Challenges of Regenerative Systems Design (Part 3 of 4)
When Success Depletes Its Source: How Hidden Costs Accumulate Across an Interconnected System
Part 2 explored how different mathematical models define systems, establish boundaries, and determine what becomes visible. We saw that simplification is not inherently problematic. Every model simplifies reality in order to make it understandable. The challenge emerges when a model’s boundaries exclude relationships that remain essential to the functioning of the system the model is used to guide.
This progression leads us to ask:
What happens when the real costs of economic activity—such as ecological degradation, social harm, diminished human well-being, and long-term risk—do not appear in the calculations used to guide it?
To understand why ecological degradation, financial instability, public health crises, and social fragmentation often emerge together, we must examine what happens when interconnected relationships are systematically removed from view.
The consequences are rarely immediate. Hidden costs often accumulate gradually beneath the surface, obscured by indicators that suggest stability, efficiency, or success, until they cross a threshold and coalesce into a crisis. Although delayed feedback obscures the connection between cause and consequence, it does not sever it. Real systems remain interconnected, and what the model excludes continues to shape outcomes.
This is how disconnection compounds into systemic fragility.
Economic Models Overstate Success When They Exclude Its Full Costs
Externalities Shift the Uncounted Burden to the Larger System
In order to understand how separation becomes fragility, we first need to understand externalities as they are the mechanism of separation. Their effects reveal what happens when a model excludes relationships that remain active in the larger system and costs disappear from the calculation without disappearing from reality. Those costs are instead transferred to communities, ecosystems, workers, future generations, or the system as a whole.
Externalities are commonly defined as costs or benefits generated by an activity that are not reflected in its price.
We often encounter externalities throughout the modern economic systems as:
Pollution excluded from production costs
Resource depletion not priced into goods
Unpaid care work sustaining labor markets
Burnout reducing long-term human capacity
Public health impacts displaced onto communities
These examples show how accounting boundaries separate costs from the transactions that produce them. Although the framework may not recognize those costs, their consequences remain tangible in people’s lives and in the ecological and social systems on which economic activity depends.
Externalities institutionalize this separation by routinely excluding these relationships from economic calculations. This enables activities to appear successful while transferring part of their true costs to the larger system.
To understand why economic frameworks continue to exclude these costs, we must look beyond individual transactions to the assumptions that determine what they recognize as valuable in the first place. This gives us a window into the actual function of economic systems today in how they determine what is valuable and that influences decisions made from their limited perspective.
What the Model Does Not Value Disappears from the Decision
Externalities persist because costs outside market transactions remain inconsequential, even when they diminish the systems that make economic activity possible.
Externalities are not simply overlooked. They emerge from assumptions that determine which forms of value become visible, which timeframes matter, and which relationships count as part of economic success.
Many traditional economic frameworks assume that:
Markets capture the most relevant costs and benefits.
Individuals act primarily to maximize self-interest.
Natural and human-made capital are largely substitutable.
Short-term production reflects economic performance.
Market participants possess sufficient information to make efficient decisions.
These assumptions shape what enters the model and, just as importantly, what remains outside it. When established accounting practices exclude costs that extend beyond immediate market transactions, those costs carry little or no weight in economic decisions, even when they reflect changes to relationships essential to the functioning of the larger system.
The gap between the model and reality becomes visible in the disparity between measured economic success and the declining condition of the systems that make that success possible.
GDP measures the value of production but does not subtract the depletion of forests, soils, fisheries, or other natural assets that make future production possible.
Quarterly earnings reward short-term financial performance even when business practices diminish workforce well-being, ecological resilience, or long-term productive capacity.
Market prices often fail to incorporate delayed ecological and social consequences because immediate transactions do not account for those costs.
When integral relationships within the system are separated from the calculation, activities that degrade long-term system health can still appear economically successful. This disparity is a structural consequence of how economic models define and measure value.
When the indicators guiding decisions exclude ecological relationships, human well-being, or long-term resilience, those dimensions receive less consideration in economic decision-making. The model does not reveal the full condition of the system; it reveals only the portion it was designed to measure.
This leads to another fundamental question:
What happens when businesses, governments, and institutions make decisions using incomplete representations of reality?
Incomplete Measures Reward Organizations for Weakening the Architecture of the Larger System
Extracting value appears rational when the resulting loss of relationships, resources, and capacity remains uncounted.
