A proposed system can look convincing before its most important assumption has been tested. A diagram may show a legacy application returning information through an API, while nobody knows whether the application can provide that information quickly enough or without disrupting its existing workload.
A proof of concept, or POC, is a bounded experiment that investigates whether an approach is feasible under defined conditions. Its purpose is to produce evidence for a decision before the organisation commits to broader implementation.
Consider a team proposing a customer portal over an older account-processing system. The portal design is straightforward. The uncertain part is whether account information can be retrieved with acceptable performance and isolation while scheduled processing continues.
That uncertainty should shape the POC. Building a polished portal around an untested integration would answer a less important question first.
Define the Assumption Before Building the Demonstration
A useful experiment begins with a claim that could turn out to be wrong. For the portal, the claim might be that the proposed adapter can retrieve an account summary under representative concurrent load without materially degrading the scheduled workload.
The team then needs to specify what those conditions mean. Which account types are included? What workload is representative? How will degradation be measured? What level of freshness does the portal require?
- Identify the uncertaintyState the assumption that needs to be tested.
- Define the evidenceDecide what result would help assess that assumption.
- Run a representative experimentUse the smallest experiment that contains the relevant difficulty.
- Assess results and limitationsRecord what the experiment establishes and what remains unknown.
- Choose the next stepProceed, revise the proposal, investigate further, or stop.
This sequence makes the demonstration accountable to a question. A successful screen recording cannot substitute for the evidence the experiment was designed to collect.
Agree on Success Criteria in Advance
Criteria should describe both the desired result and the conditions under which it must hold. For an illustrative POC, the team might agree on the following:
| Question | Evidence to collect |
|---|---|
| Does the adapter return correct values? | Comparison against approved account examples |
| Is performance acceptable? | Response-time distribution under the agreed workload |
| Does it affect existing processing? | Comparison with a baseline scheduled run |
| Can failures be recognised? | Behaviour when the source is unavailable or returns incomplete data |
| Is access appropriately restricted? | Results for permitted and unauthorised requests |
The actual thresholds belong to the use case. Choosing a convenient number after seeing the results weakens the experiment.
Include a time and spending boundary. If the team cannot obtain representative data or an appropriate environment within that boundary, the finding may be that feasibility remains unresolved. That is more useful than quietly substituting an easier experiment and reporting success.
Keep the Scope Small Without Removing the Risk
A POC does not need the complete customer portal. A minimal client that requests an account summary may be enough to investigate the integration.
However, simplifying away the uncertain dependency defeats the purpose. A mock legacy service can help develop the interface, but it cannot establish the real system’s locking behaviour, data availability, or capacity.
Use synthetic or appropriately protected data where possible, and document how it differs from operational data. If the POC requires access to a shared environment, agree on limits and isolation before running it. A feasibility experiment should not accidentally become an uncontrolled production workload.
A useful boundary can also clarify the design. An anti-corruption layer translates between systems with different models and interfaces. A POC can investigate whether that translation preserves the meaning the portal needs, without implementing every future endpoint.
POC, Prototype, MVP, and Pilot Answer Different Questions
These terms overlap in practice, but distinguishing their purpose helps prevent misplaced confidence.
A POC investigates feasibility. A prototype explores a proposed design or interaction. A minimum viable product delivers a limited useful product to learn from real use. A pilot introduces a solution into a bounded operational setting to examine how it performs there.
For the portal, a clickable prototype could reveal that customers cannot find the information they need. The integration POC could show that current account summaries cannot be retrieved within the required time. A pilot could expose support and onboarding problems that neither experiment addressed.
One artifact may support several investigations. The important requirement is to state which questions it actually answered.
Preserve Evidence That Can Contradict the Proposal
The team building the POC has often invested in the proposed approach. That makes a repeatable evidence record valuable.
Retain the tested configuration, input characteristics, measurements, failures, and important exclusions. Compare the result with a baseline or alternative where that comparison affects the decision. Investigate unexpected success as well as unexpected failure: a fast response may come from a cache that does not meet the freshness requirement.
Review the findings with people responsible for the affected system. A satisfactory average response time might conceal a small set of expensive accounts or a slowdown during the busiest scheduled run.
The result should explain what was demonstrated, under which conditions, and what remains unknown.
A Successful POC Creates a Delivery Decision
Passing the experiment justifies a next step. It does not establish that the implementation is ready for customers.
The production plan may still need monitoring, deployment automation, credential management, accessibility, support procedures, recovery, and broader testing. Some POC code can be retained; some may be deliberately disposable. Assess it against delivery requirements rather than promoting it because it already exists.
For a legacy modernisation programme, the result might support a limited integration while ruling out a larger migration. A negative finding may save the organisation from committing to an unsuitable architecture.
A valuable POC leaves a smaller, better-understood uncertainty behind it. The evidence should make the next decision easier to defend, including a decision to stop.
Key Takeaways
- A POC tests a specific feasibility assumption under stated conditions.
- Define success criteria, scope, and limits before collecting results.
- Simplify the implementation without removing the dependency being investigated.
- Treat success as evidence for the next decision, with production requirements still explicit.
