Once one of the most secret know-hows of Toyota's LEAN Engineering, the “Architecting” Design Engineering phase is now known as the biggest lever to improve the performance of next generation products and services. The major players are investing a lot in it; and this can easily be explained in a few points.

Making the right architecture choices is critical for your success

System Architecting has become too complex for the human brain -

even for the smart ones

Engineering teams need a new solution

Early engineering decisions are the main cost drivers for the end-product. This also highlights the importance of architecting decisions (by definition in the early phases of engineering design). Moreover, according to AFIS and industrial feedback, it is less known that early architecting decisions are the main trade-off drivers for the system. Indeed, Architecting choices will induce constraints that will cut off parts of the Design Space: some trade-offs will no longer be an option! More than 50% of overall trade-offs are unconsciously locked during early architecting choice. Why? Because system architecting has become too complex...

The human brain is able to manage about 7 criteria while making a decision. Design teams usually take into account 5 to 10 performance criteria (or requirements) when studying and then choosing a technical alternative. But need analyses as well as calls for tenders often involve hundreds of requirements; it is, from a human perspective, impossible to make the good decision. And this does not even consider the fact that design teams make choices from their own point-of-view… by discipline. While architecting a satellite, less than 20% of expectations are considered, the rest is RISK taking!

Today, an engineering team iterates to make the product or service satisfactory, with no assurance that the solution is optimal regarding the original problem setting.

With the right Architecting enablers, System Engineer and Design Team would:

  • Explore more alternatives, including innovative ideas,

  • Assess more performance criteria and consider the entire product life cycle,

  • Make informed decisions regarding need and technical trade-offs,

  • Reduce (not probably avoid) the number of iterations to find a feasible architecture,

  • Understand if innovation will actually bring value to the system,

  • Extract point-of-views for any stakeholder all along value chain,

  • Define and optimize a product line,

  • Improve the collaboration between disciplines.

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