Handling complex scientific issues in government is never easy — especially during a crisis, when uncertainty is high, stakes are huge and information is changing fast. But for some of the nations that have fared the worst in the COVID-19 pandemic, there’s a striking imbalance between the scientific advice available and the capacity to make sense of it. Some advice is ignored because it’s politically infeasible or unpragmatic. Nonetheless, much good scientific input has fallen aside because there’s no means to pick it up.

Part of the problem has been a failure of synthesis — the ability to combine insights and transcend disciplinary boundaries. Creating better syntheses should be a governmental priority as the crisis moves into a new phase.

Both the theory and practice of synthesis remain inadequate. I saw this when I ran the UK Government’s Strategy Unit in the early 2000s: I developed policy for everything from energy and carbon reduction to health care. I helped to set up a similar unit in Australia and have advised dozens of governments, from Canada to Bangladesh, France to Finland.

Over the past year, I’ve helped to run the International Public Policy Observatory (IPPO), based at University College London, with partners such as the International Network for Government Science Advice. IPPO organizes evidence syntheses on issues such as teen mental health, homelessness and the unplanned push towards online learning. Our techniques include roundtables, systematic reviews and global evidence scans.

Input from evidence synthesis is crucial for policymaking. But the capacity of governments to absorb such evidence is limited, and syntheses for decisions must go much further in terms of transparently incorporating assessments of political or practical feasibility, implementation, benefits and cost, among many other factors. The gap between input and absorption is glaring.

I’ve addressed teams in the UK prime minister’s office, the European Commission and the German Chancellery about this issue. In responding to the pandemic, some countries (including France and the United Kingdom) have tried to look at epidemiological models alongside economic ones, but none has modelled the social or psychological effects of different policy choices, and none would claim to have achieved a truly synthetic approach.

There are dozens of good examples of holistic thinking and action: programmes to improve public health in Finland, cut UK street homelessness, reduce poverty in China. But for many governments, the capacity to see things in the round has waned over the past decade. The financial crisis of 2007 and then populism both shortened governments’ time horizons for planning and policy in the United States and Europe.

Governments are now even less capable of using high-quality advice, assuming they obtain it. Ministries — such as those for agriculture and education — often have plenty of experts siloed within their own specialties. But teams around executives struggle to weave advice and evidence together. They tend to be small and consumed by ‘firefighting’. Politicians are too busy and distracted to do the job of synthesis, and civil servants are usually more comfortable with law and economics than with science or statistics, or the practicalities of implementation.

The Chinese mainland does have some central capacity to shape policy (as well as many officials with backgrounds in science and engineering), which might help it to navigate out of its zero-COVID stance. Taiwan, Singapore and South Korea — which had dramatically lower death rates than the United States and United Kingdom — also did well in leveraging data from tests, mobile phones and much more to guide policy.

The worst governments rely on intuition. But even the best resort to simple heuristics — for example, that it’s best to act fast, or that prioritizing health is also good for the economy. This was certainly true in 2020 and 2021. But that might change with higher vaccination and immunity rates.

What would it mean to transcend simple heuristics and achieve a truly synthetic approach? It would involve mapping and ranking relevant factors (from potential impacts on hospital capacity to the long-run effects of isolation); using formal and informal models to capture feedbacks, trade-offs and synergies; and more creative work to shape options.

Usually, such work is best done by teams that encompass breadth and depth, disparate disciplines, diverse perspectives and both officials and outsiders. Good examples include Singapore’s Strategy Group (and Centre for Strategic Futures), which helps the country to execute sophisticated plans on anything from cybercrime to climate resilience. But most big countries, despite having large bureaucracies, lack comparable teams.

Establishing such teams should be a priority. So should supporting a better science of synthesis. Universities’ interdisciplinary projects often stop short of true synthesis and recommending specific strategies (such as on carbon reduction) or making sharp judgements about priorities. Despite the contributions of behavioural science, complexity theories, computer science and social sciences, understanding of how whole systems could behave better is rudimentary.

I hope one legacy of the pandemic will be a concerted effort to improve both the theory and practice of sophisticated synthesis — to help us cope with the many crises ahead, from transitioning energy and transport to avert climate change to reducing inequality and rebuilding public trust in science.