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How do you manage uncertainty in Systems Engineering? I hope this helps?

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Uncertainty is inevitable in systems engineering, as it involves dealing with complex, dynamic, and interdependent problems that span multiple domains and stakeholders. Uncertainty can arise from various sources, such as incomplete or inaccurate information, variability or randomness, ambiguity or vagueness, and human factors or biases. Managing uncertainty is crucial for ensuring the quality, reliability, and feasibility of systems engineering solutions, as well as reducing risks, costs, and errors. In this article, you will learn some practical strategies and techniques for managing uncertainty in systems engineering.

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Chen Zach
Kutay ?etin, CSEP

Systems Engineering Voice, Aerospace & Systems Engineer, DfSS Green Belt, SAFe Practitioner
Simon Han, MIRSE, CPEng, MIEAust, NER, MIET, MEng, APEC IntPE(Aus)

Railway Control Systems Engineering at MTM

1 Identify and classify uncertainty

The first step in managing uncertainty is to identify and classify its sources, types, and levels. This can help you understand the nature and extent of uncertainty, and how it affects your system requirements, design, analysis, testing, and operation. You can use various tools and methods to identify and classify uncertainty, such as stakeholder analysis, risk analysis, assumption analysis, scenario analysis, sensitivity analysis, and uncertainty propagation analysis. You can also use different frameworks and taxonomies to categorize uncertainty, such as the ISO 31000 standard, the Knightian distinction, the Rumsfeld matrix, and the UML-S profile.

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Kutay ?etin, CSEP

Systems Engineering Voice, Aerospace & Systems Engineer, DfSS Green Belt, SAFe Practitioner
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When working on a project in Systems Engineering, dealing with uncertainty is like sorting through a pile of mixed-up puzzle pieces. First, I need to figure out what types of uncertainty I'm dealing with. It could be things like missing information, unclear definitions, or unpredictable changes. Then, I categorize these uncertainties based on their sources - like whether they come from incomplete data, random variations, or human judgment. Once I've sorted these puzzle pieces, I can better understand what I'm facing and come up with strategies to manage these uncertainties. It's like having a roadmap to navigate through the fog.

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Chen Zach
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One approach I found helpful in identifying uncertainty is getting perspectives from multiple stakeholders. For example, I'm usually collecting use cases from the customer (usually represented by marketing), from regulatory (critical in Medical Devices and Automative, for instance), and Service/customer support. This approach helps me identify the places where the use cases are not clear or even contradict

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Jonathan Geller

Sr. Product Engineer at NVIDIA
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I have found that not all uncertainty is relevant to the project. Identify the specific elements that are, and address them using risk analysis tools like risk matrices (don't be put off by the different types - they boil down to ranking and weighting risk factors). Even if you still have uncertainty, you can be sure it's impact is quantifiably limited.

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2 Reduce and control uncertainty

The second step in managing uncertainty is to reduce and control its impact on your system performance, functionality, and safety. This can help you improve your system robustness, resilience, and adaptability, and avoid or mitigate potential failures, hazards, and threats. You can use various techniques and approaches to reduce and control uncertainty, such as data collection and validation, model calibration and verification, parameter estimation and optimization, design of experiments and testing, feedback and learning, and error detection and correction.

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3 Exploit and leverage uncertainty

The third step in managing uncertainty is to exploit and leverage its potential benefits and opportunities for your system innovation, creativity, and improvement. This can help you enhance your system value, functionality, and diversity, and discover new solutions, alternatives, and perspectives. You can use various methods and practices to exploit and leverage uncertainty, such as brainstorming and ideation, prototyping and simulation, experimentation and exploration, divergence and convergence, and iteration and evolution.

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Simon Han, MIRSE, CPEng, MIEAust, NER, MIET, MEng, APEC IntPE(Aus)

Railway Control Systems Engineering at MTM
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Uncertainty may happen on the technology selection. I had the experience when selecting the message queue library (such as between ActiveMQ Artemis and others) for interface communication. Prototyping was used to validate most of the functionality pertaining to the requirements. Finally, whole team were happy with the outcome and Artemis was incorporated into the systems successfully.

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4 Communicate and document uncertainty

The fourth step in managing uncertainty is to communicate and document its sources, types, levels, impacts, and actions for your system stakeholders, users, and customers. This can help you increase your system transparency, credibility, and trustworthiness, and facilitate collaboration, coordination, and decision-making. You can use various formats and media to communicate and document uncertainty, such as reports and presentations, diagrams and graphs, tables and matrices, indicators and metrics, and annotations and comments.

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Chen Zach
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An approach that works for me is first to conduct technical discussions, either structured or brainstorm-like. Once uncertainty is well understood, a critical step is to use requirement management techniques to document them. This could be any requirement document, e.g., Engineering Requirement Document (ERD) or Product Requirement Document (PRD). Please note that companies/industries use different software and naming conventions to describe these documents.

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5 Monitor and review uncertainty

The fifth step in managing uncertainty is to monitor and review its changes, trends, and effects on your system lifecycle, performance, and outcomes. This can help you evaluate your system effectiveness, efficiency, and suitability, and identify gaps, issues, and areas for improvement. You can use various tools and measures to monitor and review uncertainty, such as dashboards and visualizations, audits and assessments, reviews and feedbacks, benchmarks and standards, and lessons learned and best practices.

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6 Update and adapt uncertainty

The sixth and final step in managing uncertainty is to update and adapt your system requirements, design, analysis, testing, and operation based on the new information, knowledge, and insights gained from the previous steps. This can help you cope with the dynamic and evolving nature of uncertainty, and respond to the changing needs, expectations, and preferences of your system stakeholders, users, and customers. You can use various methods and processes to update and adapt uncertainty, such as agile and lean systems engineering, systems thinking and modeling, trade-off and option analysis, change and configuration management, and continuous improvement and learning.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How do you manage uncertainty in Systems Engineering? I hope this helps?

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2

3

4

5

6

7

1 Identify and classify uncertainty

2 Reduce and control uncertainty

3 Exploit and leverage uncertainty

4 Communicate and document uncertainty

5 Monitor and review uncertainty

6 Update and adapt uncertainty

7 Here’s what else to consider

Systems Engineering

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How do you manage uncertainty in Systems Engineering? **I hope this helps**?

1

2

3

4

5

6

7

1 Identify and classify uncertainty

2 Reduce and control uncertainty

3 Exploit and leverage uncertainty

4 Communicate and document uncertainty

5 Monitor and review uncertainty

6 Update and adapt uncertainty

7 Here’s what else to consider

Systems Engineering

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How do you manage uncertainty in Systems Engineering? I hope this helps?