2 min read

Stop testing everything the same way.

Stop testing everything the same way.

Your systems are unpredictable but your testing philosophy doesn't need to be.

Composable commerce, third-party APIs, real-time pipelines, AI-driven logic... there's an infinite number of possible states so why are retail tech teams still applying the same testing philosophy across everything?

Retail engineering teams have done far more than just accumulate complexity. They've now become unpredictable and traditional QA can't keep up.

The result is a growing blind spot. Systems that look stable in staging fail unexpectedly in production. Edge cases aren't rare, they're the system. And the cost isn't just defects; it's slower shipping, constant firefighting and a quiet erosion of trust in every release.

Teams need a shared model for how confidence should scale with risk and we believe our Graded Test Approach is the answer.

"The big question becomes: How do we apply the right level of scrutiny, visibility and resilience based on where this system sits on the Graded Test Approach?"

Darryl Kennedy

 

The Graded Test Approach at a glance

Stage Stage name Signal
G0 Personal Utility "If it breaks, I shrug"
G1 Shared Team Tool "If it breaks, someone pings me"
G2 Internal Dependency "If it breaks, work stops"
G3 Customer-Facing "If it breaks, customers notice"
G4 Mission Critical "If it breaks, we lose money or trust"

 

Not all failures carry the same consequence

A G1 internal tool breaking is an inconvenience but a G4 checkout flow breaking is a revenue event. Treating them with the same testing philosophy is how teams either over-engineer too early or under-protect what actually matters.

Our Graded Test Approach makes something explicit that most teams handle implicitly: different systems deserve different levels of testing, and different failures carry different consequences.

As a service moves from G0 to G4, the expectation shifts to a fundamentally different release posture, observability requirement and evidence of control.

At G3, you need a go/no-go decision with the right people reviewing test evidence. At G4, it's something closer to a formal change board: because if you've done a major marketing push and gone live with an enterprise-wide release, pulling it back is a business decision as much as a technical one.

Download the full Graded Test Approach

In detail: G0 through G4, release posture, observability expectations, and how it sits alongside Spike's FLOW methodology.

 

Precision over completeness

In this new world, exhaustive testing is a false goal. Instead, you've got to question what failure means at each stage, and what the team is willing to tolerate. That's a risk judgement, and the Graded Test Approach gives it a structure.

For a CTO, the shift is subtle but important. Testing becomes a risk-weighted system of evidence with proportionate scrutiny, proportionate visibility, proportionate resilience. You need a common language for making decisions that scale with stakes, without creating bureaucracy for low-risk work or cutting corners on what genuinely matters.

Control comes from being explicit about confidence at each grade, before anything ships.

"Precision about what failure means at each stage is how teams regain control. Confidence scales with risk or it means nothing."

Steve Dennis

Where this fits in delivery

The Graded Test Approach sits alongside our FLOW methodology. FLOW governs how work moves through a team while the Graded Test Approach governs how much confidence is required before it does.

Together, they give retail technology teams a proportionate, evidence-based delivery system, one that scales with the complexity of modern composable environments without slowing down the work that doesn't need it.

The Graded Test Approach: a practical guide for retail technology teams

A six-page detailed walkthrough of each grade, what evidence of control looks like at each stage, how to apply proportionate release posture, and how the framework integrates with real delivery workflows.

Built for CTOs, engineering leads, and QA principals navigating AI-assisted, composable-commerce environments.

 

Related posts

The challenges for retail

1 min read

The challenges for retail

The retail sector has faced ongoing disruption in recent years with the rise of ecommerce, click-and-collect, next-day and even same-day deliveries....

Read More
What retail tech leaders are talking about: Retail Jam 2026

1 min read

What retail tech leaders are talking about: Retail Jam 2026

A day at Knebworth Park. Two roundtables, dozens of frank conversations, and one big question hanging over the room: what happens to quality when AI...

Read More
De-risking complex retail tech stacks

1 min read

De-risking complex retail tech stacks

The retail tech stack is growing – but so are your risks. Here's how to stop it becoming a mess. The recent Retail Technology Show in London had so...

Read More
Making UAT more agile: Functional slicing

1 min read

Making UAT more agile: Functional slicing

In the first article in this series, we looked at why UAT fails and what good looks like at a structural level. This article goes deeper on one of...

Read More
Moving to continuous delivery in retail without increasing risk

1 min read

Moving to continuous delivery in retail without increasing risk

In our recent article around the “good enough” debate, we explored the tension between speed and quality in retail digital delivery. If you’re...

Read More
The Shopify project that's harder than it looks

1 min read

The Shopify project that's harder than it looks

For most retailers, moving to Shopify looks straightforward on paper. The front end is clean, the configuration is fast, and the platform's...

Read More