Executive Summary

Benevolent Disruption: The Fortune in Solving Humankind’s Biggest Problems introduces a data-driven investment thesis: companies that address entrenched structural problems deliver consistently higher returns than traditional venture investments.

Drawing on one of the largest private datasets in venture capital history – 40 years, 500 funds, 16,000 companies – this research identifies a new source of alpha: “Problem-Solving Companies”. These businesses embed solutions to large-scale challenges (examples including financial exclusion, climate risk, knowledge access, and security) into their business models. Some do this directly: generating revenue by solving the problem itself. Others do it indirectly: enabling systemic remediation of these externalities while monetizing elsewhere in the value chain. It is only with access to such long-term fund data, that investors and allocators are able to spot this extraordinary relationship between financial returns and Problem-Solving Companies.

The findings are unequivocal:

• Problem Solvers deliver 51% higher returns than traditional venture investments
• Indirect Problem Solvers, whose business models solve foundational problems even if they monetize elsewhere, generate 67% higher returns
• Problem Solvers are counter-cyclical, outperforming during downturns when systemic failures surface and demand for real solutions intensifies

This outperformance can be explained by commercial dynamics. Companies solving foundational challenges benefit from stronger demand signals, broader stakeholder alignment, and faster regulatory tailwinds. These forces compound into what this paper terms supercharged incentives – where customer need, policy relevance, and market infrastructure reinforce structural demand and long-term defensibility.

This performance-based lens breaks from two prevailing, yet flawed, conventions. First, ESG investing has become more marketing than methodology. It was designed to mitigate downside risk, not capture upside performance. It rewards disclosure and optics – how a company presents itself –  rather than operational strength or value creation. The result is a bloated compliance layer that constrains exposure and misprices capital. Second, mainstream venture capital increasingly behaves like a speculative engine. Cycles of thematic hype, shallow diligence, and benchmark-driven capital deployment have crowded portfolios with short-cycle bets. These companies often chase visibility over durability. Recent cycles have shown how quickly these assumptions collapse.

Benevolent Disruption offers a third approach: a returns-first framework based on common-sense fundamentals. It gives allocators a practical toolkit to identify companies with embedded commercial advantage, where business model design is aligned with long-term relevance, defensibility, and scalable demand.

This is not an aspirational view of what companies should do. It is a pattern recognition exercise based on what actually delivers outsized performance in venture portfolios.

Foreword

Venture Capital in the Macro-Economic Context.

Professor Josh Lerner, Harvard Business School

“Innovation is the central issue in economic prosperity.”
– Michael Porter

Economists, policymakers, and practitioners across industries generally agree on the need for greater innovation. This consensus, among groups with often disparate goals, stems from the fact that innovation drives economic growth. As early as the 1950s, academics such as Abramowitz and Solow (who would go on to win the Nobel Prize in Economics for his work on this topic) determined that technological progress catalyzes economic progress by improving the effectiveness of labor and capital. Policymakers prioritize innovation given the potential for economic growth to reduce poverty and enhance living standards. And for practitioners, new technologies help make their businesses more resilient, productive, and profitable.

However, lagging productivity growth across many Western countries has prompted broad concerns about innovation. Research efficiency is falling across fields as ideas appear to be getting harder to find. Large firms are investing less in R&D, with the decline concentrated in research expenditures. Is this a response to public investors’ unwillingness to reward these activities? Or perhaps changing corporate incentive schemes? Whatever the causes, the consequences will likely be substantial given innovation’s role in economic prosperity.

Against this troubling backdrop, the venture capital (VC) industry has remained one bright spot. VC has financed startups at early stages that have ultimately grown into some of the largest and most well-known companies around the world. Research similarly shows how VC involvement often leads to greater and more impactful innovation, and formerly VC-backed companies spend disproportionately more on R&D after going public.

However, VC investment has been concentrated in a narrow slice of technological innovation despite the significant increase in capital deployed by VC investors and the growing number of startups receiving funding. Over the past 35 years, VC funds have largely shifted their focus away from computer hardware (which received approximately half of all VC dollars between 1985 to 1989) towards software and services startups (which received three-quarters of all VC dollars between 2015 to 2019). This shift reflects the fact that funds can relatively quickly and cheaply learn whether these businesses – which generally rely on intangible assets – are likely to be promising. Similarly, VCs have increasingly gravitated towards startups with business models that optimize existing products and services for convenience, cost, or other similar dimensions instead of more “radical” forms of innovation.

These considerations highlight that VC in its current form is not a cure-all to stagnating innovation. There may exist promising startups poised to tackle society’s biggest challenges; but because their businesses face greater regulatory, technology, or market risks, they may receive relatively less – or no – attention from VCs relative to “safer” startups that provide incremental innovation only. As a result, much-needed technological progress in key areas of the economy may be stymied.

Thus, the inflection point at which VC currently finds itself undoubtedly presents both challenges and opportunities. For investors willing to take the sorts of calculated risks that characterized the early VC industry, some of the most difficult problems facing society today also may present some of the greatest investment opportunities. Adopting new approaches for thinking about VC investment – for instance, by recognizing that outsized financial returns can be produced while solving big issues at scale – could be integral to the next wave of innovation.

