Trends in Benchmarking
Evaluating System Performance
Prepared for:
September 26-28,2017
MWU Presentation 9.26-28.17
CONFIDENTIAL
2
Today’s discussion
• Introduction
• Topics for Discussion
o Infrastructure Condition
o Utility Personnel
o Financial Tracking
• Benchmarking Process
Agenda
MWU Presentation 9.26-28.17
CONFIDENTIAL
3
Today’s discussion
• Introduction
• Topics for Discussion
o Infrastructure Condition
o Utility Personnel
o Financial Tracking
• Benchmarking Process
Agenda
MWU Presentation 9.26-28.17
CONFIDENTIAL
4
There are a number of drivers for utilities seeking to pursue system automation
programs
• Improve the effectiveness of customer service
• Reduce customer service costs (meter read labor, truck rolls, collections, etc.)
• Increase distribution operations efficiency
• Increase capital efficiency
• Enhance customer satisfaction
• Manage non-revenue water (NRW)
• Support or enhance conservation
• Increasing billing frequency
• Aging meters
• Foundation for utility of the future
AMI/Smart Water
MWU Presentation 9.26-28.17
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While many utilities think of the immediate applications, there exists an
opportunity to significantly transform many utility operations
Next Generation Water Utility
MWU Presentation 9.26-28.17
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6Leak Detection
For example, AMI-based acoustic leak detection helps non-revenue water
management
MWU Presentation 9.26-28.17
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7Technology
New technologies and service offerings are now changing the nature of water
utility automation projects
• Non-moving part meters
• Second generation acoustic leak detection
• Customer portals
• Data analytics
• Hosted software
• Network management
• Meter reading as a service
• Remote control shut-off
• Pressure and temperature sensors
MWU Presentation 9.26-28.17
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8Key Findings
The new wave of AMI and smart water programs are showing more value returned
to utilities
• 60-70% of the value of past AMI projects was left on the table
– Primarily used for simple meter reading
– Much valuable data lost in the shuffle
• Today, AMI projects are oriented toward a data centric model
– Complex data management and analysis systems are being designed to maximize benefits and enable
more complex functionality.
– 10-15% of project costs are now focused on system integration due to the complexity of the system
– Projects are being undertaken with the goal being asset management and the data analytics are the
drivers
MWU Presentation 9.26-28.17
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9Current State of Technology
The maturity of newer system is a key driver in returning value to water utilities
and the communities they serve
• Deployments have been going on for a long time, and we are in 3rd to 5th generation of technology
• Systems are moving way beyond billing information into utility management
• Cost versus benefits in most cases supports moving to the new systems
• Product constraints/environmental issues require better management of utility systems
• Advanced metering improves customer relationships
MWU Presentation 9.26-28.17
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10Water AMI
For many, AMI serves as the starting point for broader water system automation
initiatives
• Advanced metering should be an asset management tool in the utility segment
• A significant cost reduction in data collection and customer service
• It offers a significant change in the ability to utilize utility staff and capital based on data driven events
– Engineering design issues
– Capital budgets outlays
• It is a network that is expandable for other city services, or can connect to existing networks
MWU Presentation 9.26-28.17
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11Coming Attractions
Emerging technology offers the potential to further increase the potential reach for
water utilities
• Pressure sensors build into the water meter
• Water quality AMI sensors
• Composite digital mag meters
• Integrated disconnect meters (no plumbing)
• Improved battery lifecycle
• Acoustic sensors becoming a more integrated part of the smart water systems
MWU Presentation 9.26-28.17
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12Integrating Systems
One of the challenges that water utilities face is dealing with a water distribution
system that is far from uniform
1920 1st Phase
$20M (06 dollars)
1932 2nd Phase
$8M (06 dollars)
1940 3rd Phase
$ 20M (06 dollars)
1960 4th Phase
$160M (06 dollars)
1980 5th Phase
$65M (06 Dollars)
2007Total Infrastructure= $265M
Water Loss = 30%
MWU Presentation 9.26-28.17
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13Integrating Systems
For an increasing number of water utilities, the AMI network serves as the core of
a new asset management system
MWU Presentation 9.26-28.17
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14Integrating Systems
The new AMI system can now be used to identify water loss and other problem
areas
Old pipe from
1920s
Leaks near
commercial
areas with 1960s
clay pipe
Low-pressure
in 1980s
Plastic pipes
MWU Presentation 9.26-28.17
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15Data Analytics
Clear value propositions can be achieved from managing/using the data correctly
