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 consideration is fidelity: the degree to which the model accurately (and confidently) describes the domain. 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. You don’t yet know enough to assert anything firmly. Instead, you make a shitty first draft. The goal: to start an evolutionary process. Make a sketch, get feedback, sketch again, etc.
Confidence in the model builds as you test it against others’ understanding and real-world conditions. As you do, you make new versions with greater fidelity and granularity. The end result is a clear, crisp, appropriately detailed 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 is to admit that, in 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.
This post first appeared in my newsletter.
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