Doubt-driven decision making: navigating negative space
In our increasingly data-rich world, we often rely on empirical evidence for decision making. While data-driven decision making is valuable, the available data may not be enough for effective decisions in complex adaptive systems where outcomes are emergent and unpredictable. Such systems require that decisions are taken step by step, taking into consideration the changes and new insights that accompany each step. This is not only defensive. By actively observing the environment, we discover opportunities that we would have missed when marching blindly towards a predetermined end state.
Negative space
We could call this doubt-driven decision making: embracing uncertainty and the absence of data. This method recognizes that in complex scenarios, the absence of data ("negative space") is as crucial as its presence.
Key principles:
Frameworks
This concept is not new. You see this in the Cynefin sense-making framework that encourages you to think about the nature of your system, in particular its (lack of) linear causality, and to choose your actions appropriately. Toyota Kata also supports this by establishing multiple intermediate target conditions (and therefore assuming some linear causality) before achieving the desired outcomes. The OODA loop [1] is another example, that emphasizes continuous observation and orientation in rapidly changing circumstances.
OODA loop
The OODA loop is often contrasted with the PDCA cycle that is used in more stable situations. I like the distinction between Observe and Orient (that are in PDCA's Plan). At first glance, however, PDCA's Check and Act seem to be missing in the OODA loop. This effectiveness check is implicit and occurs through the continuous cycling of the loop itself. After the Act step, the loop immediately returns to Observe. In this new Observe cycle, the results of the previous action are inherently part of what's being observed. Orient then interprets these observations, including the outcomes of the previous action, leading to the next Decide and Act steps. So, in the OODA loop, the effectiveness check is integrated into the continuous, rapid cycling of the loop rather than being a distinct step. Learning is also implicit in the OODA loop. I have made Check and Learn explicit in the diagram below. I have also depicted Observe as continuous, reflecting the need to monitor whether the situation has changed such that refinement is needed.
Ma
Interestingly, doubt-driven decision making mirrors the Japanese aesthetic principle of "Ma" (間) - the meaningful empty space in art and life. This includes architecture, music, and even social interactions, where a pause in conversation is meaningful rather than embarrassing. In decision making, we navigate or "mavigate" through the unknown, treating uncertainty as an opportunity for discovery and innovation.
Summary
By recognizing and adopting doubt-driven decision making, we cultivate adaptability, mindfulness, and resilience in the face of uncertainty. It's not about abandoning data, but complementing it with a nuanced appreciation of the unknown "negative space".
Notes
[1] The Observe and Orient steps in OODA (the others are Decide and Act) remind me of something that I learned in a Project Management course at the start of my career. Before you take a decision, make a distinction between gathering the facts and forming judgements about them. This often makes discussions more effective.