The Antifragility of Complex Adaptive Systems
Evolution is constant. Whether it be in sports or business, organizations are always looking for ways to grow, adapt, and ride industry waves to maintain their competitive edge. Today’s article focuses on complex adaptive systems and antifragility, and how these two frameworks combine to explain some of the nuances of organizational evolution and change.
A powerful mental model extracted from engineering is systems thinking, which essentially encompasses looking at things as if it were a system. Fundamentally, a system is a group of parts that work together to form a unified whole. While some systems are simple, many have layers of complexity (which makes them harder to understand). The hallmark of a complex system is one where the components are interdependent; in fact, the word complexity comes from the Latin word plexus, which means interwoven. When components in a system are interwoven, it’s hard to isolate the individual components because of the degree to which they are influenced by their interaction with other components. As components within a system continually interact, the behavior of the system constantly changes; it is this property which makes certain complex systems adaptive. Systems that are both complex and adaptive are known as complex adaptive systems, and can be found anywhere. Nature, markets, and sports teams are just a few examples of these complex adaptive systems which permeate our everyday lives.
An important facet of complex adaptive systems is the relationship between the system and its individual components. A key mental model which helps explain this relationship is antifragility. As Nassim Nicholas Taleb writes, “Some things benefit from shocks; they thrive and grow when exposed to volatility, randomness, disorder, and stressors and love adventure, risk, and uncertainty.” The word Taleb uses to describe this phenomenon is antifragile. While the fragile is prone to breaking down when exposed to the world’s randomness and volatility, the antifragile treats pain and stressors as information, and leverages them to grow. How does this relate to complex adaptive systems? Simply put, the source of a system’s antifragility is the fragility of some individual components.
Natural selection is probably the best example which illustrates the tradeoff between the whole and its subsequent parts. As Taleb writes, “The most interesting aspect of evolution is that it only works because of its antifragility; it is in love with stressors, randomness, uncertainty, and disorder — while individual organisms are relatively fragile, the gene pool takes advantage of shocks to enhance its fitness.” In this situation, the given species is the system, while the organisms that make up that species are the individual components. Natural selection boils down survival of the fittest; the definition itself indicates the fatality of the unfit, which underscores the fragility of some individuals. Quoting the great Ray Dalio, “nature optimizes for the whole, not for the individual.”
This plays out in many other areas as well. Think of business and the economy: companies are competing against each other each day to bring customers the best product or service, and thus the organizations which fail to adapt to changing circumstances will be fragile. This is exactly why the failure rate for startups is so high; the fragility of some startups (underscoring the high standards which startups need to meet to survive) optimizes for the value created by those which succeed, making the startup ecosystem antifragile. Think of the inverse: if all companies and startups were robust (hence immortal), they would have no incentive for creating more value or adapting to change (because their lifeblood doesn’t depend on it and they’ll stay alive either way), thus drastically lowering the value created by the collective and making it fragile.
The same is true for sports teams, which can be looked at as complex adaptive systems as well (with the players, coaches, and front office being the interdependent components which make up the system). Teams are antifragile and able to adapt to change when they acknowledge that some players are fragile, and those who aren’t performing at the level which is needed are the ones who will have to go. It is when teams forget this and keep their players for too long (regardless of their performance) that they fall behind and lose their advantages. One example of this is the Lakers in the early 2010s. Once a great team which had won back-to-back championships, the Lakers were on a downhill slope, in large part due to the regression of their star Kobe Bryant. If the Lakers were an antifragile system, they would have recognized the increasing fragility of Kobe Bryant (a player who hadn’t adapted to the fast pace of play), and made objective decisions on his compensation based on his true real-time value (perhaps asking him to take a pay cut, like other veterans like Tim Duncan and Dirk Nowitzki were doing at the time). Instead, the Lakers gave Bryant a huge contract which made him the highest paid player in the league, despite not performing at a level which warranted that. While rewarding Bryant for being their franchise centerpiece and superstar of two decades is certainly commendable, this move decreased the overall fitness and adaptability of the system which was the Lakers team, making it fragile to changes in the overarching NBA landscape and putting them at the bottom of the league.