Models do more than describe reality. They influence decisions within it. People, organizations, and institutions respond to the information, incentives, and measures available to them.
Organizations often make rational decisions based on incomplete measures of value. When financial returns and growth are visible but ecological depletion, social harm, and long-term resilience are not, resources flow toward what the model rewards rather than what sustains the system. The result is not irrationality, but rational behavior based on an incomplete view of reality
When costs do not return through prices, regulations, or other forms of feedback:
Pollution lowers production costs.
Resource extraction increases returns.
Overwork boosts short-term productivity.
Ecosystem depletion appears efficient.
Burnout appears as an individual failure rather than a sign of systemic strain.
The model does not merely conceal these costs; it can reward the activities that create them. As organizations repeatedly respond to those rewards, displaced costs accumulate beyond the boundaries of the original calculation.
The larger and more persistent the gap between the model and reality becomes, the greater the risk that hidden costs will accumulate faster than the system can absorb them.
Economic Models Can Produce the Scarcity They Assume
When models reward extraction while undervaluing renewal, they progressively weaken the resources and relationships on which the system depends.
Fragility begins when displaced costs accumulate faster than a system can absorb or repair them. What began as an accounting omission becomes a change in the condition of the system itself.
This is how a framework designed to manage scarcity can contribute to producing it.
Economics often begins with scarcity as an underlying assumption. More precisely, economic success is evaluated according to how efficiently resources assumed to be scarce are allocated. When that assumption also determines how success is measured, attention turns toward how efficiently limited resources can be acquired, allocated, and converted into output. The relationships that enable those resources to regenerate—including healthy ecosystems, resilient communities, social trust, knowledge sharing, and long-term ecological capacity—receive less attention because they are difficult to quantify or fall outside conventional market transactions. As a result, the system becomes more efficient at extracting value from the limited resources it depends upon without accounting for whether it is preserving their capacity for renewal.
As the costs of externalities accumulate, they create a powerful feedback loop in which organizations responding to these metrics become increasingly efficient at extracting value from existing resources while investing less in the relationships that replenish them:
Forests become timber inventories rather than living ecosystems.
Workers become labor inputs rather than sources of creativity and resilience.
Soil becomes a production medium rather than a living system.
In each case, the model rewards the conversion of regenerative capacity into immediate output. Over time, that conversion produces the conditions of scarcity the model assumed from the beginning. Resources become increasingly constrained not because scarcity was inevitable, but because the relationships that sustained their renewal were excluded from the definition of value.
Scarcity is no longer only an assumption of the model; it becomes an outcome of the decisions the model encourages.
Conventional economic indicators measure current performance, while resilience concerns the system’s capacity to withstand future disruption. A model organized around interdependence asks which relationships sustain regeneration. A model organized around scarcity asks how limited resources should be allocated. Each directs attention toward different measures, creates different incentives, and encourages different decisions. As those decisions accumulate, they reshape the system until it increasingly reflects the assumptions of the model guiding it.
The central paradox is that economic models begin by assuming scarcity and then reward decisions that diminish regenerative capacity, leading to the creation of real scarcity.
This decline in the regenerative capacity of resources integral to the system marks the beginning of fragility. Fragility rarely results from a single externality. Rather, it emerges when displaced costs accumulate across interconnected parts of a system, contributing to ecological degradation, public health crises, resource scarcity, financial instability, and social fragmentation.
A company can appear profitable while exhausting its workforce.
A fishery can appear productive while depleting its breeding population.
A region can appear economically successful while degrading the ecosystems supporting its long-term prosperity.
A financial system can appear stable while accumulating systemic risk.
These contradictions create an illusion of stability because conventional indicators register immediate performance without revealing whether the system retains the capacity to sustain it. Stability becomes confused with the absence of visible problems rather than understood as the capacity to adapt and remain viable under changing conditions.
Fragility is not the crisis itself. It is the accumulation of vulnerabilities before the crisis makes them visible. A system may appear most successful at the moment it is becoming least capable of absorbing disruption.
The 2008 financial crisis reveals this dynamic at a systemic scale. Vulnerabilities accumulated beneath the very conditions that made the system appear stable, until a change in those conditions exposed how little capacity remained to absorb disruption.
The 2008 Financial Crisis Exposed the Fragility That Measures of Success Had Concealed
Short-term indicators continued to signal stability while interconnected risks accumulated beyond the financial system’s capacity to absorb disruption.