1. From Paradox to Synthesis: How Systemic Problem-Solving Drives Venture Returns

1.1 What is a Problem-Solving Company? 

A Problem-Solving Company, or Problem Solver, is a business that addresses systemic, persistent societal challenges. Examples include (but are not limited to) climate change, healthcare access, financial inclusion, knowledge gaps, or security risks. While most businesses aim to solve a problem of some kind, what distinguishes Problem Solvers is the depth, scale, and relevance of the problem the address.

Not all problems are created equal, and neither are the companies solving them. While companies solving inconsequential inconveniences have raised venture funding (from instant cookie delivery to simultaneous front-and-back photos), big problems are structural; they stem from persistent challenges affecting billions and shaping our future.

Ask the average person, conduct a search online or review the UN’s Development Goals, and five large-scale challenges consistently recur (see Figure 1): Knowledge Barriers, Financial Exclusion, Healthcare Vulnerabilities, Security Failures, and Climate Change.

These challenges aren’t inefficiencies at the margins nor are they abstract development goals like ending poverty or eradicating hunger.

Rather, they are venture-scale problems with clear commercial pathways and scalable addressability. They include improving access to essential financial services, digitizing healthcare delivery, accelerating the deployment of clean energy solutions, expanding participation in the formal economy, and securing digital systems and infrastructure.

Identifying or investing in Problem Solvers begins with first-principles thinking: by linking business model incentives to systemic problems (as set out in Figure 1). Some do this directly, generating revenue by solving the problem itself, like Remitly generating profits from global remittances to enable financial access or Octopus accelerating renewable energy adoption.  Others do it indirectly, enabling systemic remediation of these externalities while monetizing elsewhere in the value chain, like Shopify empowering small businesses or Zoom reducing travel emissions by enabling remote work with video-conferencing software.

The paper outlines a clear playbook to spot these companies systematically, and repositions systemic relevance not as a moral signal, but as a recurring driver of superior financial returns.

Figure 1: Problem Solving Companies: Matching Business Model Incentives to Systemic Problems

Summary: Each bubble shows a major global problem and examples of the Problem Solvers addressing it, grouped by whether their business model addresses it directly (core to profit) or indirectly (as a byproduct).

1.2. The Hidden Pattern, and the Implication for Capital Allocators 

Balancing what is good for business and what is good for society has long been seen as a trade-off. But for today’s allocators, the data tells a different story: solving the world’s biggest problems is one of the most consistent drivers of outsized financial returns.

Until now, however, it has been almost impossible to find the data to examine the relationship between systemic problem solving and returns. Venture capital operates in private markets, where fund-level returns are rarely disclosed publicly. It is called “private” market data for a reason: it is typically disclosed only to the limited partners of each specific fund, and almost never shared publicly. Meanwhile, traditional databases, from Bloomberg to Crunchbase, rely heavily on self-reported valuations, not returns. It is perhaps because of the lack of availability and transparency in fund and returns data that investors and allocators have missed a crucial pattern. Unlike public markets where data is public, in venture capital no one has been able to zoom out and view the asset class holistically. As a result, investors have not been able to take a data-driven approach as to what does and doesn’t work.

This research creates a rare exception. Through proprietary access to VenCap International’s unrivaled dataset (spanning 40 years, 500 funds, and over 16,000 portfolio companies), this research offers a rare, extensive empirical lens into the anatomy of venture returns. Crucially, this data is built not on interim valuations, but on verified, cash-on-cash fund returns; providing an objective and longitudinal view of venture capital’s true performance drivers.
This extent of breadth and depth matters. By covering multiple fund generations, economic cycles, and technological shifts, the dataset flattens out cyclical noise and reveals durable structural patterns – something short-term or partial datasets cannot achieve. Moreover, because VenCap has consistently backed many of the world’s leading venture firms, the sample reflects a peer group operating at the highest end of the market – offering a focused lens on where enduring value is created.

Access to this unprecedented dataset has revealed a striking set of truths:

• Defined investment universe:  Approximately 30% of companies are ‘Problem Solvers’. This figure affirms an important yet under-discussed point: a meaningful minority of companies are actively driving positive change. ESG frameworks ensure there is only a small portion of businesses that meet their criteria. However, this demonstrates Problem Solvers are not rare exceptions, they form a substantial and investable subset of the venture landscape.
• Better returns: Problem Solvers on aggregate deliver 51% higher returns than traditional venture investments (non-Problem Solvers). This shows that aligning investment with systemic problem-solving materially enhances financial outcomes.
• Higher strike-rate: These companies make up less than 30% of venture portfolios, yet they represent 38% of fund-level outliers. This translates to a 27% higher likelihood of identifying a breakout success, representing a material increase in hit rate for investors. In practical terms, backing Problem Solvers improves the odds of finding fund-defining investments.
• Hidden value: Indirect Problem Solvers – solving foundational problems less obviously – generate the highest returns of all: 67% higher than traditional venture investments. This suggests the greatest upside potential lies in investing in companies whose business models solve systemic problems without fitting conventional impact categories.

1.3. Thesis Background: The Paradox of Progress 

Historical Context:

Figure 2: Timeline of Competing Narratives in Modern Capitalism

Capitalism is a tale of competing narratives (Shareholders vs. Stakeholders, Profit vs. Purpose, Private vs. Public) that distract us from a far greater opportunity: What if the greatest economic opportunities of our time lie in solving humanity’s biggest challenges?

