Why is it that in some organizations, the boss is on a pedestal, while in others, they're just a colleague at the next desk with a fancier title? Throughout our lives, we're constantly surrounded by people in authority—our bosses, leaders, even parents. In fact, our model of behavior toward managers and leaders forms long before our first workday. For example, family dynamics, relationships with parents, student-teacher interactions, and cultural nuances shape how we communicate with managers and subordinates.

The better question to ask is: what distance should be maintained when it comes to the “power game”?

Power Distance Index

The Power Distance Index (PDI) was developed by one of the most prominent researchers in organizational culture typology, Geert Hofstede. This typology’s main criteria are national and ethnic factors. The PDI explains how much a culture encourages the use of power by its leaders. Inequality exists in all cultures, but the level of acceptance toward it varies.

How Does Power Distance Affect Us?

Power distance affects our work style—from behavior in meetings to how comfortable we feel sharing new ideas. In high-PDI cultures, you’re unlikely to encounter open debates or spontaneous idea sessions. Instead, the leader speaks, and others listen. In low-PDI settings, the opposite is true: every team member contributes, and authority is more flexible. However, this may also mean that a lack of clear instructions can sometimes lead to delays in decision-making or even a bit of chaos.

So, which is better? It actually depends on values—clear structure or open dialogue? Each approach has its own advantages and challenges.

Power Distance in Organizational Culture

Culture plays a significant role in how power is perceived. In high-PDI countries like China, Russia, or Mexico, hierarchy is important. Authority is respected, seldom questioned, and there is a clear distance between the leader and subordinates. The leader appears to stand on a mountaintop, with others looking up. The organizational structure is more centralized, and decisions are made at the upper management level.

There are also cultures with low power distance, like Denmark, the Netherlands, and even the USA, where people feel much more comfortable with equality. In such an environment, the manager is simply a regular team member. Critical discussion of ideas, feedback, and collaboration without excessive focus on hierarchy are encouraged. The idea is that power should be distributed, not concentrated in one place.

In these cultures, team members openly debate with the manager, and the organization is more decentralized. Leaders often rely on the expertise and experience of their employees when making decisions.

Power Distance in Georgia

According to a study by The Culture Factor Group based on Hofstede’s model, Georgia’s power distance index is 65, indicating that a hierarchical order is generally acceptable in society, with each person having their place. Hierarchy is viewed as inherent inequality. The unequal distribution of power justifies why certain segments of society receive more advantages than others.

If we look back at our distant and recent past, we find confirmation of all this on the pages of history: monarchy, a communist past, a society imbued with a mentality of obedience to leaders after gaining independence—this is our cultural heritage. A characteristic feature of culture is the drive to maintain internal balance, but on the other hand, it also holds the inevitability of change. We can plainly see how quickly we moved from the "hibernation" phase to an era of motion. This shift is partly influenced by generational change and partly by globalization.

The differences between generations have probably never been as clear as they are now. The new generation is rewriting the rules of power. Unlike previous generations, millennials and Generation Z grew up in an era of globalization and technology. They are unafraid to challenge the status quo. For them, power doesn’t necessarily imply distance. On the contrary, they expect collaboration, transparency, and a more equitable approach within organizations. They grew up in a time when questioning authority is not only acceptable but often encouraged—whether it’s corporate ethics or the pursuit of a better work-life balance. This generation confidently declares, "I have a better idea."

"Fathers and children"—revolution or evolution? For millennials and Generation Z, hierarchy is outdated. The traditional model of “Sit down, do your job, and don’t ask questions” has shifted to a “Let’s come up with it together” approach. They want flexibility, autonomy, and a work culture where not only leaders’ voices are heard, but everyone’s.

By 2030, Generation Z will make up 30% of the workforce, and organizations will have to reach a completely new level of power distribution—in the truest sense of the word.

The process of change is like walking a tightrope because you don’t have a magic wand to erase the differing expectations of Boomers or Generation X, nor can you make Generation Z and millennials love a strict hierarchy created for organizational structure. However, you do have magic words through which you can acknowledge Boomers' experience while letting Generation Z know that they are heard, because in their world, everyone has a voice (and likely a podcast too).

Flexible leaders can strengthen diverse teams while maintaining authority. Engage Generation Z and millennials in decision-making in a way that doesn’t disrupt the structure that Boomers and Generation X value. It’s like sitting front-row at a fashion show—everyone can see the show, but some still deserve reserved seats.

