Antifragile, Flexibility, Robust, Resilience, Agility, and Fragile
Thriving on chaos in an age of discontinuity — where the past is plagued with incoherence & inconsistency, the present is plagued with chaos & ambiguity, and the future is plagued with unpredictability & uncertainty (volatility, turbulence, stress, disruption, etc.) — is Reality!
How do Antifragile/Antifragility, Flexibility, Robust/Robustness, Resilience, Agility, and Fragile/Fragility relate?
Nassim Nicholas Taleb (@nntaleb) (Facebook page and Homepage) explores the Triad — Antifragile, Robust, and Fragile — in Antifragile: Things That Gain from Disorder. Taleb focuses on disorder and nonpredictive decision making under uncertainty. Taleb’s distinction between antifragile and fragile is quintessential.
C. S. Holling (Facebook page) explores Resilience with panarchies and adaptive cycles in Understanding the Complexity of Economic, Ecological, and Social Systems and Panarchy: Understanding Transformations in Human and Natural Systems. Holling focuses on evolution (transformation). Holling’s adaptive cycle and panarchy are quintessential, but particularly the omega and alpha stages regarding ecosystem resilience (versus engineering resilience) are quintessential.
Jan Husdal (@janhusdal) (Blog) explores Flexibility, Agility, Robustness, and Resilience in How to build a resilient, robust, flexible and agile supply chain. Husdal’s distinction between flexibility and agility is quintessential.
— — — Please see the figures below for an overview — — —
Creative destruction is at the root of Taleb’s, Hamel’s, and Holling’s perspectives and approaches.
For Taleb, creative destruction is essentially antifragility (but described in its own way).
For Hamel, revolution is creative destruction, renewal is creative reconstruction, and resilience is continuous reconstruction (or invention).
For Holling, release (omega stage) is creative destruction, reorganization (alpha stage) is renewal, and resilience is adaptive-ness (adaptive capacity).
Generally, Hamel’s revolution is similar to Holling’s release (omega stage), Hamel’s renewal is similar to Holling’s reorganization (alpha stage), and Hamel’s resilience is similar to Holling’s resilience.
Antifragile/Antifragility, Robust/Robustness, Resilience, and Fragile/Fragility
Please see the figures below for an overview.
Taleb’s, Hamel’s, and Holling’s core distinctions are very nuanced.
Taleb distinguishes between antifragility, resilience, robustness, and fragility where antifragility involves “gain” or “benefit” (“less harm”), fragility involves ”loss” or “penalization” (“more harm”), resilience involves “resisting” or “staying the same”, and robustness involves being “neither harmed nor helped” relative to disorder.
Hamel distinguishes between strategic resilience and operational resilience where strategic resilience involves “continuously anticipating and adjusting” and operational resilience involves “responding” or “rebalancing” relative to turbulence.
Holling distinguishes between engineering resilience and ecosystem resilience where engineering resilience involves “returning to equilibrium” and ecosystem resilience involves “flipping” relative to evolution.
Generally, Hamel’s strategic resilience is similar to Holling’s ecosystem resilience and Hamel’s operational resilience is similar to Holling’s engineering resilience while Taleb’s fragility is similar to Holling’s vulnerability, Taleb’s robustness and resilience are similar to Hamel’s operational resilience & Holling’s engineering resilience, and Taleb’s antifragility is similar to Hamel’s strategic resilience & Holling’s ecosystem resilience.
Fundamentally, antifragility emerges from strategic resilience (where there is “gain”) while fragility emerges from vulnerability (where there is “loss”) — as Taleb emphasizes: “a lot of things people call robust or resilient are just robust or resilient, the other half are antifragile.”
Flexibility and Agility
Please see the figures below for an overview.
Husdal distinguishes between flexibility and agility where flexibility involves “planned adaptation” for the “expected” while agility involves “unplanned adaptation” to the “unexpected”.
Husdal distinguishes between robustness and resilience where robustness involves “enduring without adaptation” and resilience involves “surviving despite impact”.
Generally, Husdal’s robustness is similar to Hamel’s operational resilience, Holling’s engineering resilience, and Taleb’s robustness and resilience while Husdal’s resilience is similar to Hamel’s strategic resilience, Holling’s ecosystem resilience, and Taleb’s antifragility.
