The Choice-of-Future Problem in Systemic Investing (Part I): Introduction
This is the first article in a three-part series on the Choice-of-Future Problem in systemic investing. Part II presents a framework for working through the problem and Part III discusses special topics that arise from it. These three parts are meant to be read sequentially, as each builds on the preceding one.
Systemic investing is directional investing. Its purpose is to help human systems evolve toward a future of a particular quality, such as environmental sustainability and social equity.
From this intent emerges an interesting problem: Which future, exactly, should investors choose to foster?
At the TransCap Initiative, we recently encountered this problem in our prototype on mobility in Switzerland. The project’s objective is “to catalyze the net-zero transition of the Swiss personal transportation system”. In pursuit of this goal, we chose to focus on accelerating the uptake of all-electric vehicles. But we could have also decided to promote technologies running on other energy carriers, such as hydrogen or synthetic hydrocarbons, as these also tick the net-zero box.
Which version of the future to champion matters because not all possible futures are equally desirable, nor will the benefits, costs, and risks be equally distributed across different parts of society. Moreover, betting on one future could mean losing money when another future becomes dominant.
So how should investors go about choosing which future to support?
In search of answers, we cannot look to the traditional world of investing. Not only are traditional investors agnostic about the direction in which the economy evolves as long as it grows. But they also tend to prefer diversification over concentration to manage risk. Both factors together mean that traditional investors do not have to take a stance in the same way purpose-driven investing calls for.
This article series explores the nature of what we call the Choice-of-Future Problem in systemic investing and presents a theoretical framework for how to address it.
The Basics of Futuring
Before we delve in, we must first introduce a few key concepts from the fields of futuring and innovation studies. These are critical to understanding the nature of the problem and the design of our theoretical framework.
The Three Axioms of Futuring
Futuring is the field of thinking about, imagining, and planning for the future. Recalling its three axioms is essential for understanding the root of the Choice-of-Future Problem:
- The future is not predetermined — there is an indefinite number of possible futures.
- The future is not predictable — actions in service of the future happen in the context of fundamental uncertainty.
- Future outcomes can be influenced by our choices in the present — our actions and inactions influence the shape of the future that will eventuate.
What these axioms imply is that those concerned with shaping the future (singular) must choose which one of the many possible futures (plural) to champion.
What’s On the Menu?
There are two tools from futuring that are helpful for categorizing different possible futures and thus making sense of the options on the table.
The first is the Three Horizons Model, which differentiates between futures that are extrapolations of the system dominating the present (Horizon 1), futures that are the ambitious visions toward which transformative action should be oriented (Horizon 3), and patterns of transition activities that act as bridges between the two (Horizon 2).
The other is the Futures Cone, which suggests that a taxonomy of potential futures can be represented as a cone diagram with different classes. Possible futures are all futures we can imagine — those that might happen, no matter how far-fetched or unlikely, and even if they require knowledge we currently do not possess. Plausible futures are those that could conceivably happen according to our current knowledge. Probable futures are those likely to happen and stem in part from the continuance of current trends. And preferable futures are those that are desirable, the ones we want to happen.
What is important to note is that whereas the first three classes of the Futures Cone are concerned with objective probabilities (what could be), the last one is concerned with a value judgment (what should be). So preferable futures can lie in any of the three aforementioned classes, or they can span multiple of them.
The last concept we need to introduce is that of techno-economic paradigms (TEPs). It was coined by Carlota Perez, an economist who studied “great surges of development” that have historically led to wholesale shifts not only in the technology landscape but also in policy and society. The advents of electricity, railways, mass production, the steam engine, and the Internet are all examples of technological revolutions following the TEP logic.
Shifting from an incumbent TEP (such as a hydrocarbon-based transportation system) to a new TEP (such as electric mobility) is one way to define systems transformation. The key here is that TEPs represent dominant system configurations, or what Perez calls “common sense economic logics”. So different future TEPs might stand in competition with each other, and this competition may lead one TEP to crowd out all others.
For instance, both hydrogen-based and electricity-based technology platforms could produce environmentally safe and socially just outcomes in a country’s mobility system. But the way in which that mobility system would be configured — its physical infrastructure, supply chain designs, business models, and consumer behavior — would be significantly different in these two versions of the future, to the point where it might be unable to accommodate both technology platforms simultaneously.
With these three concepts — Three Horizons, Futures Cone, and Techno-Economic Paradigms — in hand, we can now reflect on the nature of our problem.
