General Direction

2026 United Nations High Level Political Forum

Manhattan is a perfect grid.

At least, that is how it appears on a map.

Avenues run north and south. Streets run east and west. This was one of the first things I had to learn when I first arrived in New York City in May of 2022.

The numbering system in Manhattan [and really most of NYC] is logical enough that, after only a few days in the city, most people can navigate without much difficulty. Yet after spending another week walking across Manhattan, I became convinced that the grid itself is not what makes the city so efficient. The real design innovation lies in how it manages movement. Traffic rarely stops everywhere at once. When one direction pauses, another typically continues. The city has not eliminated friction. It has distributed it in a way that allows movement to remain continuous.

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Systems Thinking

Over the past two weeks, I have been listening to Systems Thinking by Donella Meadows, and reflecting on how to solve big problems in rather simple ways.

Thinking in Systems is a concise and crucial book offering insight for problem solving on scales ranging from the personal to the global. Edited by the Sustainability Institute’s Diana Wright, this essential primer brings systems thinking out of the realm of computers and equations and into the tangible world, showing readers how to develop the systems-thinking skills that thought leaders across the globe consider critical for 21st-century life.

Some of the biggest problems facing the world—war, hunger, poverty, and environmental degradation—are essentially system failures. They cannot be solved by fixing one piece in isolation from the others, because even seemingly minor details have enormous power to undermine the best efforts of too-narrow thinking.

General Direction

This past week brought me back to New York for two reasons: I was here to attend my Schengen visa interview ahead of my upcoming trip to Europe, while also taking advantage of the opportunity to reconnect with former colleagues and attend discussions taking place alongside the United Nations High-Level Political Forum on Sustainable Development.

My first stop was, of course: Sweet Linda – a new bar by one of my best friends, Aury.

Sweet Linda

As has often been the case throughout my career, moving between embassies, conference venues, meetings and the United Nations Headquarters meant covering much of the city on foot. Walking is often [and perhaps ironically] the fastest way to travel through Manhattan, and after enough journeys, one begins to notice patterns that are difficult to appreciate from inside a taxi.

Episode 11: Lessons Conversation

#LessonsWeekly

[Listen to the Podcast for Context, or Keep Reading Below]

• Direction should remain stable even when the route changes: Long-term objectives provide coherence, while flexibility in execution allows institutions to respond intelligently to new information.
• Movement generates evidence: Some forms of knowledge can only be produced through implementation rather than planning.
• Optimisation is an iterative process: Under conditions of uncertainty, better decisions emerge through successive learning rather than perfect foresight.
• Information has become cheaper than adaptation: Many institutions struggle not because they lack evidence, but because they lack mechanisms for acting on it.
• Strategy and implementation serve different purposes: Strategy establishes direction; implementation determines the most effective path towards it.
• Continuous evidence changes the nature of planning: When information is constantly updated, planning must become an ongoing process rather than a one-time event.
• Institutional capability matters more than institutional certainty: Resilient organisations are defined by their capacity to adapt, not by their ability to predict.
• Technology changes decision-making by lowering the cost of learning: Its greatest value lies not in automation itself but in improving the speed and quality of institutional judgement.
• Uncertainty is a characteristic of complex systems, not a planning failure: The objective is to manage uncertainty, not eliminate it.
• Feedback is a strategic resource: Systems that incorporate evidence continuously are better positioned to improve their performance over time.
• Static plans perform poorly in dynamic environments: Institutions designed for adaptation are more resilient than those designed solely for compliance.
• Good systems minimise the cost of changing course: Effective institutions make adjustment possible without losing strategic coherence.
• Development is better understood as navigation than prediction: Progress depends on maintaining direction while continually refining the route.
• Learning is an institutional capability: The speed at which organisations convert evidence into action increasingly determines their effectiveness.
• The quality of a strategy is ultimately revealed through its ability to support adaptation: A strategy that cannot accommodate new evidence becomes less valuable as conditions change.

A Perfect Grid

Suppose I need to travel from 44th Street and 1st Avenue to 56th Street and 7th Avenue.

There are numerous possible routes, each differing by only a few minutes. I have never found it worthwhile to stand at the starting point trying to calculate the optimal path. Instead, I clarify what the general direction is, and I simply begin moving towards the destination. If the avenues are flowing, I head north. If the cross streets are moving more freely, I turn west. Every intersection provides new information. A red light may encourage another block north before crossing. A series of green lights may make an earlier turn more efficient than I had anticipated. The route is not predetermined. It emerges through continuous adjustment.