Every component of a system can be looked at as a subsystem with its own parts working together to create its whole, while every system can be looked at as a small unit within a larger collective. Sports teams are a good example of this: they were described earlier as systems with their own interdependent units, but can also be looked at as components within a broader system (which is the sports leagues they play in). Leagues are antifragile in their own right, and evolve in response to stressors which give teams (the components) a clear choice: adapt and succeed or stay stagnant and fall miles behind. In fact, the best innovations in sports have come from situational difficulty.
One key example of this was the adoption of analytics in sports. The Moneyball revolution and sports analytics movement wasn’t a nerd experiment of, “hey, let’s see if we can take these fancy statistical techniques from advanced economics classes and see if they have any application in baseball.” It was of a function of sheer situational difficulty, where the Oakland Athletics were at a steep financial disadvantage and needed a contrarian approach to compete with big market teams. For baseball teams, lower payrolls (in comparison to other teams) were the stressors which caused many small-market clubs to plummet to the bottom of the league, accentuating their fragility. The Athletics, on the other hand, responded to these exact same stressors by zigging when others zagged, leveraging statistical analysis and data (a contrarian approach at the time) to exploit market inefficiencies and find players who were undervalued. They built a team which rose to the top of the MLB in the 2002 season, winning as many games as the New York Yankees (a team which spent roughly 3.15 times more money on players than the Athletics did). The success of the A’s didn’t come despite their situational difficulty, but rather because of it: the stressors which they faced forced them to pioneer a new approach to building baseball teams, an approach which not only catapulted them to the top of the league but also changed sports forever. The story of the A’s was a pivotal point in the evolution of Major League Baseball, as the years which followed saw many teams build out analytics departments and completely adopt methods of statistical analysis when it came to player evaluation. In fact, the use of analytics permeated to all sports, with every general manager consulting an army of data-driven minds (and supercomputers with incredibly high horsepower) to make use of the most granular data in order to make their decisions as objective as possible. Randomness, volatility, and stressors may reveal the fragility of certain components of a system, but at the same time they force the fittest to adapt and find new ways to succeed, leading to innovations which drive the evolution of the system and demonstrates it’s antifragility.
An important point that’s been made in this article is the importance of adaptability. Business landscapes are constantly changing by the day: those that embrace this will be antifragile to the inherent randomness and volatility in their industry, while those who don’t will be fragile and eventually relinquish any advantage they once had. This leads us to question: if being able to adapt is so critical to long term success, then why do so few organizations possess this trait? The answer lies in a mental model from physics: inertia. According to Isaac Newton’s first law of motion, “An object at rest stays at rest and an object in motion stays in motion with the same speed and in the same direction unless acted upon by an unbalanced force.” Inertia is traditionally defined as the resistance an object has to change its state of motion; however, this idea of resistance to change goes far beyond physics. Physicist Leonard Mlodinow talks about how inertia helps explain how our minds work, saying: “for, like a mass in Newton’s first law of motion, once our minds are set in a direction, they tend to continue in that direction unless acted on by some outside force.” Organizations are simply the collective sum of multiple human minds, hence the same principle not only applies, but is amplified.
As Mlodinow points out, the one thing that can counteract inertia is an outside force. These outside forces are behind every major change made by organizations, and come in many different forms. What were the outside forces which influenced the A’s adoption of an analytics driven approach? As Moneyball talks about in depth, there was a colossal amount of organizational inertia which Billy Beane (GM of the A’s) faced for his new decision-making strategy, as most of team’s scouts were accustomed to the old school of baseball evaluation and analysis (which was using the eye test and subjective judgments). How did Beane push through this inertia to truly implement his data-driven approach? Sure, one outside force was their circumstances: if the A’s had a higher payroll, they would’ve been able to retain their three top players from the 2001 baseball season, voiding any immediate need for an analytics-driven approach to find undervalued talent. While this turn of events was certainly unfortunate for the A’s, the root cause of losing their top players wasn’t unique to them: all small market teams with low payrolls were prone to seeing the star players they developed leaving their clubs for greener pastures with more lucrative deals. Circumstances weren’t the only force which helped counteract the A’s organizational inertia; the other (and perhaps just as important) force important in the A’s adoption of analytics was the infusion of outside minds and perspectives. When Billy Beane hired Harvard economics graduate and Cleveland Indians scout Paul DePodesta in 1999 as his assistant general manager, what he brought to the organization was a decision-maker who would think about and look at problems from a radically different point of view.
