Project managers elaborate detailed plans with successive activities. Program managers build high-level plans that track the progress and the interdependencies of their components. All this seems linear by definition.
Yet, most of these projects and programs show clear characteristics of complexity. Among these are a number of interactions impossible to explain and many nonlinear behaviors. But you cannot use linear approaches to solve nonlinear problems. Only nonlinear approaches can fit the needs of complex project management. So, here a few related recommendations for project management practitioners.
Complex systems are nonlinear
Take the two pendulums of the figure 1 as an example. Each pendulum in isolation is a simple system. It has a deterministic nature. Once a college student gets his initial conditions, he is able to predict the system behavior. This is the red curve.
However, add now a second pendulum to the first one as shown in the figure 1. The second pendulum follows a trajectory that looks chaotic (the green curve).
You have now a complex two-pendulum system. It is nonlinear and nondeterministic.
This nonlinear behavior explains a large part of the challenges any project sponsor, project manager, project team and PMO has to overcome.
Yet traditional project approaches address systems as if they were simple and linear
Newtonian sciences are linear by nature. They describe cause and effect relationships with a very mechanical vision of the world.
Scientists working under Newton’s laws consider that an (approximate) knowledge of a system initial state and the comprehension of the law of nature render you capable to determine an (approximate) behavior of the system.
They generate an approach called reductionism, which breaks complex phenomena into simple components, with the belief that complex systems are the sum of its individual parts.
In this approach, a human or a project are the sum of components X1 + X2 + X3… This is the traditional paradigm that drives sciences from that point in time.
In the same manner, I have the feeling that traditional project management tries to predict an output and its benefits within a set of constraints as is everything was knowable, reducible to its components and linear.
However, most systems are complex and nonlinear
Nonlinearity arises indeed from the fact that when you put two or more things together, the result may not necessarily be a simple addition of each element’s properties in isolation.
In contrast, you can get a combined effect that is greater or less than the simple sum of each part. The parts of something are only explicable by relationships to the whole. They have a nonlinear relationship.
A second paradigm is now being developed, the paradigm of synthesis and systems thinking that tries to understand an entity through the context of its relations within a whole of which it is part.
Nonlinear systems may appear chaotic, unpredictable, or counterintuitive, contrasting with the much simpler linear systems. In nonlinear systems, deterministic principles are defied. Simple additions do not work anymore. Two thirty- to fifty-year old men do not add up to an eighty-year old man.
Feedback loops change the ratio between inputs and outputs, challenging the homogeneity principle. System’s actions effect the environment. Effects feedback to alter future inputs. Infinite scaling is not possible either.
Project Managers as well as PMOs need therefore to learn how to deal with nonlinearities.
Most projects show clear characteristics of complexity.
Additionally, programs that connect different projects together behave like several pendulums attached together. They generate behaviors that become rapidly chaotic .
This phenomenon requires specific approaches.
Here are a few paths that PMs and PMOs may want to explore, among others:
- First, consider the interrelationships of your many intertwined stakeholders more than the stakeholders themselves.
- And study the whole system behavior more than the individual behavior.
- Prepare also to facilitate the emergence of unpredictable new behaviors.
- Beware of the observer’s influence on the system under observation.
- Expect sub-optimal states where fitness is relative.
- Control the complex system with simple rules.
- Yet remember that a controlling system must be more nimble than the system it controls.
- Finally, capitalize on the self organizing capabilities of a complex system.
You cannot use linear approaches to solve nonlinear problems. Only nonlinear approaches can fit the needs of complex project management.