Fundamentally, something may be agile & fragile (Fragile Agility or Fragile Agile), agile & antifragile (Antifragile Agility or Antifragile Agile), flexible & fragile (Fragile Flexibility), or flexible & antifragile (Antifragile Flexibility) — essentially antifragility & fragility and flexibility & agility are orthogonal dimensions where flexibility & agility focus on adaptation and antifragility & fragility focus on gain and loss.
Gain/Loss and Adaptation
Fundamentally, Taleb’s approach focuses on Gain and Loss while Hamel’s, Holling’s, and Husdal’s approaches focuses on Adaptation — each perspective and approach emphasizes various aspects of Reality.
Taleb’s Antifragile is tremendous in reinforcing and expanding the concept of creative destruction. We now have the onus to further explore antifragility, integrate antifragility with other concepts, and leverage antifragility in practice… our journey begins!
Taleb introduces antifragility:
Some things benefit from shocks; they thrive and grow when exposed to volatility, randomness, disorder, and stressors and love adventure, risk, and uncertainty. Yet, in spite of the ubiquity of the phenomenon, there is no word for the exact opposite of fragile. Let us call it antifragile.
Antifragility is beyond resilience or robustness. The resilient resists shocks and stays the same; the antifragile gets better. This property is behind everything that has changed with time: evolution, culture, ideas, revolutions, political systems, technological innovation, cultural and economic success, corporate survival, good recipes, the rise of cities, cultures, legal systems, equatorial forests, bacterial resistance … even our own existence as a species on this planet. And antifragility determines the boundary between what is living and organic (or complex), say and what is inert.
Taleb emphasizes that “resilience” involves “resisting shocks and staying the same”.
Taleb offers rationale for the subject:
Antifragility has a singular property of allowing us to deal with the unknown, to do things without understanding them — and do them well.
By grasping the mechanisms of antifragility we can build a systematic and broad guide to nonpredictive decision making under uncertainty in business, politics, medicine, and life in general — anywhere the unknown preponderates, any situation in which there is randomness, unpredictability, opacity, or incomplete understanding of things.
Antifragile and Fragile
Taleb explores the distinction between antifragility and fragility:
In every domain or area of application, we propose rules for moving from the fragile toward the antifragile, through reduction of fragility or harnessing antifragility. And we can almost always detect antifragility (and fragility) using a simple test of asymmetry: anything that has more upside than downside from random events (or certain shocks) is antifragile; the reverse is fragile.
Fragility — which had been lacking a technical definition — could be expressed as what does not like volatility, and that what does not like volatility does not like randomness, uncertainty, disorder, errors, stressors, etc.
Further, everything that does not like volatility does not like stressors, harm, chaos, events, disorder, “unforeseen” consequences, uncertainty, and, critically, time.
And antifragility flows — sort of — from this explicit definition of fragility. It likes volatility et al. It also likes time. And there is a powerful and helpful link to nonlinearity: everything nonlinear in response is either fragile or antifragile to a certain source of randomness.
The fragile wants tranquility, the antifragile grows from disorder, and the robust doesn’t care too much.
Everything gains or loses from volatility.
Fragility implies more to lose than to gain, equals more downside than upside, equals (unfavorable) asymmetry.
Antifragility implies more to gain than to lose, equals more upside than downside, equals (favorable) asymmetry.
For the fragile, shocks bring higher harm as their intensity increases (up to a certain level).
For the antifragile, shocks bring more benefits (equivalently, less harm) as their intensity increase (up to a point).
Fragility … simply vulnerability to the volatility of the things that affect it.
For the fragile, the cumulative effect of small shocks is smaller than the single effect of an equivalent single large shock.
Nonlinearity comes in two kinds: concave (curves inward) … or its opposite, convex (curves outward). And of course, mixed, with concave and convex sections.
If for a given variation you have more upside than downside and you draw the curve, it will be convex; the opposite for the concave.
Why the convex likes volatility. If you earn more than you lose from fluctuations, you want a lot of fluctuations.
Taleb emphasizes that fragility involves “more to lose”, “more downside”, and “more harm” and that antifragility involves “more to gain”, “more upside”, and “more benefit” (“less harm”).
