In changing times its important to recognize both the words change and time if we want to understand systems.
On a social and economic level we’ve never seen more transformation of everyday life come or affect systems as we have with the global COVID-19 pandemic. What it provides us is an opportunity to learn, contemplate, and plan for how we affect systems change to deal with what’s transpiring.
“Changing times” comprises both change and time — two variables that are critical to system dynamics, complexity, networks — and yet are remarkably misunderstood , poorly articulated, or completely ignored in practice.
Understanding both has enormous implications for strategy and evaluation in helping us act wisely in dynamic situations.
Time: Echoes of the Past
Our understanding of, use, and experience of time shapes nearly everything we do and are symbiont with our emotions.
With something like COVID-19 time is particularly problematic. The virus has an estimated 14-day incubation period (range) where most who contract it experience symptoms in the middle of that (~5-11 days) When we see spikes in cases within a geographic area, it reflects behaviour that took place up to 14 days earlier. That means that social distancing efforts of today won’t be really felt for another two weeks.
What we are seeing on any given day is the echo of past actions and choices.
Public health professionals are pleading for action now knowing that whatever we do today won’t have much bearing on healthcare utilization and infection rates today. It’s hard to reassure people when they don’t see an obvious link between what they do (or don’t do as the case may be with social isolation) right now and what they see on the news.
What adds to this is the effect that comes from system-level effects. Within the two weeks that go by our system has already transformed because of the scale and speed of change we are seeing in the number of cases. Whatever capacity we have for dealing with the problem will be different in two weeks. (This might be more in some areas like number of hospital beds, but more in the availability of things like hand-sanitizer thanks to many creative efforts to make it).
One of the flaws in much evaluation and strategy is that we often confuse moving things with static things in our approach to understanding them. At a system level this can get more problematic when we consider the manner in which system variables influence each other at different levels and rates of speed, intensity, and amount. Heraclitis’ words on the bridge above ring true: We are not acting on the system we have data on.
It is here that we need a developmental and systems mindset. Strategy involves generating intentions and organizing actions based on assumptions about how the world works and how we seek to influence that world in the future. The only way a strategy is likely to be effective at creating influence into that future world is if we have the correct assumptions about the systems we’re working in.
This is where evaluation comes in. Evaluation is that activity that looks at what we do and assesses the effects that come from it. Taken a bit further, it is also a means of serving as a feedback mechanism in a complex system by providing real-time data on what is happening and what observable, possible, and (when possible) likely consequences of our action.
New Models of Evaluation + Strategy
To act within systems, we need frameworks of understanding the system, sensemaking what we see, and means of acting upon that information. This is the challenge for strategy (and evaluation).
Cynefin Framework. This sensemaking framework can also serve as a form of ‘diagnostic’ to help us assess what kind of environment we are in and what kind of actions are likely to produce desirable outcomes. Chris Corrigan has written on how Cynefin applies to evaluation and complexity that is worth reading. It is only by appreciating what kind of systems we are dealing with are we equipped to begin understanding time and motion effects.
Developmental Evaluation. This approach to evaluation considers the way in which programs evolve and respond to complexity. It is as much a mindset as a means to organize ways to do evaluation. DE is often considered to a means of accounting for complexity to engage in strategic learning about systems.
Design-driven Evaluation. What DE does not do is provide explicit guidance on what to do with what you learn. It is still apart of the actual intervention that is under examination — and sometimes that’s a useful thing. However, when we seek to transform systems through intervention (e.g., strategy, programs, etc.) the coupling of what we do, how we do it, and the system we do it in often requires we embed evaluation into the fabric of our efforts – not as an adjunct, but as a core. It also means tying what we learn (evaluation & sensemaking) with what we create (design). Like DE, this is less about a set of methods and tools, but a mindset and approach.
Strategy. In all three of these concepts strategy is either implicit or explicitly tied to what we monitor and what data we have. By gathering data in a manner that recognizes the time factors (e.g., system lags, delays, bottlenecks, and transforming contexts) with the motion (e.g., rate of change, amplification and dampening of effects tied to other actions) we can better anticipate what might come and design an approach to acting that can better absorb disruption and work with (or around it) while keeping some integrity to our actions.
It’s in these cases where principles-focused approaches can be further combined to our strategy and evaluation.
These are changing times. Having a mindset and vision that can better help us see what’s changing through evaluation and data and transforming that into strategy is what will help us get through them rather than let them go through us.