Introduction
First-principles process compression is the practice of stripping onboarding and workflows down to what is truly necessary. Instead of inheriting processes, you ask what must be true for a person to function effectively. Everything else is negotiable. This method treats complexity as a cost, not a default.
The Compression Question
The core question is: what is the smallest set of concepts and actions that produces competent behavior? You can think of it as building a minimal viable mental model. If a new hire knows only these essentials, can they act effectively and safely?
Decomposing the Process
You break a process into its atomic steps and identify which steps carry information and which steps merely carry habit. Often, you discover redundant approvals, repetitive communications, or rituals that no longer serve a purpose.
Encoding the Essentials
Once the essentials are identified, you encode them into concise formats:
- One-page maps.
- Short decision rules.
- Minimal checklists.
You avoid long narratives unless they provide unique context. Compression is about reducing entropy, not removing meaning.
The Role of Constraints
Some complexity is irreducible due to regulatory, safety, or technical constraints. Compression doesn’t eliminate those; it clarifies them. When constraints are explicit, new hires understand why certain steps exist and are less likely to treat them as arbitrary.
Example
Consider a product release process with 12 steps. Compression might reveal that only three steps prevent serious failure: dependency checks, security review, and rollout monitoring. The remaining steps can be reduced to optional checks or automated. The onboarding content then focuses on the critical three, with optional depth for the rest.
Risks
Compression can oversimplify if done carelessly. The key is to preserve the causal structure: the reasons behind steps. A compressed process without rationale becomes brittle. So you keep minimal explanations that preserve intent.
Going Deeper
Process compression is not about minimizing effort; it is about maximizing signal. When you do it well, you create systems that are easier to learn, harder to misuse, and more adaptable.