Water utilities worldwide wrestle with the challenges of a dynamic, highly deregulated, and competitive market. Climate change, water shortages, unpredictable weather patterns, aging infrastructures, and funding gaps underscore the need to respond and adapt quickly to new business and technology requirements. While advances in digital technology and analytics can help overcome these issues, evaluating, identifying, and sustaining the appropriate initiatives requires specialized capabilities, a proven process framework, solid implementation methodologies, and a carefully defined vision, strategy, and roadmap.

1. Cognizant 20-20 Insights | December 2017
Digital
Disruption in
the Water Utility
Value Chain
Executive Summary
The water utilities industry is quickly evolving to meet
the demands of a dynamic, highly deregulated and
competitive market. Climate changes are generating
water shortages and altering flood patterns. Global
warming is giving rise to extreme weather conditions
– causing urban water supplies to dry down. Infrastruc-
ture issues and droughts only add to these concerns.
Performing long-termimpactassessmentsandmanaging
ecosystems to monitor resource extraction, industrial
use, and consumption are no longer optional.
In response, water utilities continue to navigate the
unsteady path to transformation. Change manage-
ment has become a daily task rather than a one-time
activity, compelling companies to respond and adapt
quickly to new business and technology requirements.
Yet along with these challenges come opportunities.
Globally, utilities are the beneficiaries of advances in dig-
ital technology and analytics. Some of these (predictive
analytics; machine learning and artificial intelligence;
unstructured data analytics; video and thermal imagery
from drones; cognitive computing; robotics; the Inter-
net of Things; and blockchain) can resolve many of the
problems facing water utilities. The key is to identify and
segment issues, and develop scenarios to overcome
them. (See Figure 1, next page).
COGNIZANT 20-20 INSIGHTS

2. Cognizant 20-20 Insights
2Digital Disruption in the Water Utility Value Chain |
Water Utility Market Constraints
Figure 1
Climate
Change
Stiff
Competition
Drying
Water
Resources
Funding
Gaps
Aging
Infra-
structure
Demand Growth
DIGITAL DISRUPTORS
Conserving treated water in whatever form remains
a critical issue. Digital technologies can play a major
role in helping the water utility market reduce con-
straints moving forward. Figure 2 highlights digital
advancements that can enhance the water value
chain and help conserve this critical natural resource.
Digital Disruptors that Reduce Market Constraints
AI, Machine
Learning
Blockchain
Cognitive
Enabled
Automation
Connected
Network
(IoT)
Drones, Big
Data
Analytics
Robotics-
Enabled
Automation
DIGITAL
DISRUPTORS
Figure 2

3. Cognizant 20-20 Insights
3Digital Disruption in the Water Utility Value Chain |
QUICK TAKE
Water Utility Business Challenges How Digital Technology Can Help
• Machine learning improves the accuracy of
weather-related data, the impact on resources,
and the predictions of asset failure.
• Robotics and big data analytics help assess the
condition of the waste water pipeline.
• Artificial intelligence-based quantitative risk
modeling can perform pipeline risk assessments
and rehabilitation.
• Drones-based inspection and LiDAR data
analytics improve productivity by executing tasks
faster and more accurately.
• Smart sensors installed on the network improve data
visibility through the Industrial Internet of Things (IIoT).
• Blockchain concepts for smart contracts and
billing reconciliation improve auditability and
traceability.
• Outlier analysis based on cluster algorithms and
big data analytics help uncover anomalies in
consumption and billing.
• Cognitive-based situational intelligence helps
optimize water production planning.
Demand Forecasting,
Asset Failure
Electricity Consumption & Cost
Optimization in Water treatment
Customer Consumption &
Billing Patterns
Water Production Planning
Aging Infrastructure
Non-Revenue Water
Asset Health Monitoring
Contracts & Billing

