Want to improve your decision making? Start with creating a better understanding at the beginning of the process. Making quality decisions requires a clear understanding of key definitions by stakeholders and the decision makers. Making quality decisions also requires facilitators and analysts to consistently apply those definitions throughout the decision-making process.
Some common terms that require establishing consistent definitions include: A DECISION is an irrevocable allocation of resources. It is different than a mental agreement or an agreement to an intended course of action. A decision requires someone to commit resources. And this definition also provides clarity in terms of who is the decision maker. If someone is not responsible and accountable for allocating resources, then he or she is not the decision maker.
RELIABILITY has the most universal definition among technical terms such as reliability, risk, resiliency. It is most often defined as “the probability that an item will perform its intended function for a specified interval under stated conditions.” This definition was somewhat institutionalized in the post-World War II era by the aerospace and US military sectors and has been adopted as the dominant definition among all industry sectors that have adopted formal reliability approaches and standards.
The reliability definition contains four distinct parts that should require additional clarification: a probability, which means there is some uncertainty; a function (or functions); a stated interval or time period; and stated or assumed operating and environmental conditions. The reliability definition is very objective and specific, and in turn, lends itself to the ability to assign quantitative numbers.
RISK is defined by the international risk standard, ISO 31000, as “the effect of uncertainty on objectives.” Few people, including most risk managers, cannot cite this definition. And to make matters worse, the international risk standard cites over 20 ways that risk can be expressed. For example, the multiplicative product of the consequence of failure and the likelihood of failure is not the definition of risk but rather one way to express risk. Even simple terms like "failure" are not commonly understood and their applicable definition should be established.
FAILURE is commonly defined as the event, or inoperable state, in which any item or part of an item does not perform as previously specified. But good systems engineers will be quick to remind us that failure can also be further subdivided into forms such as catastrophic failure, partial failure, intermittent failure, hidden failure, critical failure, dependent failure, and functional failure.
RESILIENCE is traditionally defined as the ability to return to the original form or state after being stressed. In made-made systems, we usually consider that most systems to not fully ‘bounce back’, and eventually some form of renewal or replacement is needed. In natural systems, we usually consider that systems will replenish themselves, or fully bounce back, if we do not stress them beyond certain thresholds (forests and fisheries are examples). Systems that bounce back fully to their original state are considered ‘sustainable’. This second potential definition of resilience makes resilience and sustainability synonymous.
The third definition of resilience has emerged in recent years from the climate change and environmental protection communities. It expands the typical definitions to include survive, adapt, and flourish in the face of turbulent change and uncertainty. Essentially a system should return to a state beyond the original basis of design by anticipating future trends and adapting natural systems to those anticipations. This is a tall order, and one that often bogs down allocating resources, or decision making.
I am often asked in my workshops and webinars on Communicating to Decision Makers whether formal definitions should be explained in presentations to decision makers. My answer is always the same – “yes”.
Whether facilitating consensus among diverse groups with multi-criteria analysis or doing probability encoding for a quantitative Monte Carlo simulation, establishing and maintaining consistent definitions throughout the process is critically important. Legends in the field such as Howard Raiffa and Ron Howard, who coined the phrase “decision analysis”, said it was so more than 50 years ago. And it rings true just as strongly today.
The illustration “Decision Maker at Risk” and excerpts from this article are taken from the first edition of JD Solomon's book, Communicating Reliability, Risk and Resiliency to Decision Makers: How to Get Your Boss's Boss to Understand.” The second edition is now available. 2022. Sign-up for updates at Communicating with FINESSE.