In Part 1, I described my experience watching the 2008 financial crisis unfold on the streets of New York City. I was disturbed by how people who had seemingly achieved financial security suddenly discovered how fragile that security was, while even leading experts struggled to explain what was happening. I thought I knew the formula, but the math didn’t add up. It was not only a collapse of certainty; it was a rupture in the silent agreement that playing by the established economic rules would lead to security and prosperity.
I did not yet have the language for it, but I was witnessing the divide between visible success and the underlying resilience of the system.
The 2008 financial crisis provides a case study through which we can examine the mechanisms behind what I first felt viscerally. Model boundaries obscured critical relationships. That limited visibility shaped incentives; those incentives amplified systemic risk, and the resulting vulnerabilities accumulated while conventional indicators continued to signal success.
The crisis brings the central insight of this article into focus: short-term performance metrics cannot, on their own, measure the long-term health of systems whose resilience depends on interconnected relationships. When those metrics are treated as sufficient, apparent success can conceal the erosion of the relationships sustaining the system over time.
Financial Models Treated Connected Risks as Separate, Allowing Them to Grow into a Threat to the Whole System
The story begins with a reasonable strategy. Financial institutions relied on models that simplified an enormously complex system in order to make risk calculable. These models measured performance under a limited set of prevailing conditions, such as housing prices, default rates, liquidity, and diversification. However, they did not account for the health of the interconnected system over time.
The simplification itself was not the problem. The challenge emerged when the assumptions embedded within the models were mistaken for the behavior of the system as a whole. Prevailing models assumed that housing prices would remain stable or continue rising, defaults could be estimated from past behavior, diversification would disperse risk, and markets would remain sufficiently liquid.
Individual financial products appeared manageable according to the established measures of stability. Across the wider system, however, debt and risk were becoming increasingly interconnected. Institutions accumulated overlapping obligations, incentives rewarded short-term gains, and dependencies formed that no individual balance sheet could fully reveal.
The economic models produced analytical clarity about the performance of individual assets and institutions under existing conditions. However, they provided far less visibility into whether the relationships connecting the financial system could remain resilient as those conditions changed. Risk appeared to be distributed when it had actually become increasingly interconnected. The assumptions underlying these models operated within a limited time frame. The apparent ascent concealed the drop-off: each rise in housing prices and returns seemed to validate the models while increasing the system’s dependence on the conditions they assumed would continue.
Short-Term Incentives Amplified the Production of Systemic Risk
Once limited measures defined what counted as stability, incentives turned the models’ blind spots into risk-producing behavior.
The financial system appeared stable because risk had been distributed and abstracted, while significant exposures remained outside visible accounting boundaries. Financial institutions responded to incentives created by short-term indicators that suggested the risk was manageable. While risk quietly accumulated behind the veil of narrow measurements, lending expanded, leverage increased, and complex financial products proliferated. More capital flowed into housing, more debt entered the system, and more institutions optimized for immediate gains. The longer the system appeared stable, the more participants behaved as though that stability would continue.
The apparent success of these decisions reinforced the behaviors behind them. Rising housing prices, expanding credit, and growing returns appeared to confirm that risk had been effectively managed. However, the indicators measured what the system was producing under favorable conditions, not whether it was preserving the capacity to remain viable if those conditions changed.
The model did not merely predict the system; it helped shape it. The longer short-term performance appeared strong, the more participants behaved as though that performance demonstrated long-term stability. This increased the system’s dependence on continuously rising housing prices and readily available credit.
Short-term metrics encouraged institutions to proliferate risk and continue extracting value from the hollowed-out housing market. Beneath the indicators of success, leverage was rising, lending standards were declining, and obligations were becoming more tightly coupled. These were not isolated vulnerabilities. As these vulnerabilities became more tightly interdependent, their combined effects reduced the financial system’s capacity to absorb disruption. The same activities generating rising asset values and short-term returns were weakening the relationships and capacities on which future stability depended.
Short-term indicators incentivized institutions to extract immediate value without preserving the relationships that produced it. This created a one-sided and exploitative exchange that transferred costs elsewhere while progressively depleting the capacities on which future value and stability depended.
The longer these hidden dependencies accumulated, the greater the gap became between what the indicators suggested and the actual resilience of the system. When the vulnerabilities created by these dependencies crossed a threshold, risks cascaded throughout the global financial system.