Taleb emphasizes that the “cumulative effect” being smaller than the “equivalent single effect” of a shock indicates fragility.
Taleb emphasizes that convexity indicates antifragility while concavity indicates fragility.
Taleb explores the breadth and depth of “disorder”:
Fragility and antifragility mean potential gain or harm from exposure to something related to volatility. What is that something? Simply, membership in the extended disorder family.
The Extended Disorder Family (or Cluster): (i) uncertainty, (ii) variability, (iii) imperfect, incomplete knowledge, (iv) chance, (v) chaos, (vi) volatility, (vii) disorder, (viii) entropy, (ix) time, (x) the unknown, (xi) randomness, (xii) turmoil, (xiii) stressor, (xiv) error, (xv) dispersion of outcomes, (xvi) unknowledge.
It happens that uncertainty, disorder, and the unknown are completely equivalent in their effect: antifragile systems benefit (to some degree) from, and the fragile is penalized by, almost all of them.
Taleb emphasizes that fragility involves “penalization” and that antifragility involves “benefit” due to “disorder”.
Taleb explores the relationship between Black Swans and antifragility:
Black Swans (capitalized) are large-scale unpredictable and irregular events of massive consequence — unpredicted by a certain observer, and such unpredictor is generally called the ”turkey” when he is both surprised and harmed by these events.
An annoying aspect of the Black Swan problem — in fact the central, and largely missed, point — is that the odds of rare events are simply not computable.
Antifragility is not just the antidote to the Black Swan; understanding it makes us less intellectually fearful in accepting the role of these events as necessary for history, technology, knowledge, everything.
Taleb explores detecting antifragility and fragility:
Let us examine a method to detect fragility.
Now what I believe is my true specialty: error in models.
So these errors are in the long run neutral in effect, since they can affect you both ways. They increase the variance, but they don’t’ affect your business too much. There is no one-sidedness to them. And these errors can be kept under control thanks to size limit.
But this is not the case with most things we build, and with errors related to things that are fragile, in the presence of negative convexity effects. This class of errors has a one-way outcome, that is, negative.
This one-sidedness brings both underestimation or randomness and underestimation of harm, since one is more exposed to harm than benefit from error. If in the long run we get as much variation in the source of randomness one way as the other, the harm would severely outweigh the benefits.
So — and this is the key to the Triad — we can classify things by three simple distinctions: things that, in the long run, like disturbances (or errors), things that are neutral to them, and those that dislike them.
This method is very general.
The number of cars is something, a variable; traffic time is the function of something. The behavior of the function is such that it is, as we said, “not the same thing.” We can see here that the function of something becomes different from the something under nonlinearities.
- The more nonlinear, the more the function of something divorces itself from the something. If traffic were linear, then there would be no difference in traffic time between the two following situations: 90,000, then 110,000 cars on the one hand, or 100.000 cars on the other.
- The more volatile the something — the more uncertainty — the more the function divorces itself from the something. Let us consider the average number of cars again. The function (travel time) depends more on the volatility around the average. Things degrade if there is unevenness or distribution. For the same average you prefer to have 100,000 cars for both time periods; 80,000 than 120,000, would be even worse than 90,000 and 110,000.
- If the function is convex (antifragile), then the average of the function of something is going to be higher than the function of the average of something. And the reverse when the function is concave (fragile).
Antifragile and Robust
Taleb explores the distinction between robust and antifragile:
“So what is the difference between robust and antifragile?”
It is worth re-explaining the following: the robust or resilient is neither harmed nor helped by volatility and disorder, while the antifragile benefits from them. But it takes some effort for the concept to sink in. A lot of things people call robust or resilient are just robust or resilient, the other half are antifragile.
Taleb emphasizes that robustness involves being “neither harmed nor helped” due to “disorder” but antifragility involves “benefit” due to “disorder”.
Roots of Antifragility
Taleb emphasizes the roots of antifragility:
Nietzsche‘s potency as a thinker continues to surprise me: he figured out antifragility. While many attribute (mistakenly) the notion of “creative destruction” to the economist Joseph Schumpeter, while, as we saw, the more erudite source it to Karl Marx, it is indeed Nietzsche who was first to coin the term with reference to Dionysus, whom he called “creatively destructive” and “destructively creative.” Nietzsche indeed figured out — in his own way — antifragility.
