Applying a Systems Thinking approach to the IT Operating Model

A Systems Thinking approach allows you to tackle complex problems more effectively. Systems thinking is based on the premise that everything in is interconnected and interdependent.

In contrast to analysis, which seeks to break down complexity into isolated components, synthesis allows you to see the whole and the parts at the same time.

The individual parts of an interconnected system stand in a cause-and-effect relationship with one another, forming dynamic feedback loops.

Creating a visual representation that highlights how the system’s individual parts interact with one another allows you to understand how an intervention will change the system. 

A Systems Thinking approach allows you to tackle ITOM review or design more effectively and create better and more meaningful insights. 

These six core Systems Thinking concepts should be considered when diagnosing an operational or organisational problem in an existing ITOM or when developing a new or transformed ITOM:

Interconnectedness – To understand the complexity of an Enterprise IT organisation, assume that every function is interconnected and depends on something else to work effectively. 

Synthesis – The goal of Systems Thinking is to combine or synthesise disparate elements to form something new. In contrast to analysis, which seeks to break down complexity into isolated components, synthesis allows you to see “the whole ITOM and the individual functions at the same time” and understand how these functions are connected.

Emergence – The interaction of functions and practices gives rise to the complete ITOM, which is  a complex system. Emergence is a phenomenon that occurs in a nonlinear and self-organizing fashion.

Feedback Loops – The individual functions and practices of an interconnected ITOM influence one another through “feedback loops and flows.” In a “reinforcing” feedback loop, an event leads to more of the same, such as when algae multiply exponentially and come to dominate a local ecosystem. In a “balancing” feedback loop, in contrast, the components that make up the system create an equilibrium, such as in predator-prey ecosystems.

Causality – Once you understand how the functions and practices of an ITOM affect one another, you will be able to determine the cause-and-effect relationships among them. Causality thus helps you understand the dynamics of the entire ITOM holistically.

Systems Mapping – If you want to introduce changes to an ITOM through purposeful intervention, you will first want to create a visual representation that highlights how the ITOM’s individual functions and practices interact with each other. To do so, you may use tools like cluster mapping and digital feedback analysis.