For over two centuries, capitalism – and corresponding advances in technology – have been a driving force for human progress. Without capitalism, societies would not have innovations from IVF to indoor plumbing and electricity. Yet, capitalism has also been a system riddled with contradictions, marred by unintended consequences. While market forces have reduced extreme poverty from the long-term average of 79% in 1820 to less than 10% today, these same forces have exacerbated climate risks, widened inequalities, and spurred technological disruptions with profound unintended consequences.2

Consider the industrial revolution, which brought unparalleled economic growth but did so at a cost – reliance on fossil fuels that now threaten the planet. The digital revolution has similarly transformed human connectivity and productivity while introducing cybercrime, privacy erosion, and amplified social polarization. As a new era of artificial intelligence emerges, technology is transforming knowledge access, while simultaneously raising concerns of surveillance, job displacement, and the concentration of power.

This duality is a structural feature of capitalism, which has long been defined by opposing forces: ‘Shareholders vs. Stakeholders,’ ‘Profit vs. Purpose,’ and ‘Private vs. Public’. To the extent that the tension between ‘doing good’ and ‘making profit’ often feels irreconcilable. But what if the most significant opportunities of our time lie precisely at the intersection of these competing forces?

Before evaluating this question, it’s worth asking: why has it been missed by capital allocators and innovators alike? The answer lies in the tug-of-war between two legacy worldviews: the ‘Benevolents’ and ‘Disruptors’ (see timeline in Figure 2). Benevolent Disruption transcends these binaries of the past; rejecting both techno-solutionism detached from real needs, and virtue signaling detached from commercial viability.

Today’s investment landscape demands a rethink. From geopolitical fragmentation to fragile supply chains and declining trust in institutions, the conditions shaping modern markets have outpaced the logic of legacy playbooks. In response, Benevolent Disruption returns to first principles; solving foundational problems that matter to both business and society. The result is a practical roadmap for capital allocators seeking to back companies that don’t just move fast and break things, but build better systems, unlock real-world value, and outperform in the process.

The most resilient, high-performing companies of the next decade won’t choose sides. They’ll operate at the intersection. These are the fault-lines where value concentrates. This is the essence of Benevolent Disruption: a framework to reconcile this false dichotomy, escape the distraction of competing heuristics and identify businesses at their intersection, which address the ‘big problems’ affecting humankind while generating extraordinary economic returns.

Amidst the distraction of two persistent but limiting heuristics, this paper lays out four signals for Benevolent Disruptors to factor into their investment frameworks – as a mental model for portfolio selection. The result is a new template for capital allocators seeking to back companies that don’t just move fast and break things, but build better systems, unlock real-world value, and outperform in the process.

Why Venture Has Missed the Moment 

Venture capital has long positioned itself as the engine of innovation. But in practice, it has become a machine for optimizing the familiar: faster, cheaper, slicker versions of what already exists. Over the past two decades, the industry has drifted toward trend-chasing and hype cycles, funding “feature factories” for Big Tech while systematically underfunding the foundational systems that underpin resilient economies. Rather than tackling climate resilience, healthcare infrastructure, or education access, the industry has defaulted to convenience apps and incremental software plays Even in high-impact areas such as clean energy or biotech, private capital often follows only after public or philanthropic capital has absorbed early-stage risk.

While venture capital has generated significant financial returns and driven technical progress, its current heuristics – focused on speed, simplicity, and rapid exits – are not well-suited to identifying or supporting businesses solving long-term structural problems. The result is an innovation pipeline that underrepresents some of the highest-leverage opportunities across both societal and financial dimensions.

Why Current Frameworks Have Failed 

The universe of businesses driving positive change and the frameworks that seek to capture them do not match. What began as an effort to align capital with people and planet has fractured into a patchwork of ESG ratings, disclosure criteria, and impact classifications. These frameworks were designed to formalize responsible investing. Instead, they have often produced confusion and constraints. The same company might be rated a sustainability leader by one agency and a laggard by another, depending on which data is selected, how it is weighted – and when. Arms manufacturers, for example, may be included or excluded depending on the geopolitical context.

Similarly, companies with strong governance structures but limited or even negative societal impact can still earn top ESG scores. These contradictions have created what many now refer to as the ESG standoff - a market dynamic where the appearance of sustainability often matters more than actual effectiveness. In addition, greenwashing – the practice of overstating or misrepresenting environmental or social impact – is a valid and growing concern. The problem lies not just in corporate intent, but in how rigid frameworks in fact make greenwashing easier to perform and harder to detect. When compliance with labels or checklists becomes the goal, companies are incentivized to optimize for perception over performance. Impact is often measured in disclosures and ratings, rather than in real-world outcomes.

This misalignment has led to a distorted investment landscape. Capital flows toward companies that conform to frameworks, regardless of whether they generate meaningful real-world impact. Businesses that score well on ESG metrics or fit neatly into sustainability classifications often trade at a premium – not because they are solving systemic problems, but because they check the right boxes. This has introduced what many describe as the sustainability premium: higher entry prices, limited scalability, and a narrower universe of investable opportunities. At the same time, companies delivering tangible solutions to foundational challenges are frequently overlooked or excluded, simply because they do not fit the frame.