• 60-70% of the value of past AMI projects was left on the table
• However, many utilities today are seeking more integrated approaches to capture additional value
– State of the art 24/7 monitoring of accounts worth over $15 million in revenue per year and over $265
MM in fixed asset replacement value
– Reduction in customer service costs and service issues by up to 75% within 3 years
– Real time emergency response to account issues
– Elimination of safety issues in reading meters
– Daily sales revenue from key accounts
– Continual improvement on asset performance
– Proactive customer service
MWU Presentation 9.26-28.17
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16System Architecture
The Meter Data Management System is typically used as a central repository of
data that can be accessed by a myriad of supporting systems
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17Business and Data Models
The optimal approach calls for integrating business and data models
MWU Presentation 9.26-28.17
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18Future State Workflows
Value is created when future state workflows take advantage of the new
technologies and systems that have been put in place
Water Meter
Data: (Meter
Read)
MIU GatewayAMI Server
(MDM)
Operations
Billing/CIS
Usage Profile
Bill Generation/
Customer Calls
Water Meter
Data: (Tamper
Alarm)
MIU GatewayAMI Server
(MDM)
Operations
Billing/CIS
Site Investigation
Bill Generation/
Customer Calls
Security Team
Water Meter
Data: (Leak
Detection)
MIU GatewayAMI Server
(MDM)
Billing/CIS
Work
Management
Customer Calls
Repair Kits
USER FUNCTIONSDEPARTMENTMETER & AMI SYSTEM
MWU Presentation 9.26-28.17
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19Customers
In addition, water utilities now have new tools to communicate with customers on
an ongoing basis
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20Potential Programs
There are quite a few different sources of value that water utilities may consider
• Business Process Engineering
• Line Loss Program Implementation
• Business Analysis
• C&I program Management
• Customer Communication
• Cyber Security Implementation
• Data Analytics Design
• Systems Engineering Program
• Water Management
• MDMS Configuration
• Meter Data Mapping
• Meter Specification & Configuration
• Conservation Program
• Theft deterrent program
• Prepay Implementation
• Web-Portal Implementation
• Social Media
• Project Management
• Kiosk Implementation
MWU Presentation 9.26-28.17
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21
Advanced metering applications are the most popular among utilities because of
their ability to reduce costs and improve operations, while providing more value
to customers
• Many utilities are looking at options in advanced metering to streamline operations, enhance financial
flexibility, and support smart grid potential for the future
• Utilities with a rural component are more likely to pursue advanced metering efforts than purely
urban/suburban utilities due to their rural reach and customer service orientation
Advanced Metering
• Tamper, theft and outage detection
• Consumption patterns can be tracked
and analyzed to provide more accurate
forecasting of trends
• Improved customer service
• Value added services can be offered to
customers
• Asset management
OPPORTUNITIES
MWU Presentation 9.26-28.17
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22Automatic Meter Reading
Advanced metering reduces costs through operational efficiency, more accurate
billing, and greater consumption control
• In addition to using this to reduce meter reading costs, utilities are taking advantage of having a sensor on
the distribution network; some are even using it to send reads from gas and water meters
Automatic Meter
Reading
Prepaid Metering
Basic Facts Benefits
• Automatic, real time data
collection from metering devices
transfers data to central
database for billing and analysis
• Technologies have included
handheld, mobile and network
devices based on wired and
wireless, radio, and power line
transmission networks
• Attainable data includes tamper
and leak detection, battery life,
reverse flow data, interval data,
meter events
• Operational efficiency achieved by
preventing the need for employees
to visit customer locations each
month
• Offer customers actual readings
instead of estimation or self-reads
• Accurate load data from remotely
accessible meters helps to balance
the supply portfolio
• Furthermore, data can be used to
control ToU with load profiling and
customer usage patterns
Advanced
Metering
MWU Presentation 9.26-28.17
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23Prepaid Metering
With prepaid pricing, consumers pay for service prior to delivery and as they use
electricity their balance is reduced each day until exhausted
• This feature is becoming more popular among consumers in many utility territories
Basic Facts Benefits
• Advanced meters support this
customer-controlled usage by
providing real time data
regarding usage, dynamic
costs, etc. via a web-based
interface or in-home display
• Prepaid pricing helps to eliminate accounts
receivable and late fees because service is
automatically disconnected when the balance
runs out
• Cash flow improvement
• Greater customer relationship management as it
helps customers to directly control costs and
consumption levels
Automatic Meter
Reading
Prepaid Metering
