Difference between revisions of "Systems Engineering Heuristics"
Tag: visualeditor |
|||
| Line 5: | Line 5: | ||
== Overview == | == Overview == | ||
| − | Heuristics have always played an important part in the history of engineering and shaped its progress, especially before science developed to the point when it could also assist engineers. Systems Engineering is still at a stage at which there is no sufficiently reliable scientific basis for many of the systems being built, which has triggered a renewed interest in heuristics to fill the gap. | + | Heuristics have always played an important part in the history of engineering and shaped its progress, especially before science developed to the point when it could also assist engineers. Systems Engineering is still at a stage at which there is no sufficiently reliable scientific basis for many of the systems being built, which has triggered a renewed interest in heuristics to fill the gap. This is especially true as the practice of Systems Engineering is extended to provide solutions to inherently complex, unbounded, ill-structured, or "wicked" problems (Churchman 1967). |
| − | Using heuristics does not guarantee success under all circumstances, but usefulness of a heuristic | + | Using heuristics does not guarantee success under all circumstances, but usefulness of a heuristic can be maximized if the known extent of its applicability is made clear. At their best, heuristics can act as aids to decision making, value judgements, and assessments. |
Heuristics have the potential to be useful in a number of ways: | Heuristics have the potential to be useful in a number of ways: | ||
| − | · reduce the amount of thinking (or computation) needed to make a good decision or a choice | + | · reduce the amount of thinking (or computation) needed to make a good decision or a choice |
| − | · help in finding an acceptable solution to a problem | + | · help in finding an acceptable solution to a problem |
| − | · identify the most important factors to focus on while addressing a complex problem | + | · identify the most important factors to focus on while addressing a complex problem |
| − | · improve the quality of decisions by drawing on best practices | + | · improve the quality of decisions by drawing on best practices |
| − | · avoid repeating avoidable mistakes | + | · avoid repeating avoidable mistakes |
| − | · act as an entry point to wider knowledge of what has been found to work. | + | · act as an entry point to wider knowledge of what has been found to work |
| + | |||
| + | == Historical Background == | ||
| + | Engineering first emerged as a series of skills acquired while transforming the ancient world, principally through buildings, cities, infrastructure, and machines of war. Since then, mankind has sought to codify the knowledge of "how to.". Doing so allows each generation to learn from its predecessors, enabling more complex structures to be built with increasing confidence while avoiding repeated real-world failures. Setting out the aims for engineering in the 1st Century BCE, Vitruvius proposed a set of enduring principles: Strength, Utility and Beauty. He provided many examples of their applications to the fields of engineering of the time. | ||
| + | |||
| + | Vitruvius’ writings were rediscovered in the Middle Ages, forming the basis of the twin professions of architecture and engineering. Early cathedral builders encapsulated their knowledge in a small number of rules of thumb, such as: "maintain a low centre of gravity," "put 80% of the mass in the pillars," and "observe empirical ratios between cross-section and span for cross-members.". Designs were conservative, with large margins, the boundaries of which were largely unknown. Numerous excellent structures resulted, many of which have endured to this day. When the design margins were exceeded, for example out of a desire to build higher and more impressive structures, a high price could be paid, with the collapse of a roof, a tower, or even a whole building. From such failures, new empirical rules emerged. Much of this took place before the science behind the strength of materials or building secure foundations was understood. Only in recent times has computer simulation revealed the contribution towards certain failures played by dynamic effects, such as those of wind shear on tall structures. | ||
| + | |||
| + | Since then, engineering and applicable sciences have co-evolved: science providing the ability to predict and explain performance of engineered artifacts with greater assurance, and engineering developing new and more complex systems, requiring new scientific explanations and driving research agendas. In the modern era, complex and adaptive systems are being built which challenge conventional engineering sciences, with the builders turning to social and behavioral sciences, management sciences, and increasingly systems science to deal with some of the new forms of complexity involved and to guide the profession accordingly. | ||
| + | |||
| + | == Modern Interest == | ||
| + | Renewed interest in the application of heuristics to the field of Systems Engineering stems from the seminal work of Rechtin and Maier, and their book1 remains the best single repository of such knowledge. Their motivation was to provide guidance for the emerging role of system architect as the person (or team) responsible for coordinating engineering effort towards devising solutions to complex problems and overseeing their implementation. Rechtin and Maier observed that it was in many cases better to apply ‘rules of thumb’ than attempt detailed analysis, especially when this was precluded by the number of variables involved, the complexity of the interactions between stakeholders, and the internal dynamics of system solutions and the organisations responsible for their realisation. | ||
| + | |||
| + | An argument in favour of the wider use of heuristics was also made by Mervyn King, who was Governor of the Bank of England during the 2008 global financial crash. Looking back2, he said ‘it is better to be roughly right than precisely wrong’: banks which observed the old bankers’ rule of maintaining capital assets equal to 70% of their loan book survived, while those who relied on complex (and flawed) mathematical models of derivatives failed. He has become a powerful advocate for the use of heuristics alongside formal economics to allow bankers and others to deal with the uncertainties of global financial affairs in the modern interconnected world. | ||
| + | |||
| + | Further backing for the contemporary use of heuristics comes from Simon2, who coined the term satisficing for a situation in which people seek solutions, or accept choices or judgments, | ||
| + | |||
| + | that are "good enough" for their purposes, regardless of whether they can be further optimized by precise analysis. He made the point that some heuristics were scientifically derived from experiment or systematic collection and analysis of real-world data, while others were just rules of thumb based on real-world observation or experience. | ||
==References== | ==References== | ||
===Works Cited=== | ===Works Cited=== | ||
| − | + | Churchman, C.W. 1967. "Wicked Problems". ''Management Science''. 14(4): B-141–B-146. | |
===Primary References=== | ===Primary References=== | ||
Revision as of 12:21, 8 April 2021
Lead Author: Peter Brook
Heuristics provide a way for an established profession to pass on its accumulated wisdom. This allows practitioners and others interested in how things are done to gain insights from what has been found to work well in the past and to apply the lessons learned. Heuristics will usually take the form of short expressions in natural language. These can be memorable phrases encapsulating rules of thumb, shortcuts or "words to the wise", giving general guidelines on professional conduct or rules, advice, or guidelines on how to act under specific circumstances. Common heuristics do not summarize all there is to know, yet they can act as useful entry points for learning more. This article overview heuristics in general as well as those supporting systems engineering practice.
