Happy 2018! Like many of you, I take the occasion of the passage of another year to think about ways to improve the consistency of making more successful lifestyle choices. Because I am also something of an obsessive-compulsive nerd that feels the need to inject the scientific method into almost everything I do, year after year I try to take a methodological and evidence-informed approach to designing my decision process for my behavioral response development.
For instance, using a merit-based review of some recent wellness improvement activity suggestions à la various online information sources I have decided to vote YES on implementing into my own process of daily living:
- Incrementally waking up earlier each morning to ensure I fit exercise into my schedule
and NO on including:
- “Detoxing” my physiological system using a coffee enema
The second proposition actually gets a “HARD PASS,” due to its dubious footing in anything that resembles viable wellness research and because the traditional drinking method for enjoying my double espresso Americano on the way to a morning meeting is much easier to do while driving.
The real test of success that most of us face is not in making the decisions meant to change our behavioral response systems. The challenge as the minutes, hours, days, weeks, etc. of the coming year pass-by is in keeping our well-intended responses steadfast and “resilient,” especially in the wake of unexpected life events. Impelled by this problem this year, I started wondering if it might be possible to possibly design algorithms for better maintaining various types of systems response resilience. (I know…who really thinks about this stuff other than me. But again, I am both admittedly systems-science-obsessed and between semesters at the moment, so indulge me).
So, what exactly is “RESILIENCE” is it and why is it important? The WHY in this case is likely easier for us to wrap our minds around than WHAT “resilience” is meant to convey in most cases. You and I know that to be resilient in the face of change or unexpected events is a positive. The ability to respond in a manner that is both anticipatory and adaptive is a good thing whether we are talking about an individual human being or a collective system of some sort. However, the meaning of response resilience is where things may become a bit unclear. Resilience is one of those expressions that due to its context of use and somewhat ambiguous connotation is often difficult to define in a fixed manner. This is because resilience is a construct that exists in two distinct knowledge camps: Human Psychology and Systems Engineering.
When viewed through the lens of Psychology, resilience embodies those behavioral qualities and attributes of an individual that enable them to thrive and in the face of adversity or unanticipated circumstances (Connor & Davidson, 2003). Resilience in Engineering, on the other hand, describes how elements of a system can sustain operations and evolve under expected and unexpected events in an efficient manner and evolve to an improved state of function (Hollnagel, 2013). These definitions, at first, may seem to be somewhat dichotomous in meaning. However, a key characteristic in both descriptions mandates that entities, whether human or built systems, must respond in an adaptive manner to unforeseen or surprising events to be considered “resilient.” This allows us a window of opportunity in unifying the psychological and engineering definition intent of this response descriptor. To be resilient human, technological, or operational activity systems need to be functionally adaptive. For these systems to be adaptive they typically need a reliable process algorithm and support context. This procedural framework includes the generalizable achievement drivers of: goals, incentives and/or inspiration, a launch point, plans, supportive infrastructure and resources, and finally a viable process for attainment. These inciting elements present a socio-technical interaction environment where the construct of Human Factors proves to be a useful context for establishing and measuring goodness of fit for systems’ response resilience.
Human Factors, like the concept of resilience, is a construct whose study and methods of analysis also reside in the fields of Psychology and Engineering. Human Factors basically is the scientific discipline of evaluating how individual people and human activity systems respond to external stimuli in various environments and under different situations (Hendrick & Kleiner, 2001). Why is this approach so valuable for designing systems’ resilience in general? Because for a system to be resilient it must include some form of sentience, e.g. intelligent input and anticipatory response (Hollnagel, 2013). Although Artificial Intelligence is continuing to gain ground in achieving independent and self-mobilizing cognition, system sentience to date can only be achieved by the presence of human-interaction with systems. Because as humans we know at times we are prone to error and response inconsistency, especially during unpredicted or stressful events, to ensure response success reliability, systems need to have several layers of corrective or fallback provisions. Because the systems planned using Human Factors are person centered rather than process driven they are designed to provide remedial support to human operators. “A resilient system includes not just well-tuned humans but also systems that complement the ability of the human to be resilient.” (Boring 2009) This is a bit different than some other Quality/Behaviors Management tactics whose focus is on compelling human behavior to adapt to consistent procedures always and under any circumstance. Something that any of us who have begun a strict diet as part of a new year resolution, is an approach that often has a variable success rate and fairly short “shelf-life.”
A Human Factors-based algorithm for sustaining systems response resilience would need to include key response intelligence supporting factors of:
- Motive as a kickstart variable and the primary navigator of resilience strategy and response.
- Ingenuity, which is essentially the applied combination of incentive and innovation to guide design of decision parameters
- Support elements that not only fuel resilience achievement but provide corrective contingencies for fallible human response
These elements supporting human sentience would also need to be both guided and driven by the decision points of:
- Action: i.e. response
- Strategy: i.e. plans
- Systems: i.e. power
At first glance, this algorithmic approach may appear overly complex for guiding seemingly basic behavior change response. However, when viewing this process holistically, we can see that it is relatively straightforward. This evidence-based method essentially provides us both a systems response component checklist and guideline for benchmarking our decision effectiveness progress. Moreover, it’s generalizability allows us to apply it as a template to plan both individual and collective systems for discrete or enterprise-wide response strategy. So, although this method may seem overly complicated in devising plans to get up at 6:00 a.m. rather than 6:30 a.m. to fit in 30 minutes on the elliptical, viewing it as an approach to fundamentally change your overall wellness behavior resilience likely has more merit. Not to mention, the latter more comprehensive intent likely has a more profound and sustainable impact on actual and measurable benefit outcomes.
Whether we like it or not, considering the increasing change in the socio-technical systems which we find ourselves operating, resilient anticipatory feedback and response is a new reality. There is an escalating need for more consistent and dependable action mechanisms within human-guided interaction environments and activity systems. These mechanisms should ideally be comprised of reliable components and straightforward processes. A Human Factors approach to resilient systems design will allow us as human-beings to focus on what we are inherently good at creativity, communication, compassion, and when the occasion calls, drinking our coffee.
Boring, R. L. (2009, October). Reconciling resilience with reliability: The complementary nature of resilience engineering and human reliability analysis. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 53, No. 20, pp. 1589-1593). Sage CA: Los Angeles, CA: Sage Publications.
Connor, K. M., & Davidson, J. R. (2003). Development of a new resilience scale: The Connor‐Davidson resilience scale (CD‐RISC). Depression and anxiety, 18(2), 76-82.
Hendrick, H., & Kleiner, B. M. (2001). Macroergonomics: An introduction to work system design. Human Factors and Ergonomics Society: Santa Monica, CA.
Hollnagel, E. (2013). Resilience engineering and the built environment. Building Research & Information, 1-8.
Hollnagel, E., Braithwaite, J., & Wears, R. L. (Eds.). (2013). Resilient health care. Ashgate Publishing, Ltd..
Lisa Sundahl Platt is the CEO and Founder of UMNSystems LLC. She writes about the systems and science of organizational and cultural resilience and how it impacts the human experience.