Taleb emphasizes that antifragility is associated with “creative destcruction”.
Hamel offers rationale for the subject and introduces resilience:
Call it the resilience gap. The world is becoming turbulent faster than organizations are becoming resilient.
Any way you cut it, success has never been so fragile.
The fact that success has become less persistent strongly suggests that momentum is not the force it once was.
For all these companies, and for yours, continued success no longer hinges on momentum.
Rather, it rides on resilience — on the ability to dynamically reinvent business models and strategies as circumstances change.
Revolution, Renewal, and Resilience
Hamel explores the distinction between revolution, renewal, and resilience.
Revolution: Industry revolution is creative destruction. It is innovation with respect to industry rules.
Renewal: Strategic renewal is creative reconstruction. It requires innovation with respect to one’s traditional business model.
Resilience: Resilience refers to a capacity for continuous reconstruction. It requires innovation with respect to those organizational values, processes, and behaviors that systematically favor perpetuation over innovation.
Hamel distinguishes between “creative destruction” (which involves “revolution), “creative reconstruction” (which involves “renewal”), and resilience (which involves “continuous reconstruction”).
Resilience: Strategic and Operational
Hamel explores the distinction between strategic strategic and operational resilience:
Strategic resilience is not about responding to a onetime crisis. It’s not about rebounding from a setback. It’s about continuously anticipating and adjusting to deep, secular trends that can permanently impair the earning power of a core business. It’s about having the capacity to change before the case for change becomes desperately obvious.
In fact, a company can be operationally efficient and strategically inefficient. … While companies have many ways of assessing operational efficiency, most firms are clueless when it comes to strategic efficiency.
An accelerating pace of change demands an accelerating pace of strategic evolution, which can be achieved only if a company cares as much about resilience as it does about optimization. This is currently not the case. Oh sure, companies have been working to improve their operational resilience—their ability to respond to the ups and downs of the business cycle or to quickly rebalance their product mix—but few have committed themselves to systematically tackling the challenge of strategic resilience.
Hamel distinguishes between “strategic resilience” (which involves ”continuously anticipating and adjusting to deep, secular trends”) and “operational resilience” (which involves ”responding” or “rebalancing”).
Fundamentally, “strategic resilience” involves “continuous reconstruction” or “continuously anticipating and adjusting to deep, secular trends”, which includes “creative destruction” and “creative reconstruction” (“renewal”).
Hamel explores how to become resilient:
Any organization that hopes to become resilient must address four challenges:
- The Cognitive Challenge [and Conquering Denial]: A company must become entirely free of denial, nostalgia, and arrogance. It must be deeply conscious of what’s changing and perpetually willing to consider how those changes are likely to affect its current success.
- The Strategic Challenge [and Valuing Variety]: Resilience requires alternatives as well as awareness — the ability to create a plethora of new options as compelling alternatives to dying strategies.
- The Political Challenge [and Liberating Resources]: An organization must be able to divert resources from yesterday’s products and programs to tomorrow’s. This doesn’t mean funding flights of fancy; it means building an ability to support a broad portfolio of breakout experiments with the necessary capital and talent.
- The Ideological Challenge [and Embracing Paradox]: Few organizations question the doctrine of optimization. But optimizing a business model that is slowly becoming irrelevant can’t secure a company’s future.
Fundamentally, the cognitive challenge involves “awareness”, the strategic challenge involves “options”, the political challenge involves “experiments”, and the ideological challenge involves “questioning the doctrine of optimization”.
Essence of Resilience
Hamel emphasizes the essence of resilience:
Any company that can make sense of its environment, generate strategic options, and realign its resources faster than its rivals will enjoy a decisive advantage. This is the essence of resilience.
Panarchy and Adaptive Cycle
Holling offers rationale for the subject and introduces panarchies and adaptive cycles:
“Panarchy” is the term we use to describe a concept that explains the evolving nature of complex adaptive systems.
Panarchy is the hierarchical structure in which systems of nature, and humans, as well as combined human-nature systems and social-ecological systems, are interlinked in never-ending adaptive cycles of growth, accumulation, restructuring, and renewal. These transformational cycles take place in nested sets at scales ranging from a leaf to the biosphere over periods from days to geologic epochs, and from the scales of a family to a sociopolitical region over periods from years to centuries.
