Illusion of control: (institutional) artifacts of certainty
Weeknote by Millie Begovic
‘We do not rise to the level of our goals but fall to the level of our systems,’ James Clear
We had a visit this past week from colleagues at UNDP Ghana and the Mastercard Foundation (MF) — they are kicking off a partnership to learn about conditions that help empower young people & build their agency to pursue livelihood opportunities.
The key thread in our conversations were some very early insights from this work that point to a tension between the more mainstream ways of working in public & development sector (premised on stability & predictability therefore doing things ‘the way we’ve done them all along’) versus how life happens (messy, unpredictable, and constantly shape shifting).
Borrowing a page from Vaughn Tan’s work, one could say that the thread really focused on what would an institutional structure built for the world of uncertainty vs. risk look like. For example, the MF has tested various hacks to move beyond the space of the obvious — their Employee Innovation Fund enables its staff to look for organizations, individuals, business models whose work doesn’t fit the established ‘buckets’ (eg. governance, employment) but instead operates in the ’in between’ spaces (eg. trust, role of grandmoms in youth driven innovation).
So, we went down the rabbit hole in mapping out different institutional responses that tend to provide an illusion of control versus those that take constant change as a default.
Risk/control: Objective vs. Uncertainty/emergence: Intent
Declaring a preferred destination or a clear goal has an air of control & power to it — it signals we know exactly what we want (eg. we will reduce the time it takes to get a drivers license by 30%). Starting with a sense of direction on the other hand says we know where we’re going but leaves decisions about how to get there open (eg. we want to rethink mobility to make cars redundant). In doing so, it helps prevent lock ins to a single course of action, it builds a consensus through creating a space for exploration & co-creation, and it generates more possibilities and choices an organization can take as the context changes. The intent though calls for very different ways of managing the journey, so we come to the next set of artifacts:
Risk/control: KPIs & log frames vs Uncertainty/emergence: Sensemaking
American writer Doctorow once said that writing a novel ‘is like driving a car at night — you can only see as far as your headlights, but you can still make the whole trip that way.’ You can’t know all the landmarks you might pass on the way (read: KPIs) or parts of the road that might require a detour (read: risks) so instead you focus is on navigating, collectively making sense of the context on the go and continually generating new ways of acting.
Vaughn’s work suggests that just an acknowledgment that we’re in a situation of ‘not knowing’ could increase the intensity of other senses (think about the last time you drove in a fog) & create the space for using making decisions in a different way — iterative & rapid loop of observing, orienting, designing & acting.
Doing this is not easy for organizations structured around functions (modelling, statistics, scientific advice, communications) or departments (health, energy, transport). The functional or departmental siloes make synthesis very difficult & with it the organizational ability to ‘see’ the type of issues that fall ‘in between’ them. At UNDP we deploy a sensemaking protocol for this very reason — a capability for continual synthesis of many different fragments of information into new micro decisions.
Risk/control: Lessons learned, best practices vs Uncertainty/emergence: Dynamic management
‘It is not just that we do not know what will happen. We often do not even know the kinds of things that might happen,’ Radical Uncertainty, Decision Making for an Unknowable World
Whether you refer to them as lessons learned, best practices or inductive/deductive reasoning, the underlying logic remains the same — past is a good predictor of what will happen and therefore offers a sense of control & empowerment in guiding our decisions today. Dynamic management on the other hand recognizes that existing playbook of policy choices is not a good match with a tackling declining citizen trust in institutions or youth agency.
Instead, it calls for a focus on constant churning of answers to a seemingly banal question ‘what is going on here?’ And it does so by a continuous effort to understand connections (among people, organizations, places, events, sectors), anticipate what they might evolve into and on those bases generate constant supply of new interventions.
Geoff Mulgan & Giulio Quaggiotto write about building policy steering rooms (we’re creating a version of our won in UNDP) with the intention of continually synthesizing information into intelligence & more options to act. We collaborated with the Center for Performance Studies that synthesizes learnings across disciplines to help navigate uncertainty in dynamic ways — cardiothoracic surgeons learn from textile experts on how to manipulate delicate materials and development executives learn from forensic investigators on how to surface underlying dynamics that are often unseen.
Consistent with this, research shows that the organization’s ability to quickly reallocate resources across different parts of business in response to emerging opportunities & risks is a single largest driving of growth — but when it happens, it does so either as an exception or a response to a crises, not as an organization default.
Risk/control: Cost-Benefit analysis, vs. Uncertainty/emergence: Risk-Opportunity analysis
Adding up costs and benefits assumes they can be predicted and quantifiable. But much of those associated with, for example, a just & circular transition are impossible to know with confidence — from speed of how the new tech develops & its impact on labor market, to business models, supply chains & societal health. Converting the impact of these variables into a single metric (money) at best biases toward inaction and at worst undermines trust & robust political decision making.
Instead, organizations like the Economics of Energy Innovation & System Transition do risk-opportunity analysis- mapping various variables especially in cases when we can’t put a number on them, comparing expected outcomes of policies & dynamic changes in the economy (read: feedback loops that accelerate or hinder change). The dynamism of these efforts (compared to cost benefit analysis) are seen as more coherent with the way context changes & able to build agency of decision makers by continually feeding them with a supply of policy options to choose from.
Risk/control: Single Asset investment vs. Uncertainty/emergence: System-driven finance
Dominant investment decisions continue to be driven by a series of ‘control’ artifacts — from a narrow concept of impact (financial revenues) and inadequate accounting of primary and secondary benefits (extraction of minerals & air pollution) from individual projects (and their interconnection), to frequent underestimation of strategic risks of action & inaction.
This makes it very difficult to deploy capital in a way that maximizes alignment between different constituents & changes the rules of the game. For example, transforming a mobility system of a city might require reinforcing its power distribution grid, adding renewable energy generation & building vehicle charging infrastructure (largely optimizing the existing system) while at the same time pursuing urban planning decisions that reduce a need for individual mobility options (changing the system). Tackling the puzzle of transforming the city’s mobility infrastructure is just about impossible if investments transact based on individual pieces rather than looking at the system as a whole.
There were a few other risk vs. uncertainty ‘artifacts’ we discussed that I may leave for another post. For example, a difference between industrial type scaling premised on carrying ‘solutions’ from one context to another versus scaling learning, relationships & speed of adaptation that helps the organization navigate the unknown. We also got hung up on differences between annual staff performance evaluations versus open roles that evolve in lock step with how the context changes — and a very different type of accountability structures that grow out of two different approaches to human resource & talent development.
Both indicate very different mindsets & relationship to the unknown. Juha Leppanen from Demos reminds us that institutions can be understood as mere encoders of collective actions. Viewed through this lens, we seem to be witnessing nascent efforts to grow a new stock of maybe not outright new institutions but ways of acting that might be a better fit for the world of ‘not knowing.’ A lot hinges on our ability to do so quickly.
*With thanks to Obeng Ennin, Mastercard Foundation lead of innovation & digital economy, Sukhrob Khoshmukhamedov & Allen Anie, respectively Deputy Resident Representative & head of experimentation at the UNDP Ghana CO. Also thanks Thea Snow for the inspiration with her Certainty Artifacts piece, Giulio Quaggiotto & Sir Geoff Mulgan for different type of spaces for collective decision making (policy steering rooms), Vaughn Tan for his work on not-knowing & CHÔRA Foundation for being a fantastic intellectual sparing partner on our journey
