The 10 Biggest Illusions of Systems Engineering

The 10 Biggest Illusions of Systems Engineering

When systems engineering became established in the middle of the last century, it was based on a number of assumptions. However, these assumptions were not systematically captured, but were based on the environment of the time, particularly in the context of aerospace and defense programs. This is not consistent with today’s environment — they are illusions.

Michael J. Pennock and John P. Wade of Stevens Institute of Technology have examined this issue and have come up with a list of the 10 biggest illusions in systems engineering based on this issue. Of course, that’s not the end of the story: the authors also lay out a research plan to mitigate these shortcomings.

The following is now the list of the 10 illusions. This article is also available in German at SE-Trends.

The Research

So the authors have published their work open access articles. This means the free access to scientific literature. Since I myself publish a lot in the open source or open access environment, I am happy about this. The 8-page paper can be downloaded here.

10 Illusions in Systems Engineering

Let’s get to the real topic, the 10 illusions in systems engineering (SE). The authors first discuss the history of systems engineering. The authors also address the more or less often discussed identity crises in Systems Engineering.

Systems Engineering has a clear mission, a clear goal. But it is easy to lose sight of this and see it as an end in itself. Undoubtedly, this is the cause of some of the illusions. In addition, under certain circumstances, classical (!) systems engineering no longer works. Some practitioners do not accept the approaches that work as “real” systems engineering. Agile approaches are a good example.

1. Illusion: Systems Engineering is Absolute

Traditional SE assumes that there is a “right”, or optimal, solution. In reality, the task is to optimize and apply best practices, rather than being a subjective and contextual process. This is one of the key assumptions that often separates traditional systems engineering from systems thinking, which takes into account the soft and often inconclusive nature of systems.

2. Illusion: Systems Engineering is Unambiguous

One premise of systems engineering is the illusion that it is possible to express unambiguous requirements in human language. Of course, experience teaches us that people may well interpret a requirement in different ways. To make matters worse, we expect these requirements to be decomposable into further, subordinate requirements.

3. Illusion: Systems Engineering is Sequential

Traditional SE requires a fundamentally sequential approach to development. This does not mean that there are no feedback loops at all, but generally the nature of the system being developed is such that its development can be decomposed in time and performed sequentially. This makes it difficult to develop systems that must be adaptive.

4. Illusion: Actors in Systems Engineering Act Rationally

We often assume that decision making in engineering is similar to that of business actors: Engineers and managers are rational decision makers who have access to complete and perfect information. In real life, systems engineers are under deadline, political, and resource constraints. As a result, they often do not have the information they need to make informed or “optimal” decisions. In the face of such ambiguity, the apparent best option may be to do things the way they have always been done. However, in the case of complex systems or systems of systems, this may be exactly the wrong way to go.


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5. Illusion: Systems Engineering Leads to Reductionistic, Loosely Coupled Systems

The key to systems engineering is the ability to divide and rule. But for this to work, we must decompose the system in into reasonably loosely coupled subsystems. As complexity increases, reductionism becomes problematic as subsystems become more artificial and potentially counterproductive from an engineering standpoint, because critical interactions cannot be adequately accounted for or detected.

6. Illusion: Systems Engineering has Central Control

Control over the development organization(s) is centralized and absolute. Traditionally, this has been governed by contracts and similar mechanisms. However, with “Systems of Systems” there are often no explicit contracts. As a result, it is more difficult for the Systems Engineer to maintain technical control. Subsystems can change unexpectedly, which can cause problems and failures.

7. Illusion: Systems are Immutable

Traditional SE assumes that system needs and system context essentially do not change. In the real world, of course, competitors behave unexpectedly, new technologies appear, suppliers go out of business, etc. As social and technological change accelerates over time, static solutions may become obsolete before they can be deployed.

8. Illusion: Systems Engineering is Mechanistic

Traditional systems engineering is blind to the human element, including culture and history. There is an implicit assumption that these factors do not significantly affect outcomes. However, norms and values can affect the selection of potential solutions and influence how a systems engineering program is executed. The potentially detrimental effects that an inappropriate organizational structure can have on systems development are well known.

9. Illusion: Systems Engineering is Deterministic

Traditional systems engineering assumes that system behavior is deterministic. Input “A” combined with state “B” always produces output “C” (or at least captures the probability of C with a well-defined probability distribution). This view becomes problematic for adaptive systems where some fault tolerance is required in exchange for the benefits of adaptability. An example for this is the use of AI.

10. Illusion: Systems Engineering is Context-Free

Best practices are universal and do not vary by context. In other words: If a particular systems engineering approach has proven itself in the aerospace industry, it must also work well in the IT industry. No way! This view neglects the importance of tailoring. Different aspects of the systems engineering process may be more or less important for different types of systems and industries.

How to Deal With the Illusions?

Pennock and John Wade, based on these illusions, have created a research agenda (to be read in the paper, Chapter 5, Research Agenda). This may be all well and good in an academic setting, but how does it help us in practice?

It’s not that hard: the most important thing is to recognize these illusions in the first place. Because if we are aware of them and have created an awareness of them in the project, then we are already a good deal closer to the goal.

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