In reality, the principle of evolution and adaptation extends to all aspects of our lives, including organizations. Today's challenge is not in choosing between hierarchical and non-hierarchical approaches but in finding the right “fit”—where both the seasoned boss and the forward-looking Gen Z team member feel equally comfortable.

Finally, the question stands: if the younger generation does not accept the previous structures of power, what awaits organizations that refuse to change? Thinking about the answer to this question, I remembered the dinosaurs. Sixty-five million years ago, the largest and strongest creatures on Earth left only traces because they could not adapt. So before deciding to become a "dinosaur," think carefully—because you may someday share their fate.

Preface: To Communicate Your Data Effectively With Others, First Communicate With It Yourself

During World War II, the Allies faced a critical decision: how to armor their planes for maximum protection without adding too much weight. They examined returning aircraft and found the most damage to the wings and tail, prompting them to reinforce those areas. However, mathematician Abraham Wald pointed out a flaw - the data only came from survivor planes. The ones that didn’t return likely bore damage in more vital areas, like the engines. This insight changed their strategy and, in turn, the air-to-air combat situation (Eldridge, 2024).[1]

This story highlights a key lesson: data is only as effective as it is interpreted and communicated. Whether in military or business strategy, successful decisions depend on understanding the complete picture, not just what is immediately visible. In today's world, misinterpreting or poorly communicating data can lead to failed strategies and costly mistakes. This article explores why effective data communication begins with fully understanding your data - because to communicate your data effectively with others, you must first communicate with it yourself.

Data Has Become the Backbone of Strategic Decision-Making

When entering new markets, developing innovative products, or refining operational processes, companies rely on data to inform their every step. However, data alone is insufficient, as how businesses interpret and act on it ultimately determines success or failure.

Data reduces uncertainty. For example, when a company considers entering a new market, they often rely on data to assess market demand, customer preferences, and competitor dynamics. Instead of relying on gut instincts or assumptions, data offers objective insights that help companies tailor their strategies. This same principle applies to product development, where data from customer feedback, sales trends, and competitive analysis informs design, features, and pricing strategies.

• Consider Netflix’s success in shifting from a DVD rental service to a streaming platform, thanks not only to its technology but also to its data-driven approach. By analyzing user behavior - viewing patterns, completion rates, and paused shows - Netflix curated personalized recommendations that boosted engagement. However, they went further, allowing this data to guide original content production, such as House of Cards, knowing that users favored political dramas and Kevin Spacey’s work. This calculated approach, based on data, helped Netflix produce hit content and dominate the streaming industry (Fan, 2024).[2]

Data doesn’t just describe patterns - it also creates them. This example illustrates how accurate data interpretation can shape strategic choices that position companies for long-term success. By understanding user behavior and preferences, Netflix wasn’t merely reacting to trends but actively shaping them. Data became their tool for driving both innovation and customer loyalty.

However, the success of data-driven strategies depends on the accuracy and depth of data interpretation. Misreading or miscommunicating the data can lead to costly missteps. Take the housing market crash from 2007-2008, during which the correct and incorrect data interpretation led to cardinally different outcomes:

• During the 2008 financial crisis, banks issued subprime mortgages - risky loans to people with poor credit - assuming housing prices would keep rising. They believed that if borrowers defaulted, they could repossess homes and sell them at a higher price. However, when borrowers went bankrupt, the housing bubble burst, and home prices dropped sharply. Banks repossessed homes but couldn’t sell them for enough to cover the original loan amounts. The misinterpretation of data - such as overinflated housing prices, growing risky loans, and market saturation - led to massive financial losses and a global economic collapse. 
  
  However, some investors, like Michael Burry, Steve Eisman, and John Paulson, correctly interpreted the data. They saw the unsustainable housing bubble and bought Credit Default Swaps (CDS) - a type of insurance that would pay them if the mortgages they were betting against defaulted. The sellers of CDS, including Lehman Brothers, Bear Stearns, and American International Group (AIG), thought they were making easy money, believing the market was safe and that defaults were unlikely. When the market collapsed, these institutions were obligated to pay out massive amounts while being unprepared for the scale of the defaults. Lehman went bankrupt, Bear Stearns sold at a discount, and AIG required a government bailout (FDIC, 2013). [3]

In this way, data doesn’t just inform decisions - it drives them. Successful companies take the time to deeply understand their data before making strategic moves. By communicating with their data first, they can effectively act on it, ensuring alignment and clarity in their strategies. This process ensures that decisions are data-driven, reducing the risk of miscommunication and enhancing the overall success of the company’s goals.