I got to reflect on this: something I do quite intrinsically, yet seem more efficient than how some of my friends move in NY. For me, the optimisation does not occur before movement begins; it occurs because movement has already begun. Every block travelled generates additional information that was unavailable one block earlier. Every decision improves upon the previous one because it incorporates new evidence. Standing still may produce the appearance of careful planning, but it produces very little new information. Movement, by contrast, is itself a mechanism for learning.

Development Practice

Development practice has traditionally approached planning in the opposite direction. We frequently assume that successful implementation depends upon producing sufficiently detailed strategies before implementation begins. National development plans, sector strategies, logical frameworks, theories of change and implementation roadmaps are often expected to anticipate the majority of future decisions in advance. The quality of planning is therefore judged by the completeness of the document rather than by the capability of the institution responsible for adapting it. The implicit assumption is that uncertainty can largely be resolved before action starts.

That assumption has become increasingly difficult to defend.

The Fourth Industrial Revolution has fundamentally changed the economics of information. Artificial intelligence can synthesise volumes of evidence that previously required months of analysis. Satellite imagery provides near real-time observations of agricultural production, infrastructure and environmental conditions. Sensors generate continuous operational data across supply chains and public infrastructure. Predictive models identify emerging patterns before they become visible through conventional reporting systems. Information that once arrived periodically is now available continuously, and analytical capacity that was once scarce has become increasingly accessible.

Ironically, many institutions continue to organise decision-making as though these changes have never occurred. Strategies are still often treated as fixed products rather than adaptive instruments. Monitoring remains something conducted after implementation rather than during it. Evaluation is frequently positioned as a retrospective exercise instead of an input into ongoing decision-making. We have invested heavily in improving our ability to produce evidence while paying comparatively less attention to improving our ability to use it. As a result, faster information does not always translate into faster learning.

This distinction becomes increasingly important as governments confront more complex problems. Climate adaptation, demographic change, artificial intelligence, food security and urbanisation are characterised by uncertainty that cannot be eliminated through additional planning alone. These are dynamic systems in which conditions continue changing during implementation. Under such circumstances, the objective cannot reasonably be to identify a perfect sequence of actions in advance. The objective is to build institutions capable of adjusting intelligently as conditions evolve without losing sight of their long-term direction.

This is one of the ideas explored throughout A New Normal. The central challenge facing many institutions is no longer a shortage of evidence. Increasingly, it is a shortage of adaptive capability. We know far more about many development problems than previous generations did. The constraint is often institutional rather than informational. Organisations struggle not because evidence is unavailable, but because their structures, incentives and decision-making processes make continuous adaptation difficult. The problem therefore shifts from producing better knowledge to designing better systems for acting upon it.

Seen from this perspective, strategy serves a different purpose than it traditionally has. Its role is not to prescribe every future decision but to establish direction. Evidence provides feedback on whether movement remains aligned with that direction. Technology reduces the cost of acquiring and processing that feedback. Implementation becomes a continuous process of navigation rather than the mechanical execution of a predetermined script. The destination remains stable while the route remains open to revision.

This way of thinking also changes how we understand optimisation. Optimisation is often treated as an activity that precedes implementation: enough analysis, enough consultation and enough modelling should eventually reveal the best possible course of action. Yet optimisation under uncertainty rarely functions that way. It is iterative rather than static. Decisions improve because learning accumulates over time. Waiting indefinitely for perfect information may produce increasingly sophisticated plans, but it also delays the acquisition of the only evidence that implementation itself can generate.

Walking through Manhattan is, of course, a trivial example. No comparison between urban navigation and national development should be taken literally. Yet simple systems often reveal larger principles. The city works not because uncertainty has been eliminated, but because its design allows people to continue making progress despite uncertainty. Each intersection creates another opportunity to incorporate new information without abandoning the overall destination. Good systems rarely eliminate uncertainty. They reduce the cost of responding to it.

That may ultimately become one of the defining institutional questions of the Fourth Industrial Revolution. As information becomes faster, cheaper and more abundant, competitive advantage will depend less on possessing knowledge than on converting knowledge into better decisions. Countries, organisations and communities that learn continuously are likely to outperform those that continue relying on static plans developed for a slower world. Direction remains indispensable, but direction alone is insufficient. The capacity to optimise while moving may prove to be one of the most valuable capabilities modern institutions can develop.

Read my Published Works:

If you’d like to go deeper into my journey — from Malawi, through the United Nations and Microsoft to now building my own companies in Detroit, you can find it in my books.

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