The Scottish Government’s agenda to drive the growth of technology companies as promoted by Mark Logan in his Scottish Technology Ecosystem Review is laudable.

By accelerating the rate of tech start-ups, supporting companies to scale, and creating a community of entrepreneurs and investors it is hoped that we can strengthen our position within the global tech economy and attract the best talent and leadership to our shores. It aligns with our deep-seated heritage of leading in innovation and design thinking.

Having watched the exponential growth of internet companies in Scotland over the last 20 years it is not difficult to support this initiative 100%, but we also need to think about how we use and deploy technology to stimulate an equal amount of growth in our non-service sectors too – particularly in manufacturing, engineering, and construction.

It is often said that automation will drive down the number of jobs in these typically goods-producing industries, with robots supplanting workers and software replacing administrators, but what will drive those industries to grow and scale?

In the same way that our service industries need people that can develop with digital and data, our older, more established industries need creative, innovative thinkers to design and build the smart systems, processes and production lines of the future. Advanced digital capability is not only required by Scottish tech companies, but across all sectors to build our economy, future-proof and safeguard vital industries.

Finding the tech talent is not always easy and for some businesses the need to hire those with new digital skills is not as pressing as filling existing roles.

With digital transformation having taken root in both public and private sector organisations it is essential to have these skills in-house and although engineering and manufacturing have long been at the forefront of technical innovation there is a lot of room for growth.

But change is a challenge and pushing a traditional organisation towards digital transformation requires leadership that understands and can write the strategy. A strategy that will foster a data-driven, digital culture through purpose-led leadership, communication, and vision.

At the core of this is the necessity for leaders to infuse a data-driven culture across their organisation and to build employees’ data capabilities at all levels to alter and augment ways of working.

Using data not only to measure performance but to probe issues and prompt questioning is the key and this requires a data-led mindset. Staff in the field or on the shop floor can rapidly improve performance and avoid problems if they can access, understand and use data to make decisions on the spot.

Empowering employees to see where problems lie, to access internal and external intelligence, predict outcomes and contribute to company-wide operations can be critical to the company’s growth and ability to remain competitive.

Data-led change also opens doors to achieving outstanding outcomes and Tata Steel’s factory in the Netherlands is glowing example. One of a handful of global organisations to be awarded the WEF’s Manufacturing Lighthouse status, it exemplifies how industry led by digital thinkers can create the factory of the future.

In 2018, Tata adopted a data-driven approach to realise a more efficient, productive steelmaking process, optimising the use of raw materials and improving production which resulted in improved quality, increased yield and 15% upturn in profitability.

But key to this change was their establishment of an advanced analytics academy to give their employees the ability to use data to finding solutions for everything from waste management to quality control and production processes. Along with the tech, this was the change that accelerated capacity and growth – proof positive that competent, confident people were still at the heart of their business.

This advance towards smart manufacturing, enhanced by skills in aggregating and analysing the data also enables organisations to reduce consumption, re-use materials and recycle by-products gaining efficiencies in their processes and production.

Edinburgh-based Topolytics are experts in this field and their WasteMap analytics platform enables companies to gain visibility over their waste and by-product flows, generating better commercial and environmental outcomes.

Bellrock Technology in Glasgow amplifies this by turning organisations’ data science models into applications that allow them to understand their data better – unlocking its value and increasing operational efficiency. And at Hypervine they are using AI and blockchain with satellite technology to deliver accurate and intelligent data to construction companies on how their sites are operating and pointing to potential savings.

Innovative solutions to old problems are the natural domain of data.  At Howdens in Renfrewshire, they have not only created a digital equipment testing studio, but optimised it to enable remote testing for customers worldwide to validate expected performance against data from a digital twin with results delivered instantly to any smart device globally. And many others are developing data applications in to predict maintenance issues, evaluate quality control, enhance engineering design and develop simulations.

Alongside investment in intelligent software to drive manufacturing capability is the parallel need to develop the deep tech talent that can code, problem-solve and use data to keep a business productive.

These skills, as the Tech Ecosytem Review points out, are not only needed now but must be embedded in our education system (alongside, I would argue, the arts) to ensure we develop creative thinking and cognitive diversity.

That is the long-term goal, but in the interim, we must look to our existing teams and focus on upskilling and reskilling those who understand the business and can apply tech thinking to industry problems.

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At Heriot-Watt we are proud of our long history in producing leaders in these industries – we have led in STEM education for over 200 years and continue to deliver cutting-edge online leadership courses in Digital Transformation, Business Analytics and Logistics & Supply Chain Management. And our Data Science Graduate Apprenticeship provides an ideal opportunity to upskill existing staff.

Uniquely, this Graduate Apprenticeship is delivered by the School of Engineering and Physical Sciences, where apprentices study Engineering topics but also Computer Science, Artificial Intelligence, Machine Learning, Mathematics and Advanced Statistical methods.

This breadth of subjects gives our GAs a great range of skills in the fields of engineering and manufacturing, but they are equally valued by financial services and general management because of their training and abilities in quantitative problem solving and analytical reasoning. You can find out more by visiting our Data Science Resource Centre or emailing us on ga@hw.ac.uk

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