Looking beyond what survived to understand the complete picture
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.
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.
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.
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 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.
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 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.
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.
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.
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?
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.
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.)
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.
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.
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.
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.
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 stubbornly held onto your initial judgment despite mounting evidence to the contrary? That’s conservatism bias at work—our tendency to insufficiently update our beliefs when presented with new information.
We pride ourselves on being rational thinkers, weighing evidence objectively before forming conclusions. Yet cognitive science reveals a systematic flaw in how we process new information: conservatism bias. This tendency to insufficiently revise our beliefs when presented with new evidence affects everything from personal finances to organizational strategy.
Conservatism bias occurs when people update their existing beliefs too slowly in the face of new, relevant information. First documented by psychologist Ward Edwards in the 1960s, this bias shows how we tend to “anchor” to our initial judgments, making only modest adjustments even when confronted with substantial contradictory evidence.
Unlike confirmation bias (where we seek information supporting our existing views), conservatism bias focuses on how we process new information once we encounter it—typically giving it less weight than statistical reasoning would suggest is appropriate.
Consider an investor who believes a particular stock is undervalued. When the company releases disappointing quarterly earnings, they might acknowledge this negative news but still underestimate its significance. Research from the Indian Securities and Exchange Board shows retail investors typically adjust their price expectations by only 40% of what would be statistically justified following earnings surprises, whether positive or negative.
A 2020 study in the Indian Journal of Medical Research found that physicians who made initial diagnoses were 30% less likely to completely revise their assessment when contradictory test results arrived compared to doctors seeing the case fresh. This “diagnostic momentum” demonstrates how early judgments resist appropriate updating.
Organizations frequently underreact to market changes that challenge their existing business models. Kodak famously recognized the threat of digital photography (their engineers actually invented the first digital camera in 1975) but significantly underweighted this evidence when planning their future, clinging to their film-based business model until it was too late.
Several factors contribute to conservatism bias:
Thoroughly revising beliefs requires significant mental energy. It’s simply easier to make minor adjustments to existing views than to completely reconsider our position.
We tend to overestimate the accuracy of our initial judgments. This overconfidence makes us less receptive to evidence suggesting we might be wrong.
Humans have a natural tendency to prefer existing states over change. This status quo bias reinforces conservatism in updating beliefs.
Changing our minds dramatically can feel uncomfortable, especially when we’ve publicly committed to a position. This social pressure reinforces incremental rather than transformative belief updates.
Using numerical probabilities rather than vague beliefs makes it easier to update appropriately. For instance, assigning specific likelihood percentages to potential outcomes forces more rigorous updating when new evidence arrives.
People without attachment to initial judgments can more objectively assess new information. Creating “red teams” tasked with challenging existing views helps organizations overcome institutional conservatism bias.
Decide in advance what evidence would change your mind, before seeing the results. This prevents moving the goalposts when confronted with belief-challenging information.
Named after 18th-century mathematician Thomas Bayes, Bayesian reasoning provides a formal framework for updating probabilities based on new evidence. Even informal Bayesian thinking—explicitly considering both prior beliefs and the strength of new evidence—can improve belief updating.
Conservatism bias isn’t just an academic curiosity, it has substantial real-world consequences. Companies that fail to adequately update their strategic thinking face extinction. Investors who insufficiently revise their market views sacrifice returns. Medical professionals who inadequately integrate new test results may miss critical diagnoses.
By recognizing our tendency toward conservatism bias, we can deliberately counteract it, ensuring that our beliefs more accurately reflect all available evidence rather than giving undue weight to our initial judgments.
The next time you encounter information challenging what you believe, ask yourself: Am I giving this evidence the weight it truly deserves, or am I being conservative in updating my beliefs?
I recall when I brought my Jeep, with very peculiar and unique grey color, I suddenly I’m seeing grey Jeep everywhere. On my commute, in parking lots, at the grocery store—they’re multiplying like rabbits! Or are they? This phenomenon has a name: selective attention bias.
Let me share what I’ve learned about this fascinating quirk of our minds and how it shapes our daily experiences, both personally and professionally.
