• Supply chain issues, rising prices, and post-pandemic fatigue are among many factors making time an increasingly scarce commodity for most businesses.

    So, what if we told you that with some tweaks to the way you plan and prepare for an R&D tax relief claim, you could make your life a lot easier when it comes to submitting one?

    Understand your company structure and status

    Understanding your company structure and status for the purposes of an R&D tax relief claim is key and will affect whether you’ll be making a claim through the SME or RDEC scheme.  The outcome will impact both the expenses you’re eligible to claim for and the rate of relief you can receive. Changes to your size, structure, ownership or how you fund your R&D can all impact this and therefore it’s not a given that an upcoming claim will be made under the same scheme as a previous one. It’s better to know this sooner rather than later as it may influence decisions you make throughout the year.

    Implement good internal processes and record-keeping

    When working on what you believe may be qualifying projects, try to get into the habit of documenting key activities – such as the advances being sought, uncertainties faced and the outcome of tests. Even if you’re unsure, note it down anyway as your advisor will be able to look over these to see if there is any qualifying activity.

    Project management tools or online shared documents are a good way to do this; if your R&D lead leaves your business or isn’t available, for example, you’ll still need to access this information for your claim. Good record keeping will contribute towards building a robust claim capable of withstanding HMRC scrutiny. You can then also be confident that you’re receiving a fair return for your R&D efforts (not lowering or inflating the value of your claim).

    Communicate this best practice to your team to ensure that the burden doesn’t fall on one individual and that nothing is missed.

    As well as recording your qualifying activity you also need to identify expenses you’re incurring for R&D throughout the year. A good way of doing this is to highlight different projects in the accounting software you use (such as Xero) and tag invoices and receipts relating to a specific project. If you’re unsure how to do this your advisor should be able to help.

    As a reminder, the types of expenses you will incur relevant to an R&D tax relief claim are:

    • Payroll

    • Subcontractors

    • Externally provided workers

    • Utilities

    • Materials and Equipment

    • Software

    People-related expenses are usually a key R&D cost and one that many businesses struggle to accurately determine. Whether it be through payroll, clocking-in systems or timesheets you’ll want to keep track of who is working on these projects and when. It’s also important to clearly document the nature of the relationship with any external staff undertaking R&D, as HMRC will want to know the costs for any subcontractors and externally provided workers (EPWs) separate from that of your payroll.

    As with all activity and expenses, if you cannot accurately identify or define these you may be reducing the amount of R&D tax relief you can claim.

    Liaise with your advisor throughout the year

    Utilising your advisor’s expertise is another way to make your life easier when claiming R&D tax relief. Many businesses make decisions throughout a year that unknowingly impact their R&D tax relief claim – and often don’t realise until it’s too late.

    For example, using grant funding or subcontracting R&D are both common and can have an effect on the relief you’re able to claim. The key thing here is forward planning and getting good advice from the outset.

    Your advisor will also be able to keep you up to date with any rule changes that may affect your claim. From PAYE & NIC caps to changes in eligible expenditure and amendments to the schemes you need to stay abreast of.

    We’re here to help

    The appropriate and realistic amount of planning and preparation you’re able to achieve will depend on your individual circumstances. But we’d encourage you to communicate these best practices to your team and make sure you’re using an advisor that can be there all year round to provide the best advice.

    If you’re looking to make a claim or would like a second opinion on a claim you’ve already submitted, get in touch to speak with one of our advisers today.

  • Last week was the annual Advanced Engineering show, the UK’s leading gathering of OEMs and engineering supply chain professionals.

    As usual, the show was packed with great suppliers, leading innovations and inspirational talks from some of the best in the world of manufacturing and engineering.

    The themes coming out of the show were expected, and clear: successfully bridging digital and physical worlds presents huge opportunity; net zero must be prioritised but challenges remain; and, fundamental to both of these things, access to the right talent and skills is still a threat to the future of key productivity sectors.

    Matt Bradney, Director of Business Development for Prodrive Composites Ltd and Chair of the Composites UK Skills and Workforce Development Working Group, gave an inspiring short presentation on the Composites Engineering Forum stage on day 1 entitled ‘The Workforce Challenge’.

    In it, he painted a clear picture that most in technical sectors can agree on; the demand for apprentices and skilled operators will continue to outstrip supply if we don’t do more to bring people into the workforce.

    What is the issue?

    Particularly true of many sectors represented at Advanced Engineering, perception is a big issue when it comes to promoting STEM careers. However, that is changing – slowly.

    The most recent Deloitte and The Manufacturing Institute 2022 Manufacturing Perceptions Study shows that perceptions about manufacturing jobs are improving in the US, with 25% more people believing that said jobs are creative and innovative compared to the previous study in 2017.