Efforts to bring structure through regulation, such as the EU’s Sustainable Finance Disclosure Regulation (SFDR), have added clarity in some areas but also reinforced rigidity. Fund managers are increasingly forced to allocate based on classification thresholds rather than investment insight.

Further, ESG has become increasingly politicized. The public discourse and debate has been targeted by all sides of the political spectrum with some urging that it infringes too far in capitalist processes, with others arguing it doesn’t go far enough. The politicization has mainly served to reduce confidence and disincentivize investors from interacting with the process. Investors are increasingly concerned by the potential political backlash they may be subjugated to from all sides in this space. As a result, they have often chosen the path of least resistance – doing nothing.  

In sum, the current frameworks are often not fit for purpose. This is because they do not accurately or effectively capture the universe of businesses they intended for – those driving positive change.

1.4. Introducing Benevolent Disruption 

Benevolent Disruption is a new investment concept. It is a practical roadmap to enable improved financial returns by focusing on a minority of companies that are solving fundamental problems for society and the planet.

Instead of relying on external frameworks, Benevolent Disruption prioritizes the one thing capital should ultimately measure: outcomes. It restores a principle too often lost in today’s investment landscape – common sense – and empowers investors to focus on what matters. This paper proposes a fundamentally different logic: that companies solving meaningful problems at scale are best positioned to outperform. It treats the size and complexity of a challenge as a signal, not a barrier. And it offers a practical way to identify winners in spaces others tend to ignore – whether passed over by venture capital, or left out of ESG frameworks because their impact isn’t immediately obvious. Yet this is exactly where some of the most durable and mispriced opportunities are emerging.

This approach restores what the current system tends to suppress: space for investment discretion. The term “benevolent” itself comes from bene (good) and velle (to will); implying that the role of the investor is not simply to comply with a checklist, but to actively shape a portfolio that delivers value across societal and financial dimensions.

By prioritizing business model outcomes – not frameworks – this approach captures businesses that actually solve for systemic challenges, including those that do so indirectly or across multiple systems. While broader discretion always carries some risk, the alternative is worse: rigid frameworks that exclude meaningful solutions and fail to evolve with real-world change. Further, as this paper will demonstrate, in practice, it’s counterintuitive for bad actors to exploit this model – because doing so would mean missing out on the very upside created by solving structural problems.

Benevolent Disruption enables a ‘common sense’ approach to evaluating whether a company is addressing big problems. Some of the most returnable solutions exist in the grey space. A cybersecurity firm protecting critical infrastructure might not screen as green, despite enabling climate resilience. A company improving data center efficiency may not qualify as sustainable, even though it enables the energy transition at scale. And that is why investing at the frontier of systemic change requires room for judgment.

This is not a moral stance, it is a practical lens for surfacing high-conviction opportunities that conventional models miss. It enables investors to move beyond template-driven decisions and toward a logic better suited to the problems – and the returns – that define the next economy. If allocators care about impact, they should underwrite it the way they underwrite financial performance: by evaluating what companies actually deliver. If they trust the approach, they allocate. If not, they don’t. In either case, market discipline – not box-checking – leads.

2. The Fortune at the Heart of LP Returns Data

Spotting a Pattern in the Data 

This inquiry started with recurring anecdotes – shared among top-performing fund managers (several of whom feature in this paper) – that the enduring winners in venture portfolios tend to tackle deep, structural problems. Not hype-driven gadgets or fleeting trends, but fundamental, societal and planetary pain points.

This intuition was first tested through analysis of the Crunchbase Unicorn Board – a globally recognized ledger of the world’s most successful private companies. As the most visited startup and venture data platform, Crunchbase provides real-time intelligence on company growth trajectories, funding patterns, and market trends. Its curated Unicorn Board tracks over 1500 venture-backed firms valued at $1 billion or more as of Q1 2025, offering a dynamic view into how disruptive business models scale within the competitive VC ecosystem.

On initial review, one signal stood out: roughly 30% of these companies, those categorized as Problem Solvers, account for a disproportionate share of total enterprise value (see Figure 3). This early finding affirmed what many investors have long sensed but lacked the data to verify.

Figure 3: Example Global Unicorns Solving the World’s Biggest Problems 

Summary: 30% of the world’s most valuable tech companies are Problem Solvers; ventures built to address structural externalities across sectors like health, inclusion, climate, knowledge access, and security. This is a growing trend, as solving systemic problems becomes a dominant pathway to outsized value creation.

But even clear-cut patterns, like those surfaced in the Crunchbase Unicorn Board, aren’t enough for capital allocators making high-conviction, long-term investment decisions. While Crunchbase provides valuable visibility into the most successful private companies globally, it captures only part of the picture:

1. The analysis reflects a point-in-time snapshot, not a longitudinal study of outcomes over extended periods, meaning it does not guarantee a repeatable investment formula.
2. The data measures company valuations, not actual returns to investors; a company’s value today can rise or fall sharply, and only returns or sustained long-term value retention offer true evidence of success.
3. Much of the observed value creation has already been captured; while this supports the underlying pattern, it also underscores the need to focus on building exposure to emerging Problem Solvers earlier in the cycle.

