Resilience is understood to be the ability of a system to snap back quickly from a shock to some recognized, acceptable status quo. Shocks, of course, can come from a variety of sources natural or human-made, can impact various components of a system, and can have a wide range of effects from mild to severe. This is so because most systems of interest are beset by various types of security challenges. These security challenges can lead to brand degradation from competitor action, changes in an audience’s perception, a bad decision by managers, other factors.
What often makes managing resilience difficult is not just the unknown, sometimes unknowable security risks, it is that the systems in which systems must thrive are often chaotic or complex adaptive systems necessitating special techniques and approaches. Further, to understand resilience it is also necessary to understand its related terms such as robustness, coping, fragility, and anti-fragility.
Resilience engineering, then, is the science of designing and building robust and adaptive systems in order to secure against threats and failures and assure quick and efficient rebounds from systemic shocks. Using some of the technologies taught in our Modeling Complexity for Strategic Design we will teach students how to model a scenario of interest and build simulations to engineer resilience. We will work with different measures of resistance and provide the skill sets necessary to engage various types of systems and engineer their resilience.
By effectively and efficiently modeling scenarios of interest in new and robust ways, and using advanced simulation and analytic techniques, we can anticipate threats and design Resilience Strategies. The key insight here is that by breaking a system in simulation, you learn where the system’s weaknesses and strengths are.
Resilience Engineering can help end-users decide which strategy to undertake, where to invest resources, what advertising or messaging campaign to launch to help manage cultural factors, what likely responses will be like from audiences and adversaries, and what options are best to pursue should a shock to the system occur. Further, Resilience Engineering can forecast strategies across various time horizons to help in long-term design.
When Netflix wanted to reduce drops in service through their distributed computing delivery system, they use Resilience Engineering and broke their own system repeatedly. Fail often is the mantra. Fail often in controlled environments. For systems in use and of high value this is impossible without careful, theoretically informed and data driven modeling.
Students who complete “Resilience Engineering” should demonstrate the ability to:
- Understand the complexity of the context in which they are operating
- Understand the nature of the problem set they are trying to manage
- Understand the linkages between problem sets and between problem sets and context and the mental models they are using to understand these linkages
- Use basic vocabulary of knowledge management as a frame of reference for studying wicked problems
- Demonstrate basic ability in several types of modeling
- Demonstrate the ability to understand vulnerabilities of systems, experiment with systems, produce recommendations
- Use design thinking, modeling techniques, and creative problem-solving skills to identify and frame wicked problems with more discipline before considering alternative solutions
- Design innovative, holistic resistance engineering strategies
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