instead? How would I value this differently?”
Use Anonymous Data
When possible, evaluate information without knowing its source. Many progressive organizations now review job applications with names and previous salary information removed to prevent anchoring on irrelevant factors.
Establish Pre-Commitment Criteria
Before seeing any numbers or options, document your decision criteria. A construction company I consulted with requires managers to write down their vendor selection criteria before seeing any bids, preventing the first price from becoming an anchor.
A Leader’s Reflection Exercise
The next time you’re about to make an important decision, pause and ask:
“What number or reference point came to my attention first?”
“How might this initial information be distorting my subsequent judgments?”
“If I had encountered completely different initial information, would my decision process be different?”
By recognizing the subtle yet powerful influence of anchors, leaders can make more objective decisions that better serve their organizations and teams. After all, awareness of our biases is the first step toward overcoming them.
What initial reference points might be unconsciously anchoring your leadership decisions today?
