What systems thinking taught me about development aid failure
Learning about systems thinking through a skills module as part of my MA has been the most intellectually transformative part of my studies.
To think in systems means to understand that all of life is one big ecosystem where phenomena and actors interact and that there are no boundaries.
It has helped me articulate what I have long felt about finding solutions to problems; it is rarely about tinkering with numbers (budgets, quotas) and more so about the wrong system goals (e.g., GDP), missing or incorrect information (e.g., disbursement rate), incorrect assumptions (e.g., linearity of events) and paradigms of any kind (e.g., growth is good).
Let me illustrate what I mean with a familiar example of seeking the wrong goal (which is one of many examples of how systems fail):
Take developmental aid. For decades, the dominant measure of development success has been GDP growth. Growth (marked by GDP) = development. Aid architecture, from the World Bank to bilateral donor frameworks, has been built around this goal.
And yet GDP tells you very little about whether people are actually living better lives and even less about wealth distribution. A country can grow its GDP while inequality widens, ecosystems decline and the majority of people see no material improvements to their conditions.
When you design a system around the wrong goal, the system will deliver the goal but not the outcomes you wanted!
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You can keep throwing money at it (e.g., increase budget), trying to pump more interventions (but ignore system delays), ultimately creating aid dependency rather than solving the problem (e.g., because organisations whose existence depends on aid delivery have an incentive to perpetuate the aid chain rather than eliminate it). Or you can try to balance it, like they tried in the 90s, by giving women small loans to start their businesses so that incomes can rise and poverty falls. But what they missed was that the capital wasn’t the main constraint. Debt repayment cycles preceded income generation, while the structural conditions determining whether businesses could thrive (infrastructure, markets, governance) remained untouched.
But the “growth” problem does not stop at statistics; it shapes how development problems get defined and tackled. Hence, the issues are perpetuated by the frameworks embedded in the aid architecture itself.
Take, for instance, gender equality and the OECD DAC Gender Equality and Empowerment of Women and Girls. When growth was stagnating in the 50s and 60s, following the economic model, we figured out that something in the chain was inefficient. Women’s roles. Women are under-leveraged; the missing piece is making women economically active (because domestic unpaid labour doesn’t count, and let’s not have them sit idle). The answer repeated across decades and eventually institutionalised in frameworks such as DAC. My favourite quote to demonstrate: “It has been estimated that if women participated in the economy at the rate men do, USD 28 trillion, or 26%, would be added to annual global GDP in 2025, compared with a business-as-usual scenario.” (McKinsey Global Institute 2015). But I digress.
Aid frameworks such as DAC have historically been designed by institutions dominated by the Global North economies, whose own growth models depend on the very relationship and resource extraction that keep recipient economies dependent. The GDP as a marker of growth is not just the wrong goal; it also happens to benefit most the countries which “give” aid to the “developing” countries. And take a guess who ultimately decides on whether the aid programme or intervention was successful.
As you are probably starting to see, this goes farther than the GDP marker. It is the market economy where the ultimate goal is not competition but eradication of competition. Any system, if unchecked and unregulated, will want to grow exponentially and absorb anything in its way, including driving itself to a halt.
Systems thinking taught me that the most powerful interventions are hiding underneath the questions we avoid asking. Not how we make aid more effective, but who decided what ‘effective’ means and who benefits from that definition remaining unchallenged. Meadows (2008) argues that the highest leverage point in a system is a paradigm — the shared assumptions from which goals, rules and structures emerge, which we need to continuously subject to scrutiny. To come back to the cited paradigm, growth is good, yes, but not at the expense of human rights, dignity and ecological stability.
The most fragile systems are those optimised so efficiently around a single goal that they have lost their flexibility to do anything else. It is a much better idea to design resilient systems that have the flexibility to (self-) reorganise when conditions shift.
And in case you are interested, I am currently writing my thesis on DAC policy guidelines, centring on women’s empowerment, where many of these dynamics play out in detail. Stay tuned.
