Optimisation

✅ What this stage is about

Optimisation is about making everything better—smarter, leaner, and more sustainable.

The Optimisation stage focuses on improving the product, process, or system after it's already working. It involves analysing data, reducing waste, increasing efficiency, and resolving recurring issues. You’ll iterate designs, engineering details, and production steps—balancing quality, performance, and cost. Optimisation isn’t just tweaking—it’s structured improvement with clear constraints.


📘 What you’ll manage

  • Where bottlenecks, inefficiencies, or recurring issues are costing you
  • What improvements reduce lead times, defects, or user complaints
  • How your product or workflow can be simplified or standardised
  • What data from usage, testing, or production guides decision-making
  • How iteration loops are planned and completed within budget

🛠️ Tools and methods

🔄 Iteration Loops in Optimisation

There are two key iterative loops in the IEN development model:

Loop TypeCycle StepsPurpose
Design LoopConcept → Design → Engineer → RepeatEvolve ideas into detailed, feasible outputs
Build-Test LoopEngineer → Build → Test → RepeatResolve performance, usability, or compliance risks

Each loop continues until the output is “refined enough” for sign-off.

🛑 The limit isn’t perfection—it’s the budget.

✅ The Definition of Done (DoD) in the Specification Sheet should clearly define when to stop refining and start finalising.

Additional Optimisation Tools

ActivityPurpose
Process mappingIdentify where time, cost, or quality is lost
Lean / 5 WhysFind and address root inefficiencies
User behaviour data reviewImprove user journeys or feature flow
Quality issue trackingResolve recurring product or process failures
Sustainability improvementLower waste, material impact, or carbon footprint
  • Combine engineering judgement, user data, and cost analysis
  • Track each change: what it fixes, what it affects, and what it costs

⚠️ Watch-outs

  • Iterating without a defined stopping point
  • Changing specs without updating documentation or test plans
  • Over-optimising before reaching a stable baseline
  • Ignoring user, supplier, or compliance feedback

💡 Tips from the field

“We iterated the clip design six times—but the final fix took 20 minutes. It’s not about how many loops—it’s knowing when to stop.”

– Senior Mechanical Engineer, Wearables Manufacturer

💡 Know your DoD before you start optimising—or you’ll never stop.


🔗 Helpful links & resources

  • Optimisation Loop Tracker
  • Download: Iteration Log + Definition of Done Template
  • Tool: UX Data–to–Change Sheet
  • Article: When to Stop Iterating – Budget-Driven Optimisation for Product Teams

✍️ Quick self-check

Are we tracking each design or test loop clearly?
Is our Definition of Done (DoD) linked to spec and signed off?
Do our improvements reduce cost, time, or failure risk?
Are we measuring optimisation efforts—not just making changes?

🎨 Visual concept (optional)

Illustration: Two circular loops—Design Loop (Concept → Design → Engineer) and Build-Test Loop (Engineer → Build → Test)—both feeding into a DoD checkpoint box with a green flag labelled “Stop Here”. Budget slider bar shown underneath.

Visual shows how optimisation loops function inside controlled boundaries—focused on smart improvements, not endless revision.

🔄 Next Steps for Content Creation

Add visual: “Dual Iteration Loops + DoD Gate”
Link subpages: Design Loop, Build-Test Loop, DoD in Specification
Create Optimisation Toolkit (Iteration Log, Budget Tracker, DoD Guide)
Option: Connect to future page – V2.0 Planning or Scaling
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