Sequential engineering
Description
In sequential engineering, the workflow moves in only one direction: forward. If an error is detected during the process, it is necessary to go back to the stage where it originated in order to fix it, which may mean redoing work already completed in later phases.
It is a relatively slow process, but one that requires little cross-disciplinary coordination effort. Each department hands its work over to the next with minimal overlap: "You build what I design, and he sells what you build."
When it makes sense
Sequential engineering is not universally inappropriate. It makes sense in contexts where:
- Requirements are stable and well known from the outset, and are very unlikely to change.
- The cost of an error in production is so high that it justifies exhaustive verification at each phase before moving forward.
- Industry regulations require detailed documentation of each phase (aeronautics, medicine, defense).
In these contexts, the rigorous control imposed by the sequential model is an advantage, not a drawback.
Limitations in Uncertain Environments
In projects where requirements evolve during development—which is the norm in software and digital product development—sequential engineering has significant limitations:
- The customer sees nothing working until the end of the project, when it is already too late to correct errors in approach.
- Changes to requirements, which are inevitable in long projects, are costly to incorporate because they force the team to go back up the chain.
- Risk is concentrated at the end of the project: that is when it becomes clear whether the product does what the customer needed.
These limitations are what drove the development of iterative and incremental approaches: first concurrent engineering, and later agility.
Common mistake
Presenting sequential engineering as an outdated model without nuance. It is true that in software and digital product development it has been displaced by more adaptive approaches, but it remains the right model in sectors with stable requirements and heavy regulation. Understanding its limitations—and the contexts in which it is valid—is part of understanding why agility emerged.
See also
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