Selective attention bias occurs when our minds prioritize information that aligns with our current focus or interests while filtering out everything else. As cognitive psychologist Daniel Kahneman explains in his book “Thinking, Fast and Slow,” our brains have limited processing capacity and must be selective about what information receives our conscious attention.
“We can be blind to the obvious, and we are also blind to our blindness,” Kahneman writes. This blindness isn’t a flaw, it’s a feature that helps us navigate an overwhelmingly complex world.
That experience with my Jeep Compass? It has another name: the Baader-Meinhof Phenomenon or frequency illusion. Once something enters your awareness, you start noticing it everywhere.
Stanford linguistics professor Arnold Zwicky coined the term “frequency illusion” in 2006 to describe this cognitive bias. The thing isn’t actually more common, you’re just more attuned to it 😀.
Look at the FedEx logo. Do you see the arrow between the “E” and “x”? Once someone points it out, you can’t unsee it. But many people go years without noticing this clever design element.
The Amazon logo has an arrow that points from A to Z (suggesting they sell everything) while forming a smile. Before someone mentions it, most people only see the smile without noticing the A-to-Z connection.
The Toblerone logo contains the silhouette of a bear hidden in the mountain imagery, a nod to Bern, Switzerland (known as the “City of Bears”) where the chocolate was created. Once seen, it’s obvious, but many chocolate lovers miss it completely.
We tend to notice information that confirms our existing beliefs while overlooking contradictory evidence. This confirmation bias affects everything from which news sources we trust to which products we buy.
Marketers leverage selective attention brilliantly. As marketing professor Jonah Berger notes in his book “Contagious,” “People don’t think in terms of information. They think in terms of narratives.” Brands create narratives that align with your current focus, making their products seemingly appear everywhere.
Being aware of selective attention bias can help us grow. By consciously exposing ourselves to diverse perspectives, we can counteract our brain’s natural tendency to filter information that challenges our worldview.
Last month, I was researching ergonomic office chairs for myself (exciting, I know). Within days, I started noticing office chair ads everywhere online, colleagues’ chairs during video calls, and even found myself analyzing seating in coffee shops.
Was the universe suddenly obsessed with office furniture? Nope—just my brain selectively focusing on what had recently become important to me.
Understanding selective attention bias has made me a better professional:
As American psychologist William James observed back in 1890, “My experience is what I agree to attend to.” By becoming conscious of our selective attention, we gain more control over our experience of the world.
What are you selectively attending to today? Look around, you might be surprised by what you’ve been missing!
When What Comes to Mind Isn’t What Matters: Availability Bias in Daily Life
We all make dozens of decisions every day, from what to eat for breakfast to how to approach a work project. But how rational are these choices? Cognitive psychologists have identified numerous biases that influence our thinking, and one of the most pervasive is availability bias: our tendency to overweight information that easily comes to mind.
Availability bias occurs when we base judgments on information that’s mentally “available”, examples that easily come to mind because they’re recent, emotional, or vivid, rather than on complete data or statistics.
As Nobel Prize-winning psychologist Daniel Kahneman noted, “The mind overestimates unlikely events that are easy to recall.” This bias affects everyone from consumers to CEOs, subtly shaping decisions in ways we rarely notice.
In 2019, after a dramatic machinery accident at a textile factory in Tirupur received significant media coverage, many Indian textile manufacturers invested heavily in that specific type of machine safety equipment. However, data from the Directorate General Factory Advice Service showed that more common hazards like improper material handling caused 58% of factory injuries that year, while machinery accidents accounted for only 14%.
After Air India Express Flight 1344 crashed in August 2020 during the pandemic, many Indian travelers expressed increased anxiety about flying. Meanwhile, National Crime Records Bureau statistics showed that road accidents in India claimed over 150,000 lives that same year—making car travel approximately 1,000 times more dangerous per kilometer traveled than flying.
When a major smartphone battery defect made international headlines in 2016, consumers worldwide became hyper-aware of potential battery issues. A 2017 survey by the Consumer Electronics Association found 74% of respondents listed battery safety as a top concern when purchasing a new phone, despite the actual failure rate being less than 0.01% of devices.
