Decision Support & Stakeholder Alignment
Context
A €5M, 48-month Horizon Europe innovation project with 20 participating organizations overall, with 15 organizations participating in the AI-enhanced monitoring and benchmarking work package. The project focuses on AI-enhanced monitoring, data-intensive research and risk-based urban water-quality management.
Challenge
Translate high-level project objectives and fragmented partner inputs into a workable monitoring and benchmarking approach, while making dependencies across sensors, case-study sites, lab validation, data flows, AI needs and downstream modelling visible.
My role
Project Manager at Wetsus, coordinating Wetsus' lead role in the AI-enhanced monitoring and benchmarking work package and connecting project governance with technical and case-study stakeholders.
What I did
- Translated high-level objectives into operational and technical planning across sensor development, case-study implementation, data collection, lab validation, data-flow requirements, AI needs and downstream modelling.
- Elicited and consolidated requirements around monitoring locations, installations, sampling logic, validation needs, data availability, responsibilities and timelines.
- Facilitated partner discussions and technical meetings to resolve ambiguity, validate assumptions and make decision points, risks and dependencies visible.
- Developed shared operational overview structures covering ownership, readiness, open points, dependencies, risks and follow-up needs.
Outcome or value
- Created clearer visibility across partner ownership, readiness, risks, dependencies and open decisions.
- Helped turn fragmented technical and stakeholder input into clearer decision points and more structured coordination across the work package.