A framework and guide for using value chain approaches to understand, improve, measure, and design early warning systems
- 1Bureau of Meteorology , Research, Docklands (Melbourne), Australia (beth.ebert@bom.gov.au)
- 2University of Reading, Reading, UK
- 3China Meteorological Administration, Beijing, China
- 4Environment and Climate Change Canada and University of Waterloo, Canada
- 5University of Leeds, Leeds, UK
- 6GNS Science, Wellington, New Zealand
- 7Finnish Meteorological Institute, Helsinki, Finland
- 8Natural Hazards Consulting, Melbourne, Australia
Early warning systems can be conceptualised as information value chains or cycles consisting of a complex and dynamic web of nodes—where information is produced, interpreted, and used—and flows representing the communication of information, movement of resources, and nature of relationships among actors operating at each node. Value is created when information flowing through the chain supports decisions and actions that result in improved social, environmental and/or economic outcomes.
Value chain studies can provide useful insights for groups involved in early warnings. National weather services and their partners have a strong stake in understanding and improving the warning value chain because it directly affects their activities and their stakeholders. Authorities and funding bodies need to ensure that the warning services are operated according to agreed regulations and that they represent value for money. User communities in all parts of the chain receive and transmit warning information that assists them to take appropriate action at the right time; they also provide important feedback on warning effectiveness, thereby contributing to their improvement.
The WMO WWRP Value Chain project is developing a framework and guide for using value chain approaches to understand, improve, measure, and design early warning systems. Building on the seminal work of WMO (2015), Golding et al. (2019) and Lazo & Mills (2021), it draws on expertise from practitioners in the broader warning community and researchers in the natural and social sciences. It brings together process-oriented “top-down” perspectives and people-oriented “bottom-up” perspectives, offering a variety of approaches that are suitable for different types of value chain studies. Unlike most cost/benefit studies, value chain studies emphasize the means of getting to the benefits.
The framework begins with describing an existing service chain, then progresses to describe approaches for guiding service improvements, assessing the social and economic value of service improvements using quantitative and qualitative methods, and designing a new service. It includes tools and workshop ideas as well as examples of how value chain approaches are being successfully applied in the field of hydrometeorology.
The framework is currently undergoing review and is expected to be released by the WWRP around the end of 2023.
Golding, B., M. Mittermaier, C. Ross, B. Ebert, S. Panchuk, A. Scolobig, D. Johnston (2019). A value chain approach to optimizing early warning systems. Global Assessment Report on Disaster Risk Reduction, 30 pp.
Lazo, J. K., & Mills, B. (2021). Weather-Water-Climate Value Chain(s): Giving VOICE to the Characterization of the Economic Benefits of Hydro-Met Services and Products. American Meteorological Society.
WMO (2015). Valuing weather and climate: Economic assessment of meteorological and hydrological services. WMO-No. 1153, 286 pp.
How to cite: Ebert, E., Hoffmann, D., Da Costa, J., Liang, X., Mills, B., Mooney, C., Msemo, H., Pastor-Paz, J., Perrels, A., and Tupper, A.: A framework and guide for using value chain approaches to understand, improve, measure, and design early warning systems, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-498, https://doi.org/10.5194/ems2023-498, 2023.