Common Pitfalls in Data Interpretation

But why do some fail to interpret their data? Because it requires vigilance. Common mistakes, such as confirmation bias, lead decision-makers to favor data that confirms their pre-existing beliefs, often ignoring contradictory evidence. The approach skews strategies toward comforting but faulty conclusions.

• In the late 1990s, Kodak fell victim to confirmation bias. Despite inventing the first digital camera in 1975, the company remained focused on its profitable film business, convinced, consumers would continue using film. Kodak interpreted their data in a way that confirmed their belief that film cameras and production were preferable, ignoring the growing demand for digital technology. This bias toward their then success shut their eye on the shift in consumer preferences. On January 19, 2012, one of America’s great success stories, the Eastman Kodak Company, filed for bankruptcy (Anthony, 2016). [4]

Recording assumptions before analyzing data and revisiting them afterward to ensure they haven’t influenced interpretation helps avoid confirmation bias. It’s essential to avoid cherry-picking data and to consider all evidence equally. This approach helps prevent biased conclusions and promotes more accurate decision-making.

Another issue is selection bias, where data is drawn from a non-representative sample, leading to flawed insights. For instance, a company that tests new product features exclusively with loyal customers might overestimate broader demand because loyal customers tend to be more forgiving and enthusiastic.

• In the early 2010s, Google misinterpreted market interest with the launch of Google Glass. They primarily tested the product with tech enthusiasts eager to embrace cutting-edge technology. It led Google to believe there was broad consumer demand for the product. However, the general public found Google Glass too invasive and impractical for everyday use. The reliance on a non-representative audience led Google to overestimate its appeal, resulting in the product’s commercial failure (Weidner, 2024). [5]

Mitigating selection bias requires ensuring randomized data collection and representation. It's crucial to use diverse sampling methods to gather inclusive and accurate insights, reflecting the full scope of the audience. This approach helps prevent bowed results that could lead to faulty conclusions.

Historical bias can emerge when companies use outdated data to predict future trends. Such bias can lead to strategies based on assumptions that no longer hold.

• In the early 2000s, Nokia dominated the mobile phone market. Due to relying on its past success with feature phones, they believed consumers would continue favoring hardware-based innovations, like durable phones and physical keyboards. However, Nokia ignored the new data showing that smartphones, driven by software and touchscreens, were the future. Their reliance on outdated data about consumer preferences led them to miss the rise of iOS and Android, causing them to lose their market leadership to Apple and Samsung (Wang, 2022). [6]

A practical way to avoid historical bias is by incorporating data from recent, diverse sources that reflect current social, economic, and technological changes. It's essential to acknowledge the limitations and biases within older data and orient on forward-looking, inclusive data practices that account for evolving trends. This approach ensures that strategies remain relevant and adaptable to new dynamics.

Survivorship bias occurs when focusing only on successes while ignoring failures. This selective view can lead to inaccurate conclusions about what drives success. By neglecting to analyze failures, valuable insights that could improve strategies fade.

• During the dot-com era, many companies only focused on the success of Amazon and eBay, believing that launching online businesses would guarantee success. They ignored the failures of companies like Pets.com and Webvan, which expanded rapidly without sustainable business models. Other startups, such as Boo.com, made similar mistakes by prioritizing growth over addressing logistical and market challenges. While concentrating only on success stories, they overlooked lessons from these failed ventures, leading to their eventual downfall (Wray, 2005).[7] 

To avoid survivorship bias, teams should gather data from successes and failures. Considering both provides a complete picture of what works and what doesn’t. This balanced approach ensures that conclusions derive from both - fly and die cases.

Availability bias occurs when decisions are made based on the most easily accessible or recent data rather than the most relevant or comprehensive information. Such an approach often leads to contorted judgments because the data at hand, may not represent the bigger picture. 

• In 2016, Samsung initially focused on a few prominent reports of battery failures in the Galaxy Note 7, assuming the problem was limited to isolated cases. Samsung reacted to the most visible data without thoroughly investigating whether the issue was widespread. The company didn’t realize that the defect affected many not-yet-reported devices. By not digging deeper into the broader problem, they underestimated the scale of the defect, leading to delayed action and a costly recall of the entire product line (Samuelson, 2016). [8]

Focusing on trends and patterns rather than vivid but isolated incidents helps prevent availability bias. Thoroughly investigating all data sources ensures a more accurate understanding of the issue rather than relying on immediately available but potentially unrepresentative information. This approach helps reveal the full scope of a problem, leading to more informed and balanced conclusions, as opposed to drawing decisions from isolated, prominent cases that may not reflect the broader reality.

