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This paper summarizes how a well-understood problem—optimal control and estimation in “noisy” environments—provides a framework to advance understanding of a well-known but less well-mastered problem—system innovation life cycles and management of decision risks and learning. The ISO15288 process framework and its exposition in the INCOSE Systems Engineering Handbook (2015) describe system development and other life cycle processes. Concerns about improving the performance of processes in dynamic, uncertain, and changing environments are partly addressed by “agile” systems engineering approaches. Both are typically described in the procedural language of business processes, so it is not always clear whether the different approaches are fundamentally at odds, or just different sides of the same coin. Describing the target system, its environment, and the life cycle management processes using models of dynamical systems allows us to apply earlier technical tools, such as the theory of optimal control in noisy environments, to emerging innovation methods.

How we represent systems is fundamental to the history of mathematics, science, and engineering. Model-based engineering methods shift the nature of representation of systems from historical prose forms to explicit data structures more directly comparable to those of science and mathematics. However, using models does not guarantee simpler representation—indeed a typical fear voiced about models is that they may be too complex.

Minimality of system representations is of both theoretical and practical interest. The mathematical and scientific interest is that the size of a system's “minimal representation” is one definition of its complexity. The practical engineering interest is that the size and redundancy of engineering specifications challenge the effectiveness of systems engineering processes. INCOSE thought leaders have asked how systems work can be made 10:1 simpler to attract a 10:1 larger global community of practitioners. And so, we ask: What is the smallest model of a system?

Engineering disciplines (civil, mechanical, chemical, electrical) sometimes argue their fields have “real physical phenomena”, “hard science” based laws, and first principles, claiming systems engineering lacks equivalent phenomenological foundation. We argue the opposite, and how replanting systems engineering in model-based systems engineering (MBSE) / pattern-based systems engineering (PBSE) supports emergence of new hard sciences and phenomena-based domain disciplines.

Supporting this perspective is the system phenomenon, wellspring of engineering opportunities and challenges. Governed by Hamilton's principle, it is a traditional path for derivation of equations of motion or physical laws of so-called “fundamental” physical phenomena of mechanics, electromagnetics, chemistry, and thermodynamics.

We argue that laws and phenomena of traditional disciplines are less fundamental than the system phenomenon from which they spring. This is a practical reminder of emerging higher disciplines, with phenomena, first principles, and physical laws. Contemporary examples include ground vehicles, aircraft, marine vessels, and biochemical networks; ahead are health care, distribution networks, market systems, ecologies, and the IoT.

Processes and procedures are the heart of current descriptions of systems engineering. The “vee diagram,” ISO 15288, the INCOSE Systems Engineering Handbook, and enterprise-specific business process models focus attention on process and procedure. However, there is a non-procedural way to view systems engineering. This approach is to describe the configuration space “navigated” by systems engineering, and what is meant by system trajectories in that space, traveled during system life cycles. This sounds abstract because we have lacked explicit maps necessary to describe this configuration space. We understand concrete steps of a procedure, so we focus there. But where do these steps take us? And what does “where” mean in this context? Clues are found in recent discoveries about ancient navigation, as well as later development of mathematics and physics. This paper, part I of a case for stronger model-based systems engineering (MBSE) semantics, focuses on the underlying configuration space inherent to systems.

System complexity continues to grow, creating many new challenges for engineers and decision makers. To maximize value delivery, “both” systems engineering and decision analysis are essential. The systems engineering profession has had a significant focus on improving systems engineering processes. While process plays an important role, the focus on process was often at the expense of foundational engineering axioms and their contribution to system value. As a consequence, systems engineers were viewed as process developers and managers versus technical leaders with a deep understanding of how system interactions are linked to stakeholder value. With the recent shift toward model-based systems engineering (MBSE), systems engineering is “getting back to basics,” focusing on value delivery via first principles, using established laws of engineering and science. This paper describes how pattern-based systems engineering (PBSE), as outlined within INCOSE's model-based systems engineering (MBSE) initiative, explicates system value through modeling of first principles, re-uniting systems engineering and decision analysis capabilities.

