R&D investment
Turning research into revenue
Generating growth from research and development can be a challenge. Julian Heaton, at Innovate UK, looks at the support available from the UK government to encourage innovation
L
ong-term economic growth and higher living standards are driven by increased productivity, as measured by the
amount of work produced per working hour. Unfortunately in the UK, productivity growth has been sluggish over the past decade as the economy has recovered from the downturn triggered by the financial crisis. Te UK is employing more people, but they are being employed in less productive jobs. Te UK Office of National Statistics figures show productivity in the fourth quarter of 2018 was 18 per cent below its pre-downturn trend. Tere is a demonstrable link between
expenditure on research and development in a national economy and increase in productivity. Te UK government’s industrial strategy has a target of increasing R&D expenditure to 2.4 per cent, as a percentage of GDP, by 2027. Progress to this target is being made, with the UK reaching a figure of 1.69 per cent of GDP in 2017, although this is still lower than the estimate for EU countries of 2.07 per cent. Imaging and machine vision is a rich
source of innovation, with many research and development streams capable of delivering significant added value to the economy. Innovation areas of machine vision include: • Improved image processing techniques: enables better perception and manipulation of the environment, as well as identifying people and reading emotions, and detecting pests and diseases in crops. Application areas are broad, including industrial and agricultural efficiency, animal welfare, health and security.
• Artificial intelligence and machine learning: AI and machine learning delivers innovation in image analysis, for example improving detection and diagnosis of structural and medical anomalies. Innovate UK has provided £50m funding for five AI centres for digital
26 Imaging and Machine Vision Europe • Yearbook 2019/2020
pathology and imaging (London, Glasgow, Leeds, Coventry and Oxford), as part of the Industrial Strategy Challenge Fund wave two challenge: ‘Data to early diagnosis and precision medicine’.
• Cloud-based access to information: enables improved machine learning through access to greater amounts of data.
• Block-chain security technology: creating a ‘digital trace’ that authenticates data moving between elements of a system, enabling new security-sensitive application areas.
Managing across three horizons Established businesses use profit-oriented metrics to evaluate projects and prioritise deployment of resources. Decision-making does not always give sufficient consideration
to early stage, high-risk activities that are not yet revenue-generating, such as research and development. Te better a company becomes at lowering operational costs to achieve short- term success, the harder it is to justify longer- term exploratory activities. Te Alchemy of Growth (Baghai, Coley
and White, 1999) proposes that to ensure sustained growth a company must deliver a continuous pipeline of business-building initiatives, and that this is best achieved by managing to three distinct horizons. Horizon one covers a company’s core business, usually the one on which its
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