As DePodesta himself has said: “In retrospect, I had a distinct advantage over everybody else in the industry at the time in that I knew absolutely nothing. Because I knew nothing, I observed everything critically and took nothing for granted. I spent my first few years with the Indians analyzing all of their systems, from contracts to player development and scouting. Because I had no preconceived notions over how an organization ought to be run, this was an education for me.“ DePodesta’s naivety in how baseball organizations traditionally worked was a blessing, as it enabled him to look at things from a fresh perspective and constantly question why things were done the way they were. He was quick to notice the irrational subjectivity apparent in baseball scouting and analysis, but the Cleveland Indians didn’t provide him with a platform to architect a change: the team had made the World Series in 1997, thus doing things “the way they had always been done” was fine for the time being. Beane and the A’s, on the other hand, were circumstantially in need of a contrarian approach to help them win with a low payroll. Paul DePodesta was the perfect fit as Beane’s right hand man, as the two were willing to test new approaches to see what could win. According to Beane, “I think, if anything, we certainly didn’t fear failure, because we felt like going a traditional path was certainly the surest of failure, based on our revenues and the payroll that we were on.” Together, Beane and DePodesta recognized the hidden optionality of their approach: even if they had failed, the downside would have been low because of how failure was the expectation for low payroll teams. Knowing this gave them the confidence to go all-in on their approach, pushing all of their chips to the middle of the table when it came to using analytics and making purely objective decisions. While the Oakland A’s didn’t to win a championship in the Moneyball era, their ability to fight internal inertia to implement a new approach certainly speaks volumes, and it was a result of two outside forces: circumstances and new blood.
Zooming out, we can see the circumstances which the A’s dealt with were simply a form of stressors and pain points which forced them to grow. Shocks, volatility, pain, and disorder (things that the antifragile love) can often combine to act as an outside force which spurs change amidst huge inertia. But shocks and stressors can never be the only outside force: when they are, it is the cause of extinction for the fragile. What differentiates the antifragile from the fragile is the way they think about the problems they face. When exposed to such volatility and disorder, the fragile stays stagnant and allows their situational difficulty to write their death sentence. Many other low payroll baseball teams (predating the A’s) are good examples of this: they continued evaluating players in a traditional and subjective manner (the way it at always been done), and settled for being able to acquire less talented players because of the small markets they played in. The antifragile, on the other hand, leverages their situational difficulty as a means for innovation, and incorporates new and diverse ways of thinking to increase their adaptability. These new ways of thinking, which often carry so much weight that it alters the organizational operating system, is the second outside force which is essential to combating internal inertia.
A simple formula: organizational change = circumstances + new thinking
A great business example of this is the technology company Microsoft. While Microsoft helped lead the PC revolution in the 1980s and was a dominant player in the operating systems market in the 1990s (and early 2000s), the glory days of the tech titan were followed by some gloomy ones. Under the leadership of Steve Ballmer, Microsoft missed many trends in the changing technological landscape: mobile, search, and even social networking. PC shipments were the financial lifeblood of Microsoft, but even those were experiencing a descent from past levels. The public caught on to the company’s stagnation, and Microsoft’s stock price dropped a staggering 40% during Ballmer’s tenure. A shift to cloud computing (pioneered by Amazon with Amazon Web Services) represented the next major technological wave, and the pressure was on: if Microsoft missed it, their days as a tech giant would surely be numbered.
Satya Nadella (current Microsoft CEO) knew this. A Microsoft lifer who had essentially grown up at the company, Nadella was a huge advocate for a shift to cloud computing. But at the same time, he was acutely aware of the inertia which the STB (servers & tools business) division had for cloud infrastructure products. The STB division was Microsoft’s third largest group by revenue, and was made up of many brilliant minds when it came to distributed systems (if anyone was to architect a shift to the cloud, it would be them). But despite their deep expertise, those within the STB division neglected learning about cloud computing, despite all signs pointing towards a cloud-driven future. Chief software architect Ray Ozzie even tried to incubate a cloud infrastructure initiative with the code name Red Dog, but was essentially ignored by the entire STB division (leading to internal politics and Ozzie eventually leaving Microsoft).
