Tag Archives: complexity science

Knowing when to avoid left turns

This month’s issue of The Actuary features the last article in a three-part series on thinking and decision making co-authored by Milliman’s Neil Cantle and by Willis Re’s Dave Ingram. Entitled “Actuarial Thinking: Knowing When to Avoid Left Turns,” the article explores when actuaries should use a heuristic or systems analysis method of decision making. Here’s a sample:

Integrating techniques more formally into actuarial work that can help to make sense of the underlying mechanisms of problems will help to ground models more clearly in reality and therefore enhance the role of actuaries in explaining their models and demonstrating their value. It will also help users to understand the deficiencies of models so that they appreciate when the model can be used and when it cannot.

Read the entire article here.

What is the greatest barrier to ERM success?

The results from our first 50 enterprise risk management iPad surveys are streaming live at the Milliman ERM Symposium booth. One of the more intriguing early findings: Two barriers have jumped out as major impediments to ERM success. Risk professionals are asking: How do we measure value? And how do we navigate the complexity of an ERM program?

Anyone interested in participating in the survey or in seeing the full results should visit the Milliman booth.

 

Systems thinking: Looking at risk management holistically

When faced with a wall of complexity, most people have been taught to immediately seek to break the problem into more digestible pieces, study them, and then reaggregate to understand the “whole.” This approach actually works pretty well if the situation does not change too frequently. Generations of practitioners studying the problem will find increasingly better ways of breaking it up, and reaggregating the solution. But what if things are frequently changing and adapting? In this case the collaboration over time no longer yields the improving accuracy you would hope for.

The reductionist approach is so ingrained in our training that the idea of looking at the full holistic picture as a first step nearly always sounds like a daunting and fruitless route to take. As it happens, this is exactly what we need to do.

This article, published in the April/May issue of The Actuary magazine, introduces some of the ways you can look at the world holistically, but rapidly get to an understanding of which tools can be used to model and manage risk appropriately. See the full article here.

An evolutionary approach to emerging and enterprise risks

Risks bear considerable similarities to organisms: They exist in a particular environment, change over time, and have uncertain outcomes. The evolution of risk is partly determined by the uncertain nature of risks and partly by the environment and human intervention.

In the 18th century, Linnaeus pioneered a classification system by grouping organisms in accordance with their similarities and differences. Linnaeus’ work, much like traditional risk management, can be described as systematic, instead of evolutionary, as the objective was to place all known organisms into a hierarchical structure.

Phylogeny, on the other hand, being inspired by Darwin’s evolutionary approach, not only indicates the similarities and difference between species, but also illustrates their evolutionary relationships.

Risks, like organisms, can be classified in accordance with their evolutionary relationships to obtain insight and knowledge regarding the patterns that emerge through phylogenetic analysis. A risk DNA can be achieved, and, as in biology, it could start to unlock some of the deep, interconnected secrets of complex risk behavior.

A recent article by Milliman consultant Neil Cantle, published in InsuranceERM (subscription required), explores these issues and more in detail.

Management risk and the internal organic network

All risk is ultimately management risk. It is the risk of strategic error, of operational blunder, or even of fraud. Nonetheless, as complex as it is, management risk can be monitored, analyzed, and mitigated. This process begins with an understanding of organizational dynamics.

This dynamic is explored in a new article, “Mapping the ION: Management risk and the internal organic network.”