Feedback Excluded from the Models Returned as Cascading Failure
A model can separate relationships analytically, but the system itself remains interconnected. Every model draws boundaries to simplify complexity, but the relationships outside those boundaries continue to operate. In an interconnected system, feedback cannot be eliminated by excluding it from measurement. Feedback excluded from the model is eventually expressed within the system itself.
When housing prices stopped rising, mortgage defaults increased. Liquidity disappeared. Confidence collapsed. The relationships treated as largely independent were revealed to be tightly interwoven through layers of debt, leverage, and financial dependency. The decline in housing prices did not create these vulnerabilities. It exposed what had accumulated while short-term indicators continued to signal success.
Risks that appeared to have been distributed across the system interacted and amplified one another, and the collapse propagated across the global financial landscape.
The crisis revealed the difference between performance and system health. Performance metrics described what the financial system was producing under favorable conditions, but not whether the relationships sustaining that performance would remain viable over time or under stress. By treating short-term performance as evidence of long-term health, the system allowed risks excluded from its measures to accumulate beneath the appearance of stability. When conditions changed, those accumulated vulnerabilities overwhelmed the system’s diminished capacity to absorb them, producing cascading failure.
The 2008 financial crisis demonstrated the danger of treating short-term performance as sufficient evidence of long-term health in an interconnected system. Reality reconnected what the models had separated.
A Window into an Incomplete Model
Short-Term Gains Appeared Profitable Because Institutions Captured the Benefits While Others Absorbed the Long-Term Costs
In 2006, I was speaking with a friend who was taking her first real estate classes. She was excited to be entering a booming industry, but a comment from her instructor unsettled her. The instructor explained that a record number of foreclosures was expected in the coming years.
This warning echoed in my mind when I saw posh men crying on the subway in 2008. Signs of growing vulnerability had already been observable two years before the crisis unfolded—so clearly that instructors were telling real estate students about them. It was not a secret; it was commonly shared industry knowledge. What remained unclear was the scale of the implications for the larger financial system. What remained absent was a meaningful incentive to respond.
This reveals an important distinction between visibility and consequence. Information becomes visible when it can be observed or known. It becomes consequential when it carries enough weight within the models, metrics, and incentives guiding decisions to change behavior. Rising foreclosure risk may have been visible, but rising housing prices, expanding credit, and short-term returns remained the dominant indicators of success. As long as those measures continued to signal growth, responding to the warning signs was less rewarding than continuing the activities producing them.
The problem, then, was not simply a lack of information; it was that the framework guiding financial decisions made some information more consequential than others. Short-term gains directly benefited the institutions positioned to shape market behavior, while the growing risks to households and the wider financial system carried far less weight in the calculations defining success. Lending expanded, leverage increased, and exposure deepened even as evidence of vulnerability accumulated.
This is how visible risk can remain structurally inconsequential. Model boundaries determine what receives attention. Metrics define which outcomes count as success. Incentives reward the decisions that improve those metrics. Evidence that does not affect measured performance can therefore be acknowledged without meaningfully changing behavior. The resulting costs are displaced onto households, communities, and the wider system until accumulated vulnerability becomes systemic fragility.
The warning signs were not entirely invisible. What the prevailing framework failed to recognize was their significance to the long-term health of an interconnected system. When prevailing metrics made those risks inconsequential, institutions were rewarded for continuing to produce and displace them.
Information alone cannot protect a system when the incentives governing behavior continue to reward the production and displacement of risk.
The Larger Pattern: When Short-Term Performance Is Framed as System Health
Exploitation Creates Fragility by Depleting the Relationships That Make Continued Success Possible
The 2008 financial crisis was not an exception. It was one particularly visible expression of a pattern that extends across ecological, economic, and social systems. When models obscure important relationships, the metrics and incentives derived from them can reward institutions for capturing immediate benefits while displacing the corresponding costs. Behaviors appear successful in the short term while vulnerabilities accumulate beneath the surface. Eventually, those hidden costs return through delayed feedback.
Climate change, biodiversity loss, resource depletion, public health crises, and financial instability emerge through different mechanisms, but they reveal the same fundamental limitation: short-term performance metrics cannot, on their own, indicate the long-term health of systems whose viability depends on interconnected relationships.
When immediate, measurable outputs become the dominant definition of success, institutions optimize for what those measures reward. Extraction can appear productive even while regenerative capacity declines. Efficiency can increase while resilience weakens. A system can therefore perform well according to its prevailing indicators while becoming progressively less capable of sustaining that performance.