Outlier bias occurs when extreme data points - significantly different from the rest - mislead the interpretation of data. These unusual data points can swerve the overall analysis, causing conclusions that do not reflect the typical patterns. The presence of outliers may result in overemphasis on rare occurrences, leading to distorted insights. Without proper context or further investigation, decisions based on outliers can overlook the trends or central tendencies of the data, potentially leading to ineffective or misguided strategies.

• In 2014, GoPro's stock surged due to the excitement around its action cameras and a viral user base, creating a sudden spike in sales and market value. This outlier event led the company to focus on expanding rapidly, assuming continued high demand. However, this was a temporary surge driven by a niche market. Over-relying on that outlier data point led to overproduction and market saturation, which ultimately caused the company stock to plummet in the following years (Victor, 2024). [9]

Mitigating the outlier bias includes full-scale data examination - often a reference to the mode and median instead of the average, and investigating any outliers without allowing them to dominate the strategy. This approach ensures that rare or extreme data points are understood in context, preventing them from sabotaging the overall analysis and leading to more balanced and accurate decision-making.

Avoiding biases such as confirmation, selection, historical, survivorship, availability, and outlier bias - along with many others - is a precursor to effectively communicating data with decision-makers. Interpreting data correctly and ensuring it is free from bias, can provide clear, actionable insights that foster alignment and well-informed strategies, ultimately enhancing decision-making processes and outcomes.

Data Only Whispers, Communication Makes It Heard Across Audiences

Effective data communication is not one-size-fits-all. Tailoring the communication style to the audience’s needs and the decision context helps convey the data insights.

Figure 1. Types of Data Communication. Source: Rogue Penguin

• Descriptive Data Communication: When the audience needs to understand specific technical details and has the requisite knowledge, describing the data is most effective. This method delivers detailed, granular information that explains the „what“ of the data.
  
  
• Informative Data Communication: If the audience is well-versed in the subject but doesn’t need to act immediately, an informative approach provides educational or updating data without pressing for direct action, ensuring key stakeholders remain informed about developments.
  
  
• Persuasive Data Communication: When immediate action is required, data communication must persuade. Highlighting critical insights and actionable steps connects data to decisions and motivates the audience to act.
  
  
• Narrative Data Communication: When the audience is more interested in understanding what happened rather than why, narrating data is most effective. This method weaves data into a coherent story, helping the audience follow the sequence of events leading to a specific outcome.
  
  
• Explanatory Data Communication: When the audience is less concerned with immediate technical details and wants to know why certain events occurred, an explanation is a go-to. This approach focuses on interpreting the data to provide deeper insights into the causes behind trends.

Selecting the appropriate data communication strategy and approach based on the audience's specifics is mandatory. Without this consideration, valuable data insights can remain ineffective and fail to drive informed decision-making. Tailoring the data communication strategies to the audience helps ensure that conclusions resonate, fostering better understanding and engagement.

Conclusion

Effective data communication hinges on recognizing and mitigating biases that can distort interpretation. Embracing diverse communication strategies tailored to specific audiences helps transform raw data into powerful insights. This careful consideration not only enhances understanding but also fosters informed decision-making. Ultimately, recognizing the nuances of data communication empowers us to navigate complexities, ensuring that insights resonate and lead to meaningful outcomes in an ever-evolving landscape.

References: 

[1] Eldridge, E. (2024). Survivorship Bias. Encyclopedia Britannica. Retrieved from: https://www.britannica.com/science/survivorship-bias. October 3, 2024.

[2] Fan, H. (2024). Leader in the Digital Entertainment Market: Netflix's Continued Success in a Fiercely Competitive Environment. Advances in Economics, Management and Political Sciences 73 (1)

[3] Federal Deposit Insurance Corporation (FDIC) (2013). Origins of The U.S. Financial Crisis of 2008 . Retrieved from https://www.fdic.gov/sites/default/files/2024-03/chap1_0.pdf. October 3, 2024.

[4] Anthony, D. S. (2016). Kodak’s Downfall Wasn’t About Technology. Harvard Business Review. Retrieved from: https://hbr.org/2016/07/kodaks-downfall-wasnt-about-technology. October 3, 2024.

[5] Weidner, J. B. (2024). Why Google Glass Failed. Investopedia. Retrieved from: https://www.investopedia.com/articles/investing/052115/how-why-google-glass-failed.asp. October 3, 2024.

[6] Wang, S. (2022). Explanations to the Failure of Nokia Phone. 2022 7th International Conference on Financial Innovation and Economic Development.