A study published in the Indian Journal of Medical Research found that patients were significantly more likely to reject a treatment if they personally knew someone who had experienced a rare side effect. This occurred even when presented with statistics showing the treatment’s overwhelming benefits for most patients.
When the Indian stock market experienced a sharp correction in early 2022, many retail investors pulled their money out, fearing another major crash like 2008. However, historical data from the Bombay Stock Exchange shows that staying invested through downturns has consistently produced better returns than trying to time market exits and entries.
When a story grabs your attention, actively look for statistics that put it in context. Is this dramatic event representative or an outlier?
Consuming varied information sources helps provide a more balanced view of reality. Look beyond trending stories to understand what issues might be important but less visible.
Recording your decisions and their outcomes helps identify patterns where availability bias might be influencing your choices. Many successful business leaders in both India and internationally credit this practice with improving their decision quality.
When evaluating a situation, ask: “How common is this generally?” For example, before panicking about a medical symptom featured in a news story, check how frequently it actually occurs in the population.
Availability bias isn’t something we can eliminate, it’s hardwired into how our brains work. However, awareness of this bias can help us pause and consider whether our intuitive judgments might be skewed by what easily comes to mind rather than what actually matters.
By balancing vivid stories with statistical context, we can make decisions that better reflect reality rather than merely what’s most available in our memory.
The next time a dramatic story influences your thinking, ask yourself: Is this truly representative, or simply what comes to mind most easily?
We’ve all been there. You’re driving to a destination using your usual route when a traffic alert pops up on your phone. There’s major congestion ahead, but you think, “I’ll stick with this road anyway—it’s the one I know best.” Twenty minutes later, you’re sitting in bumper-to-bumper traffic, watching cars zip by on the alternate route you could have taken.
What just happened? You experienced plan continuation bias—a cognitive trap that affects everyone from everyday commuters to airline pilots, business leaders, and project managers.
Plan continuation bias (sometimes called “get-there-itis”) is our tendency to continue with an original plan despite changing conditions that make the plan no longer safe, viable, or beneficial. It’s our natural reluctance to revise or abandon a course of action once we’ve committed to it, even when warning signs suggest we should.
This bias is particularly dangerous because it operates below our conscious awareness. We don’t actively decide to ignore new information—we simply fail to give it appropriate weight against our pre-existing plan.
Several psychological factors contribute to plan continuation bias:
The concept of plan continuation bias was first extensively studied in aviation, where it contributes to numerous accidents. For example Air India Express Flight 812 crash On 22 May 2010, the Boeing 737-800 passenger jet operating the flight crashed on landing at Mangalore. The crash exemplifies this bias in action. Despite flying into known trouble and deviating many guidelines, the pilots continued their planned route rather than diverting, ultimately encountering shorter runway that led to the crash and loss of almost of all 158!souls on plane. https://en.wikipedia.org/wiki/Air_India_Express_Flight_812
Kodak’s infamous decline illustrates plan continuation bias in business. Despite developing the first digital camera in 1975, Kodak continued focusing on its traditional film business. As digital photography revolutionized the market, Kodak stubbornly stuck to its original business model until it was too late.
Let’s take an example, Kingfisher Airlines’ Aircraft Manufacturing Partnership (2005-2012):
While persistence is often celebrated as a virtue, knowing when to change course is equally important. The most successful individuals and organizations aren’t those who never fail, but those who recognize failure quickly and adapt accordingly.
Remember: The most dangerous words in business (and life) might just be “we’ve always done it this way” or “we’ve come too far to turn back now.”
By understanding plan continuation bias and actively working to counteract it, we can make better decisions, avoid unnecessary risks, and ultimately achieve better outcomes—even if the path to those outcomes looks different than we initially imagined.
Have you ever found yourself stuck in a failing plan? What strategies helped you recognize when it was time to change course? Share your experiences in the comments below.