Overview
Heuristics have always played an important part in the history of engineering and shaped its progress, especially before science developed to the point when it could also assist engineers. Systems Engineering is still at a stage at which there is no sufficiently reliable scientific basis for many of the systems being built, which has triggered a renewed interest in heuristics to fill the gap. This is especially true as the practice of Systems Engineering is extended to provide solutions to inherently complex, unbounded, ill-structured, or "wicked" problems (Churchman 1967).
Using heuristics does not guarantee success under all circumstances, but usefulness of a heuristic can be maximized if the known extent of its applicability is made clear. At their best, heuristics can act as aids to decision making, value judgements, and assessments.
Heuristics have the potential to be useful in a number of ways:
· reduce the amount of thinking (or computation) needed to make a good decision or a choice
· help in finding an acceptable solution to a problem
· identify the most important factors to focus on while addressing a complex problem
· improve the quality of decisions by drawing on best practices
· avoid repeating avoidable mistakes
· act as an entry point to wider knowledge of what has been found to work
Historical Background
Engineering first emerged as a series of skills acquired while transforming the ancient world, principally through buildings, cities, infrastructure, and machines of war. Since then, mankind has sought to codify the knowledge of "how to.". Doing so allows each generation to learn from its predecessors, enabling more complex structures to be built with increasing confidence while avoiding repeated real-world failures. Setting out the aims for engineering in the 1st Century BCE, Vitruvius proposed a set of enduring principles: Strength, Utility and Beauty. He provided many examples of their applications to the fields of engineering of the time.
Vitruvius’ writings were rediscovered in the Middle Ages, forming the basis of the twin professions of architecture and engineering. Early cathedral builders encapsulated their knowledge in a small number of rules of thumb, such as: "maintain a low centre of gravity," "put 80% of the mass in the pillars," and "observe empirical ratios between cross-section and span for cross-members.". Designs were conservative, with large margins, the boundaries of which were largely unknown. Numerous excellent structures resulted, many of which have endured to this day. When the design margins were exceeded, for example out of a desire to build higher and more impressive structures, a high price could be paid, with the collapse of a roof, a tower, or even a whole building. From such failures, new empirical rules emerged. Much of this took place before the science behind the strength of materials or building secure foundations was understood. Only in recent times has computer simulation revealed the contribution towards certain failures played by dynamic effects, such as those of wind shear on tall structures.
Since then, engineering and applicable sciences have co-evolved: science providing the ability to predict and explain performance of engineered artifacts with greater assurance, and engineering developing new and more complex systems, requiring new scientific explanations and driving research agendas. In the modern era, complex and adaptive systems are being built which challenge conventional engineering sciences, with the builders turning to social and behavioral sciences, management sciences, and increasingly systems science to deal with some of the new forms of complexity involved and to guide the profession accordingly.
Modern Interest
Renewed interest in the application of heuristics to the field of Systems Engineering stems from the seminal work of Rechtin and Maier, and their book1 remains the best single repository of such knowledge. Their motivation was to provide guidance for the emerging role of system architect as the person (or team) responsible for coordinating engineering effort towards devising solutions to complex problems and overseeing their implementation. Rechtin and Maier observed that it was in many cases better to apply ‘rules of thumb’ than attempt detailed analysis, especially when this was precluded by the number of variables involved, the complexity of the interactions between stakeholders, and the internal dynamics of system solutions and the organisations responsible for their realisation.
An argument in favour of the wider use of heuristics was also made by Mervyn King, who was Governor of the Bank of England during the 2008 global financial crash. Looking back2, he said ‘it is better to be roughly right than precisely wrong’: banks which observed the old bankers’ rule of maintaining capital assets equal to 70% of their loan book survived, while those who relied on complex (and flawed) mathematical models of derivatives failed. He has become a powerful advocate for the use of heuristics alongside formal economics to allow bankers and others to deal with the uncertainties of global financial affairs in the modern interconnected world.
Further backing for the contemporary use of heuristics comes from Simon2, who coined the term satisficing for a situation in which people seek solutions, or accept choices or judgments,
that are "good enough" for their purposes, regardless of whether they can be further optimized by precise analysis. He made the point that some heuristics were scientifically derived from experiment or systematic collection and analysis of real-world data, while others were just rules of thumb based on real-world observation or experience.
References
Works Cited
Churchman, C.W. 1967. "Wicked Problems". Management Science. 14(4): B-141–B-146.
Primary References
None.
Additional References
None.