4. 4Digital Disruption in the Water Utility Value Chain |
Machine Learning
As global warming becomes more prevalent,
extreme weather conditions are a common
occurrence across the globe. Given the part that
weather-related data plays in monitoring and man-
aging the water supply chain, it is more important
than ever to accurately predict water shortages,
track flood patterns, and identify asset failures early
on. Machine learning can play a crucial role here.
Machine learning adapts to changing conditions
using real-time information gathered from histor-
ical data. The accuracy of the information – and
resulting decisions – improve with each weather
event/scenario. Predictions concerning weather
patterns, floods, droughts, and asset failures are
thus more reliable because the impact of weather
on field assets is continually analyzed in real time.
Robotics & Big Data for Assessing &
Rehabilitating Waste Water Pipelines
Robotics-based process automation is applied
across the utility industry to eliminate manually
intensive, repetitive activities and address haz-
ardous conditions. Tasks that are prone to human
error and accidents can now be performed by
robotics solutions reliably and accurately. Robotic
sensors embedded with artificial intelligence
and equipped with “smart” pipeline inspection
gauges, or pigs, run inside waste water pipelines,
using video and big data to capture, analyze, and
report the condition of these structures, as well
as potential hazards, in real time. (See Figure 4).
1
Robotics-Enabled Process Automation
in Water Utilities
Waste Water
Treatment
Distribution
Pipeline
Inspection
Event
Monitoring
Underground
Asset Cross
Bore Inspection
Figure 4
Mapping Activities & Challenges
Figure 3
Value Chain Key Activities Challenges
Catchment &
Abstraction
Water
Treatment
Storage &
Distribution
Customer
Consumption
Waste Water
Collection
Waste Water
Treatment
Sludge
Disposal
• Reservoir Level Management
• Catchment Management
• Abstraction Monitoring
• Drought Monitoring
• Raw Water Pumping
• Customer Management
• Customer Complaints
& Feedback
• Outage Management
• Metering
• Billing
• Waste Water Collection
Operations
• Asset Maintenance
• Waste Water Pumping
• Conversion of Sewage into
Biogas, Water, Electricity
• Grit Removal
• Disinfection
• Filtration
• Digestion
• Composting
• De-Watering
• Sludge Transport
• Sludge Trading
• Sludge Disposal
• Pre-Ozonation
• Clarification
• Filtration
• Aeration
• De-Salination
• Storage Level Monitoring
• Pressure Monitoring
• Maintenance & Operations
• Supply Pumping
• Demand Forecasting
• Optimized Production Planning
• Electricity Consumption
• Pump Scheduling
• Lack of Data & Visibility
• Aging Infrastructure
• Non-Revenue Water
• Asset Health
• Customer Engagement
• Demand Side Management
• Customer Bill
• Asset Failure
• Sewer Flooding
• Frequency of Data
• High Cost of Treatment
• Electricity Consumption
• Lack of Visibility
• Trade Setup
• Price Forecasting

5. Cognizant 20-20 Insights
5Digital Disruption in the Water Utility Value Chain |
Drone Inspections & LiDAR Analytics
Utility companies use drones to inspect areas of
their network that are difficult to access during
manual inspections. In the case of water utilities,
drones can fly in dense forest regions that are
hard to penetrate during harsh weather conditions
— recording data for pipeline inspections as well as
thermal/laser imagery data captured over time.
By overlaying this imagery with time-series anal-
ysis of structural conditions, utilities and can gain
deeper insight into their business and technology
operations, and initiate proactive maintenance
and operational activities to increase the longev-
ity of their distribution network.
Modern drones are equipped with analytics
that can handle large gigabytes of video and
imagery data, which is then integrated with
enterprise-level collaboration and content man-
agement systems to manage unstructured data
on big data platforms.
The Industrial Internet of Things
The Industrial Internet of Things (IIoT) opens
huge opportunities for water utilities in the form
of connected devices, human resources, and
networks. In water and waste water treatment,
reducing electricity consumption is a major cost
saver. The granular data collected from water
and waste water treatment plants can be of even
greater value if the right sensors are installed on
the network. By combining data from real-time IoT
platforms with predictive analytics, data variables
can be monitored, tracked, and analyzed easily to
make informed decisions. (See Figure 5 above).
Monitoring pump performance is another
area where the IIoT can help by tracking the
performance of pumps and their operational
characteristics more efficiently – leading to
more accurate failure predictions and proactive
maintenance to assure asset longevity. Today’s
IIoT devices are also used to help monitor water
quality at various consumer end points in the
network.
Artificial Intelligence for Risk Modeling,
Risk Assessment & Rehabilitation
Artificial intelligence (AI) self-learning techniques
are increasingly used by water utilities to assess
and resolve equipment-related issues, including
those in the pipeline. In these cases, AI algorithms
How the Industrial Internet of Things Benefits Water Utilities
Water
Quality
Monitoring
Water &
Wastewater
Treatment
Asset
Failure
Prediction
Abstraction
Monitoring
Electricity
Consumption
& Cost
Pump
Performance
& Health
Monitoring
Industrial IoT
Figure 5