[7] Wray, R. (2005). Boo.Com Spent Fast And Died Young But Its Legacy Shaped Internet Retailing. The Guardian. Retrieved from: https://www.theguardian.com/technology/2005/may/16/media.business. October 3, 2024.

[8] Samuelson, K (2016). A Brief History of Samsung’s Troubled Galaxy Note 7 Smartphone. Time Magazine. Retrieved from: https://time.com/4526350/samsung-galaxy-note-7-recall-problems-overheating-fire/. October 3, 2024.

[9] Victor, D. (2024). GoPro Stock Is at an All-Time Low. Is It a Buy? The Motley Fool & Nasdaq. Retrieved from: https://www.nasdaq.com/articles/gopro-stock-is-at-an-all-time-low.-is-it-a-buy. October 3, 2024.

As the world increasingly transitions to a digital landscape, businesses are compelled to adapt, evolve, and navigate a rapidly changing environment. This raises a critical question: "Are you drinking the water or riding the wave?" This metaphor highlights a crucial decision that organizations must confront: to manage only immediate changes—the water—or to actively lead and influence these changes—the wave. The latter represents a proactive approach that is vital for survival in a complex and competitive digital ecosystem. Traditional management strategies are progressively inadequate for this challenge, rendering digital leadership and innovative thinking essential for success. 

Digital Leadership: Managing Transformation at the Speed of Change 

The cornerstone of any successful digital transformation is effective digital leadership. Leaders in forward-thinking companies do not merely respond to trends; they proactively manage them. According to James McGregor Burns' theory of transformational leadership, these leaders possess the ability to inspire their teams and unify them around a shared vision. They cultivate an environment where continuous learning and adaptation are integral to their organizational culture. Leaders who effectively navigate digital transformation actively engage with emerging technologies, support their teams in addressing various technological challenges, and seize opportunities for innovation. 

Consider Microsoft's transformation under Satya Nadella. When Nadella became CEO in 2014, the company found itself at a pivotal juncture. In the personal computer sector, the once-preeminent tech giant had fallen behind in critical areas such as cloud computing and mobile technology. The company's focus remained on its traditional products—Windows and Office. However, Nadella articulated a clear vision to position Microsoft as a leader in cloud computing and artificial intelligence (AI), thereby redefining the company's role within the swiftly evolving technology sector. 

Under Nadella's leadership, Microsoft's strategy has undergone a significant transformation, with a robust emphasis on cloud computing through Azure. Azure has experienced remarkable growth, establishing itself as a formidable competitor to Amazon Web Services (AWS), which plays a crucial role in Microsoft's long-term objectives. Additionally, Nadella has championed AI as a transformative force, highlighting the Azure AI platform and cognitive services as essential solutions for businesses seeking to enhance operations and customer experience. 

These strategic shifts exemplify how digital leadership can redefine a company's strategic focus, rendering it more innovative and competitive.  

Nadella's transformation of Microsoft extended beyond technological advancements; he spearheaded profound cultural and organizational changes within Microsoft. These key initiatives included: 

Promoting a Growth Mindset: Nadella introduced the concept of a “growth mindset,” emphasizing continuous learning and improvement. This cultural shift was reflected in Microsoft’s approach to innovation, encouraging employees to experiment, learn from failures, and remain open to new possibilities. 

Breaking Down Silos: Nadella fostered a culture of collaboration, breaking down the siloed structure of Microsoft. Cross-functional teams became more integrated, facilitating the company’s rapid adoption of AI and cloud technologies. 

These cultural shifts not only support technological advancements but also lay the foundation for long-term innovation. Organizations planning for digital transformation must recognize that leadership alone is insufficient; the mindset of the entire organization plays a critical role. 

Digital Mindset: The Catalyst for Transformation 

Beyond leadership, the mindset of the entire organization is vital to successful digital transformation. A McKinsey study confirms that organizations with cultures focused on adaptability, continuous learning, and rapid response are more successful in digital ventures. This reflects the importance of fostering a "digital mindset," a concept that aligns with Carol Dweck's "growth mindset" theory. A digital mindset is characterized by the willingness to embrace challenges, learn from failures, and continually adapt. 

Incorporating a digital mindset involves several key components: 

• Continuous Learning and Adaptation: Digital organizations prioritize ongoing learning, ensuring employees stay informed on the latest trends and immediately apply new insights. 

• Agility: To succeed in digital transformation, organizations must be agile, adapting quickly to new technologies and market shifts. 

• Innovative Thinking: Encouraging creative problem-solving and experimentation is central to fostering a digital mindset. 

