Dominic Hofstetter
Jul 7 · 11 min read
A section of the Peutinger Table, an illustrated itinerarium showing the layout of the road network of the Roman Empire. It is hypothesized that the map is based on a template engraved in a marble plate that had been on display in Ancient Rome two millennia ago. (Credit: Wikipedia)

This is the first of a series of three articles exploring innovation in complex adaptive systems. Part II introduces a new innovation model capable of driving directional change in complex adaptive systems. Part III articulates the contours of a systemic investment logic.

A Story from Antiquity

Had you lived as a traveling salesman in the first century AD, you might have started preparations for your next trip with a visit to Porticus Vipsania. Located in the heart of Ancient Rome, this majestic building housed many magnificent statues and works of art. Yet one particular exhibit would have occupied your attention: an engraved marble plate.

It might not have been the most elaborate item, perhaps; yet it was useful in the extreme. For on this plate were depicted all the public roads stretching right across the Roman Empire. Close study would reveal what lay on the road ahead: the size and number of settlements, the distances between them, the quickest routes, the local topography. Two millennia before Google Maps, this marble plate was the most sophisticated tool available for planning your journey across Europe.

Visual representations of places, roads, and waterways are known as itineraria. Rising to utility and popularity in Antiquity, itineraria are similar to maps but differ in one important aspect: they prioritize practical usefulness over geographic accuracy. What is the distance between Pisa and Bologna? How long does it take to get there? Where might I find a tavern for shelter and food? These are the kinds of pragmatic, down-to-earth questions that itineraria set out to answer.

For all their usefulness as a tool of navigation, itineraria possessed a value proposition that transcended the mere practicalities of travel. Itineraria told stories — stories of foreign lands, of far-away points of interest, of unknown roadways. And through such story-telling, they succeeded at stirring people’s deep-seated sense of adventure. They tapped into the primeval nomadism that lies deep within us all. They lit the imaginations of those seeking an escape from the confines of home — and provided a key to the door. At their core, itineraria held the promise of a better future.

Perhaps it is because of this evocative power that our world is so in love with itineraria today; that we have adopted their underlying mental model in fields outside of travel, including science, engineering, business, policy-making, and social and economic development. In these and other fields, we know itineraria under their modern name: roadmaps.

Roadmaps: Today’s Itineraria

Fast-forward many centuries and the world today is blanketed with roadmaps covering all conceivable territory. Except, we no longer use them to navigate geographies. The roadmaps we have fallen in love with are made up of strategies and plans, which — when stitched together — present a vision of the future and a set of recommendations on how to get there. Think of them as a type of planning instrument, a development roadmap or a roadmap for change.

Roadmaps like these exist for addressing the most pressing and tangible problems of our time: ending global hunger; eradicating tuberculosis and cholera; promoting the economic empowerment of women; and transforming the global energy system, to name but a few. There are also roadmaps for more specific, bounded challenges, such as evidence-based clinical practice, income security, the digital transformation of organizations, antimicrobial resistance, fusion energy, impact investing, single-use plastics, and healthy ageing. Soon, there will even be a roadmap for finding life on exoplanets.

Several reasons explain the extraordinary popularity of roadmaps as a tool for inspiring and guiding change. They provide a compelling vision of a future state of the world; one that is desirable and noble and elicits our sense of adventure and courage. They break a long journey down into manageable milestones, providing changemakers with a framework for managing actions and tracking progress. They present evidence in the form of studies, charts, and tables to convey a level of scientific rigor, thereby allowing funders, policy-makers, and executives to use them as a decision-making tool and as a mechanism to defer accountability.

What all of these roadmaps have in common is a vision of a goal to be reached and a hypothesis of how to get there. At their core, these roadmaps thus resemble itineraria. But there are some crucial differences. Whereas itineraria present real places in physical space, roadmaps for change lead to imagined destinations. And while itineraria offer descriptive logistical information (think: “Highway 1 takes you from San Francisco to San Diego”), roadmaps offer prescriptive advice on how a destination might be reached (think: “First, invent the battery; then, install charging stations; then, introduce tax incentives; lastly, watch electric vehicles replace fossil fuel-powered cars.”)

Roadmaps for change are thus mere hypotheses, in both journey and destination. They represent the aspirations, desires, and hopes of their creators while putting forward a step-by-step action plan for how these objectives might be achieved. Herein lies the essence of the Roadmap Fallacy: a tool originally developed to represent existing realities doesn’t work well as a mental model for creating new realities.

Why Roadmaps Fail

Roadmaps so often fail because their inherent characteristics sit at odds with the properties of the systems they seek to change.