Leadership is a widely discussed topic, also one of the favoured topic of mine to read and write. And again and again I came across more or less same question, what truly defines a “good leader”? I recently came across a thought-provoking question that captures a common debate:
A. A good leader expects people to decide for themselves what they should do.
B. A good leader makes it clear to everybody what their jobs are
PS: I was taking survey made by Sejal Waghmare at TheVibrantAura
Both statements present unique perspectives on leadership, each with its own strengths and weaknesses. I would like to discuss how these ideas can influence team productivity and promote human-centric work environments..
Leaders who allow team members to decide for themselves foster autonomy, trust, and innovation. This approach taps into intrinsic motivation—when people have ownership over their work, they’re often more engaged and creative. It’s especially effective in environments where flexibility and adaptability are valued.
However, too much autonomy without guidance can lead to confusion, misaligned priorities, and duplicated efforts. Not everyone feels comfortable making decisions without a framework, especially new or less confident team members.
On the other hand, leaders who clarify roles and responsibilities help ensure alignment, accountability, and efficiency. When everyone knows what’s expected, teams can focus, collaborate more smoothly, and avoid wasted time or misunderstandings. This style supports productivity, especially in high-pressure or complex situations.
But there’s a downside: if directions are too rigid or prescriptive, team members may feel micromanaged or stifled, leading to disengagement and missed opportunities for innovation.
The most effective leaders balance both approaches. They provide clarity about goals, roles, and expectations while encouraging team members to use their judgment and creativity within that framework. This balance empowers individuals and drives productivity, while also fostering trust, engagement, and growth.
The key is clarity, which requires excellent communication skills and empathy when conveying information to the individual.
Leaders who aspire to lead a successful team, needs to get him self clarified first when it comes to expectations and deliverables.
Deliverables can be effectively defined using various tools such as the SMART framework (Specific, Measurable, Achievable, Relevant, Time-bound). However, setting expectations requires more than just defining deliverables; it demands a clear and detailed job description along with a well-articulated objective for the role. Only with this clarity can alignment between individual performance and organizational goals be ensured.
Often, team members are unable to see how their roles contribute to the organization’s broader goals. When this connection is clearly communicated, it significantly enhances both motivation and alignment. A clear line of sight between individual responsibilities and organizational outcomes fosters a stronger sense of purpose and accountability.
A good leader doesn’t choose between clear direction and empowering autonomy—they blend both to bring out the best in their teams. By doing so, they create environments where people know what to do, feel trusted to make decisions, and are motivated to excel.
Happy reading. See you soon.
Winners Focus on Processes, Losers Fixate on Goals – anonymous
Ever hit a big goal, then found yourself slipping back to old habits? That’s the problem with goal-setting without a process.
Many people believe that setting ambitious goals is the key to success. However, high achievers don’t just set goals—they build systems and processes that make success inevitable.
Many of us believe SMART goal is enough to deliver, what we miss is “how to repeat the performance”? And that’s answered by the process. A process to achieve the Goal is more important than the only focusing on Goal, this will help keep the pace when the goals become blurry due to some unforeseen conditions in the way to achieve the goal.
This idea is best captured by James Clear in Atomic Habits:
You do not rise to the level of your goals. You fall to the level of your systems.
Let’s break this down further.
Imagine two runners preparing for a marathon:
• Runner A sets a goal to finish the race in under four hours but doesn’t follow a structured training plan.
• Runner B sets the same goal but focuses on a disciplined routine—consistent training, proper nutrition, and recovery strategies.
When race day arrives, Runner B is far more likely to succeed. Why? Because they followed a process that naturally led to their goal.
A goal is just an outcome. A process is the repeated effort that makes the outcome possible.
Goals are the destination; systems are the GPS.
A common mistake people make is thinking, “Once I achieve my goal, I’ll be happy.” But this mindset often leads to frustration:
• A student who aims for straight A’s but crams before exams is unlikely to retain knowledge.
• A company that chases revenue targets without refining its operations will struggle to scale.
On the other hand, successful people don’t just work toward a goal—they enjoy the daily habits and actions that bring them closer to it.
Cramming may get grades, but not confidence. Growth without good systems leads to stress, not scale.
• Goals create temporary motivation , You push hard until you reach the target, but what happens next? Without a system, success isn’t sustainable.
• Goals rely on external validation , If you only measure success by hitting targets, you might feel like a failure when you miss one.
