simplifying risk management
Before you conduct any risk management project, I'd recommend starting from first principles, asking, 'what effect is this program meant to achieve?' Keeping this top-level outcome in mind will ensure that you achieve the aim and don't just conduct a check-the-box exercise.
The Signal and The Noise is a great read that explains why and how you need to mix statistics and experience in your predictions and decision-making. It may seem technical and math-heavy at first glance, but Nate Silver makes this an easy read.
Something that's very hard to do as a consultant is to say, 'I don't know,' or admit a knowledge gap. But you've got to overcome any discomfort because it's critical that you're honest about your knowledge gaps if you want to understand an organization or situation.
An update on the risk metrics project: 20 metrics that are worth tracking for your threat and risk assessments
A problem I've observed is that we often mistake deciding what we need to do and how we will do it. This confusion makes us think that a problem's been solved when, in fact, all we've done is identify the effect we want to achieve, not how we're going to get there.
Flirting with Disaster is a great read for anyone wishing to mitigate and avoid catastrophic events. There's enough technical info to help you understand the key concepts but the pace is fast and the story-telling is engaging. It's definitely a must-have for any risk manager or decision-maker's bookshelf and I've returned to it many times in my work.
Establishing a set of metrics we can use for risk management and decision-making is a big topic I've been working on for a long time - over 20 years at this point. It's a challenging problem and one that has seen off better people than me but I think that a simple model will help speed up, simplify and remove the subjectivity from risk assessments. In turn, that will help improve the speed and quality of our decision-making. Here's an outline of the project
'Barbara' is my shorthand for the person who's essential to an organization. The real Barbara was the founder's EA at a firm where I worked and, having been there since the very beginning, knew everything there was to know about the business. But over time, I realized that most organizations have a Barbara (or Bob) and they're essential to keeping things going.
ESG is under attack and, in some cases, rightly so. Here's an overview of some of the issues it's facing and why it's time to break up the ESG party.
Data or information by itself is meaningless. For it to be useful, we need to add context. This is the difference between information and intelligence: once we've analyzed the information and put it into context, the resultant intelligence gives us an understanding of a situation. Developing this context can be difficult but this technique of applying different lenses will help you establish context and put your information to work quickly.