So, the question remained: do funds that back more Problem Solvers systematically outperform their peers? Or was this just a retrospective bias applied to already-successful firms? To test whether backing Problem Solvers delivers consistent, predictive upside to venture funds, access to the one thing venture markets seldom make public was needed: actual fund-level returns data.

2.1. The VenCap Dataset 

Lacking access to large datasets of fund-level data is likely the reason that investors and allocators have not been able to spot the extra ordinary pattern in the data that this paper highlights. This paper draws on a uniquely privileged source: proprietary access to one of the most extensive and detailed datasets in global venture capital, provided by VenCap International. Founded in 1987, VenCap is one of the most established and enduring venture capital fund-of-funds globally. The dataset comprises detailed performance data across 500 venture capital funds and over 16,000 underlying portfolio firms across a 40-year period, granting it unmatched visibility into the evolution of private market landscape. 

What makes this dataset extraordinary is not only its scale and breadth, but also its historical depth. Spanning multiple economic cycles, technological shifts, and geopolitical transitions, it provides a longitudinal view of how value is created in venture capital over time. This long-range perspective enables a far more robust understanding of what consistently drives returns, regardless of prevailing market narratives or temporary hype cycles.

Equally important is the nature of the data itself: returns tracked at the individual fund-level.

This kind of transparency is extraordinarily rare in venture capital. Fund managers and allocators only have access to the funds they manage or invest in and therefore cannot have the broader perspective this dataset provides. Aside from anonymized benchmarking tools such as those provided by Cambridge Associates, there are virtually no public sources that offer this level of empirical insight. As such, the VenCap dataset constitutes one of the few publicly shared windows into the actual distribution of venture outcomes. For the first time, it is possible to move beyond abstract theories and identify, with precision, what creates long-term value in the venture ecosystem.

For an audience of practitioners evaluating the financial viability of fund strategies and alternatives, this kind of high-fidelity data is invaluable. Anchored in the lived realities of top-tier venture portfolios, it provides unparalleled visibility into the “engine room” of venture capital. This perspective enables a structural rethinking of how capital allocators might identify and systematically back the next generation of enduring winners.

In sum, it is only through access to such a large and long-term dataset that enables investors and allocators to spot this crucial pattern in the data.

The Power Law Principle 

Venture capital isn’t a game of averages; it’s a hunt for anomalies. The “power law” defines the landscape: a tiny slice of investments – often fewer than 5% – drives more than half of a fund’s total returns. In the VenCap dataset, this pattern is constant (see distribution in Figure 4): most bets don’t return capital, but a few rare outliers deliver exponential gains.

For allocators investing in venture as an asset class, this skews traditional metrics like mean and median, making simple averages a poor guide to performance. As Sebastian Mallaby underscores in The Power Law, venture success hinges not on picking safe bets, but on backing the outliers early – the companies that reshape industries and define new categories altogether. That’s why this analysis focuses on both population-level trends and on identifying the characteristics that consistently distinguish outliers. Outperformance is not random. It follows recognizable patterns; and this paper sets out to measure them systematically.

Figure 4: The Non-normality of Venture Capital Returns in the VenCap Data Set 

3. How to Spot Problem Solving Companies: Four Signals for Benevolent Disruptors

The data tells a compelling story: Problem Solvers outperform traditional venture investments. They comprise more outliers, deliver stronger return multiples on invested capital, and show up more often in the best-performing venture portfolios. But they don’t always wear badges. Many fly under the radar, missing traditional ESG filters or impact labels.

It is therefore necessary to understand the defining traits of Problem Solvers, distilled from industry case studies and investment heuristics, to help capital allocators spot these hidden winners.

3.1. Business Model Outcomes vs. Optics 

The strongest companies don’t always say the right things – they do the right things. In a landscape saturated with ESG ratings, sustainability frameworks, and impact metrics, true value lies in outcomes, not branding.

Fund managers are often encouraged, explicitly or implicitly, to prioritize companies that fit into familiar categories: those that report against key ESG metrics, use the right language in their disclosures, and present a recognizable impact narrative. Yet this focus on external alignment can distort the investment process, diverting capital towards businesses that look socially responsible on paper, while overlooking those that deliver real system-level change.

Many of the businesses solving the most pressing global problems fall outside traditional ESG screens and impact narratives. They may not identify as climate or social enterprises, yet often address negative externalizes more profoundly than those that do. Their impact is embedded in the structure of their business model, not in how that model is packaged. By focusing on output, not input, Benevolent Disruption expands the investable universe and unlocks higher returns.

Crucially, the data supports this approach. Indirect Problem Solvers – those companies whose positive impact emerges not through direct positioning or as their core driver of revenue, but through the structure of their operations – generate 67% higher returns than traditional VC investments. These outsized returns are not a function of storytelling, but of real business model advantage. Benevolent Disruption guides capital allocators to identify companies that deliver such outsized returns by focusing on two simple dimensions:

Focusing on the Outcome, not the Optic

Figure 13: Investment choice is critical in rationalizing portfolio selection. First Principles or ‘Common Sense’ Approach to selecting Problem Solvers into Fund Portfolios  

Summary: Fund managers can surface overlooked upside by analyzing how a company’s business model mediates negative externalities — either directly or indirectly. The key is understanding whether the externality is solved as a core function of the business or as a consequence of its design. In a landscape dominated by rigid impact and ESG frameworks, discerning investors focus on structural relevance and problem-solving potential, using discretion to surface outsized value that others overlook.