• A manager focused solely on reducing machine downtime in the current quarter might skip preventive maintenance to hit the target faster. While short-term numbers improve, long-term reliability suffers—leading to higher breakdowns, team burnout, and customer dissatisfaction. By chasing the goal without investing in a sustainable process, the manager risks the organization’s future stability for a quick win.
It’s like building a house on quicksand. Looks fine—until it starts sinking.
• Want to lose weight? Instead of setting a target weight, focus on sustainable daily habits like balanced meals and regular exercise.
• Want to grow your business? Instead of obsessing over revenue numbers, refine processes for sales, marketing, and customer service.
• Want to improve leadership? Instead of aiming to “be a great leader,” create a habit of active listening, mentorship, and continuous learning.
The key? Make success a byproduct of your habits, not just a one-time event.
The magic happens when your habits become who you are.
True transformation happens when success is not just something you chase but part of who you are. If you focus on the right habits:
• You’re not “trying to get fit”, you are someone who exercises daily.
• You’re not “working toward a book”, you are a writer who writes every day.
• You’re not “trying to hit sales targets”, you are a business that consistently delivers value.
In the long run, winners win because they commit to the process, not just the prize.
Goals are good for setting direction. But processes are what create real, lasting success. The next time you set a goal, ask yourself:
“What system can I build to make this success inevitable?”
That’s what separates winners from the rest.
Management attention is the ultimate constraint!
Eliyahu M. Goldratt
When it comes to new ideas and innovations from the team, the ultimate bottleneck is management. Their time and interest define whether the ideas are going to see the light of day! And as usual, words drown in various biases, and a billion-dollar idea will be killed without even realising its potential, just because the manager could not agree or find time to “rethink” his objections. Clearly, it’s not a new issue.
When iPhone peaches to Steve Jobs, he ridiculed it initially, believing that a mobile phone should focus on essential functions rather than extravagant features. It was he who was thinking differently while reviving Apple and avoiding bankruptcy, ultimately leading to the creation of the revolutionary iPod, which transformed how the world consumed music. However, it was his ingenious team, fueled by innovation and creativity, who dared to think again and found a compelling use case for the iPod as a phone. They envisioned a seamless integration of music, communication, and internet capabilities within a single device, thus paving the way for what would become the iPhone and revolutionizing the entire smartphone industry in the process. Through their collaborative efforts, they not only changed the way individuals interacted with technology but also set a new standard for what a mobile device could achieve in our daily lives.
For sure, each successful enterprise has an innovative founder, however it’s the team who make the enterprise succeed again and again and give the edge.
The book “Think Again” by Adam Grant, discusses the importance of rethinking and unlearning in a changing world. It emphasizes the value of being open to changing one’s mind and embracing doubt. Confidence combined with humility leads to better rethinking and learning. Challenging our own beliefs and seeking new perspectives can improve decision-making. Encouraging others to question their assumptions can lead to more open-minded conversations.
It’s important to recognise the mode that we operate in while discussing an idea with someone. Especially when the ideas is not belongs to us, but we are the decision makers. The three modes quoted in the books are preachers, prosecutors, and politicians.
In each of these modes, we take on a particular identity and use a distinct set of tools. We go into preacher mode when our sacred beliefs are in jeopardy: we deliver sermons to protect and promote our ideals. We enter prosecutor mode when we recognize flaws in other people’s reasoning: we marshal arguments to prove them wrong and win our case. We shift into politician mode when we’re seeking to win over an audience: we campaign and lobby for the approval of our constituents. The risk is that we become so wrapped up in preaching that we’re right, prosecuting others who are wrong, and politicking for support that we don’t bother to rethink our own views.
The mode which emphasis on questions everything is called as Scientist mode. For sure, it’s a methodology which researchers are trained to use, it’s not limited to white lab coats. This mode comes to action when we are in search of truth. The way to operate this mode is build the hypothesis, which you like to make it happen, and test this hypothesis by discovering knowledge.
The biggest hurdle of using Scientist mode is “ego”, and “we have done everything in past” a status quo bias.