The idea of panarchy combines the concept of space/time hierarchies with a concept of adaptive cycles.
“Hierarchies”, but not in the sense of a top-down sequence of authoritative control. Rather, semi-autonomous levels are formed from the interactions among a set of variables that share similar speeds.
Each of the levels of a dynamic hierarchy serves two functions. One is to conserve and stabilize conditions for the faster and smaller levels; the other is to generate and test innovations by experiments occurring within a level [an adaptive cycle].
Holling emphasizes “transformational cycles” (adaptive cycles) being “nested at scales/levels” (panarchies) to “explain the evolving nature of complex adaptive systems”.
Notably, transformational cycles are pivotal in cultural transformation (and our transformation practice)!
Resilience: Engineering and Ecosystem
Holling introduces resilience:
There are three properties that shape the adaptive cycle and the future state of a system.
- The inherent potential of a system that is available for change, since that potential determines the range of future options possible. This property can be thought of, loosely, as the “wealth” of a system.
Potential sets limits to what is possible — it determines the number of options for the future.
- The internal controllability of a system; that is, the degree of connectedness between internal controlling variables and processes, a measure that reflects the degree of flexibility or rigidity of such controls, such as their sensitivity or not to perturbation.
Connectedness determines the degree to which a system can control its own destiny, as distinct from being caught by the whims of external variability.
- The adaptive capacity; that is, the resilience of the system, a measure of its vulnerability to unexpected or unpredictable shocks. This property can be thought of as the opposite of the vulnerability of the system.
Resilience determines how vulnerable a system is to unexpected disturbances and surprises that can exceed or break that control.
Resilience, as achieved by adaptive capacity, determines how vulnerable the system is to unexpected disturbances and surprises that can exceed or break that control.
Holling explores the distinction between engineering and ecosystem resilience.
Engineering resilience … stability near an equilibrium steady state, where resistance to disturbance and speed of return to the equilibrium are used to measure the property … focusing on efficiency.
Ecosystem resilience … conditions far from any equilibrium steady state, where instabilities can flip a system into another regime … focusing on existence.
Holling distinguishes between “engineering resilience” (which involves ”returning to equilibrium”) and “ecosystem resilience” (which involves ”flipping into another regime”).
Holling emphasizes that the opposite of “resilience” is “vulnerability”.
Holling explores the details of adaptive cycles:
The trajectory alternates between long periods of slow accumulation and transformation of resources (from exploitation [growth] to conservation [maturation], or r [instantaneous rate of growth] to K [sustained plateau or maximum]), with shorter periods that create opportunities for innovation (from release [death] to reorganization [birth], or omega [represents the end] to [renewal] alpha [represents the beginning]).
The phase from omega to alpha is a period of rapid reorganization during which novel recombinations can unexpectedly seed experiments that lead to innovations in the next cycle. The economist J. A. Schumpeter appropriately called this phase “creative destruction.” Initially, the “front loop” of the trajectory, from r to K, becomes progressively more predictable as it develops. In contrast, the “back loop” of the adaptive cycle, from omega to alpha, is inherently unpredictable and highly uncertain. At that stage, the previously accumulated mutations, inventions, external invaders, and capital can become reassorted into novel combinations, some of which nucleate new opportunity.
If the progress from r to K represents a prolonged period during which short-term predictability increase, the shift from omega to alpha represents a sudden explosive increase in uncertainty.
The alpha phase turns what might otherwise be a fixed, predictable progression or cycle into a wonderfully unpredictable, uncertain options for the future.
The alpha phase is the stage that is least examined and the least known. It is the beginning of a process of reorganization that provides the potential for subsequent growth, resource accumulation, and storage.
There are four key features that characterize an adaptive cycle, with its properties of growth and accumulation on the one hand and of novelty and renewal on the other. All of them are measurable in specific situations:
- Potential (that is, wealth as expressed in ecosystem structure, productivity, human relationships, mutations, and inventions) increases incrementally in conjunction with increased efficiency but also in conjunction with increased rigidity. This is the phase from r to K.