The most viable businesses solving societal problems are not always the most ESG visible. By focusing solely on the impact outcome, and ignoring all other metrics, it enables a more accurate view of those businesses driving positive change. Reconsidering what qualifies as a business driving systemic change is necessary. This requires applying logic rather than relying solely on sector, taxonomy, or label (section 2.ii Methodology). A company does not need to explicitly define itself as “impact” to have significant, measurable effects on the climate, on equity, or on access.

Consider Zoom. It is rarely mentioned in the context of sustainability and would almost certainly fall outside the scope of any impact or climate fund. Yet, by enabling remote work at scale, it helped reduce global business travel and aviation emissions during and after the COVID-19 pandemic. The change it enabled – how organizations work, how people commute, how infrastructure is used – has had a substantial indirect impact on energy use and emissions. Zoom is not a climate company by branding, but its operating model has generated clear climate.

Recognizing When Optics Hide Structural Weakness

Second, optics can mask deeper business model weaknesses, and in some cases, even accelerate them. The most visible ESG businesses are not always the most viable. High-impact branding can create the illusion of strong fundamentals, even when a company’s business model is fragile underneath. When capital is allocated based on ESG visibility or narrative fit, rather than actual performance, it can push companies to raise at inflated valuations and scale before they’ve proven they can do so efficiently or sustainably. That’s the risk behind the “sustainability premium” – when demand for labeled impact assets drives prices higher, regardless of whether the fundamentals justify it. In the short term, these companies may be celebrated. In the long term, many struggle to meet expectations.

Northvolt offers a telling example. The much-celebrated Swedish battery manufacturer that aimed to accelerate the electric vehicle transition and became a public exemplar of sustainable innovation, along with others like Arrival and SunPower. On paper, it was everything an ESG-aligned investor could want. In practice, it lacked the capital efficiency, scalability, and operational resilience needed to build a long-term business. The company’s recent bankruptcy underscores a painful lesson. The product was needed, the mission was aligned, but the underlying business model did not hold. Its failure illustrates that solving a big problem is not enough if the business cannot do so at scale, with efficiency and endurance.

Viewed alongside Zoom, Northvolt highlights the disconnect between surface-level alignment and deep structural impact. The former received capital and acclaim but ultimately collapsed. The latter lacked ESG visibility yet has had broad systemic influence and continues to deliver strong financial performance. The comparison underscores a crucial point for fund managers: impact is not always where they are told to look. The most investable companies are not necessarily those with the strongest sustainability narrative, but those whose operations, by design, contribute to real-world outcomes.

For capital allocators, the challenge is not simply to filter for intent or optics, but to assess whether a business is solving a meaningful problem in a way that is financially viable, operationally scalable, and structurally resilient. This is why Benevolent Disruption insists on intentionality over prescription. By empowering fund managers to lead rather than follow, it allows them to find value where others are not looking – among the indirect, under-the-radar Problem Solvers that are structurally built to scale.

Figure 14: The Problem-Solver Spectrum: Hidden Value Beyond the Obvious 

Summary: In a market driven by optics, Problem Solvers distinguish themselves through outcomes. They create the value where it’s least obvious: by embedding solutions into scalable business models rather than signalling intent. This framework helps distinguish companies delivering real systemic outcomes from those simply optimized to look like they are.

Case Studies:

Indirect Problem Solver: Remitly 

For years, financial institutions have marketed inclusion while keeping high fees, slow transfers, and exclusionary policies intact. Financial access was treated as a CSR initiative – not a business priority. Remitly proved otherwise – redesigning remittances through business model innovation to make financial inclusion faster, more secure, and more affordable. By expanding accessibility, it unlocked an overlooked market, turning financial inclusion into a powerful engine of growth. In 2024, Remitly processed $54.6B in remittances, expanded to 7.8M customers, and generated $1.3B in revenue. Its growth was not driven by positioning, but by operational design that expands insurance access to millions of underserved customers.

Direct Problem Solver: Marshmallow

Insurers have long framed fairness as a trade-off, arguing that inclusion in risk pricing comes at the expense of financial viability. Many embraced performative ESG commitments, marketing diversity and equity while leaving exclusionary underwriting untouched. Marshmallow flipped the script. By integrating AI-driven underwriting and alternative data, Marshmallow assessed drivers based on real-world driving behavior – not blunt proxies like nationality or credit history. This shift didn’t just improve underwriting accuracy; it expanded access and unlocked a vast, underserved market. In 2023, Marshmallow grew revenue by 98% year over year, reaching more than $300M. Its success wasn’t driven by messaging – it was driven by model design. In a sector known for rebranding old models under new labels, Marshmallow exemplifies how outcomes – not optics – are what drive financial returns.

Key takeaway for capital allocators:

The most investable companies are not always the most visible, and the most visible are not always the most viable. The companies solving meaningful problems at scale often operate without ESG labels or polished narratives. By breaking away from optics and frameworks – and focusing only on whether the business model solves the negative externality – it opens up a new genre of ‘Indirect Problem Solvers’.  Benevolent Disruption focuses on businesses that embed real impact into their business model by design, not declaration.

