SWAN DaaS Playbook

LEAD AUTHORS

CASE STUDIES

Introduction

While technologies in the water sector have been advancing over the past few decades, complementary innovation in business models is now needed to support adopting these technologies. Although big data technology has been widely embraced in various industries, its implementation in the water sector has been limited. One emerging opportunity is an outsourced, performance-based approach to obtaining high quality data collection, delivery, and analysis known as “Data-as-a-Service” (DaaS).

To be successful, DaaS depends on an effective partnership between utilities, technology providers, and other relevant stakeholders. Directly linked to this is the core issue of trust. Water utilities must trust that they are investing in and implementing the right solutions, especially when their data management is being outsourced. Technology providers must trust that utilities will employ and maximise their solutions since DaaS projects usually require vendors to put forth the initial and ongoing capital investment. Furthermore, regulators must trust the validity and reliability of the data they review.

Equally as important to understanding what DaaS is, is what it is not. DaaS is not a one-size-fits-all solution. A utility’s suitability to adopt DaaS depends on several factors, such as the size and complexity of the system, the availability of data, and the specific requirements for deployment. It’s also important to consider the cost of DaaS, which can vary depending on the amount of data being collected and analysed, as well as the specific features and functionality required. DaaS is not for every utility. A utility may have its own internal solutions, desire only Software-as-a-Service (SaaS) offerings, have insurmountable internal challenges (e.g. cultural, legal, procurement), or prefer to offer DaaS themselves.

The DaaS Journey

Part one of this playbook provides an overview of DaaS in the water sector, highlighting common myths, utility drivers (benefits), barriers (initiation challenges), and a digital transformation roadmap. Part two focuses on DaaS implementation, including key project stakeholders, how to craft a DaaS contract, service level standards, and common trends. Part three demonstrates 17 real-life, DaaS water, stormwater, and wastewater utility case studies.

Common Myths

DaaS is the same as SaaS.

Both SaaS and DaaS offer insights and analytics; however, through different business models. SaaS provides software delivery and licensing via an online subscription model. Through DaaS, a provider typically manages the equipment installation, data collection, transmission, and hardware O&M, in addition to the software delivery and licensing.

DaaS is only for utilities that aren’t that advanced.

Although DaaS is more frequently adopted by utilities that don’t have the internal manpower or technology expertise to adopt big data management solutions, there are several examples of technologically advanced utilities that prefer the DaaS model, with one utility commenting, “the more you know, the more you outsource.”

With DaaS, my data is less secure.

The DaaS provider typically safeguards data security by implementing measures to preserve confidentiality, integrity, and accessibility, while also guaranteeing compliance with applicable regulations and standards. Cloud service providers also use automatic software patches, which reduces the need to continually monitor and rollout critical software updates.

With DaaS, I have to sell my data.

Most utilities that adopt DaaS do not sell their data, but instead indicate in their contract that they own the data.

Utilities: Do they have past XaaS experience? Is there an “internal champion” to act as a conduit between the utility and DaaS provider?

Labour Unions: Will they view DaaS as supplemental support or a threat?

Consultants: Will they be enablers or blockers of a DaaS project?

Regulators: Do they promote or deter innovation/data-driven decision-making?

DaaS Provider: Are the DaaS contract, terms and conditions, and procurement policies realistic to make DaaS commercially viable?

Distribution Channels: Will a DaaS provider’s
representation channel want to sell DaaS? Will there be a conflict of interest and/or lack of ownership/accountability if more than one company is involved in the supply of DaaS? (e.g. hardware manufacturer, software developer/integrator, local field service contractor, prime contractor)