• Cross-Functional Collaboration: Breaking down silos and enhancing digital collaboration across departments are essential for driving innovation. 

A Deloitte report shows that businesses fostering a digital mindset experience a 40% increase in employee productivity and innovation. This powerful statistic demonstrates that cultivating a proactive, innovative culture can yield tangible improvements in organizational performance. 

Assessing Digital Readiness: The Digital Barometer 

Evaluating the digital mindset is a critical component of assessing an organization's digital readiness. This evaluation determines whether employees and leaders are prepared to embrace the rapid pace of digital transformation or if traditional, risk-averse attitudes are impeding progress. This begs the question: how can companies measure their organization's digital mindset and leadership readiness for the digital age? 

At ACT, we have developed a comprehensive tool known as the Digital Barometer, designed to assess an organization's Digital Leadership and Mindset. The Digital Barometer evaluates how effectively teams utilize digital tools for information gathering, collaboration, problem-solving, and ensuring security. Additionally, it assesses the organization's openness to digital innovation. Through this holistic analysis, the tool assists organizations in identifying their strengths as well as areas requiring further development. 

A digital mindset assessment determines whether employees and leaders are ready to adopt new ways of thinking, learning, and working. It uncovers whether an organization is prepared to embrace the swift pace of digital change or is hindered by traditional, risk-averse attitudes. This assessment can also highlight areas where additional training or cultural shifts may be necessary to align with the organization’s digital goals. 

Ultimately, success in the digital age demands more than merely adopting new tools—it necessitates visionary leadership supported by human capital and a commitment to development. By continuously evaluating and enhancing these elements, organizations can not only navigate the challenges posed by technological change but also leverage them as opportunities for innovation and growth. 

It's hard to find a black cat in a dark room, especially if it isn't there.  

Confucius  

I first heard the phrase “Are we looking for a black cat in a dark room?” during a discussion among several scientists about the rationality of a research hypothesis.  

The search for a black cat in a dark room, especially when no cat is there, expresses the idea of futile effort. It symbolizes a pursuit of something that likely does not exist and is ultimately absurd. Although this phrase is attributed to Confucius, it is more of a philosophical concept than a direct quote. Applying this idea to the context of Organizational Behavior creates a powerful metaphor, reflecting the wasteful expenditure of energy and resources in organizational management, leading to inefficiency.  

In this article, I will try to answer the following questions:  

Why do organizational leaders search for a black cat in a dark room, losing consistency and harming the organization in the process?  

Why do intelligent people make elementary and absurd mistakes?  

To answer these questions, let's consider several theories.  

1. Fear of Missing Out (FOMO)  

Do you remember the anxiety in school while waiting for an invitation to a classmate's party? Or the feeling of missing an important event? These emotions are linked to anxiety and regret, commonly referred to as the Fear of Missing Out (FOMO).  

The Fear of Missing Out (FOMO) has been a part of human nature and our daily lives since ancient times. Early humans instinctively understood that missing out on food, shelter, or a suitable mate could jeopardize the survival of their species. Therefore, this fear is universal and present in every person, race, generation, and gender. However, with the advent of technology, particularly social media, FOMO has significantly intensified.  

Herman first highlighted FOMO in 2000 (Herman D, 2000), using the term to describe consumer behavior. However, after the COVID-19 pandemic, the term became more generalized, with modern authors using it to explain anxiety. Given this growing trend, people are often referred to in literature not as HOMO Sapiens but as FOMO Sapiens.  

In the context of Organizational Behavior, FOMO reflects human anxiety and fear of missing out on an opportunity, innovation, or trend that may be crucial. Here, we talk about a leader who, under the influence of FOMO, is constantly searching for new initiatives and losing consistency.  

FOMO can manifest in the following forms:  

1. Copying every new trend that may be less relevant or inappropriate for the business.  

2. Constantly implementing innovations and initiatives when core business processes are not yet established.  

3. Making hasty decisions that are not aligned with the company's long-term strategy.  

4. Taking unjustified risks, such as investing significant resources based on current trends and intuition without prior market analysis.  

In today's world, the pursuit of new ideas is essential. However, decisions fueled by FOMO can lead to impulsive and unpredictable leadership, much like searching for a black cat in a dark room—even when it isn’t there. 

2. Fast Thinking (System 1) vs. Slow Thinking (System 2)  

According to Daniel Kahneman's book «Thinking, Fast and Slow», people use two different thinking systems when making decisions. When the outcome is easily predictable or when we encounter something familiar, we make fast, intuitive decisions; this type of thinking is called System 1. On the other hand, when faced with a complex task or unfamiliar environment, we start applying more deliberate and slow thinking, activating System 2.  