Advanced
Metering
MWU Presentation 9.26-28.17
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24Smart Pumping
Time-stamped AMI data can be used to improve the accuracy of the current
distribution system model, which results in better predictive planning related to
water treatment, pressurization, pumping and storage
• The addition of pressure monitors to the system could help a utility reduce pumping when higher
pressures are not needed
Basic Facts Benefits
• One of the benefits of an AMI
system is the ability to leverage
the hourly meter data being
gathered several times per day
• Because one of the largest cost
line items in the water budget is
its electric bill in support of
system operation, utilities can
utilize meter data to optimize
their pumping schedules
• By avoiding peak electric
consumption periods, utilities can
realize electricity consumption
savings
• As an electric utility as well, the
benefit is only realized at the
wholesale power level
Water Operations
Smart Pumping
Leak Detection
MWU Presentation 9.26-28.17
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25Leak Detection
The desire to identify and reduce leak adjustments is a main benefit of a
dedicated water leak detection program
• An automated system can support the ability to provide customer-side leak detection to improve customer
satisfaction and to reduce costs associated with leak adjustments
Basic Facts Benefits
• One approach involves a
comparison of an interval of
time-stamped meter
consumption data from a
specific area against the data
from a district metered
area/zone
• Another approach is to deploy
acoustic leak detection devices
(ALD) and/or institute a leak
detection survey program
• Proactive customer-side leak
notification, “watch dog” service
• Opportunity to provide higher level
of pressure management, acoustic
leak detection, water quality
management
Water Operations
Smart Pumping
Leak Detection
MWU Presentation 9.26-28.17
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Today’s discussion
• Introduction
• Topics for Discussion
o Infrastructure Condition
o Utility Personnel
o Financial Tracking
• Benchmarking Process
Agenda
MWU Presentation 9.26-28.17
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The utilities industry mirrors a national trend towards work force aging
Situation Complication Key Questions
• In the US, life expectancy has
risen dramatically since the
beginning of the century to 78.4
years for the average adult, white
male from 47.9 years.
• While the aging workforce is a
national phenomenon, the
median age for workers in the
Utilities industries is 3.3 years
higher than the national average.
The Utilities industry is “older”
than the national average.
• At stake for Utilities are losses of
critical knowledge and skills due
to impending retirements.
• There are not enough young
people to replace the wave of
“Baby Boomers” approaching
retirement.
• Employers need to find new ways
to retain older workers in order to
forestall loss of expertise
• Human Resources report
difficulty in recruiting young
people, especially for craft
positions.
• Many positions within the Utilities
industry are highly specialized,
both managerial and labor,
requiring years of intensive
training.
• Investments are needed to make
the work place flexible and
accessible for older workers.The
National Organization on
Disability reports a 11.5 percent
chance of developing a disability
in people aged 45 to 54. This
figure jumps to 21.9 percent for
those 55 to 64 years.
• Recent years of economic
distress have made the
necessary investments hard to
actualize.
• Do Utilities companies recognize
the need to act now in order
minimize negative consequences
of an aging workforce?
• What programs can be
implemented to attract younger
workers?
• How can incentives be
established to attract and retain
experienced workers?
• How can utility companies
establish a succession strategy to
ease “passing of the torch”?
• What benefits will Utility
companies realize by addressing
the aging work force issue now,
before the retirement wave
peaks?
Industry Age Demographics Overview
MWU Presentation 9.26-28.17
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Median Age of U.S. Industries
25
30
35
40
45
Agr
iculture
, for
estry
, fishing
and
hun
ting
Pub
lic A
dministra
tion
Utilities
Tran
spor
tatio
n an
d war
ehou
sing
Edu
catio
n an
d he
alth ser
vice
s
Man
ufac
turin
g
Mining
Other
Ser
vice
s
Fina
ncial a
ctivities
Pro
fess
iona
l bus
ines
s se
rvices
Inform
ation
Con
stru
ction
Who
lesa
le and
Retail T
rade
Leisur
e an
d ho
spita
lity
National Median, 40.4 years
Utilities are among the oldest of US employment sectors
• Only “Agriculture, forestry, fishing and hunting” and “Public Administration” median ages are higher
Industry Age Demographics Overview
Source: US Bureau of Labor Statistics
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The Utilities Industry median age is increasing with time
• Over a period of nine years, the median age of Utilities Industry employees has risen from 41.1 to 43.7 years
• By 2050 the US total over-65 population will swell from its current 30-plus million people to an astonishing 80
million
• By that point a utility worker currently 25 years of age will be 71
• Barring massive retention of older employees, the low rates of employee replacement mean there will be
smaller numbers of people to handle work-load.
