Redesigning a School Bag for a Client Who Cannot Test It

With direct user research unavailable, she should treat the warranty log as her strongest evidence and the photographs as secondary, then be explicit about what remains assumed.

• Warranty log = observed failure data. 62% strap stitching, 21% main zip, 9% base water ingress. This is real-world use data collected over time, and it outranks opinion because it records what actually broke. It reframes the problem from 'make a nicer bag' to 'make a bag that survives adolescent use'. That is a defensible, evidence-based problem definition.
• Photographs = context of use. Thirty bags show how students actually carry loads: over one shoulder, straps dangling, bags on the ground, oversized loads. She can code these observations (e.g. 'strap length adjusted to maximum in 18 of 30') without speaking to anyone.
• School requirements = constraints, not needs. Laptop fit, colour and $45 cost are fixed boundaries the design must satisfy; they do not tell her what to prioritise.
• Explicit assumptions. She must state what she is inferring - e.g. that strap failure is caused by point loading at the adjuster rather than by total load - and flag these as hypotheses to test with the prototype.

This is the key judgement: when user access is limited, she should not invent user quotes or claim empathy she has not gathered. She should rank evidence by reliability and name her assumptions.

Spend the prototype on the highest-frequency, highest-uncertainty failure, not on the whole bag.

• Target the strap–body junction (62%). It is the dominant failure mode and the one where the cause is least certain (stitch type, reinforcement, adjuster placement, load path). A prototype that resolves it delivers the largest reduction in returns per dollar.
• Build a focused test piece, not a finished bag. A strap-and-panel assembly with two or three junction variants lets her compare stitch patterns, bar-tacks and reinforcement under load in the workshop. Load-test to failure and record where it fails. Three variants tested beats one whole bag admired.
• Use off-the-shelf components for the rest. A stock main zip and a coated-base fabric address the 21% and 9% failures with known, low-risk solutions that do not need prototyping time.
• Keep a decision log. Record what was tested, what failed and what changed, so the next iteration is evidence-driven rather than taste-driven.

Justification: with one prototype, breadth is unaffordable and depth is not. Concentrating resources where failure is most frequent and least understood maximises information gained per dollar, which is the correct trade-off under a hard constraint.

She should argue in life-cycle terms, using the returns data as the basis.

• Failure has a cost. A 62% strap-stitching return rate means the school and supplier are already paying for replacement, postage and administration. If a reinforced junction and a better zip reduce returns substantially, the effective cost per student falls even though the unit price rises.
• Quantify where possible. If returns cost, say, $12 per returned bag in handling and replacement, then a return rate falling from roughly one in five to one in twenty saves more per student than the $7 increase.
• Separate must-haves from cost drivers. Laptop fit, colour and durability are requirements; the $45 figure was a target, not a constraint handed down by the client's finance team in the scenario. She should present the $52 option alongside a $45 option that keeps the old junction, and state plainly what the cheaper option costs in returns.
• Be honest about uncertainty. The savings estimate rests on the assumption that the new junction fixes the dominant failure; the prototype test should be cited as partial evidence, not proof.

This is the professional judgement the exam rewards: designers should present trade-offs with evidence rather than either silently exceeding the budget or silently accepting a design that will fail.