6. Cognizant 20-20 Insights
6Digital Disruption in the Water Utility Value Chain |
assess pipeline risk. Various factors – static and
dynamic alike – affect the condition of pipes,
which are vulnerable to geographic, environmen-
tal, weather, structural, and internal conditions.
Until recently, statistical modeling techniques
were used to develop predictive risk models. With
the advent of artificial intelligence algorithms, the
accuracy of predictions has increased dramatically
due to the algorithms’ self-learning capabilities.
With every pipeline failure, risk modeling methods
and their impact are assessed and tuned to better
predict future incidents.
Artificial Intelligence is further enhanced by the
integration of multiple organizational systems
and the use of unstructured data to train models.
Drone imagery is an excellent example. Imagery
captured by drones is assessed in tandem with
the statistical risk models to gauge the actual
condition of an asset. The unstructured data
analysis validates the theoretical model, which
then trains itself.
Another important factor is surge from internal
water pressure variations, usually due to pump
operations and valves in the transmission and
distribution network. Given that pressure surge is
the main cause of water leaks in water pipelines,
using artificial intelligence algorithms and models
to accurately predict surges will go a long way in
reducing water leaks. (See Figure 6).
Cognitive Computing for Optimizing
Water Production Planning
Water production planning is a critical function
in the water utilities value chain – requiring
companies to comply with all licensing and stat-
utory obligations while balancing risk, capacity,
and costs. Given the increasingly competitive
landscape, optimizing production planning is no
longer arbitrary; it’s a key strategic advantage.
The amount of water treated and the timing of
the treatment have an associated cost impact.
On the demand side, variations in consumer
demands and treated water storage capacities
must be verified. On the supply side, there should
be ample visibility into the amount of water that
can be extracted within the limits set by regula-
tory authorities and the capacity of alternative
water sources. The overall goal is to ensure
ample supply at the least cost.
Among the key challenges in water production
planning is the lack of telemetry data and real-
AI-Based Asset Risk Modeling for Pipeline Rehabilitation
Figure 6
Spatial-Enabled Linear
Network Visualization
Network
Model
Weather
Data
SCADA /
Historians
EAM
CCTV
Data
GIS
Self-Learning
Model
Empirical
Model
Statistical Risk Score-
Based Prioritization
Drones, CCTV Data
Imagery Overlay
Real-Time Pressure
Surge Monitoring
Predictive Modeling Engine
Data Model / Persistence Layer
PLCs / Sensors Water Pipes
Data Extraction / Validation / Quality Management

7. 7Digital Disruption in the Water Utility Value Chain |
time information on output flows, variations in
storage capacity, unit cost metrics, chemical con-
sumptions and operational timing of pumps.
Efficient production systems depend heavily on
data collection, modeling, visualization, and situ-
ational intelligence from cognitive computing to
overcome these issues. (See Figure 7). Cognitive
computing in water production planning uses
real-time data and analytics to gather, sort, and
analyze data in a comprehensive and holistic way.
Big Data
On the retail side of the water value chain, “clus-
tering algorithms” are proving useful in finding
the root cause of discrepancies in consumption,
metering, and billing. Outlier analysis focuses
on comparing retail/industrial customers with
common attributes (location; class; size of prop-
erty; number of residents; annual income level;
credit score; and historic average consumption)
to analyze and compare usage patterns. Anal-
yses enabled by big data can highlight many of
the discrepancies that traditionally exist in billing
and metering.
Blockchain: A trusted ledger for
transactional data
Blockchain algorithms and structures, initially
developed to trade digital currencies in the
financial services world, are increasingly used in
applicationsforthewaterutilityindustry.Blockchain
technology maintains a distributed public ledger
for different types of industry transactions. Since
all industry parties share a public view of the
blockchain register, the register’s data can serve
as a trusted source for multiple market partici-
pants in areas such as carbon footprints, smart
contracts, metered consumption, settlements,
and billing reconciliations.
Cognitive Computing & Water
Production Planning
Demand
Data
Situational
Intelligence
Weather
Data
Budget/
Cost
Reactive/
Planned
Outages
Capacity
Constraints
Abstraction
Constraints
Figure 7
ProductionPlan&Schedule
Cognizant 20-20 Insights