- As potential increases, slow changes gradually expose an increasing vulnerability (decreased resilience) to such threats as fire, insect outbreak, competitors, or opposition groups. The system becomes an accident waiting to happen. A break can trigger the release of accumulated potential in what the economist Schumpeter called “creative destruction”. The trajectory then moves abruptly into a back loop from K to omega.
- Innovation occurs in pulses or surges of innovation when uncertainty is great, potential is high, and controls are weak, so that novel recombinations can form. This is the phase of reorganization where low connectedness allows unexpected combinations of previously isolated or constrained innovations that can nucleate new opportunity.
- Those innovations are then tested. Some fail, but others survive and adapt in a succeeding phase of growth from r to K.
Holling emphasizes that adaptive cycles involve four phases: exploitation (growth), conservation (maturation), release (death/end), and reorganzation (birth/beginning).
Holling emphasizes that the phase from omega to alpha involves “rapid reorganization” and “novel recombinations”, the phase from r to K is “more predictable”, and the phase from omega to alpha is “inherently unpredictable and highly uncertain”.
Holling emphasizes that the phase from omega to alpha “seeds experiments[, which nucleate new opportunities,] that lead to innovations in the next cycle.”
Holling emphasizes that “creative destruction” is associated with the shift from the “front loop” to the “back loop” or from K to omega.
Holling explores the details of panarchies:
A panarchy is a representation of a hierarchy as a nested set of adaptive cycles.
This adaptive cycle captures in a heuristic fashion the engine that periodically generates the variability and novelty upon which experimentation depends. As a consequence of the periodic, but transient, phases of creative destruction (omega stage) and renewal (alpha stage), each level of a system’s structure and processes can be reorganized. This reshuffling in the back loop of the cycle allows the possibility of new system configurations and opportunities utilizing the exotic and entirely novel entrants that had accumulated in earlier phases. The adaptive cycle opens transient windows of opportunity so that novel assortments can be generated.
When a level in the panarchy enters its omega phase of creative destruction, the collapse can cascade to the next larger and slower level by triggering a crisis. Such an event is most likely if the slower level is at its K phase, because at this point the resilience is low and the level is particularly vulnerable. “Revolt” suggests this effect, one where fast and small events overwhelm slow and large ones. Once triggered, the effect can cascade to still higher, slower levels, particularly if those levels have also accumulated vulnerabilities and rigidities.
“Remember” indicates a second type of cross-scale interaction that is important at times of change and renewal. Once a catastrophe is triggered at one level, the opportunities for, or constraints against, the renewal of the cycle are strongly influenced by the K phase of the next slower and larger level. It is as if this connection draws on the accumulated wisdom and experiences of maturity; hence, the word “remember.”
The panarchy is a representation of the ways in which a healthy social-ecological system can invent and experiment, benefiting from inventions that create opportunity while it is kept safe from those that destabilize the system because of their nature or excessive exuberance. Each level is allowed to operate at its own pace, protected from above by slower, larger levels but invigorated from below by faster, smaller cycles of innovation. The whole panarchy is therefore both creative and conserving. The interactions between cycles in a panarchy combine learning with continuity.
Holling emphasizes that “creative destruction” is associated with the omega stage and “renewal” is associated with the alpha stage.
Notably, “creative destruction” and “renewal” are pivotal in cultural transformation (and our transformation practice)!
Holling emphasizes that the phase from omega to alpha “seeds experiments[, which nucleate new opportunities,] that lead to innovations in the next cycle.”
Holling emphasizes that the adaptive cycle “generates the variability and novelty upon which experimentation depends” essential for a healthy system that can invent and experiment, benefiting from inventions that create opportunity.
Holling emphasizes that cross-scale interactions cascade to the next larger level through “revolt” and to the next smaller level through “remember”.
Husdal explores the distinction between flexibility, agility, robustness, and resilience:
… some definitions …
- Flexibility: the planned and/or scheduled adaptation to expected changing circumstances
- Agility: the unplanned and/or unscheduled adaptation to unforeseen and unexpected changing circumstances
- Robustness: the ability to withstand and endure changing circumstances without adaptation
- Resilience: the ability to survive changing circumstances despite suffering severe impact
Husdal emphasizes that planned adaptation for what is expected is flexibility and that unplanned adaptation for what is unexpected is agility while robustness involves enduring without adaptation and resilience involves surviving.