Building alignment through modeling, plus Jeff Sussna on Customer Value Charting and other things worth your attention.
INFORMA(C)TION — May 16, 2021
Building alignment through modeling, plus Jeff Sussna on Customer Value Charting and other things worth your attention.
Hello! I'm Jorge Arango and this is INFORMA(C)TION: a biweekly dose of big ideas for people who make digital things. If you like this email, please forward it to a friend. And if you're not subscribed, sign up here. Thanks for reading!
Detail of grand orrery in Putnam Gallery
Detail of grand orrery in Putnam Gallery by Sage Ross (CC BY-SA 3.0)

Clarity and Confidence

Few things are as powerful as a good model of a complex domain. A clear representation of the domain’s key elements and their relationships creates alignment. The model becomes a shared point of reference and shorthand for decision-making.

Good models eschew some complexity. But complex domains aren’t simple. A model that aims to encompass a domain’s full complexity will likely fail at building shared understanding. But a model that over-simplifies won’t be useful.

Striking the right balance requires considering granularity. How much detail should the model represent? At what level do you stop zooming? Do you dive more deeply into one part than others? How do you define these different levels?

Another tricky consideration is fidelity: the degree to which the model accurately describes the domain and demonstrates confidence in those descriptions. This calls for crisply rendering key distinctions and relationships using correct (i.e., broadly agreed) labels.

The first sketches of a new model should be low-fidelity and have low granularity. They're often hand-drawn sketches, which communicate a low degree of confidence in the model.

This low confidence is merited. In the beginning, you don’t know enough about the domain to assert anything firmly. Instead, you make a shitty first draft. The aim is to start an evolutionary process: make a sketch, get feedback, make another sketch, etc.

Confidence in the model builds over time as you test it against others’ understanding and real-world conditions. As you do, you make new versions with greater fidelity and granularity. The final result is a clear, crisp, appropriately detailed hardline drawing.

The challenge is that early low-fidelity/low-granularity sketches may not communicate with enough clarity or accuracy to elicit helpful feedback. So, you may be tempted to make ‘clean’ artifacts early on, which don’t accurately reflect your degree of understanding.

Because polished artifacts convey higher confidence, the team may be lured to believing these incipient versions of the model are ‘correct.’ It's a dangerous trap. High confidence in bad models can lead to disastrous decisions.

One solution to the dilemma is to admit that, in a project’s early stages, clarity is in tension with certainty. Aim to be as clear as possible, but not more than is merited. Acknowledge there’s only so much you know, and focus on filling the gaps. Process > artifacts.

Tweet by Dan Brown

Worth Your Attention

  • The Iceberg model, a systems thinking tool to help you better understand why things happen.

  • Flexibility vs. ease of use. An example of a common systemic tradeoff when designing an information architecture.

  • Building bridges to understanding. What cam exotic ice cream flavors teach us about information architecture?

  • A series of tubes. Molly Wright Steenson on information technologies physical and digital. “The history of information has come unstuck in time.” — Indeed.

  • How I take notes. The latest entry in the series about my personal information ecosystem, wherein I describe how I compensate for my appaling memory.

  • Thinking with environments. Call for papers for an upcoming issue of The Side View, which will focus on the influence of Christopher Alexander’s work.

  • Data authoring environments. From our friends at Dubberly Design, a fantastic overview of “over 200 examples of computer software and hardware interfaces for authoring data and programs from the 1960s through the present day.” (PDF)

  • Aristotle and human flourishing. An inspiring podcast with Leon Kass about Aristotle’s ideas on how to live well.

  • All Things Shining. Sticking with the Western classics, I loved this book about how reading them helps us lead more meaningful lives.

  • Embrace the grind. “I often have people newer to the tech industry ask me for secrets to success. There aren’t many, really, but this secret — being willing to do something so terrifically tedious that it appears to be magic — works in tech too.” (H/t John Gruber)

The Informed Life with Jeff Sussna

Episode 61 of The Informed Life podcast features another conversation with consultant and author Jeff Sussna. I say ‘another conversation’ because Jeff was previously on the show talking about cybernetics. This time, he shares with us Customer Value Charting, a tool for balancing strategy and agility.

Jeff sees the process of creating customer benefits through the lens of promises: “an intention that may or may not actually come to pass.”Customer Value Charts allow us to map such promises visually, so we can discuss them.

The Informed Life episode 61: Jeff Sussna

Parting Thought

The urge for clarity will seduce people toward polarities and extremes because absolute statements are comforting. Clarity must be both compelling and simple — but not simplistic... Clarity is mandatory, but certainty is dangerous.

— Bob Johansen, Leaders Make the Future

Thanks for reading! 🙏
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