    The study also points out one critical influencer on peoples’ perceptions: the Covid-19 pandemic.

    The effort manufacturers went to during the pandemic, pivoting operations to produce essential equipment and goods, and sustaining jobs, has left a lasting positive impression – with 61% of people saying their perception of the importance of US manufacturing has improved as a result of the pandemic.

    The Covid-19 legacy

    Although some may now be more aware of the importance of key skills like engineering and life sciences, that isn’t the only lasting legacy of Covid-19.

    The most recent ONS coronavirus statistics suggest that long Covid symptoms are affecting the day-to-day activities of around 1.6 million people in the UK. This is translating to the workforce, where one in 20 people neither employed nor seeking paid work are thought to be suffering from long Covid.

    It’s especially impacting those aged 50 to 64 years and 16 to 24 years, where economic inactivity due to long term sickness has been rising since mid-2021 (source: Employment in the UK October 2022 bulletin); in other words, those typically seeking trainee, graduate, and apprenticeship roles, and the very experienced.

    Digitisation

    That aforementioned aging workforce has also been seen as an issue; because of natural attrition through retirement and sickness, but also due to rapidly moving technology.

    Digital technology in both manufacturing and engineering isn’t new, but it is infiltrating more areas of the supply chain than ever before while demanding increasingly advanced capabilities.

    So, you can upskill an existing workforce, but there will be some areas that require training beyond what can be offered to everyone.

    Recruitment competition

    That brings us back round to the crux of the problem; there simply aren’t enough people training in the skills needed, and nor are there enough teachers to teach them.

    The 2013 Professor John Perkins’ Review of Engineering Skills by the then Department for Business, Innovation, and Skills called for the government to focus on teacher recruitment, but the follow-up in 2019 found this hadn’t gotten any better.

    It also found that the uptake of STEM subjects was still low despite efforts to promote them by a wider variety of public and private sector companies and campaigns; only around 5% of A Level students were studying physics (2019), for example.

    When you consider this against the backdrop of geopolitical unrest reducing access to overseas talent and skills, you can see why competition to attract skilled workers is fierce.

    It can be almost impossible for UK SMEs to attract people from this small talent pool when competing on salary, progression, culture, and benefits against large global companies with much deeper pockets.

    So what can be done?

    Certainly, for SMEs, more incentives to recruit apprentices or similar would no doubt be appreciated. But that’s only part of the story.

    The Engineering UK 2020 Educational pathways into engineering report outlines the following areas that need to be improved:

    • Diversity

    Females and those from socioeconomically disadvantaged backgrounds are vastly underrepresented among those progressing into engineering.

    Digital inequality is an issue, as is representation.

    • Curriculum presence

    Though STEM subjects are part of our curriculum, there’s a shortage of teachers, resources, and STEM career guidance in schools.

    Employers can do more to build links with their local schools and colleges to provide support and materials as well as work experience opportunities.

    • Support influencers

    Fewer than half of STEM secondary school teachers and under one-third of parents express confidence in giving engineering careers advice. Those who don’t have influencers from STEM backgrounds guiding them are of course disadvantaged here.

    • Policy development

    Educational reform has focused on STEM skills since the introduction of 2017s industrial strategy but it still needs work. Increasing apprenticeship standards have made training more expensive: estimates from the Learning and Work Institute suggest that the apprenticeship levy may not be enough to cover the training needed to deliver on these enhanced standards. New T Levels also face challenges, with some employers assuming technical, safety, and legal requirements make it difficult to take in students short-term to complete industry placements as requirements by T Levels.

    • Collaboration and stories

    Most industries have specific working groups now set up to help tackle some of the skills shortages and barriers to entry, but more can always be done.

    Seek out your local networks – by industry, skill, or geography – and speak to others about their recruitment experiences; build resources for parents, schools, and other employers that help break down the perceptions or barriers; and share more about what you do and the people that help make it happen.

    The onus here is not just on government, or industry, or educators, or parents – we can all do more to shape the future skills landscape, the question is – will you?

    Share your stories

    If you have a great innovation story to share, a star team member you want to highlight or a training success story that could inspire the next generation, email our team with the details and you could be featured here!

  • Lab automation is transforming the life sciences by enabling faster, more accurate results and allowing researchers to focus on higher-level tasks. However, implementing lab automation comes with challenges that can hinder its success.

    From ensuring interoperability with existing systems to managing costs and data accuracy, labs must navigate these obstacles to fully benefit from automation.

    In this blog, we explore the top five challenges in lab automation and provide practical solutions to overcome them.