Most roadmaps suggest development pathways that are linear and sequential. The underlying logic is that outcomes serve as prerequisites for other outcomes, according to the logic: A leads to B, B leads to C. Just consider the stereotypical approach to extreme poverty alleviation: “First, eradicate hunger and disease; then, educate people and create markets; finally, watch poverty decline and affluence emerge.” Simplistic as this description admittedly is, current practice often emulates its linear and sequential logic.

Further, most roadmaps are deterministic. They suggest that the cause-and-effect relationships within the system they address are either known or knowable. Deterministic approaches make assumptions about how individual elements influence, control, or trigger other elements in the same system. Similarly, they pretend to understand how different actors in the system can be incentivized and motivated to behave in certain ways. For instance: “Smallholder farmers in developing countries remain poor because they don’t know how to market their products. So, if we provide business training and access to export markets, they will become successful entrepreneurs and lift themselves out of poverty.” Or: “Childbirth prevents women from becoming fairly represented in corporate boardrooms. So, if we establish quotas, we can boost the share of senior female executives.”

Finally, roadmaps tend to assume that the context in which the problem plays out is static. They assume that the world will not change or, if it does, that it will change in an incremental way — so that the roadmap’s basic assumptions hold true for the entire planning period. Roadmaps thus do a lousy job of anticipating and accommodating non-linear, disruptive change. Nor do they have much capacity to respond to — let alone engage — randomness and serendipity.

The reason why roadmaps fare so poorly in effecting change is that the problems they seek to address occur in a world of complex adaptive systems. In these systems, nobody can be sure what the constituent elements of the system are and how they relate to and interact with each other. Such systems self-organize. They constantly change in response to internal pressures or external influences. Cause and effect can only be determined with hindsight. And dynamics of change are often characterized by unknown feedback loops.

Complex adaptive systems never reach optimality. Indeed, they never reach any sort of steady state but instead continue to evolve and exhibit new forms of emergent behavior — often in a non-linear and discontinuous fashion. Economies, immune systems, brains, and natural ecosystems are all complex adaptive systems, as are social constructs such as nation-states, families, and companies.

Roadmaps assume that the world consists of complicated problems that we can deconstruct, study, and fix by decree. Yet if the world is a complex adaptive system and consists of complex adaptive sub-systems, is it surprising that linear, deterministic, and static tools so often fail?

Consider the spectacular case of Motorola. Once the world’s biggest seller of mobile phones, Motorola started using technology roadmapping as part of its strategic planning process as far back as the 1980s. Over the years, the tool became increasingly important, and the company used it not only to understand future product needs but also to organize forecasting processes. In 2004, Motorola emphatically declared that roadmapping was ‘valuable’ and ‘working‘. Yet its results would, quickly, suggest otherwise. Motorola’s mobile phone market share plummeted from a healthy 23% in 2006 to a measly 6% in 2009. Following multi-billion losses and mass layoffs, the company split in 2011 and eventually sold its failing mobile phone business to Google.

Motorola’s story powerfully illustrates that consumer markets are complex adaptive systems that can exhibit non-linear dynamics. With hindsight, we can confidently say that the world at the time was not in need of a better flip-phone. Looking back, it is obvious that consumers were craving for something new — and that Apple was waiting in the wings with its breakthrough iPhone to give them just that. This just wasn’t clear at the time.

Motorola launched the Rizr Z8 in 2007 — the same year Apple introduced the iPhone. Technology roadmapping might work for developing a new phone (a complicated problem) but not for anticipating consumer preferences (a complex problem).

Exceptions Confirming the Rule

History is not without examples of successful roadmaps. The Manhattan Project gave us the atomic bomb. The Apollo Program succeeded at landing a human being on the Moon and returning that person safely to Earth. And the Montreal Protocol brought together the international community to protect the ozone layer by phasing out ozone-depleting substances.

But notice how the first two examples — while undoubtedly bold and ambitious — were essentially technical challenges. In the first case, the task was to build a bomb and develop a model for delivering it. In the second, the mission was to design a technology system and establish a set of operating protocols suitable for space travel. Tricky problems, without question. But they were fundamentally complicated in character — not complex. As such, it was possible to arrive at solutions with technical expertise. In addition, both efforts had significant backing from the military-industrial complex, which few of the gravest challenges of the 21st century enjoy at the same scale.

The case is different for the Montreal Protocol. In this instance, success was facilitated by the fact that the problem was clearly understood and bounded. It also helped that alternative technologies were available and that economic gains could be generated by the incumbent industry leaders. This combination of favorable conditions is rare — so far we have failed to replicate them in many other international agreements, particularly in the realm of environmental protection (think: climate change and the UNFCCC process).

Better Roadmaps

There is growing recognition of the structural mismatch between roadmaps as a planning tool on the one hand and the complex adaptive nature of our world on the other. Academics and practitioners have started to adapt the tool of roadmapping accordingly. Yet most of these attempts set out to increase our understanding of how complex adaptive systems behave. They argue that if we know more about the system, we can craft more effective roadmaps.

