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Operational Research: Roots in Retrospect
Although intellectual antecedents can certainly be identified, operational research, as a discipline under that name, had its origins in the work undertaken by scientists to help organize the air defence of the UK in the run-up to World War II. The subsequent expansion and diffusion of OR within Britain’s Armed Forces in the course of the War was remarkable, with Patrick Blackett the most prominent practitioner and advocate, and the work undertaken received wide acclaim. After the War, an energetic campaign was launched to migrate the discipline into civilian life, both in government and industry. Despite scepticism from some quarters, the campaign was essentially successful, and with many ups and downs over the years, OR has been a recognised, substantial and successful field of endeavour ever since.
But how far did the particular - and in some ways distinctly unusual - circumstances of OR’s origin and early growth influence its subsequent character and development, both positively and also (perhaps inevitably) in ways that the OR community needed to rectify as time went by? The 75th anniversary of the founding of the Operational Research Club (forerunner of the Society) presents an ideal opportunity for such a retrospect.
In November 2020, Paul Clarke stepped down as Chief Technology Officer at Ocado, where he had led the sharp end of their innovation factory for many years, cooking with a cauldron of disruptive technologies including data, AI, IoT, synthetic environments, digital twins, robotics, smart machines and living labs.
Paul is passionate about the recipes for successful invention, innovation and disruption, which in his experience are all about embracing non-linearity, mess, uncertainty, intersectional thinking, unconventionality, intuition and leaps of faith. He believes building a successful innovation factory is all about the people, culture, creativity, leadership and vision rather than just the underlying technologies, and he has spent much of his career being a piece of disruptive grit in a number of different oysters, trying to help people see what they can’t see and trying to inspire teams to do things they never dreamed possible.
He now sits on a number of government and industry advisory boards including the Robotics Growth Partnership (co-chair) and Health Data Research UK, whilst at the same time advising a growing portfolio of exciting start-ups. He was a member of the UK's AI Council, the Innovation Expert Group that fed into the UK Innovation Strategy and an advisor to the National Food Strategy.
Paul believes that on the back of existing missions and moonshots, the UK needs to assemble a “Lego set” of reusable building blocks, tools and infrastructure to enable research and innovation to be undertaken smarter, faster, and with less cost and risk. This is needed to deliver greater prosperity, resilience and defensible competitive advantage for the UK, but also at a planetary scale to tackle the growing list of wicked exponential challenges we now face as a species. To this end, he was one of the lead authors of the Cyber-Physical Infrastructure vision which was published by the government in Feb 2022 and was then the subject of a BEIS led formal consultation process.
Paul originally read Physics at Oxford, before then entering the computer industry. He has worked in software engineering, consultancy, interim management and a number of software start-ups. In what little spare time he has alongside his work and family, Paul loves to invent and build stuff, design PCBs, write software and generally tinker.
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Where our physical and digital worlds collide
None of us can escape the huge focus on, and hype around, all things digital especially of course AI, LLMs and machine learning. This "digital hysteria" has exacerbated the eclipsing of physical technologies and strands of innovation, despite the inescapable reality that we live in a cyber-physical world. Tackling the growing list of exponential and existential challenges that we face as a species will require non-linear interventions, both digital and physical, that are massively reproducible, scalable and resilient. For example with climate change, orchestrating swarms of clean energy powered smart machines, on and under the ground, on and under the sea, in the air and even in space, to help us scalable measure, monitor, clean-up, re-plant and repair our planet. Where our physical and digital worlds collide live magical technological beasts such as digital twins, smart machines and living labs, and it is at this intersection that the most important and exciting things happen. However when it comes to exploring, understanding and optimising such complex non-linear systems and predicting their futures, mathematical models and synthetic environments are the often undervalued jokers in the pack, and we need to change that.
Alison is Professor of Probability in the University of Oxford where she holds a joint position between the Mathematical Institute and the Department of Statistics. She worked and studied at UC Berkeley, Cambridge, Edinburgh, McGill, and Queen Mary University London. Her research is in probability theory and applications, with a particular focus on mathematical population genetics. She has been especially interested in the effects of spatial structure on patterns of genetic variation and on the interactions between space, natural selection, and the randomness inherent in reproduction in finite populations.
Alison has previously served as President of the Institute of Mathematical Statistics, and on the Councils of the London Mathematical Society and the Bernoulli Society. She is currently on the Council of EPSRC (following stints on the Mathematics Strategic Advisory Team and the Strategic Advisory Network), and the Royal Society, and she is currently Chair of the Council for the Mathematical Sciences (which brings together the Edinburgh Mathematical Society, the Institute of Mathematics and its Applications, the London Mathematical Society, the Operational Research Society, and the Royal Statistical Society). She is also on the scientific council of the French CNRS. She was a subpanel member in each of RAE 2008 and REF 2014 and was subpanel Chair for UOA10 (mathematical sciences) in REF 2021.
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An Academy for the Mathematical Sciences
The idea of a National Academy for the Mathematical Sciences was put forward in Philip Bond's Review The Era of Mathematics in 2018. Since then, a great deal of work by many different people has gone into scoping out what an academy would look like, where it would fit in the mathematical sciences landscape, and, crucially, what it would add. In recent months the project has gained a huge amount of momentum, and so my aim is to provide a brief update and do my best to answer questions.