While technologies in the water sector have been advancing over the past few decades, complementary innovation in business models is needed to support the adoption of these technologies. One emerging opportunity is an outsourced approach to data collection, delivery, and analysis known as “Data-as-a-Service.” This study is the first to explore the drivers, barriers, and implementation trends for water and wastewater utilities to adopt this model. The findings provide valuable insights for utility managers looking for new ways to adopt innovative technologies and regulators and policymakers seeking to encourage utilities to make data-driven decisions.
|State||Published - Apr 2023|
Bibliographical noteFunding Information:
In conclusion, the results of this study support the notion that the DaaS model can facilitate the uptake of innovative solutions within the water and wastewater sectors, such as smart metering, leak detection, water quality monitoring, CSO monitoring, and industrial pollution detection. Several barriers must be overcome, beginning with data ownership and security concerns. These findings can be useful for regulators and policymakers looking to encourage water utilities to make data-driven decisions and DaaS technology providers seeking to tailor their offerings to serve utility customers well. Future studies could explore which types of public governance arrangements and utility structures affect DaaS adoption, determine the reliability and effectiveness of internal versus outsourced data management, and the impact of the broader regulatory environment. Moreover, further research could identify the exact value of DaaS and what determines utility suitability to adopt this model by developing a maturity assessment tool.
© 2023 Elsevier Ltd
- Big data
- Public-private partnerships
ASJC Scopus subject areas
- Business and International Management
- Sociology and Political Science
- Management, Monitoring, Policy and Law