The epistemological starting point thus remains the same: systems can be understood, if only we study them more deeply. What’s driving these attempts is our innate desire to elucidate mystery and make sense of the world. But the world remains unpredictable and chaotic and non-linear, no matter how many charts and tables we include in our roadmaps and how many sources we cite. Sophistication only leads to pseudo-certainty, and while this might be enough to allow decision-makers to defer accountability, it does not bring us closer to our goals.

Why It Matters

Roadmaps that are poorly designed or deployed will inevitably fail, wasting time and resources. The UK Government wasted 168 million pounds on its carbon capture and storage (CCS) roadmap before abandoning its plan to spend up to 1 billion pounds on demonstrating the technology’s viability.

Poor roadmapping can also crowd out more promising approaches, especially if key stakeholders start to converge on a single plan. Take the Paris Agreement. Touted as a “historic international agreement”, the voluntary pledges submitted to date set the world on track for a three-degree increase of global average temperatures. This is double the Agreement’s stated goal of limiting global warming to “well below 1.5 degrees”. But because it has been so long in the making and so hard to pull off, the Agreement has bred complacency — policy-makers feel able to rest on their laurels and postpone hard choices to reduce greenhouse gas emissions.

Officials celebrating the adoption of the Paris Agreement on 12 December 2015. The historic success has bred such complacency that the world is still far off track to reach the Agreement’s goals. (Credit: UNFCCC)

Finally, repeated failures to achieve traction through roadmapping can breed cynicism and stifle crucial support in the long-run. Just consider how hydrogen fuel cell companies struggle to attract new investment and policy support despite working on a potentially critical building block of a sustainable energy system. This is partly because they have eroded hundreds of millions in risk capital in the past decade in the wake of a hype that was fueled by overly optimistic roadmaps.

Re-imagining Roadmapping

For roadmaps to remain useful in addressing the most daunting challenges of our time, it is necessary to re-imagine how we develop and employ them.

The starting point is to let go of our desire to control the evolution of complex adaptive systems. Instead, we must learn how to embrace uncertainty, unpredictability, and serendipity. We need to accept these as normal features — not bugs — of the world we live in. It is also essential to resist the temptation to promise outcomes, predict results, or prescribe interventions on the basis of poorly understood causal relationships.

Instead, the most promising way to use roadmaps is to leverage their evocative power of narration. As with itineraria of old, roadmaps tell a story of what the future might hold. In doing so, they speak to our fascination with the new, kindle our sense of adventure, give us hope, and inspire action.

The UN’s Sustainable Development Goals (SDGs) provide a case in point. Although technically and legally toothless, they tell a story of solidarity and unity while also evoking a more just, equitable, and sustainable vision of the world. The SDGs are relatively ineffective as a tool for driving systems change. But as a mechanism for convening stakeholders, influence political dialogue, and inspire action, their power is extraordinary.

The United Nations Sustainable Development Goals (SGDs) are technically and legally toothless but extraordinarily powerful in convening stakeholders and inspiring action. (Credit: United Nations)

Narration can also help us sharpen our intuition as to what a complex adaptive system might look like. Consider the approach of scenario analysis pioneered by the oil and gas company Shell. By imagining “alternative views of the future”, the Shell Scenarios provide insights into what the future might look like, including through remote possibilities and unlikely events. Or watch the Emmy-winning Netflix series Black Mirror. Each episode opens a fictional window into a future where a specific technological innovation dominantly shapes the social, political, economic and technical context of its time. Such fictional narratives succeed at generating insight and triggering action. This is partly because they are logically coherent and relatable, and partly because of the sense of urgency they instill in us.

Once we have a sense of the possible future states of the world, we can start intervening in the systems in a non-deterministic spirit.


When Christopher Columbus set out to discover a westward passage to India, the itineraria at his disposal put the distance between the Canary Islands and Japan at about 3,000 miles. As we know today, the true distance is more than six times that estimate. The discrepancy between his “roadmap” and reality amounted to the difference between eternal glory and death. Had Columbus and his crew not got lucky and bumped into the American continent, they would have met with a very different fate.

To solve the most intricate challenges of humanity, we cannot rely on luck. Roadmaps will have a role to play — albeit a limited one. What we need is a different approach; one capable of instigating and catalyzing change in complex adaptive systems. Climate-KIC, where I work, has set out to develop and practice such an approach. You can read about it in Part II of this series.

In Search of Leverage

A collection of stories exploring the most powerful levers for addressing climate change

Dominic Hofstetter

Written by

I write to inform, inspire, and trigger new strategies for tackling climate change.

In Search of Leverage

A collection of stories exploring the most powerful levers for addressing climate change

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