Industry Age Demographics Overview
Source: US Bureau of Labor Statistics, NWPPA
Utilities, Increasing Median Age
39.0
39.5
40.0
40.5
41.0
41.5
42.0
42.5
43.0
43.5
44.0
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
MWU Presentation 9.26-28.17
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30Industry Age Demographics Overview
Source: US Bureau of Labor Statistics
Age Distribution among Utility Employees
0.8%
4.4%
15.3%
30.4%
34.5%
12.4%
2.2%
0%
5%
10%
15%
20%
25%
30%
35%
40%
16-19 Years 20-24 Years 24-34 Years 35-44 Years 45-54 Years 55-64 Years 65+ Years
The 45-54 year old age group represents a large percentage of utility population
and represents a group whose loss will most severely impact the industry
• For utilities as a whole, 148,000 employees currently fall in the 55-64 years age group, another 26,000 are
over age 65
• A combined number of 172,000 utilities employees are eligible for retirement now, or 14.4%
• More significantly, approximately half of the “Boomer” group will be within range of retirement in five years,
another 17.2%
Over one-third of
workforce lies in the
critical “pre-retirement”
stage
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The demographics of utility workforce shows a clear image of a wave moving
toward retirement
• APPA describes an “Age Bubble”, a ballooning population of workers at one end of the age continuum,
followed by a deep dip in the next generation and a modest rise in the work force’s youngest members
Industry Age Demographics Overview
Sources: US Bureau of Labor Statistics, American Public Power Association
Percent of Workforce Age Curves
0%5%
10%15%20%25%30%35%40%
16-1
9 ye
ars
20-2
4 ye
ars
25-3
4 ye
ars
35-4
4 ye
ars
45-5
4 ye
ars
55-6
4 ye
ars
65 y
ears
and
ove
r
Utilities
US Total
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Chief among concerns dealing with the issue of an aging workforce is the loss of
knowledge base
• By far the issue of most concern to all within the utilities industry is the loss of critical knowledge and skills due
to massive numbers of retirements
– Losses are anticipated across the entire scope of organizations
– Not only are people with unique technical knowledge about to depart, but executive managers and skilled
workers as well
• The challenge facing the industry is successful transfer of knowledge from a large number of experienced
people to a limited pool of young replacements, to condense many years of knowledge into digestible form
– This must be done in coordination with advancing technologies, that themselves impose increasing
demands upon resources
– A knowledge objective is finding ways of employing new technologies to ease burdens rather than
increasing them
• Unlike other industries, utilities have the added responsibility of protecting the public welfare
– The unique knowledge and skill-sets of utility workers may be considered public assets
Effects of Aging Workforce on Utilities
MWU Presentation 9.26-28.17
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Business challenges and opportunities present themselves as the work force
ages
• An informed and competent work force is increasingly critical to an organization’s financial well being as
technology advances
– Failures in an automated power grid scenario hit the bottom line in terms of loss of immediate revenue, damaged reputation, increased competitive pressure, and possible fines
– Managing knowledge transfer and skills development as part of a successful succession strategy clearly impacts utility companies’ future financial viability
• The cost of workforce turnover is significant, typically ranging from 25 to 200 percent of an employee’s annual compensation
– Costs associated with employee replacement will escalate during the next decades
– Companies find it is financially advantageous to encourage employees to work past the traditional retirement age, for two reasons;
· First to forestall and better manage the cost of employee replacement
· Secondly to allow greater time for transfer of knowledge to the younger generations
• It makes good business sense to invest in accessible and assistive technologies allowing older workers to remain in the work place
Effects of Aging Workforce on Utilities
Source: Energy Pulse, Microsoft, AgeLight Marketing Consultancy
“ Companies that figure out how to manage (the rise in the average age of the work force) will
have a clear competitive advantage over those who let the demographic trend wash over them.”
