The Hidden Cost of Not Knowing What Works
Most sustainability efforts still don’t know if they’re working—that's a risk
There’s a strange paradox at the heart of the sustainability movement. We’re spending more than ever—financially, politically, emotionally—to address environmental and social challenges. Yet the truth is: we often have no idea whether our interventions are actually working.
And that’s not just a theoretical problem. It’s an economic, strategic, and even moral one.
The Illusion of Progress
Walk into any sustainability team at a major corporation or asset manager, and you’ll hear a familiar set of words: decarbonization pathways, science-based targets, materiality matrices, double materiality, impact alignment, ESG integration.
These sound sophisticated. And they often are—on paper. But dig deeper, and you’ll often discover a startling absence of feedback loops.
Did emissions fall because of a certain policy, or in spite of it?
Did a climate risk tool change decision-making, or just tick a compliance box?
Did the firm’s “green” portfolio actually outperform because it was greener—or because of unrelated macro trends?
In short: where is the causal evidence?
Too often, we conflate activity with effectiveness. We assume that because something aligns with a framework or scores well on a rating system, it must be valuable. But systems thinking—and sustainability is nothing if not a systems problem—tells us this is a dangerous assumption.
Why This Matters More Than Ever
We’re entering a new era in which capital will increasingly flow toward sustainable technologies, projects, and companies. The EU alone is mobilizing hundreds of billions through the Green Deal and its taxonomy. Major institutions are under pressure to prove alignment with net zero, biodiversity, and social justice goals.
But if we don’t know what’s working, how can we steer these flows wisely?
This is where the hidden cost creeps in. When we don't rigorously evaluate what works:
We waste capital on initiatives with low or no real-world impact.
We create false confidence, leading to reputational and regulatory risk.
We lose time, which—given the urgency of climate tipping points—is the most precious resource of all.
This is especially risky for investors. A sustainability strategy without causal feedback is like trading without a backtest, or allocating capital based on vibes.
From Correlation to Causation
The good news is that the tools to fix this gap exist. They come from fields like causal inference, time-series econometrics, and even theoretical physics—disciplines used to tease apart signal from noise in complex systems.
What if we applied these methods to sustainability?
Instead of asking “Did emissions go down?”, we could ask:
Did emissions go down because of this policy, after controlling for energy prices, weather, and economic activity?
Instead of tracking ESG scores and hoping they correlate with returns, we could ask:
Does improvement in a company’s water management causally affect long-term operational stability in drought-prone regions?
This is the frontier we’re working on at Wangari Global: embedding causal intelligence into sustainability strategy. We’re building tools that help analysts and decision-makers trace what actually caused what—and what didn’t.
Because in a world full of complexity, we need clarity. And clarity doesn’t come from dashboards—it comes from asking the right questions, and testing them rigorously.
Why Isn’t This Already Standard?
One reason is cultural. Sustainability has grown from a values-driven, often qualitative movement. Its roots lie in doing good, raising awareness, and mobilizing action. All of which matter.
But at scale, good intentions are not enough. As sustainability gets institutionalized, it needs to evolve into a decision science.
Another reason is that measurement is hard. Not everything has a clean KPI. Many impacts unfold over long time scales, or in nonlinear ways. There’s discomfort in admitting uncertainty, especially in an environment where firms want to show progress fast.
But real progress demands intellectual humility. It requires admitting what we don’t know—so we can learn, adapt, and improve.
This is how medicine evolved. This is how aerospace evolved. Why should sustainability be any different?
The Upside of Not Knowing
Here’s the paradox: admitting what we don’t know unlocks real power.
It shifts us from performative sustainability to transformative sustainability.
From optics to mechanics.
From belief to evidence.
It also creates a better conversation with stakeholders. Imagine being able to say:
“Here’s the change we tried. Here’s what we expected. Here’s what we actually saw. And here’s what we’re learning and adjusting.”
That’s not weakness. That’s leadership.
It also attracts capital. Sophisticated investors increasingly ask hard questions:
What’s the theory of change?
What’s the sensitivity of outcomes to this intervention?
What’s the confidence interval?
The more we can speak this language, the more we can align sustainability with rigorous portfolio management—and vice versa.
A New Role for Analysts
This shift has implications for financial analysts, too. The analyst of the future is not just someone who reads balance sheets or interprets earnings calls. They're someone who can:
Formulate hypotheses around sustainability drivers,
Test them with real-world data,
Communicate uncertainty with clarity,
And spot where ESG metrics are more misleading than useful.
In that sense, the analyst becomes a kind of sustainability detective. And the better their tools, the better their results.
The Bigger Picture
This isn’t just about improving ROI or compliance metrics. It’s about making sure our best efforts actually make a dent in the problems we’re trying to solve.
Because if we’re going to tackle planetary-scale challenges—climate breakdown, ecological collapse, social fragmentation—we can’t afford to work in the dark.
We need visibility. We need learning loops. We need truth.
And truth, as any scientist knows, starts with doubt.
Next Friday’s article (paywalled) will take this a level deeper: I’ll show a worked example of a causal impact model on a sustainability dataset, using Python and the DoWhy library. If you're curious about how this gets done technically, make sure you're subscribed.
Wangari’s Curated Reads
- has a trenchant critique of Canada's developmental inertia, especially in infrastructure, digital services, housing, and sustainability. Why Canada Is Falling Behind Europe draws a sharp contrast with Europe's proactive policies, suggesting that without bold reforms and a coherent national vision, Canada risks economic and social decline. For sustainable finance professionals, it’s a compelling case study on the consequences of policy stagnation and a reminder that investments in livability, green infrastructure, and tech modernization are not luxuries but essential drivers of long-term national resilience.
The IEA's World Energy Investment 2025 report, as summarized by
, underscores major shifts relevant to sustainable finance: clean energy investment has surged past $2 trillion, driven by solar, batteries, and EVs, with grid infrastructure now emerging as the critical bottleneck. China’s dominance in manufacturing is reshaping global supply chains and costs, especially for emerging markets, while AI and grid modernization present compelling efficiency opportunities. For investors, this report is a strategic roadmap—pointing toward where capital, innovation, and geopolitical attention will be most intensely focused in the clean energy transition.Should We Care about Grid Inertia? ask our friends at
. The short answer is yes. Using the Iberian blackout as a case study, the piece highlights the operational challenges of integrating inverter-based resources like solar and wind, and underscores the importance of battery storage, fast frequency response, and interconnection. For those funding or evaluating clean energy projects, it’s a useful reminder that achieving decarbonization also requires investment in grid modernization and resilience to avoid undercutting long-term sustainability goals.