But as Nadella soon realized, the problems which Microsoft faced externally and in specific subdivisions were actually a function of the organization’s poor internal compass. The resistance to change seen within the STP division was simply one instance of a trend which was beginning to define the entire company. In a talk with Greylock’s Reid Hoffman, Nadella used a funny analogy to illustrate the issue: “At Microsoft we had like this amazing advantage called Bill Gates, and then we had an amazing disadvantage called a bunch of people who were roaming around Microsoft thinking they were Bill Gates.” Simply put, people became a bit too comfortable. Microsoft was a successful company, but that success came at a cost: it diminished their collective drive and bias towards innovation. At its core, the company had become an organization of stagnation which was increasingly incapable of responding well to a dynamic technological landscape.
If Microsoft wanted to survive, dramatic change was needed: not just quick strategy adjustments of one or two divisions, but a large-scale transformation of the fundamental organizational operating system. The painful circumstances which Microsoft was dealing with internally served as one outside force helpful in breaking down the barriers of inertia: as Nadella describes it, “The company was sick. Employees were tired. They were frustrated. They were fed up with losing and falling behind despite their grand plans and great ideas. They came to Microsoft with big dreams, but it felt like all they really did was deal with upper management, execute taxing processes, and bicker in meetings.” These are all stressors and pain points, features of disorder which often kill the fragile. Microsoft’s antifragility in rebounding from this mess is, in large part, due to the infusion of new thinking they received when Nadella took the reins as CEO in 2014.
Satya Nadella differs from Paul DePodesta in the sense that, while DePodesta came to the A’s as an outsider, Nadella rose to prominence in Microsoft as a consummate insider. For DePodesta, it was his naivety to the baseball industry which allowed him to spur change in Oakland. For Nadella, on the other hand, it was his internalization of Microsoft’s past mistakes which enabled him to accurately assess how he should write the company’s next chapter. Satya Nadella was by no means a newcomer, but his different perspective (in comparison to past Microsoft CEOs) represented a new line of thinking at the top of the organization.
Nadella’s new line of thinking started with the purpose of the company, asking the question of “why are we here?” The answer he reached was universal throughout the organization: Microsoft’s purpose was to build products that empower others, whether it be people or institutions. This idea of empowering others with technology was in their core DNA, as the company was founded with the mission of democratizing computing by putting a PC in every home. As Nadella knew, the successive application of this idea would be reinventing productivity by building cloud infrastructure and platforms to help people achieve more. In order to execute on this bold purpose, Nadella built a culture revolving around the idea of a growth mindset. He was heavily influenced by Carol Dweck’s book Mindset, which categorized human mindsets as one of two types: fixed or growth. People with a fixed mindset behaved like “know-it alls” who failed to confront their inadequacies, with their mind closed to any feedback pointing out flaws or areas of improvement. Those with a growth mindset, on the other hand, were “learn-it-alls” who relished any opportunity for progress, with an open mind to any information which gave them insight on how to get better. To Nadella, building a culture of dynamic learning would be the key to their transformation, and it would require embracing a growth mindset and applying it to all possible areas.
To get the ball rolling, Nadella began by implementing a growth mindset in three key areas: customer obsession, diversity and inclusion, and uniting as one. With customers, he focused on putting curiosity and empathy at the core of their work, trying to learn and absorb as much as possible about the customers and their unmet, unarticulated needs. By starting with a beginner’s mind and learning from the outside, Microsoft would be able to build the best possible solutions to help their customers. For diversity and inclusion, Nadella made it a point to ensure that everyone in the organization was heard, encouraging people to have an open mind and seek out different opinions and perspectives. Lastly, he emphasized really coming together and being united as one company, not a confederation of different divisions and departments. In the words of Nadella (at the time), “We must learn to build on the ideas of others and collaborate across boundaries to bring the best of Microsoft to our customers as one — one Microsoft.” All three areas had one common thread running through them: the dynamic ability to use learnings, whether it be from the outside or the inside, as a focal point to cultivate progress and improvement. That is the very heart of a growth mindset culture.
