Home
Our Approach
JPAGE_CURRENT_OF_TOTAL

Learning from Complexity Theory

How can that be applied in enterprise projects? Let’s look at an example: Among others, complexity and network theory characterize systems by non-linearity, emergent properties, self-similar structures, and nested layers. To balance performance with risk, they need a sense of purpose, the right structure of nodes, and simple rules that optimize the flow of information and decision-making.

Traditional tools of project management can lay a part of the foundation, but they alone fall short. Therefore we propose to deliberately incorporate into enterprise project solutions aspects like:

  • Decentralized and nested project structures with node sizes and communication lines that allow for most effective collaboration across the system. This considers features identified in small world networks, including efficiencies gained through fractal structures.
  • Define standard business processes to set rules for the by-and-large independent players to consider when optimizing their job. This borrows concepts of swarm intelligence.
  • Guide the purpose and direction of the project system by focusing on consistently adjusting and fine-tuning guidelines and specifications to keep the overall effectiveness maximized. We look at projects as dissipative systems that need to continuously consider feedback loops from within and from their external environment. This usually is complex in itself.

Points like the above build the foundation to turn complex projects, which enterprise projects usually are, into complex adaptive systems that allow for much quicker system reaction. This does of course change the role of software applications and technologies, project team members, and of project and program management itself.

 


<< Start < Prev 1 2 Next > End >>