INCOSE's Vision 2025 identifies the development of systems thinking and technical leadership as one of seven key areas of systems engineering ‘competency’ required for delivery. Vision 2025 states: “Education and training of systems engineers and the infusion of systems thinking across a broad range of the engineering and management workforce will meet the demands for a growing number of systems engineers with the necessary technical and leadership competencies.” “The roles and competencies of the systems engineer will broaden to address the increasing complexity and diversity of future systems.” “The technical leadership role of the systems engineer on a project will be well established as critical to the success of a project.” These requirements imply the need to rapidly expand the art and science of systems technical leadership. In response to this need, INCOSE established an institute for technical leadership. This paper describes the Institute and the work that the first cohort (“Cohort of 2017”) has accomplished on developing a technical leadership model for systems engineers. It is envisaged that this first technical leadership model for systems engineers will be further developed and matured by the following cohorts of the INCOSE's Technical Leadership Institute.

The world is filled with hard and complex problems, oftentimes requiring involved solutions. In large organizations attempting to solve these types of problems, a mindset shift and key candidate methodologies centered on collaborative systems thinking culture (CSTC) can assist significantly. The paper explores the state of the practice, change involved with implementing systems thinking, impacts of a collaborative approach within an organization, as well as the seven phases that a reader can introduce into their organization to realize some of the benefits. The same approach was used to create this paper under collective authorship from cohort 6 of the INCOSE Technical Leadership Institute (TLI); an international group of individuals collaborating exclusively through virtual platforms. From writing papers to executing large technical programs, the CSTC approach will prepare technical teams for tackling challenging problems in an inclusive way with the intent to finish projects on time while also cultivating healthy systems engineering habits and practices. This lessens the reliance on corporate engineering procedures to drive collaborative behavior by fiat. Finally, blending CSTC into the fabric and culture of an organization is emphasized as being needed for the full benefit. That benefit includes saving programs by moving to a CSTC.

The world is increasingly virtual and complex, with many relationships and teams at a global scale. The situation will not be changing any time soon. Sometimes, it is only possible to interact at a distance, of not only time zones and space, but also sometimes interpersonal distance, where names and voices make up another person. Regardless, technical teams will need good leadership to address complex situations in these virtual and remotely distributed (VaRD) environments. So, in a VaRD environment, do leadership practices and skills have to change? Do the tools, techniques, and technology make current practices for leadership in general, and the application of those practices obsolete? Maybe not.

This paper seeks to examine the nature of what is really changing when leading in a VaRD environment through the lens of engineers leading teams in global and complex technical challenges. Those perspectives are analyzed to determine the factors that go into a VaRD environment. In addition, this paper analyzes how interactions between teams compare to an in-person environment, how leadership practices are applied in this environment, and how technical leadership is tailored for these new environments.

Tinkering — or making small changes to experiment toward an improvement in performance — is seemingly a natural characteristic of many systems engineers. As such, systems engineers are uniquely qualified to develop complex solutions necessary to overcome lack of clarity, achieve order, and avoid failure. Further, there is a much broader conversation surrounding the possibility of “failure” being beneficial in systems engineering projects. In response to the needing to inform judgment in situations shrouded in uncertainty, members of INCOSE's Technical Leadership Institute (TLI) cohort 8 examined the role of safe-to-fail probes play in informing judgement for systems engineers. Within the constraints of the TLI's major project, virtual workshops and qualitative interviews were two data collection mechanisms established to empirically investigate the role(s) of safe-to-fail probing in systems engineering. Overall, the data sets offered conclusions describing the potential role(s) of safe-to-fail probes for systems engineers working in uncertain environments. Resulting from this (limited) empirical exploration are additional insights and implications for how systems engineers may invoke safe-to-fail probes to improve decision-making in uncertain and challenging situations. Such a tinkerer's mindset can help systems engineers transition from the constraints of “intolerable failure” to the opportunities related to probing-sensing-responding to “responsible failures.”

Technical leadership is a skill defined in the INCOSE professional competencies. This paper presents reflections on a shared learning journey about technical leadership from the perspective of a group of emerging technical leaders. These reflections provide insights around building awareness, navigating power and influence, benchmarking personal performance, developing capacity for change, and establishing critical friends. The final section provides lessons for working as a global team in technical leadership. This paper is of relevance to any technical leader looking to develop this capacity across technical sectors.