The Nature of the Choice-of-Future Problem
It is the combination of 5 circumstances that gives rise to the Choice-of-Future Problem. These circumstances can combine in different ways, and thus our problem can express itself in variations, as we will see later.
1) Need for Intent Setting
As in all impact investing, systemic investors must take a stance on which possible future to support. This is different from traditional investing, whose imperative to optimize financial risk/return ratios leads investors to be agnostic about which version of the future materializes so long as the economy grows and asset prices rise. In contrast, whoever seeks to catalyze systemic change must decide what kind of future to build.
2) Futuristic Pluralism
Intent statements in systems change work are often very broad, articulated as landing zones rather than landing spots. Consider Kate Raworth’s Doughnut Economics, whose definition of humanity’s defining challenge — to create “an environmentally safe and socially just space in which humanity can thrive” — is specific enough to assess what is in and what is not, yet broad enough to accommodate different versions of the future.
And because multiple versions of the future (or, multiple TEPs) can meet the definitions of a landing zone, and because these versions may have wildly different and possibly mutually exclusive configurations, systemic investors must articulate intent statements that are quite specific.
3) TEP Lock-In
An investor’s initial investments may lead to a situation of lock-in into a specific TEP, and if another TEP becomes dominant in the long run, those investments may perform poorly. For instance, investors wanting to champion hydrogen-based mobility will almost certainly make investments in the hydrogen supply chain, for instance in the development of electrolysis technology. Much of this investment could be stranded should electric vehicles prevail as the dominant transportation technology of the future.
4) Uncertainty and Probability/Preferability Trade-Offs
It cannot always be known which, in a set of competing futures, is the most probable or most desirable one. And even if it is known — or can be forecast to a reasonably high degree — sometimes the most probable future is the least desirable one, creating a trade-off between financial risk and impact potential.
5) Do-No-Harm Doctrine
We believe that any purpose-driven investor should observe the do-no-harm doctrine. (NB: This is, obviously, a normative statement, but we believe most impact investors would agree.) Adhering to this doctrine means that choices can be restricted if there is a large degree of uncertainty about outcomes.
Contextualizing the Problem
To make it easier to comprehend our proposition for how to deal with the Choice-of-Future Problem, we have created a set of hypothetical examples to illustrate how different versions of the future can differ in terms of probability and preferability.
Consider a systemic investor interested in transforming the mobility system of her home country. The investor conducts a systems analysis with a foresight component and identifies a set of plausible futures which she makes sense of using the Three Horizons framework.
Here is what she gets:
- i) Extrapolated Status Quo (H1): Drive-Your-Own-Car remains the dominant paradigm in personal transportation. The internal combustion engine (ICE) continues to be the most popular technology platform, albeit with improved tank-to-wheel energy conversion efficiency. Gasoline and diesel remain the dominant fuels but have slightly better well-to-tank environmental footprints than today’s options, thanks to AI-enabled leak prevention in the refinement and distribution stages of the oil supply chain.
- ii) Self-Owned Electric Mobility (H2): All-electric vehicles replace ICE vehicles as the dominant technology platform. These vehicles are powered mainly by wind and solar energy, and charging takes place primarily at home. Individual car ownership remains the most popular business model, and cities continue to be designed around the needs of the personal car.
- iii) Self-Owned Hydrogen Mobility (H2): Same as (ii), except that fuel-cell vehicles powered by green hydrogen are the dominant vehicle technology, and the hydrogen is provided by centralized filling stations.
- iv) 2D Mobility-on-Demand (H3): The Drive-Your-Own-Car paradigm is abandoned in favor of an AI-enabled mobility-as-a-service system. Fleets of all-electric autonomous vehicles powered by renewable electricity roam the streets, picking up passengers on demand. This greatly reduces the need for inner-city parking and lane capacity, triggering a revolution in urban planning and returning space to citizens for play, recreation, and urban farming.
- v) 3D Mobility-on-Demand (H3): Same as (iv), except that urban transportation goes to the third dimension, enabled by advances in electric aviation. It is the advent of the flying car.
What should be apparent from these examples is two things. First, their relative preferabilities differ, (broadly) increasing in ascending order. Second, their relative probabilities differ, (broadly) decreasing in ascending order. This could look something like this:
- Probability: i > ii > iii > iv; probability of (v) not determinable
- Desirability: iv > ii, iii > i; preferability of (v) not determinable
So how should our investor go about picking one over the other?
That is exactly what we are going to explore in Part II of this article series. Stay tuned.