8. Cognizant 20-20 Insights
8Digital Disruption in the Water Utility Value Chain |
A GOVERNANCE FRAMEWORK
FOR DIGITAL TRANSFORMATION
Digital transformation obliges companies to
engage all stakeholders and project implemen-
tation teams. When prioritizing digital projects,
water utilities should consider the business value
and long term-benefits of digitization.
Assessing digital maturity requires a clearly
defined vision, strategy, and roadmap, plus a sup-
porting organizational structure and framework.
(See Figure 8).
• Digital vision, strategy & roadmap: This
phase focuses on where the organization is
headed, its short and long-term vision, the
expected benefits, and what the business will
look like over time – with clearly stated mile-
stones and associated returns. This high-level
view will define and guide subsequent activi-
ties of digital implementations.
• Digital organizational structure: Success-
ful digital initiatives require companies to
restructure their operating environment.
Maintaining a longer-term perspective always
yields better results than attempting to imple-
ment shorter, more drastic changes. Industry
best practices indicate that digital organiza-
tional structures call for innovative office setups
and specific roles, including chief digital officer,
digital strategist, and digital ambassador. Digital
environments depend on digital champions and
officers to prioritize and run digital transfor-
mation projects. Adequate authority, roles, and
responsibilities should be in place to inform and
improve decision making.
• Digital processes: Business processes need to
align with digital initiatives. Increasingly, Agile
and DevOps-based methodologies are moving
into mainstream implementations projects.
Quick prototyping and sprint-based delivery
cycles can deliver benefits to customers faster
during short development cycles.
• Digital competency framework: Water utility
companies must equip their employees – from the
front office to the field – with the skills and respon-
sibilities they need to enable a seamless digital
transformation.Frameworksforidentifyingknowl-
A Digital Governance Framework
Digital Vision,
Strategy & Roadmap
Digital Transformation Initiatives
Customer
Engagement
Employee
Engagement
Digital
Organization
Digital
Processes
Digital
Competency
Framework
Digital
Opportunities
Evaluation
Figure 8

9. Targeting Opportunities in a Digital Environment
Cognizant 20-20 Insights
9Digital Disruption in the Water Utility Value Chain |
edge and skill sets within the organization should
be identified and mapped accordingly.
• Digital opportunity evaluation: Water utilities
should create frameworks and procedures for
gauging digital opportunities. A solid business
case that articulates and prioritizes these initia-
tives must be in place. Goals such as improving
the end user experience, increasing return
on investment, and making the best use of
resources, skills, and budgets can be the basis
for targeting opportunities in a digital environ-
ment. (See Figure 9).
Digital
Maturity
Identification
Identification Parameters
• Business Focus Alignment
• Sufficient Technology Capability
• Availability of Resources
• Availability of Skills
• Budget Constraints
Use Case
identification
Use Case
Implementation
Performance
Monitoring
Sustain
Change
Use Case
Prioritization
BusinessImpact
LowHigh
Ease of Implementation
Low High
Use Case Prioritization
Figure 9
Digital
Strategy for
Current & Next
Stage Evolution

10. Cognizant 20-20 Insights
10Digital Disruption in the Water Utility Value Chain |
QUICK TAKE
Prioritizing opportunities can be as simple as an m X n matrix, which factors in such things as
ease of implementation and business impact. (See Figure 9). Opportunities associated with
digital business are evaluated against criteria such as alignment with the business strategy,
availability of resources, and skills, and budget constraints. Opportunities with the highest
potential for delivering the most business value can be measured against profit / revenue
generation. Ease of implementation can be gauged by the level of difficulty and complexity,
and the amount of effort required by human resources.
Digital initiatives must be evaluated and prioritized from various aspects.
10Digital Disruption in the Water Utility Value Chain |
Evaluation criteria
• Alignment with overall
business strategy
• Effort to effect business
change
• Filling skills & competency
gaps
• Return on investment
• Business user experience
• Reduce process complexity
Evaluation criteria
• Difficulty of technology
rollouts
• Complexity of
customization
• Duration of the project
• Stability of the
technology platforms
• Clarity on the result
• High – if both BV and EI
are high
• Medium – if either BV or
EI are low
• Low – if both BV and EI
are low
Business Value (BV) Ease of Implementation (EI) Priority