Fast thinking, or System 1, is the brain's automatic mode, which conserves effort and energy. It is formed based on previous experience, decisions, and the environment in which we grew up. Often, System 1 is helpful as it saves energy, helps us navigate our environment, and avoids constantly reconsidering details. For example, in everyday life, we use System 1 more frequently, while System 2, which involves slow thinking, can be tiring and irritating when used often.  

However, it's important to note that System 1 has its drawbacks—it is prone to errors, subjective judgments, and biases. System 1 does not account for important details and relies on existing experience.  

The choice between fast thinking (System 1) and slow thinking (System 2) is fully conscious; a person chooses which system to rely on when planning. It is also worth noting that System 1 operates automatically, like an autopilot, so in stressful situations or when fatigued, a person is inclined to make decisions with minimal energy expenditure, using System 1. 

This is why intelligent people sometimes make very simple mistakes and, based on System 1, may instruct their team to search for a black cat in a dark room, as it worked in the past. In such cases, we encounter a pattern-based approach and a rigid attitude toward the surroundings ("don't miss the important stuff"). As a result, the company may stagnate instead of correctly utilizing and developing new opportunities. 

How can this be changed? 

Fear of missing out (FOMO) can be a powerful and legitimate motivator for both leaders and teams. However, it's crucial to recognize its potential downsides. Striking a balance between fast, instinctive thinking (System 1) and slow, analytical thinking (System 2) is essential for effective decision-making. 

While it's natural to rely on fast thinking for routine tasks, navigating complex situations requires the deliberate approach of slow thinking. It's important to remember that both FOMO and fast, automatic thinking are intrinsic parts of us. They can be managed through self-reflection, continuous development, seeking feedback from your team, and maintaining a healthy work-life balance. These practices help ensure that you don’t overlook critical details due to stress or incomplete information, avoid making decisions driven solely by FOMO or Fast thinking, and most importantly, resist the temptation to chase a black cat in a dark room, especially when it isn’t there. 

Did you know that nearly 60% of employees report feeling emotionally drained by the end of each workday? With the evolution of the labor market, focusing on employee well-being has ceased to be a luxury or a one-off initiative—it has become a necessity for survival and the foundation for long-term success.

The driving force behind a company is its strong employees. The viability of an organization depends on the realized potential and well-being of each worker. Experience and international empirical research show a direct link between employee well-being and their productivity, effectiveness, and commitment to the organization. The higher the employee's well-being, the more they are a team player, show empathy toward others, and are more productive and effective in their work processes, which is the cornerstone of organizational success.

Given this situation, it has become evident to modern HR specialists and managers that well-being is not an additional but an integral value of the company. Consequently, for proactive, development-oriented organizations, one of the primary tasks is to implement a human-centered culture, ensure a safe environment for employees, and promote their well-being. This involves increasingly frequent and prioritized adoption of various supportive approaches and interventions.

The Concept of Well-Being

Well-being is a comprehensive concept that, according to the perspective of positive psychology, extends beyond rational factors to include psychological aspects such as socio-emotional, mental, and cognitive resilience. Various theoretical reviews and empirical studies suggest that achieving employee happiness and well-being in an organization is contingent upon providing various motivational factors and circumstances:

Emotional Well-Being: Numerous studies confirm that employees' emotional resilience, ability to self-regulate and adapt emotions, optimism, and positive attitude toward work significantly influence work motivation, approach to tasks, and the quality of work performed. Conversely, a combination of negative emotions such as anxiety, tension, and irritation can lead to emotional burnout and professional exhaustion. These symptoms often become primary or at least indirect causes of job departure.

 Social Well-Being: Considering that employees spend a third of their time at work, the style of interaction in the work environment, opportunities for receiving and exchanging support and empathy, are particularly important. Factors such as cooperation, shared joy, a sense of belonging, pride in achievements, and belief that the environment supports and values you, are guarantees of a safe environment and healthy social interaction, which, in turn, forms the basis for employee retention and the accumulation of positive capital in the long term.

 Professional Well-Being: An employee’s perception of their activities and role is a critical component of well-being. Organizations need to be aware: is the employee passionate about what they do? Do they believe in the importance of their work? Do they consider their work valuable? How competent do they feel? Do they have a sense of autonomy? Do they see their contribution to achieving the company's overall goals and vision? These questions determine internal motivation, interest, productivity, and ultimately, employee effectiveness. Providing career paths, opportunities for continuous learning, and recognizing employee achievements are effective strategies for enhancing professional well-being.