This cognitive bias leads people to prefer maintaining current practices or traditional methods, often resisting changes or new approaches. It’s driven by a comfort with the familiar and a perception that past methods are inherently safer or more effective.
In organizational settings, this bias can hinder innovation, as it causes people to dismiss new ideas by overvaluing past successes. Another related concept is sunk cost fallacy, where past investments in a particular approach make people reluctant to abandon it, even if it’s no longer the best option.
It’s all really come down to acknowledging that we are prone to these biases, and overcoming this will truly bring innovations to organisation and will sustain growth long term. Few practices mentioned below, which I believed from my experience are really helpful. Also few of them are also aligned to over all theme of “Think Again” practice mentioned by Adam Grant.
1. Embrace a Scientist Mindset: Approach ideas like a scientist rather than a preacher, prosecutor, or politician. This involves forming hypotheses, experimenting, and being willing to change beliefs based on new evidence, which can help challenge assumptions about past practices.
2. Rethink Familiar Practices: Grant suggests actively questioning the effectiveness of familiar practices and regularly asking, “What if we tried a different approach?” This helps counter the comfort of “we’ve always done it this way.”
3. Encourage Intellectual Humility: Recognize that being wrong is a natural part of learning. Leaders can set an example by admitting mistakes and valuing learning over being right, which encourages others to embrace new ideas and reduce reliance on the past.
4. Seek Diverse Perspectives: Invite input from people outside the usual circle who may offer fresh viewpoints. This approach helps expose blind spots and reduces the tendency to default to what’s been done before.
5. Focus on Small Wins: Trying small, low-stakes experiments with new ideas can make people more open to change. These incremental steps help build confidence in different approaches without overwhelming the organization.
The approach of “Think again” and “Think Different” is a practice which make us pause before getting overwhelmed by the newness of the idea.
A pause and change in perception will bring the focus back to this question of how to think differently and think again, for the concept which we may think not worth of our time.
Management being ultimate gate keeper of the funds and resources, are the responsible ones who should practice “Think Again” and allow team to “Think differently”.
I hope this small blog will bring some insights and will help you “Think Differently”
Larry Bossidy, Ram Charan, Charles Burck
The three processes—people, strategy, and operations— remain the building blocks and heart of good execution. But as the economic, political, and business environments change, the ways in which they are carried out also change.”
Change or not change, that’s the constant tug of war an organization faces. Change being only constant, and our love of inertia (why to change), leads to this war within each organization. A successful company becomes successful, by knowing customer better than its competition, but then same company faces competition to safeguard its turf due to its ‘belief’ that they know customer! Customers are more prone to change, and they have fewer option to avoid it, and the organization which constantly tap such changes in customer’s expectations make it sustain and bloom constantly!
Recently I read book “Execution: The Discipline of Getting Things Done”
Execution: The Discipline of Getting Things Done by Larry Bossidy and Ram Charan emphasizes the importance of executing strategies effectively to drive success in any organization. The book argues that many companies fail, not due to a lack of vision, but due to a failure in execution. It breaks down execution into three main processes: people, strategy, and operations. The authors highlight the role of strong leadership in establishing a culture of accountability, aligning the right people with the right tasks, and maintaining a rigorous focus on the practical steps needed to reach goals. The book provides actionable advice for leaders to ensure that plans turn into results by consistently focusing on follow-through and engagement at all levels of the organization.
With such challenges, the book help answer following three questions, these aspects not only enable a faster change but also help us being more dynamic and adaptive to constantly changing environment.
The thing is not always what we assume it is. Often, we get in our own way when solving problems with a new way of thinking, because we’re afraid it won’t yield better results than the tried-and-true methods of yesterday! We need a framework for thinking through the most common problems with a new lens on what might work to bring about the most effective, long-term solution
In business, where competition is between products rather than companies, the line of sight between a CEO’s decisions and whether a customer will buy a product at any given time is much less clear. The individual outcomes of customers’ decisions are far from easy for executives seating in head office, removed from the front line, to predict and control.
