How to Identify and Document Scientific or Technological Uncertainty for HMRC

A practical method for evaluating the technical evidence behind an R&D claim

Last reviewed 27 October 2026

Scientific or technological uncertainty is central to UK R&D tax relief eligibility.

However, identifying a difficult technical problem is not enough. Businesses also need to establish what was known at the relevant time, why established methods could not readily resolve the problem and what investigations were undertaken.

This guide focuses on how to assess and document an individual uncertainty, rather than repeating the general eligibility rules.

For the broader HMRC qualification criteria, see R&D Tax Relief Eligibility.

1. Describe the uncertainty as a specific technical question

A common weakness in R&D documentation is describing the business objective rather than the underlying uncertainty.

Consider these two statements.

Business objective:

"We wanted to develop a more durable industrial coating."

This explains the intended product improvement, but not the technological uncertainty.

Technical uncertainty:

"Could the required adhesion and corrosion resistance be achieved simultaneously under repeated thermal cycling when established coating methods did not provide a readily deducible solution?"

The second statement identifies a question that could require scientific or technological investigation.

It still requires evidence that the uncertainty was genuine and could not readily be resolved by a competent professional.

2. Establish the relevant technical baseline

Before evaluating uncertainty, describe the scientific or technological knowledge and capabilities available at the relevant time.

The baseline should consider the wider field, not only what your own company knew.

Relevant evidence may include:

  • Scientific publications.
  • Technical standards.
  • Engineering handbooks.
  • Existing industrial methods.
  • Publicly available technical reports.
  • Established algorithms or technological approaches.
  • Knowledge of suitably experienced professionals.

For each source, record its publication date, relevant findings and technical limitations.

Avoid treating an unfamiliar technology as an uncertainty merely because your team has not used it before.

Why the baseline matters

Suppose a company attempts to increase the durability of a coating.

If an established industry method already achieves the required performance and a competent professional could readily apply it, the challenge may not constitute qualifying uncertainty.

If the existing methods have demonstrated limitations and it is not readily deducible how to overcome them, further assessment may be justified.

The technical baseline provides the foundation for making that distinction.

3. Identify the correct baseline date

Three different dates may be relevant to an R&D project.

DatePurpose
Uncertainty identification dateWhen the company first recognised the technical problem
R&D activity start dateWhen qualifying work to resolve the uncertainty began
Evidence assessment dateWhen the company later reviewed or documented the available evidence

These dates should not automatically be treated as identical.

Example

On 10 January 2026, an engineering company recognises that an existing process may not achieve the required performance.

On 3 March 2026, the technical team begins experimental work intended to resolve the uncertainty.

On 20 October 2026, the company reviews published research while preparing its R&D claim information.

The relevant technical baseline should reflect the knowledge and capability available when the qualifying R&D project began.

If qualifying feasibility or investigative work actually started in January, the earlier date may be relevant. The start date should therefore be determined from the activities performed, not selected merely to match a later testing milestone.

The October review can help reconstruct the historical baseline, but later scientific discoveries should not be incorrectly presented as knowledge that was available at the earlier date.

4. Test whether the solution was readily deducible

The key assessment is whether a competent professional working in the relevant field could readily determine how to resolve the uncertainty using existing knowledge.

A useful technical review asks:

  1. Which established solutions were available?
  2. Were those solutions applicable to the required technical conditions?
  3. What specific limitations prevented their use?
  4. Could a competent professional reasonably deduce a solution without further scientific or technological investigation?
  5. What additional investigation was necessary to determine whether the intended advance could be achieved?

The review should distinguish between an inability caused by the company's own knowledge or resource limitations and an uncertainty affecting the relevant field of science or technology.

A technically demanding project is not automatically qualifying R&D.

5. Use published research to test your explanation

A literature review can help identify whether a claimed uncertainty is supported or contradicted by existing technical knowledge.

A useful review includes:

Source identification: Publication title, author, publication date and DOI or other traceable reference.

Relevant findings: What the research demonstrates about the technical problem.

Applicability: Whether the published methods apply to the company's particular technical conditions.

Limitations: What remains unresolved or cannot readily be deduced.

Professional conclusion: Whether the evidence supports the claimed uncertainty and why.

Research evidence can identify weaknesses in a company's explanation. For example, a publication may demonstrate that a supposedly unresolved problem had already been addressed using an established method.

This is a valuable finding even if it reduces the scope of the potential R&D claim.

The absence of a published solution is not proof of qualifying uncertainty. Published research is one source of evidence, not a substitute for professional knowledge of the field.

6. Record the investigation and results

Once the uncertainty has been assessed, document the technical work undertaken to resolve it.

For each significant investigation, record:

  • The hypothesis or technical approach.
  • The purpose of the investigation.
  • The methods used.
  • The measurements or observations.
  • Unexpected results and failures.
  • Changes made in response to the findings.
  • The conclusions reached.

A record such as "testing was performed for six weeks" does not explain the technical investigation sufficiently.

A stronger record explains what was tested, why the test was necessary, what was learned and how the findings affected the next steps.

7. Determine when the uncertainty ended

The qualifying R&D period does not necessarily cover the entire commercial project.

An uncertainty may end when the required technical capability has been established or when work to resolve it ceases.

For example, the company may establish a technically viable coating process in June, then spend another four months preparing commercial production.

Those later activities do not automatically qualify simply because they belong to the same project.

If a separate scientific or technological uncertainty emerges during implementation, it should be assessed and documented on its own merits.

This distinction is important when connecting project activities with proposed R&D expenditure.

8. Obtain the competent professional's assessment

The final technical explanation should be reviewed by a person with suitable experience and knowledge of the relevant field.

The professional should explain:

  • What scientific or technological advance was sought.
  • Why the technical uncertainty was genuine.
  • Why the solution was not readily deducible.
  • How the investigation addressed the uncertainty.
  • What was learned and whether the uncertainty was resolved.

The assessment should identify the professional's relevant background and involvement.

It should reflect their genuine technical judgement rather than merely approving an automatically generated explanation.

9. How Lister AI helps evaluate technical uncertainties

Lister AI assists businesses in reviewing scientific or technological uncertainties using structured, HMRC-aligned questions and relevant published research.

It helps identify gaps in the technical baseline, assess whether explanations are sufficiently supported and recommend areas requiring clarification.

This can be particularly useful when businesses are preparing retrospective evidence and need to distinguish what was known at the time from subsequent developments.

Lister AI does not certify eligibility or replace the judgement of competent technical professionals.

Better R&D evidence starts with a clearly defined and technically supported uncertainty.

Official HMRC references

This is practical documentation guidance, not a determination of HMRC eligibility.

Published by: Plio — Paylists LTD

Prepared and reviewed by: Muly Zohar, Founder & Product Architect

Last published:

Sources: Official HMRC guidance and other references linked in this article.

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