OD58: Second-Order Analysis for Decisions ∙ Building a shared language ∙ Guide to Information Overload 🌱
Second-Order Analysis for Decisions
Useful decision-making tool shared by Kevin Kirkpatrick at Path Nine:
The act of deciding is a mapping investigation that uses present details to predict the future. Great decision-makers are not superheroes, they’re just top-notch scenario predictors.
For example, great chess players can’t actually see the future, but with an unparalleled ability to quickly explore all future possibilities, they’re able to rapidly decipher the best move under the circumstances.
Every decision has many, unforeseen ripple effects. These are known as second-order effects, and it’s what causes us to make subpar decisions.
In a world that is increasingly complex, it’s worth investing the time required to think through how our decisions impact those around us, including our future selves.
We can't know or fully predict every outcome, but like chess masters, we can look a few moves ahead and try to see how our decisions may impact the future. The goal is to make decisions that take into account past, present, and future states.
What are the second-order effects of your decisions?
Building a shared language with your team
Second practical resource that we picked this week for you comes from John Cutler over at The Beautiful Mess. It’s an exercise to help teams build their own shared language.
When I meet teams, I ask them about their "work taxonomy". What is their classification system? And how do they map those classifications to their processes?
The effective teams are way more likely to have an answer. They are far more likely to support multiple ways of working, while standardizing in only the places where it really adds value. Importantly, they have evolved a shared language to describe the differences.
The language is where every company can start. Right now. The big lesson I've learned over the years is to make the language unique to your company.
Ask the team to blurt out work from the last year or so
Group similar pieces of work. Don't overthink it.
Explore why you grouped work. What made these similar? This discussion is the important part.
Note dimensions (e.g. "knowledge of key persona" or "prior work in this area of the code" or "high profile and many dependencies"). Importantly, don’t force a framework or a set of sliders. I highly recommend named types, not a bunch of sliders. If sliders are your jam, then consider doing that, and naming common patterns and clusters.
Evolve the taxonomy to a place where you can comfortably classify new ideas/initiatives
Explore your working agreements for each type of work
What’s the shared language of your team?
What might an ecological civilization look like?
Reliability and Resilience
The latest issue of the Increment Magazine explores “approaches to reliability and resiliency in our software, technologies, and teams, and offers perspectives on the realities of failure in the systems we build.”
There are lots of OD Goodies to explore, like getting a better understanding of failures and catastrophes, resilience in organizations, trust-as-a-technology, chaos engineering, failover strategies and adaptive capacity. Happy reading!
Guide to Information Overload. Curator’s Edition
Just launched the practical guide around the question of:
How do you deal with the information overload?
You will find a synthesis of 12 principles, 8 flows for curation, study & creation and also some other ideas that you might find useful 💡
Special thanks to the 8 of you who pre-ordered the guide for trusting us with creating this product for you.
There’s a minimal price of 10€+vat on the guide, so that it has a chance of standing out a bit among the other things that you download and hopefully not go to waste (e.g. the “Read Later” or “Other” folder) that easily. Enjoy!
Other Sense & Change guides that might be useful:
Guide to Team Chemistry (paid)
Guide to Dynamic Stakeholder Mapping (paid)
Thanks for reading
This newsletter is curated by Raluca and Bülent Duagi, the Sense & Change team.
As Strategy & Organization professionals, we're using systems thinking and behavioral science to advise leadership teams in tech companies to make their organizations more effective.
Our professional mission and intended legacy is:
Creating and sharing sustainable knowledge that helps people deal with the complex challenges they (will) face.