For fund managers seeking differentiated returns and real-world impact, the challenge is not to follow narratives, but to investigate structures; to look past the surface and identify the quiet operators who are, in practice, building a more resilient system.

3.2. Multiplier effects vs. Trade-offs 

Figure 15: Benevolent disruption is about multiplier effects not trade-offs 

Summary: Problem Solvers operate in the top-right quadrant, where economic and societal value reinforce each other. Instead of trading one off for the other, they generate multiplier effects by embedding impact into scalable, enduring business models.

Case Studies:

Direct Problem Solver: Octopus Energy 

Octopus Energy is a clear example of a Direct Problem Solver that generates positive multiplier effects across the energy ecosystem. In a sector historically driven by short-term extraction and incremental improvements, Octopus chose to rebuild the energy system around long-term resilience and sustainability. Its $2 billion investment in offshore wind, part of a $19.4 billion long-term infrastructure plan, was not a speculative bet on subsidies or hype cycles. It was a deliberate strategy to scale the economics of the energy transition. At the center of this model is Kraken, Octopus’s proprietary AI platform, which dynamically balances supply and demand in real time. This system-level innovation enables more efficient grid management, smoother renewable integration, and better outcomes for consumers. The result is a rare alignment of incentives: lower costs, lower emissions, and long-term energy security. With $16 billion in revenue in 2024, a rapidly expanding international footprint, and market leadership as the UK’s largest energy supplier, Octopus proves that tackling entrenched externalities can drive both commercial scale and system-wide change.

Indirect Problem Solver: Shopify

Shopify demonstrates how enabling infrastructure can drive widespread economic empowerment. Initially built as an e-commerce platform for entrepreneurs, Shopify has become a backbone for digital retail, powering over 4 million businesses globally. By lowering the barriers to starting and scaling an online business, Shopify indirectly supports financial inclusion, job creation, and economic resilience – especially for underserved communities and solo entrepreneurs. Its $100+ billion valuation and robust recurring revenue model speak to commercial strength, but the real multiplier lies in its ecosystem: from its integration with local logistics and payment systems to the success of third-party app developers and suppliers. Shopify turns entrepreneurship into an accessible tool for upward mobility, catalyzing new markets and redistributing value from platforms to producers.

Key takeaway for capital allocators:

When companies are designed to fix what’s broken in society – and can do so through commercially viable models – they unlock powerful multiplier effects throughout the systems they operate in. Alignment with regulators, relevance to consumers, and resonance with systems under stress are not trade-offs – they’re strategic advantages that compound over time.

3.3. Problem First vs Technology Solutionism 

Figure 16: Value creation emerges where technology paradigms meet big problems 

Summary: Problem Solving Companies start with real problems present within their societal context, whereas traditional venture investors focus on tech trends spurred by new platform technologies.

Case Studies:

Google DeepMind

DeepMind began with a clear problem: the pace of scientific discovery was too slow. Scientific breakthroughs have historically been constrained by limited access – confined to elite institutions, well-funded labs, and research cycles that span decades. Rather than optimizing around existing tools, DeepMind tackled this systemic bottleneck directly – asking how AI could be used to accelerate discovery itself. The results reflect this problem-first approach. AlphaFold, its protein-folding model, solved a 50-year biological challenge and made over 200 million predicted structures publicly available. This dramatically reduced research timelines and has already supported 1,000+ scientific advances in fields like drug development and synthetic biology. Crucially, DeepMind’s specific focus on fundamental barriers, whether in science, mathematics, or energy, has positioned it as an enabler of discovery. With $1.9 billion in 2023 revenue and rising profitability, DeepMind illustrates that beginning with humanity’s hardest problems isn’t altruism – it’s a scalable strategy that opens new markets, reduces global inefficiencies, and generates category-defining businesses.

Indirect Problem Solver: Clear

Clear began with a foundational security challenge: identity verification processes that were slow, outdated, and vulnerable. Instead of building point solutions for individual sectors, Clear addressed the root problem – how to verify identities quickly and safely in any high-trust environment. Its biometric platform replaced manual checks with a secure, reusable digital identity. This began in aviation but now supports access in healthcare, finance, and live events. Each new use case builds on the same core architecture, enabling the company to scale horizontally without rebuilding for each context. With over 20 million users and $770 million in 2024 revenue, Clear’s growth reflects the commercial incentive of solving a foundational need. By addressing identity as a cross-sector infrastructure problem, it has created a platform that can extend across the economy while remaining anchored in the original pain point.

Key takeaway for capital allocators:

The most transformative companies don’t start with the latest technology; they start with the problems the world can no longer ignore. By beginning with systemic pain points and working backward, Problem Solvers create products that meet urgent, real-world demand. Companies born from deep problems enjoy built-in traction: their markets are primed, users are motivated, and adoption moves fast.

3.4. Identifying Problems Early Leads to Outsized Value

Figure 17: Externalities and the technologies addressing them align with the Innovation Diffusion Curve with more enduring effects than traditional innovations 

Summary: Problem Solvers follow a relevance-driven diffusion curve. Their adoption is not driven by novelty or convenience, but by the growing urgency of the systemic challenges they address. As externalities intensify, so does adoption, accelerated by alignment with regulation, consumer demand, and participation from mainstream businesses. This process unfolds in three stages: limited early action, growing resistance and market readiness, and finally, widespread adoption as solving the problem becomes unignorable.

