Water BOOST Enabling Innovation for Future Ready Cities 2025

Second illustration: San Francisco, Valencia and Barcelona The second example (Figure 17) transitions from a binary comparison to a multi-city reflection, illustrating how similar cities can identify complementary strengths within shared typologies. San Francisco, Valencia and Barcelona are all high-income cities with established governance and infrastructure, but they present differing configurations and gaps, making them ideal for mutual learning. San Francisco demonstrates strong governance and regulatory enablers (E1), led by a proactive public utility and supportive policy mandates. However, its investor ecosystem remains relatively informal and not well connected to the broader multistakeholder community (E5), limiting the scaling of early-stage innovation. Valencia, by contrast, has a vibrant aquapreneurial ecosystem, driven by players such as GoHub and Idrica, but suffers from governance fragmentation and weak policy alignment (E1). Barcelona sits between the two, with solid foundational governance but ongoing challenges in scaling entrepreneurship (A2) and strengthening trans-level enablers (E4) that connect innovators with public institutions.By comparing these cities, Water-BOOST reveals several opportunities for strategic adaptation: Valencia could draw from San Francisco’s and Barcelona’s governance enablers (E1) to improve alignment between utilities and regulators; San Francisco and Barcelona could learn from Valencia’s aquapreneurship infrastructure (E3) to strengthen its investor pathways; and Barcelona could benchmark A2 mechanisms across both peers to refine its support for early-stage start-ups. These examples underscore a core insight: cities don’t need to replicate each other’s systems, they can adapt what works, tailored to their structure, capacity and institutional logic. Water-BOOST makes these insights tangible by focusing not just on what exists but how ecosystems interact, where the connections are weak and how they can be rewired for better system performance. As the Water-BOOST dataset grows, this functionality can be extended to regional clustering, typology-based benchmarking and strategy design tailored to city archetypes – not just individual locations. Cross-city learning, then, becomes not an exception but a tool for navigating shared complexity. Water-BOOST cross-city comparison and adaptation between San Francisco, Valencia and Barcelona citiesFIGURE 17 Source: World Economic ForumA2G2 E3 E2G1 E5 A1A1E1 E4 Weak enablerSan Francisco Valencia BarcelonaCompar e and adapt E1 from San Francisco to Valencia Compar e and adapt multistakeholder E3 from Valencia to SF and from Valencia and SF to Barcelona Compar e and adapt E1 from Barcelona to ValenciaCompar e A2 across the three cities (San Francisco, Barcelona and Valencia) and adapt the most suitable modelsWeak enablersG2E1 E3 E2G1 E5 A2 A1 E4Weak enabler E1G2 E3 E2G1 E5 A2 A1 E4