    Interoperability with existing systems

    One of the most significant challenges labs face when implementing lab automation is ensuring interoperability between new automation and existing systems. Many laboratories rely on established workflows and legacy systems that may not be immediately compatible with the latest automation technologies. This lack of interoperability can disrupt workflows, cause data inconsistencies, and lead to increased costs.

    How to overcome it

    To tackle interoperability challenges, it’s crucial to choose lab automation solutions that are flexible and easily integrated with your existing systems. Look for cloud-first automation with open APIs (Application Programming Interfaces) that support standard data formats, enabling seamless communication between new and old systems. Collaborating with vendors who offer comprehensive support during the integration process can also help ensure smooth transitions and minimal disruptions.

    Ensuring data accuracy and integrity

    Data accuracy and integrity are vital in scientific research, and automation introduces new complexities in this area. Automated systems can generate vast amounts of data rapidly, but if the data is inaccurate or poorly managed, it can lead to flawed results and conclusions. Ensuring that data remains secure and unaltered during automated processes is crucial for maintaining scientific integrity.

    How to overcome it

    Implement robust data management practices within your lab automation workflows, including regular validation and verification steps. Utilise automation software that offers real-time monitoring and alert systems to detect anomalies. Built-in error-handling capabilities are a must. Establish strict access controls and audit trails to safeguard data integrity and ensure that all data changes are tracked and recorded.

    Managing costs

    While lab automation can lead to long-term cost savings by increasing efficiency and reducing labour costs, the initial investment can be significant. Labs may be hesitant to adopt automation technologies due to concerns about the upfront costs of purchasing new systems and training personnel.

    How to overcome it

    To manage costs effectively, start with a thorough cost-benefit analysis to identify areas where lab automation will have the most impact. Focus on automating high-throughput, repetitive tasks that yield immediate efficiency gains and cost savings. Consider a phased implementation approach, gradually introducing automation across different workflows to manage budgets better and assess ROI (Return on Investment) at each stage.

    Training and workforce adaptation

    Introducing lab automation can be met with resistance from staff unfamiliar with the new system or concerned about its impact on their roles. Ensuring that the workforce is adequately trained and confident in using new systems is crucial for successful adoption.

    How to overcome it

    Invest in comprehensive training programs that teach staff how to use the new automation software and emphasize its benefits. Highlight how lab automation can enhance their roles by allowing them to focus on more complex and rewarding tasks. Foster a culture of continuous learning and provide ongoing support as staff adapt to new technologies. Involving employees in the planning and implementation process can also increase buy-in and reduce resistance.

    Maintaining flexibility in a rapidly evolving field

    The life sciences field is continuously evolving, with new discoveries, technologies, and regulations emerging regularly. Implementing lab automation solutions that are too rigid or narrowly focused can limit a lab’s ability to adapt to these changes, potentially rendering the technology obsolete within a few years.

    How to overcome it

    Choose lab automation platforms that are scalable and adaptable, allowing your lab to modify workflows and processes as needed. Opt for modular automation software that can be easily upgraded or expanded to incorporate new technologies or accommodate changes in research focus. Staying informed about industry trends and maintaining strong relationships with technology vendors can also help ensure that your lab remains at the forefront of innovation and can quickly adapt to new developments.

    Lab automation offers numerous benefits, but it also presents challenges that must be carefully managed for successful implementation. By addressing interoperability issues, ensuring data accuracy, managing costs, providing thorough training, and maintaining flexibility, labs can overcome these challenges and fully realize the potential of lab automation. As lab automation continues to advance, those labs that successfully navigate these hurdles will be well-positioned to lead in scientific discovery and innovation.

    A new kind of automation is tackling these issues

    Meet LINQ, the vendor-agnostic, adaptable, error-handling, AI-ready data generating, workflow automation platform.

    LINQ is composed of two parts – LINQ Bench and LINQ Cloud.

    With a customisable configuration, LINQ Bench is designed to fit into any laboratory and accommodate the majority of machinery. Its modular design means that the individual components of the system can be adapted as and when required and control is possible at a local workcell and total workflow level.

    LINQ Cloud features workflow building, simulation, validation, execution and control. Workflows can be fully customised with a user-friendly interface, API or SKD, and cloud-based access ensures control over the platform from anywhere in the world. LINQ Cloud also facilitates real time data transfer of fully contextualised workflow results, delivered to a data lake of your choice in an AI-ready format.

    The utilisation of LINQ enabled one lab to reduce manual interaction time by 95%, while another increased its throughput by condensing a 6-hour cell culture process into just 70 minutes.

    To hear more about what makes LINQ a different kind of automation platform, get in touch with the team today.