Leverage Point · Data Commons
Trusted, shared insight for collective prosperity
Generative AI is expanding what we can know and do. The integrity of data and how we govern it, matters more than ever.
The premise
Building trust through intentional data connection
In a world shaped by synthetic content and fragmented information, coordinated action depends on data systems that are trusted, transparent, and shared. Tackling SIPI's grand challenges requires bringing together diverse data sources, e.g., health, environment, labour, and more. But bringing data together is not sufficient on its own.
Today, many data collaboratives exist, but too often they lack a shared direction, creating noise rather than generating actionable insights. Connections must be intentional, guided by meaningful questions and responsible use of data and AI.
Insight Priorities
100 Questions Topic Map
In collaboration with The GovLab and the Swiss Data Alliance, SIPI is working to develop a shared evidence foundation for Switzerland's long-term wellbeing.
The questions and mapping presented here are an initial exploration. Far from being definitive, they illustrate the kind of work needed to guide collective action.
Disclaimer: The map presented herein has been generated with AI-assistance and is yet to be verified.
Which population-level dietary and activity interventions reduce cardiometabolic risk in Swiss working-age adults?
How does air quality variation across Swiss cantons correlate with cardiometabolic risk trajectories?
What biomarker combination best predicts 10-year cardiometabolic risk in Swiss midlife populations?
Can claims data combined with GP records identify high-risk individuals 3–5 years before hospitalisation?
What occupational stressors best predict burnout-related sick leave in Swiss healthcare workers?
What validated tools distinguish stress-related cognitive symptoms from neurodegenerative patterns?
Can GP records, wearables, and claims analytics identify MCI 2–4 years before presentation?
What proportion of burnout absence is preceded by detectable cognitive load signals in the prior 6 months?
Which clinical markers best predict frailty onset in 60–75 year olds in Swiss integrated care settings?
Can hospital discharge data identify patients on frailty trajectories before first avoidable readmission?
What is the economic return on a 1-year delay in frailty onset?
Which community-based interventions most effectively delay dependency in 70–80 year olds?
What proportion of emergency psychiatric presentations could have been averted with earlier stepped-care?
What design features of Swiss integrated care pilots most consistently reduce avoidable hospitalisation?
What reimbursement structures most effectively incentivise prevention-oriented practice without cream-skimming?
What proportion of clinician documentation time can be recovered through AI tools without quality loss?
What governance safeguards are necessary for AI risk stratification in Swiss primary care?
Can federated AI models trained on Swiss hospital data identify risk signals invisible to individual sites?
What evidence threshold do insurers require to participate in shared-savings for prevention in Switzerland?
Which LAMal revision levers have greatest potential to shift incentives toward prevention?
What is the expected ROI of CHF 1M in prevention infrastructure at Lighthouse Region scale over 10 years?
What minimum true cost indicators can food companies credibly report without new data collection?
How does the true cost differential between healthy and unhealthy convenient food vary across Swiss income deciles?
Can a standardised health-adjusted earnings metric for Swiss food companies be derived from existing datasets?
What dietary pattern data best predicts cardiometabolic risk in Swiss 40–60 year olds?
What is the DALY reduction attributable to a 10% improvement in dietary quality across the Swiss working-age population?
Does nutritional density predict frailty onset trajectory independent of physical activity in 60–75 year olds?
Does dietary pattern in Swiss midlife predict cognitive trajectory independent of cardiometabolic risk?
What dietary biomarkers most reliably predict neuroinflammation risk in 50–70 year olds?
Can gut microbiome composition serve as an actionable early indicator of cognitive vulnerability in primary care?
What agricultural practices in Swiss cantons most reliably improve nutritional density of food produced?
Is there a measurable difference in mineral density between Swiss organic and conventional food?
What cantonal agricultural subsidy levers best incentivise higher nutritional density production?
Under what conditions do choice architecture interventions produce durable dietary change?
What employer subsidy reallocation designs most effectively shift cafeteria purchasing toward nutritious options?
Can Digital Product Passports displaying true cost change procurement decisions by institutional buyers?
What is the cost-of-illness reduction from measurable dietary quality improvement over 10 years?
Under what conditions would Swiss insurers participate in shared-savings linked to dietary improvements?
What nutritional interventions most effectively reduce sarcopenia risk in 65–80 year olds?
Swiss Food and Nutrition Valley (SFNV) — topic map across food innovation, nutritional science, sustainability, digital food tech, health and prevention, ingredients and processing, policy and regulation, and talent and ecosystem development. Three levels: cluster → research question → specific topic. Cross-links to SIPI missions shown in gold.
Startup ecosystem
Incubation and acceleration programmes for Swiss food tech startups
Scale-up pathways
Market access and internationalisation for Swiss food innovators
Open innovation
Collaborative R&D between industry, academia, and SMEs
Nutrient bioavailability
How food processing and preparation affect nutrient absorption and efficacy
Health claims regulation
EFSA and Swiss substantiation pathways for nutrition and health claims
Personalised nutrition
Individual-level dietary recommendations based on genetics, microbiome, and lifestyle data
Environmental footprint
Life cycle assessment and planetary boundaries in Swiss food production
Alternative proteins
Plant-based, fermentation-derived, and cultivated protein sources for the Swiss market
Food waste reduction
Interventions reducing food loss across the Swiss supply chain
AI & data in food
Machine learning applications across the food value chain from farm to consumer
Traceability & transparency
Blockchain, IoT, and digital passports for food origin and quality verification
Precision fermentation
Microbial engineering for ingredients, flavours, and functional nutrients at commercial scale
Diet-disease prevention
Evidence-based dietary strategies for chronic disease prevention in Swiss populations
Gut health & immunity
Microbiome, prebiotics, and immune function — evidence and product development implications
Cognitive performance nutrition
Nutritional strategies supporting brain function, focus, and stress resilience
Functional ingredients
Bioactive compounds with demonstrated health-promoting properties and market potential
Clean label & minimal processing
Reformulation strategies meeting consumer demand for shorter ingredient lists
Swiss terroir & heritage
Regional Swiss ingredients and traditional food knowledge in modern applications
Swiss food law
LDAl, OSAV, and regulatory frameworks governing food products in Switzerland
Public health nutrition policy
BAG, cantonal health offices, and national dietary recommendations in practice
EU Green Deal & Farm to Fork
Switzerland's positioning relative to the EU food system transformation agenda
Workforce & skills
Education pipelines and skills gaps across the Swiss food innovation sector
Cluster & network development
SFNV's role in convening and internationalising the Swiss food ecosystem
Consumer engagement & trust
Building public understanding and trust in food innovation and novel ingredients
2026 Focus
Where the data work is heading this year.
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Cantonal federation pilots
Stand up the first cantonal federation pilots — connecting health and agricultural datasets through privacy-preserving bridges and shared Environmental Product Declaration links, under governance protocols that keep each dataset with its custodian while making the insight shareable.
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Research & cantonal integration
Embed the Data Commons in live cantonal partnerships and research consortia — pairing health offices, agricultural agencies and university teams around shared questions, so federated evidence flows directly into procurement, prevention and policy decisions.
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Open methodology & peer review
Release the true-cost accounting and federation protocols as open, peer-reviewed public goods — submitting the methodology to independent review and building partner capability to run it without SIPI in the loop.