To capture enduring value, investors must back companies solving structural problems before capital, consensus, or policy catch up.

Clayton Christensen’s disruption theory helped explain early venture success. Christensen posits that the role of venture is to identify innovation early in the adoption cycle. By supporting companies and subsidizing innovation in the early stages it provides a route to outsized financial value when the company innovation does achieve mass-market adoption. The negative externality curve follows a similar path. By identifying negative externalities early, and investing in the solution, investors also have a path to finding outsized value. A negative externality provides a market that innovation must solve. The more profound the externality on people’s lives – the increased demand for a solution. By following a negative externality earlier in its journey and in the solutions adoption curve (before the solution is mainstream) it provides investors with a pathway to isolating value potential.

This is why the most enduring companies don’t just chase trends. They solve for systemic risk early, before it’s rewarded. These Problem Solvers create value not through marginal gains, but by building foundational solutions to persistent externalities that undermine resilience, trust, and long-term systems integrity. And because they do so before consensus forms, their relevance – and returns – compound as the world shifts around them. The adoption curve tends to unfold in three stages (as illustrated in Figure 17), each rooted in the scale and persistence of the problem they aim to solve – and the lasting value they unlock.

1. Persistence of a Negative Externality: A foundational challenge becomes increasingly visible. Yet incentives are weak. Entrepreneurs working in these spaces are often early, underfunded, or dismissed

2. Resistance Meets Momentum: The externality gains visibility. Consumers shift. Governments legislate. Founders and early investors begin gaining traction. Momentum builds – quietly at first, then exponentially.

3. The Tipping Point: Market structures shift. What was once niche becomes inevitable. Capital floods in. Incumbents are disrupted not just by better products, but by models that make them structurally obsolete.

Many of the world’s most successful companies demonstrate the financial value of solving problems early. Companies that have placed early, high-friction bets that addressed systemic externalities long before consensus formed. To address healthcare vulnerabilities, Moderna invested early in mRNA platform technology –  a capital-intensive, high-risk approach with little near-term payoff.

But when COVID-19 hit, that platform enabled one of the fastest vaccine rollouts in history. To address emission-intensive transport, Tesla built out the electric vehicle supply chain amid deep regulatory and market skepticism. To address financial exclusion, Stripe turned digital payments into infrastructure – making financial tools accessible to small businesses and creators globally, while traditional banks remained fragmented and slow to adapt in the wake of the Global Financial Crisis.

These firms faced resistance, regulatory pressure, and market doubt – but persisted, aligning their growth with long-run externalities: decarbonization, health resilience, and financial access. Their dominance reflects the Problem Solver arc: identifying persistent friction, gaining momentum through aligned consumer and policy shifts, and ultimately redefining market baselines. By solving continuously solving early for problems others ignore and adapting their models as technologies evolved, Problem Solvers ultimately become the infrastructure much of the economy now relies on.

Benevolent Disruption shows us where to look now: at the world’s most persistent externalities. Enduring value is created not by cheaper tech, but by building systems people can rely on – especially as externalities become central to both regulation and consumer behavior. The sooner a company starts solving, the more of the upside it captures.

Key takeaway for capital allocators:

For investors, the clearest path to resilience and long-term value lies in backing companies that solve early: turning pain points into essential infrastructure, and systemic risk into scalable, enduring returns.

Case Studies:

Direct Problem Solver: Vinted

To address the mounting externalities of fast fashion, from overflowing landfills to carbon-intensive production, Vinted quietly built a circular economy engine long before resale was trendy.

Founded in 2008 in Vilnius, Lithuania, by Milda Mitkute and Justas Janauskas, the platform began as a grassroots solution to a common pain point: closets full of unworn clothes. But behind that simple use case lay a deeper systemic bet – that linear consumption in fashion was both environmentally unsustainable and costly for the consumer. Its peer-to-peer model removed friction from secondhand sales, investing early in trust systems, payment integration, and localized logistics. Long before “circularity” entered ESG reports or EU regulatory frameworks, Vinted was solving for fashion’s hidden costs: overproduction, waste, and consumer disempowerment. With over 80 million users today, Vinted underscores a core principle of Benevolent Disruption: the most enduring companies don’t wait for policy or public opinion to catch up. They identify negative externalities early, solve with integrity and scale, and are rewarded when the world inevitably shifts in their direction.

Indirect Problem Solver: Google

Google began as a faster, cleaner search engine. But its enduring value lies in a deeper mission: treating access to knowledge as a systemic infrastructure challenge. Over decades, Google has invested not just in speed or scale, but in reducing global knowledge asymmetries –  from indexing the world’s academic literature through Google Scholar to breaking down language barriers with Google Translate. Crucially, Google’s impact is not monetized at the point of problem-solving. Many of its most transformational tools are free, with revenue coming indirectly through an ecosystem built around them, such advertising. Google’s long-game orientation, solving a foundational problem before others saw its economic potential, transformed it into critical infrastructure for the knowledge economy. Its dominance is not just a function of algorithmic power, but of Problem Solving architecture: expanding access, embedding trust, and lowering systemic barriers at scale.