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Senior academics are ultimately accountable for research quality. However, it is technical staff who orchestrate much of the day‑to‑day field and laboratory practice and safety, software reliability and data stewardship. And their practices often sit outside traditional research leadership training, even though learning with or from technical staff, and properly recognising their contributions, can yield  in rigour, reproducibility, efficiency and collaboration.

So, what can researchers gain when they look to technicians for best practice and guidance?

Learn how to manage quality and risk from technical facilities staff

Technical facilities staff at universities design methods, train users and act as independent quality controllers. are: laboratory instruments, core technicians, training of technical staff and research community, career tracks, technical support, a supportive research community, and transparency in how the technical facility works and associated costs. These must be supported by an institutional foundation of clear policies, guidelines and leadership approaches.

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The four practical levers for rigour are: motivating adherence to best practice, explicit data management guidance, clear responsibility boundaries and improved communication along the entire experimental pipeline. These are teachable routines that principal investigators can adopt in groups.

Staff in technical facilities can teach researchers to manage quality and risk by training them to cost research activities, use calibrated instruments and robust practical routines, and offering guidance on career pathways. This provides best practice, explicit data management, defined responsibilities and end-to-end communication.

Researchers learn that technical facilities’ quality management systems – standard operating procedures, process-mapping and internal audits – lead to improved laboratory practices, more reliable results and enhanced access to funding opportunities.

Learn reliability from research software engineers

Research software engineers (RSEs) build and maintain the code that analyses data and runs instruments. – version control, modular testing, continuous integration – reduces errors and accelerates analysis. These habits also make coding reproducible, speed up iteration and facilitate trust with collaborators. 

Learning from RSEs works best when it is practical and iterative. It starts with supervised practice followed by formalisation of competence with assessments. Improvements are sustained through training around documentation, peer support and feedback. Adopting these habits – standardisation, verification and transparent record‑keeping – turns training into lasting reductions in error and risk.

Learn to collect robust, reproducible data from data stewards

Embedding data stewards has helped universities move from open science aspirations to more effective research data practices. Data stewards are faculty‑based experts who provide advice and support for research data management, tools, storage, sharing and funder compliance. 

of faculty‑embedded stewards, faculty‑specific data policies and researcher‑first consultancy shows how to normalise data management plans, metadata, repository selection and consent workflows across disciplines.  when stewards are resourced to provide support. Researchers learn tailored data management practices via training from stewards. This improves reproducibility, sharing and compliance.

Learn sustainability-focused laboratory practices from technicians

Laboratories can about 10 times more electricity than a typical campus space. Technician‑led initiatives such as My Green Lab , UCL’s laboratory efficiency assessment framework (Leaf) and Harvard’s Shut the Sash deliver quantifiable energy and safety improvements such as changing equipment settings, cold storage management and fume hood behaviours.

One way to put these guidelines into practice is  of green laboratory programmes (for example, Leaf v My Green Lab) to consider measurable behaviour change and emission savings alongside caveats about implementation gaps. These findings can be used to prioritise high‑impact actions rather than superficial wins.

Learn the business benefits of shared infrastructure

Sharing infrastructure consolidates expensive instruments and scarce expertise, lowering per‑experiment costs and catalysing cross‑disciplinary projects.  argue for central governance, service catalogues and explicit staff categories (such as scientific technical experts) to keep these platforms viable. 

Researchers learn that shared infrastructure concentrates instruments and expertise, lowering costs and enabling projects and access through governance, service catalogues and defined staff roles. Observing this practice shifts behaviour towards platforms, standardising requests, prioritising scheduling and maintenance, and collaborating rather than duplicating resources.

Learn how recognition and authorship can shift research culture

The UK Technician has driven sector‑wide changes in visibility, career pathways and governance for technical staff. Institutions report progress when technicians sit on decision‑making committees and when leadership invests in structured development. The CRediT contributorship should be adopted so specialised roles in areas such as software, data curation, resources and validation are documented in a research paper’s metadata. Most research publishers now expect transparent contribution statements, and CRediT is a widely implemented ANSI/NISO .

How to adopt good practice in 90 days

Over 90 days, university leadership teams can turn intentions into routine practice. In weeks one and two, map the technical ecosystem (list core facilities, name the RSE and data steward contacts and lead technician), schedule knowledge‑transfer sessions. In weeks three to six, categorise and test practice; adopt and document a standard approach via a reproducible template, pilot a data steward checklist on a live project, and implement two technician‑recommended sustainability changes with monitoring. In weeks seven to 10, formalise collaboration with a service‑level memorandum covering scope, costs, data ownership and acknowledgement. Pre‑agree CRediT contributor roles for research manuscripts. In weeks 11 to 13, close the loop with a review process to capture quick wins and improvements, reruns avoided and energy saved. 

To extend the gains, invite technical staff on to research and education committees and on to equipment and hiring panels, aligning practice with Technician Commitment principles.

Why this is not optional

Team science  from the US National Academies emphasises explicit charters, inclusive communication and project management discipline as hallmarks of high‑performing interdisciplinary teams. These are capabilities that technical staff practise daily and can teach quickly if invited.

Making these partnerships visible – in governance, budgets, training and authorship – improves research quality and helps sustain the infrastructure and people that make ambitious work possible.

Ian D. Williams is professor of applied environmental science in the Faculty of Engineering and Physical Sciences at the University of Southampton.

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