A complex system is hard to map. These systems involve many variables, and many of those variables are dependent on one another. You cannot control the outcome of a complex, systematic problem. However, you can learn the nuances of the system & understand outcomes retroactively. In these cases, the whole of the system is greater than the sum of its parts.

Some examples of complex systems and problems include: weather predictions, racism, or tracking a virus (epidemiology).

How are Intercultural/Inter-organizational Collaborations Complex?

So as an engineer, how should you think about systems? How often do you interact with complex systems?

If you work in construction, infrastructure planning, natural resources, or a similar field, you probably collaborate with organizations or communities with different values, goals, motives, and structure. Cross-culture or cross-organizational collaborations are complex because they involve a reliance on people, and people are complex. When you or your organization enters a collaboration, you are met with unknown unknowns. Until the project is complete, you won’t be able to track the effects of a decision since the outcome of a decision relies on numerous moving parts.

For example, let’s say you are working with a community (Town A) to build a new bridge to replace an old one that is in disrepair. You have the plans ready to travel to the community to start the project when your point of contact in Town A steps down due to personal reasons. Assume no one in the local government has the time or ability to take over the role completely, so you now have multiple points of contact who can’t dedicate 100% of their time to the bridge. What would you need to do? Well, probably reassess the situation to best work with what you have. You won’t know the true effect of any decision made in this scenario until after the process is complete. This is part of the complexity of the system.

Take a moment to reflect on other ways in which collaborative projects are complex.