Consumer Goods
Within Consumer Goods, a broad range of activities may qualify for R&D Tax Credits where competent professionals are seeking a technological advance and the solution is not readily deducible. This can include developing or materially improving product formulations and processing methods where functional performance, consistency, shelf-life, safety, and manufacturability must be achieved together at scale, rather than through routine recipe changes or standard line settings. It may also include advancing production line capability and systems integration (e.g., improving throughput, reducing waste, stabilising quality, or upgrading legacy digital/operational control) where standard OEM approaches or typical operating windows don’t deliver reliable, repeatable outcomes in live manufacturing conditions.
How our skillset can help you claim
Consumer goods development is often driven by the need to meet stringent product specifications while managing variability in ingredients, process conditions, and factory constraints. Our specialist team works directly with your technical staff to define the advance being pursued, set a clear baseline against established practice, use trial and production results to support the iterations made, and separate qualifying development from routine manufacturing, standard QA, or day-to-day process tuning. We then set out the development work in a clear and compliant narrative, supported by a practical and defensible approach to cost capture, helping you secure funding to reinvest in capability and product performance.
Project Examples
A potential advance is achieving a target nutrient performance characteristic in a food product that isn’t reproducible using existing recipes or known processing logic. Progress is shown through controlled formulation iterations supported by comparative testing and consistent end-product results.
Projects may seek to increase prodcut manufacturing throughput or reduce waste while keeping quality within specification when equipment behaviour and process dynamics become unstable at higher rates. The advance is demonstrated through iterative changes to process design, manufacturing parameters, and controls that deliver repeatable performance in live runs.
Some work focuses on making production data capture and control more reliable, especially where legacy systems or standard tools don’t support the needed validation, visibility, or automation. The advance lies in proving dependable end-to-end behaviour across real factory scenarios, not just a one-off implementation.