At that point, externalization becomes more than an accounting omission. When institutions capture the immediate value produced through a relationship while workers, households, communities, ecosystems, or future generations absorb a disproportionate share of its costs, the exchange becomes one-sided. This is exploitation: value flows toward those positioned to capture it, while the burden of sustaining or repairing its source is transferred elsewhere.
Exploitation therefore does more than distribute value unfairly. By returning too little value to the relationships that make continued production possible, it progressively depletes its own source. Workers lose capacity, ecosystems lose regenerative function, communities lose resilience, and financial systems lose the buffers required to absorb disruption. One-sided value extraction creates scarcity, and produced scarcity becomes fragility.
The sequence is now familiar: model boundaries shape what is measured, measurements shape incentives, and incentives guide decisions that accumulate across the system. The relationships given little weight in those decisions continue shaping outcomes until their deterioration can no longer be excluded from the measures of success. What first appeared as growth, efficiency, or stability is eventually revealed to be shortsighted when fragility swells into crisis. It is like kicking the can down the road while progressively weakening your ability to retrieve it. Externalization delays consequences while diminishing the system’s capacity to recover from them. This is why exploitation is not just a moral deficiency; it is a systemic dysfunction.
The challenge for regenerative systems design is therefore not to optimize existing models, but to ask whether those models make the relationships that determine long-term viability visible and, more importantly, consequential to decision-making. If short-term performance cannot, on its own, indicate the health of an interconnected system, then the condition of those relationships must become a primary measure of whether the system can endure, adapt, and regenerate.
The evidence is no longer the missing piece. The deeper problem is that established models do not merely organize information; they remove perceived value from relationships integral to the functioning of the system and organize incentives around exploitation. The recurrence of these economic patterns raises a more difficult question because their consequences are increasingly visible and, in many cases, the warning signs have been present for decades. If the limitations of these frameworks repeatedly become visible across the exploitation of ecology, finance, public health, and society, then the central question is no longer whether our models have limitations. Every model does. Now the deeper question is why we continue treating established models as sufficient when mounting evidence shows that short-term performance can conceal declining long-term system health.
The problem may no longer be about the math of economics or ecology.
To understand why we remain so attached to established methods even as the distance between the model and reality becomes evident, we must also examine the psychological role those models play and the purposes those beliefs serve. In Part 4, we will examine what keeps us attached to worldviews even when reality contradicts them—and what can help us open the door to changing our minds.
Primary Sources:
Capra, F. (1996). The web of life: A new scientific understanding of living systems. Anchor Books.
Financial Crisis Inquiry Commission. (2011). The financial crisis inquiry report: Final report of the National Commission on the Causes of the Financial and Economic Crisis in the United States. U.S. Government Publishing Office.
Lewis, M. (2010). The big short: Inside the doomsday machine. W. W. Norton & Company.
MacKenzie, D. (2006). An engine, not a camera: How financial models shape markets. MIT Press.
Mandelbrot, B. B., & Hudson, R. L. (2004). The (mis)behavior of markets: A fractal view of risk, ruin, and reward. Basic Books.
Meadows, D. H. (2008). Thinking in systems: A primer. Chelsea Green Publishing.
Mookherjee, D., & Ray, D. (2003). Persistent inequality. The Review of Economic Studies, 70(2), 369–393.
Morgenson, G., & Rosner, J. (2011). Reckless endangerment: How outsized ambition, greed, and corruption led to economic Armageddon. Times Books.
Senge, P. M. (1990). The fifth discipline: The art and practice of the learning organization. Doubleday.
Soros, G. (1987). The alchemy of finance: Reading the mind of the market. Wiley.
Stiglitz, J. E., Sen, A., & Fitoussi, J.-P. (2009). Report by the Commission on the Measurement of Economic Performance and Social Progress. Commission on the Measurement of Economic Performance and Social Progress.
Støstad, M. N., & Cowell, F. (2024). Inequality as an externality: Consequences for tax design. Journal of Public Economics, 235, Article 105139.
Tainter, J. A. (1988). The collapse of complex societies. Cambridge University Press.
Taleb, N. N. (2001). Fooled by randomness: The hidden role of chance in life and in the markets. Random House.
Taleb, N. N. (2007). The black swan: The impact of the highly improbable. Random House.