One example which demonstrates this dynamic learning culture coming to fruition is the acquisition of Minecraft. In this case, the primary architect of the deal was Phil Spencer, who was the head of Xbox. Spencer was driven to build the world’s best platform for gamers, and doing that meant developing a deep understanding of the customers and what they wanted. He was intrigued by the video game Minecraft, which had a huge and dedicated community of players. Beyond just the product-market fit which Minecraft had reached in the gaming space, Spencer was fascinated by Minecraft’s non-obvious application in the classroom, as teachers loved the game because of how it encourages building, collaboration, and exploration. Spencer had the opportunity to acquire Minecraft (earlier in his Microsoft tenure, before Nadella took over as CEO) and wanted to make use of it, but he faced a great amount of inertia and skepticism for the potential deal (which his boss decided not to move forward on). But Spencer maintained such a great relationship with Mojang (the company which built Minecraft) that, when the company went for sale again in 2014, the first text was to the Xbox team. Though this was less than a year into Nadella’s tenure as CEO, Spencer was aware of the new thinking at the top of the organization, and decided to take his (second) shot. Though the deal seemed unconventional at first, Nadella and his team rallied around it, being open to new perspectives within the organization and truly focusing on how they could incorporate this type of customer feedback into their decision-making process. Spencer’s perseverance did pay off, as Microsoft made the Minecraft acquisition in 2014, buying Mojang for $2.5 billion. Though many scratched their heads at the time, the deal was indeed a success, with Minecraft being one of the bestselling games of all-time (on the PC, Xbox, and mobile). If anything, this story is a testament to how new environments can foster different approaches to decision-making, which leads to better outcomes. Microsoft put their newfound growth mindset into action, and the collective result was the transformation they had been hoping for.
The stories of Microsoft and the Oakland A’s both show how circumstances and new thinking coalesce to help organizations fight inertia. The two are interdependent: circumstances of situational difficulty without new thinking leads to the demise of organizations, while new thinking without circumstances of situational difficulty that warrant it radically diminishes the likelihood that the new thinking will be adopted. As scientific philosopher Thomas Kuhn has written, “As in manufacture so in science — retooling is an extravagance to be reserved for the occasion that demands it.” Stressors, disorder, and pain points are the extravagances which demand new thinking; without them, innovation would not happen. Organizations who realize this understand the heart of antifragility.
How do adaptive organizations like the Oakland A’s and Microsoft fit within their respective surrounding systems? Remember, these complex adaptive systems evolve as components interact with each other. Components within such a system can be classified as antifragile or fragile; the fundamental difference between business and sports lies in what happens to the fragile. Business is a reflection of nature: the fragile eventually dies, which essentially encompasses going belly-up and failing as a company. Remember, antifragility is a function of a given point in time: organizations who are antifragile to one shift may end up being fragile to the next if they don’t maintain the same response towards stressors. Think of business: when a massive technological shift happens (say, for example, the advent of the internet), organizations who are fragile at that point in time collapse (like Blockbuster), while those who are antifragile live to see another day. But as time goes on, the surviving companies continue to compete with each other, as this is one form of the interaction between components which drives the evolution of the system. Competition strengthens the overall ecosystem by leading to the development of better and more innovative products, but at the same time leads to the downfall of companies who are fragile to the competition and can’t keep up. For example, Nokia and Blackberry were companies who were antifragile to (and born out of) the digital revolution and shift to mobile, but were fragile to the competition they faced from Apple, leading to the demise of both organizations.
All in all, circumstances of situational difficulty and events of randomness and volatility are inevitable in systems that are in constant change. The best organizations are antifragile, ones who are able to push through inertia and leverage stressors as opportunities to innovate and incorporate new thinking. As the business world continues to evolve with technological advances on multiple fronts, it will be these antifragile companies who will adapt the fastest and find the most success.
