By the end of this topic, you should be able to...
use data generated from relevant testing and/or reverse engineering to identify areas of the product that require improvement and to determine how well the product meets the needs of the user.
Guiding Question
How does product analysis and evaluation inform various stakeholders and aid in a product’s future development?
💡 Did You Know? Samsung's Galaxy Fold launched at $2,000 in 2019—and broke within days for reviewers who peeled what looked like a screen protector but was actually the essential display layer, because usability testing data never revealed this critical user error.
Why Data-Driven Design?
Opinions are cheap; data is priceless. When you test products systematically—measuring grip force requirements, drop-test impact survival, button press accuracy rates, task completion times—you replace "I think this works" with "Users failed this task 73% of the time."
When you reverse engineer products—disassembling them to analyze component choices, measure tolerances, map assembly sequences—you uncover why designers made specific decisions and where those choices succeeded or failed. Data transforms vague feedback ("this feels awkward") into actionable insights ("grip diameter of 38mm requires 12N force for 85th percentile users; reducing to 32mm drops force to 7N").
This evidence-based approach reveals function failures (mechanisms jamming after 200 cycles), performance gaps (thermal throttling under sustained load), and usability breakdowns (80% of users press the wrong button first)—objective truths that qualitative interviews miss. Without quantitative testing data and structural reverse engineering insights, you're designing blindfolded, guessing which improvements matter most.
Case in Point
When iFixit reverse-engineered Apple's AirPods Pro, they discovered a fatal performance flaw: the non-replaceable battery degraded after 18 months, but the device was sealed with adhesive that destroyed components during disassembly—a 0/10 repairability score. This testing data (adhesive bond strength measurements, component lifespan analysis) identified a clear improvement opportunity: modular construction with mechanical fasteners would enable battery replacement, extending product life 5× while meeting growing right-to-repair regulations—insights impossible without systematic reverse engineering.
Learning Goals
In this topic, you'll master testing protocols and reverse engineering methodologies to generate objective data—learning to measure function, performance, and usability quantitatively, interpret results critically, and use evidence to prioritize design improvements in your IA project.
Linking Questions
Which aspects of ergonomics are vital to establish when analysing the usability of products? (A1.1)
To what extent does the evaluation of products rely on user-centred research methods? (A2.1)
How does the product analysis and evaluation of products that include mechanical and/or electronic systems differ from products without those systems? (A3.3, A3.4, B3.3, B3.4)
Why is it important to know which manufacturing techniques were used to make a product when conducting product analysis and evaluation? (A4.1)
To what extent is product analysis a fundamental aspect of the design process? (B2.1)
To what extent does material selection have an impact on the success of a product? (B3.1)
What types of information can designers gain from product analysis and evaluation in relation to production systems? (B4.1)
Why is it the responsibility of the designer to learn from product analysis and evaluation tasks when redesigning products? (C1.1)
What is the relationship between life-cycle analysis and product analysis? (C3.2)