SWAN DaaS Themed Call Led by Meena Sankaran Founder & CEO - - PowerPoint PPT Presentation

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SWAN – DaaS Themed Call

Led by Meena Sankaran Founder & CEO – KETOS October 14, 2020

Agenda

• Introductions (5 mins)
• Open Discussion (35 mins)
• Amir DaaS PhD Update (10 mins)
• Next Steps (10 mins)

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Open Discussion

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• What does DaaS mean to you?
• It’s important to address different definitions and perceptions of how people look at it

across Utilities, Technology Vendors, Industry operators and Influencers.

• How do we debunk the myths of what it's not?
• Which vertical have you seen it resonate? Which sub-verticals have you seen

it resonate?

• What are the areas of resistance in adopting the model?
• What are common concerns from utilities and industry operators vs. lack of adequate

education from technology vendors?

• What are other DaaS issues you would like to raise?

Exploring the Impact of the Data-as-a-Service Model on Water & Wastewater Operations

Amir Cahn PhD Update

Problem Statement

What is the biggest barrier to big data utilisation within water/wastewater utilities?

Survey of 23 global water utilities about their Big Data management practices as part of a Water Research Foundation (WRF) 2017 study

What is Data-as-a-Service?

➢ A model in which a Technology Supplier is outsourced to operate and maintain certain hardware equipment (e.g. water quality sensor, flow sensor, level sensor) to measure, collect, store, and transmit data and the utility only pays for the delivered results.

As-a-Service

Infrastructure Remote Sensing Subscription model Maintenance Leasing model Software

Methodology

Wastewater and Water Utility Surveys

• 45 wastewater and 56 water responses from 22 countries
• 87% wastewater utility use online sensors (13 use DaaS)
• 93% water utilities use online sensors (17 use DaaS)

Key Stakeholder Interviews

• 14 global utilities
• 16 technology providers
• 1 regulator

Next Steps

• Statistical analysis (T-tests, ANOVA)
• Case study approach/comparison of DaaS in different sectors
• Examining the role of regulators to incentivise technology/DaaS adoption

Research Questions

What are the main utility motivations/barriers to implement DaaS? Is DaaS only suitable for utilities that do not have the capacity to install,

• perate, and maintain

their own network? How do utility DaaS practices compare across different wastewater and water applications? Does DaaS improve the efficiency of utility O&M? Do DaaS utilities prefer to just acquire data, report summaries, or also predictive insights? What makes a utility a good fit for DaaS?

DaaS Challenges (Interviews)

• Need to shift utility mindset
• Professional pride
• Slow RFP process
• Labor unions
• Data ownership/cybersecurity concerns
• Fear of being “held hostage” and sharing sensitive info
• Vendor perspective
• Wastewater is “operational hell”
• False positives/negatives
• Liability for poor results (e.g. CSO, water quality incident)

DaaS Utility Benefits (Interviews)

• Prefer DaaS since offers CAPEX investment
• Shifting risk to vendors (O&M/data transmission/data quality)
• Guarantees “in-between process” (interoperability, data integration)
• Don’t need to keep up with rapidly advancing technology
• Easier than hiring full-time employees
• “Extensible” and “flexible” for different applications

“We don’t have the expertise” “I only care about the end output” “Just give me the data”

Wastewater Water

Wastewater Water

Wastewater

Water

Wastewater Water

Discoveries (So far)

Survey

• Water and wastewater data are not the same
• Wastewater data is more complex, difficult to understand
• There are several hybrid DaaS models (e.g. who’s responsible for hardware

installation, ownership, data verification, as well as what are the desired results)

• DaaS barriers (data ownership/cybersecurity) are less real-life challenges

Interviews

• Common theme of utilities being open to be technology test beds
• DaaS contract needs to be fixed for minimum years and clearly defined
• DaaS leads to a utility-vendor partnership based on mutual trust
• Unlike models built with projections/safety nets, DaaS provides real-time data

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Next Steps

Next Steps

• Should we have another call? If so....

– Timing? – Frequency? – Open it up (allow any SWAN Member) or keep private (invite-only)?

• What would you like to get out of this group?
• What future topics should we focus on?

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