The Variability Dilemma
How might organizations better optimize between pragmatic and epistemic value?
"Coloring challenge!" by kevin dooley, licensed under CC BY 2.0.
To survive, every organism faces a trade off between adaptability and efficiency. Organizations, such as your family, company, government, or tennis club are no different. To be efficient, variability must be constrained. Yet variability is necessary to adapt. For an organization to be successful, they must simultaneously efficiently exploit what is currently available to them while simultaneously exploring the adjacent possible1, the realm of potentiality by which they may harvest new opportunities.
Organizations must be efficient and creative, yet not universally so. Efficiency and creativity must be yoked to what is relevant. Traditionally, organizations differentiate into teams that either focus on maintaining or on evolving the organization. Often, creative responsibilities are isolated within the executive team or possibly entrusted to specialized research and development teams. Throughout the rest of the organization, the merit of work performed is correlated with how well it conforms to predefined expectations.
In this structure, approved organizational variation is determined by the decisions of a few central players. This is similar to how prices are determined in a planned economy by a central department of bureaucrats. Market economies are widely agreed to be more efficient, fair, and responsive to changing circumstances than planned economies, so why are organizations consistently so restrictive with the control of their own variability?
If evolving the organization were a shared responsibility, would the organization’s potential to survive, thrive and adapt be increased? Just as in a market economy, each participant has access to unique information that they can feed into the aggregate signal, information that is impossible to accrue within a centralized system because of the fluctuating and variable nature of relevance. In the case of a market, this aggregate signal is the price of goods and services. In the case of an organization, the signal is the amount and type of internal variation.
What prevents an organization from sharing the responsibility to adapt? The difficulty lies in properly yoking variation to relevance. Unlike in a market economy, where prices are directly relevant to the interests of the buyers and sellers, the induced variation within an organization is only indirectly relevant to its participants. So although each participant potentially has privileged information that could benefit the organization, only some participants can be trusted to act according to organizational relevance.
This restriction has to do with two properties that characterize relationships between organizations and participants. First, every participant cannot be assumed to have the skills, time, or knowledge necessary to know all the factors that affect the organization’s health. Only through understanding the full breadth of an organization can one attempt to determine relevance. This is why organizations are organizations in the first place and not individuals. Organizations differentiate roles in order to manage complexity within the functions that enable their existence.
Second, even if every participant has an accurate model of what is and is not relevant to the organization, acting according to organizational relevance may not be in the participant’s interest. For example, if an office worker knows that their job could be done cheaper and better by replacing their responsibilities with a machine, it is not in their best interest to share that information. In this way, organizations and personnel are subject to the Principal-agent problem, where there is a conflict of interest when the organization’s personnel (the agents) act on behalf of another entity (the organization).
It turns out that legibly capturing the beliefs of an organization can remove the risks associated with evolving the organization. Buildonomy offers the tools to turn an organization’s belief structure into a legible model of how and why the organization functions. When beliefs are legible through the lens of such a model, organizations can communicate and act in a manner that affords:
Alignment between organizational and participant rewards and values,
A scale-free protocol for participants to both coordinate and learn, where coordination and learning is directly tied to what is relevant to the organization,
A counterfactual engine, capable of predicting outcomes due to external or internal changes to the organization.
Buildonomy enables increased autonomy and accountability to participants within an organization by providing the following high level capabilities.
Makes it easy to understand an organization’s intentions and how those intentions relate to a participant’s role and assigned tasks
Makes it easy for participants to propose new ways of operating. Describing and comparing changes to what is currently available is easily translatable into what is organizationally relevant about the proposal.
Participants can easily transform repetitive manual actions into routine and automatic actions, regardless of the scale, scope or context.
At Buildonomy we believe there is a way to surmount the variability dilemma for organizations of all sizes. We believe that it is in an organization’s best interest to radically distribute autonomy and control within their boundaries. We believe our tools, networks, and protocols will simultaneously increase an organization’s creativity and efficiency while simultaneously endowing participants with a stronger commitment to the organization’s mission. We believe that adopting our system will result in an organization that is cheaper to run, more aware of available sources of organizational value, and more flexible to changing environments.
The adjacent possible is an idea introduced by Stuart Kaufmann to describe the set of possibilities available to exploit at any given point in time. That which is “adjacent possible” is characterized by the possibility space of all potential combinations of what is known into new and potentially functionally novel configurations.