It is clear that a high level of professional well-being is key to employee productivity and, consequently, to the effectiveness and success of the organization.

 Physical Well-Being: Beyond physical endurance, a crucial aspect is the feeling of safety and security in the workplace. It is also important for the organization to understand how work conditions and the environment contribute to employees feeling good and being productive.

Financial Well-Being: The importance of this aspect relates to how employees' financial security, fairness, and adequacy of compensation compared to the work performed significantly impact their motivation, attitude toward work, and desire for long-term collaboration with the company.

Thus, focusing on individual aspects of well-being, as well as the overall picture, improves indicators of resilience, engagement, and productivity; strengthens organizational loyalty; creates a healthy and positive work climate; fosters a high-performance culture; and ultimately enhances the organization's internal success, ecosystem, viability, as well as productivity and reputational resilience.

Well-Being Diagnosis

We believe that the first step towards creating a human-centered, safe environment in an organization is assessing the components whose combination is essential for achieving well-being. Well-being diagnostics allow the organization to understand what employees think and feel, identify issues in organizational climate and culture, and determine which well-being parameters require more attention and targeted interventions.

To this end, ACT has developed a unique model—the Employee Well-Being Matrix—which is based on a holistic view of well-being and symmetrically provides organizations with data on both overall and specific well-being indicators—where it is stable and where it requires support.

The Matrix: A Compass for Employee Well-Being

The Well-Being Matrix is like a lens that allows you to see even the most challenging organizational well-being issues. In this labyrinth, the matrix is not just a diagnostic tool but a symbol of balance and clarity. Research identifies pain points, and targeted responses to them make strategic interventions much more effective.

We believe that just as the matrix creates balance, sequence, and structure in complex and sometimes chaotic data, the Well-Being Matrix will bring similar clarity and a clear vision to organizations, serving as an important compass on the path to creating a human-centered, positive climate.

When it comes to powerful storytelling in advertising, few stages are as prominent as the Olympics. Brands like Nike and Coca-Cola have long understood the value of emotional connection during such high-stakes global events. But as we’ve seen in recent Olympics, the way emotions are used in advertising can be the difference between just grabbing attention and truly moving people to action.

Take Nike’s “Winning Isn’t for Everyone” ad, for instance. At first glance, it seems like a perfect match for the Olympic spirit with its portrayal of athletes driven by a relentless, almost ruthless ambition. However, there’s a catch. The ad starts with a provocative question: “Am I a bad person?” and then goes on to link greatness with traits like deception, obsession, and a lack of empathy. On paper, this fierce drive looks compelling, but it misses the mark in some key ways.

The problem lies in the ad’s portrayal of greatness. By associating success with negative traits like ruthlessness and a lack of compassion, it creates a misleading picture. True greatness, whether in sports or any other field, is not about trampling over others or losing one’s humanity. It’s about fierce determination balanced with respect for others and a strong sense of personal integrity.

Nike's intention might have been to highlight the relentless drive required to achieve greatness, but the execution fails to address the importance of maintaining a balance between ambition and ethical conduct. Great athletes are known for their dedication and intense focus, but they also understand the significance of compassion, respect, and a well-rounded approach to success. The best athletes manage to channel their drive without compromising their core values or well-being.

In stark contrast, Coca-Cola’s “It’s Magic When the World Comes Together” ad excels by weaving a story of unity and upliftment around South African swimmer Tatjana Schoenmaker. Rather than simply showcasing competition, this ad evokes hope, redemption, and togetherness—emotions that connect on a deeply personal level. This approach not only engaged audiences but also fostered a strong emotional connection with the brand. It shows that empathy and shared human experiences can be as powerful as intensity and competition.

So, what can brands learn from these two contrasting approaches? The key takeaway is that while competition is a powerful theme, how it’s presented can make a huge difference. Nike’s ad had intensity but lacked the emotional depth needed to create a lasting impact. Coca-Cola, on the other hand, reminded us that the most memorable ads are those that go beyond competition and touch on universal human experiences.

As we look forward to future Olympic advertising, there’s an opportunity for brands to not only celebrate the triumphs of competition but also to explore the softer, more relatable sides of these stories. Whether through humor, hope, or the simple act of coming together, the ads that leave a lasting impression are those that connect with us on a human level.

In the end, the most effective creative work doesn’t just tell us who won—it shows us why it matters. And that’s a lesson worth remembering, not just for the Olympics, but for all brand storytelling.