If the judge of the value of any product or service is the customer who chooses to buy, not the provider, then it is the provider’s (Company’s) people at the front line, in front of the customer, who are best placed to determine what the customer values. It is up to the rest of the company to help the people in the front lines, where the revenues come in, to satisfy those customer needs. The lower level, in effect, is the customer of the level above it. And like a customer, it should expect to get more value from those services than it pays to get them.
Companies should build Cumulative advantage as the layer on its initial competitive advantage by making its product or service an ever more instinctively comfortable choice for the customer. Focus on helping customer make easy choice over making the product a habit.
The common belief about competitive advantage is that successful companies choose a position, focus on certain consumers, and design activities to serve them better. The aim is to get customers to buy again by matching the value offered to their needs. By creating unique and personalized experiences, the company can maintain a competitive edge. This way of thinking assumes that consumers make careful and logical decisions. Although emotions may play a role in buying, many times these decisions come from a conscious thought process. A good strategy understands and responds to this thought process. However, research in behavioural psychology suggests that buying decisions aren’t always made consciously. Our brains work more like machines that fill in gaps: they take incomplete information and quickly complete it using past experiences. This fast thinking, known as intuition, includes thoughts and feelings that come to mind quickly and strongly influence our actions. It’s not just what we remember that shapes our quick judgments but also how easy and fast we can remember it. When we decide based on what “feels right,” it usually means our thinking process was smooth and effortless. Hence, one reason people often choose the leading product is simply that it is the easiest option available, as it stands out in the shopping environment.
If consumers are slaves of habit, it’s hard to argue that they are “loyal” customers in the sense that they consciously attach themselves to a brand on the assumption that it meets rational or emotional needs. In fact, customers are much more fickle than many marketers assume: often the brands that are believed to depend on loyal customers achieve the lowest loyalty scores. So why do fringe brands like local competition survive? The answer, perhaps perversely, is that with big-brand loyalty rates at 50 percent, just enough customers will buy small brands from time to time to keep the latter in business. But the small brands can’t overcome the familiarity barrier, and although entirely new brands do enter categories and become leaders, it is extremely rare for an established fringe brand to successfully take on an established leader.
Strategic planning often gets bogged down in numbers and analysis. This creates a sense of scientific rigor, but it can also lead to a lack of creativity. Many managers find that the annual planning process is time-consuming and doesn’t produce truly innovative strategies.
To break this pattern, we need to shift our thinking. As the saying goes, “In strategy, what counts is what would have to be true—not what is true.” Developing a winning strategy is like creating and testing scientific hypotheses. It involves imagining a new reality where our ideas would work and then figuring out what needs to change to make that happen. This creative process is just as important as the analytical one.
Few steps one can follow for such strategy building: A Possibility Based Approach
It’s a new model, introduced in the ongoing dialogue about the existing frameworks we rely upon to enhance the effectiveness of our strategies. The essence of this discourse revolves around a fundamental truth: you are the master of your models. It’s vital to understand that if you find yourself constantly attributing failures to your model while simultaneously striving to harness its potential, then, inadvertently, you have granted it a monopoly over your thought processes. This situation creates a paradox where the model, rather than serving you, becomes an oppressive force, dictating your decisions and stifling creativity.
Imagine this scenario: you enter into an agreement with a model, believing it has the keys to success. You attempt to optimize your connection with it, tweaking here and there, but the results remain disappointing. Each setback chips away at your confidence, leading to a self-blame spiral. You question your abilities, thinking you simply have not mastered the model’s intricacies. This is a dangerous mindset; it breeds dependency and diminishes your agency.
In contrast, if you adopt an empowered position and hold your model accountable for its outputs, you take the reins of your intellectual journey. You evaluate its effectiveness in delivering the promised results consistently. When you find it lacking, instead of forcing it to work for you, you make the courageous decision to discard it and seek out better alternatives. It’s an exercise in discernment and strategic thinking—embracing flexibility and adaptability rather than a rigid adherence to a failing system. If a model does not meet your needs or align with your goals, there’s no shame in letting it go. After all, your primary objective is to cultivate strategies that genuinely foster growth and drive success, not to be shackled by ineffective tools. Embrace the autonomy of ownership over your models, ensuring they serve your aspirations effectively rather than the other way around.