Procedure
Processes
Procedures that, together with technology, provide the key knowledge for achieving the result. In production systems that use processes, people "help" the process.
Example: industrial production lines use processes. The person learns to execute the process and to supervise it; the knowledge lies in the process, not in the person.
Practices
Procedures that help the person work more efficiently. The person provides the tacit knowledge that is key to the result; the procedure reduces the burden of routine activities.
Example: agile methodologies (Scrum, Kanban, XP) are practices. The value of the outcome depends on the knowledge and creativity of the team; practices are a guide, not the engine of the outcome.
Why the distinction matters
This distinction is central to the value proposition of agility. The process-based models of software engineering (CMM, ISO 9000, ITIL) assumed that quality could be systematized into processes. Agility proposes that in environments of high uncertainty and innovation, quality depends mainly on people's tacit knowledge, and procedures should help people, not replace them.
This distinction is especially relevant today with generative AI: AI tools can automate parts of processes, but tacit knowledge—professional judgement, understanding of context—still resides in people.
Common mistake
Treating agile practices as processes. When a team applies Scrum mechanically—holding the events because "it's time," without judgement about what makes sense in its context—it turns practices into processes and loses the benefit that practices provide. Expert management consists precisely in knowing when to adapt practices to the context.
See also
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