11. Cognizant 20-20 Insights
11Digital Disruption in the Water Utility Value Chain |
C R Prasanth Kumar
Senior Manager,
Cognizant Consulting
Tuhin Kanti Mondal
Senior Consultant,
Cognizant Consulting
C R Prasanth Kumar is a Senior Manager, Consulting, within Cog-
nizant Consulting’s Energy and Utilities Practice. He has more than
17 years of experience in the Energy and Utility industry – primarily in
implementing large transformation and system integration programs
involving advanced digital technologies. He is a post-graduate from
the National Institute of Industrial Engineering, Mumbai. He can be
reached at prasanthkumar.cr@cognizant.com | LinkedIn: https://
www.linkedin.com/in/prasanth-kumar-c-r-3521752/.
Tuhin Kanti Mondal is a Senior Consultant within Cognizant
Consulting’s Energy and Utilities Practice. He has rich experience in
asset management, workforce management, customer experience,
and plant operation, with proficiency in data analytics. He is a cer-
tified Data Scientist in R and a Big Data Specialist. Tuhin completed
post-graduate work at the Indian Institute of Management, Lucknow,
and graduated from the Indian Institute of Technology, Kharagpur.
He can be reached at tuhinkanti.mondal@cognizant.com | LinkedIn:
https://www.linkedin.com/in/tuhin-mandal-081bb024/.
ABOUT THE AUTHORS
GETTING THERE FROM HERE
Digital disruption in the water value chain is fast becoming a reality. Sooner than later, water utilities
worldwide will make the shift to digital technologies. At the same time, there will be challenges in terms
of adoption; cultural and organizational changes; managing data; processes; and infrastructure. Evalu-
ating and identifying the appropriate digital initiatives for your company will depend on your industry’s
value chain, understanding associated business challenges, and addressing bottlenecks that may stand
in the way. Sustaining these initiatives calls for specialized capabilities, a proven process framework,
solid implementation methodologies, and a carefully defined vision, strategy, and roadmap.
Water utilities that transform to digital business will be more agile, and responsive to the demands of a
dynamic marketplace. Productivity improvements alone will allow them to stay in step with regulatory
and licensing standards, optimize costs, and streamline processes within and beyond the business.

12. World Headquarters
500 Frank W. Burr Blvd.
Teaneck, NJ 07666 USA
Phone: +1 201 801 0233
Fax: +1 201 801 0243
Toll Free: +1 888 937 3277
European Headquarters
1 Kingdom Street
Paddington Central
London W2 6BD England
Phone: +44 (0) 20 7297 7600
Fax: +44 (0) 20 7121 0102
India Operations Headquarters
#5/535 Old Mahabalipuram Road
Okkiyam Pettai, Thoraipakkam
Chennai, 600 096 India
Phone: +91 (0) 44 4209 6000
Fax: +91 (0) 44 4209 6060
© Copyright 2017, Cognizant. All rights reserved. No part of this document may be reproduced, stored in a retrieval system, transmitted in any form or by any means,electronic, mechanical,
photocopying, recording, or otherwise, without the express written permission from Cognizant. The information contained herein is subject to change without notice. All other trademarks
mentioned herein are the property of their respective owners.
Codex 2903
ABOUT COGNIZANT CONSULTING
With over 5,500 consultants worldwide, Cognizant Business Consulting offers high-value digital business and IT consulting services that
improve business performance and operational productivity while lowering operational costs. Clients leverage our deep industry experience,
strategy and transformation capabilities, and analytical insights to help improve productivity, drive business transformation and increase
shareholder value across the enterprise. To learn more, please visit www.cognizant.com/consulting or email us at inquiry@cognizant.com.
ABOUT COGNIZANT
Cognizant (NASDAQ-100: CTSH) is one of the world’s leading professional services companies, transforming clients’ business, operating and
technology models for the digital era. Our unique industry-based, consultative approach helps clients envision, build and run more innova-
tive and efficient businesses. Headquartered in the U.S., Cognizant is ranked 205 on the Fortune 500 and is consistently listed among the
most admired companies in the world. Learn how Cognizant helps clients lead with digital at www.cognizant.com or follow us @Cognizant.