George Bailey, Global Director of the Human Capital Group
MWU Presentation 9.26-28.17
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Aware, not
implementing
plans
Aware,
implementing
plans
Not aware
U.S. firms are beginning to recognize the need to retain older workers
• 61% of surveyed U.S. firms are aware of the effects of demographic changes
– However, of those aware, 55% reported that they are not actively implementing strategies to retain or
attract employees over the age of 50
Survey and Case Studies
39% 34%
27%
Source: Energy Pulse, Microsoft, AgeLight Marketing Consultancy
MWU Presentation 9.26-28.17
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Survey responses reveal a strong industry awareness of aging workforce issues
• To the question, “Would you say that there is an awareness in your organization of the current and pending
effects of workforce aging?”, 93% responded that there is an awareness
– Thus the survey finds a general industry understanding that demographic aging trends are impacting and
will continue to impact, the Utilities Industry
– Lack of awareness does not seem to be related to company size
92.9%
7.1%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Yes No
Survey and Case Studies
Source: UTC Analysis
- Awareness of Workforce Aging Effects -
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Smaller companies tend to be more proactive in addressing aging issues than
larger corporations
• Of the companies aware of age demographic trends, to the question, “Does your company have in place
procedures to minimize the detrimental effects of lost experience by retirement?”, 56% answered ”Yes”
– The smaller companies tend to be more proactive about tackling the issues
Survey and Case Studies
Source: UTC Analysis
56.4%
43.6%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Yes No
- Procedures in Place to Minimize Retirement Effects -
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Most utility companies do not specifically address retention of older workers
• Of the companies aware of demographic trends, to the question, “Does your organization have in place
procedures to retain or attract employees over the age of 50?” 28% answered “Yes”
Survey and Case Studies
28.2%
69.2%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Yes No
Source: UTC Analysis
- Program in Place for Retention/Attraction of Employees -
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As to those facing retirement shortly, the survey indicates percentages in keeping
with the statistics for the entire nation
• To the question, “Within the next five years what percentage of your workforce will be eligible for retirement?”
most respondents, over half expect to lose 16-30 percent of their work force to retirement within five years
• BLS statistics indicate that 14.4% of Utility employees are within retirement range now, with another 17.2% of
Baby Boomers eligible in five years.
Survey and Case Studies
Sources: US BLS and UTC Analysis
Percent of Utilities Work Force Eligible for
Retirement in Five Years
<5%
(3%)
6-10%
(9%)
11-15%
(11%)
16-20%
(28%)
21-30%
(26%)
31-40%
(11%)
41-50%
(9%)
51-60%
(3%)
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Answers varied widely regarding individual company expectations in retirement
patterns and preparations
• One respondent reported that 60% of the company’s employees are facing retirement within 5 years
– This company does not have in place program to address the problem
• Similarly, a large utility expects 50% of its work force to retire within the 5 year window, but it has programs in
place to address the transition
• A third company of note is a small water company with 32 employees that expects to lose 50% of its work force
within 5 years
– This company has no contingency plan in place
Survey and Case Studies
Sources: UTC Analysis
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Position Categories likely to be Impacted by Loss of
Skills Due to Retirements
2%
2%
34%
62%
Across Entire
Organization
Executive Management
Non-Union, Professional
Bargaining Unit, Craft
Respondents expressed the most concern over losses in craft positions
• When asked to name business areas in which losses of experienced personnel are likely to impact operations, the
majority of survey respondents named bargaining unit, craft positions
– By contrast, AWWA studies named executive management as the top area of concern
• Of the Non-Union, Professional group the positions of concern were mainly in Engineering and IT. Also mentioned
were Long Term Planning, Human Resources and Design
Survey and Case Studies
Sources: UTC Analysis
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• A number of companies have
formed “Employee Project
Development Teams” and are
currently studying internal work
force aging issues
• Several company respondents
stated that “intern” or “apprentice”
programs have been implemented
with local technical schools. Upon
completion of two year programs
the students stand to be hired by
the utility company
• Of interest are the efforts of a large
electric and gas company to work
closely with several local schools,
mainly in urban areas, to improve
basic math and reading skills so
that pre-employment tests might be
passed
Survey responses were enlightening in regards to self assessment and mitigation
actions taken
Chevron
• Many companies expressed deep
appreciation of the impending loss of
knowledge and experienced workers
• One respondent stated firmly that (s)he
foresees no problems with age
demographics and that the strengths of
the company will be sufficient to attract
young workers for years to come
• A large company stated that despite
proactive mitigation efforts they
anticipate impact to service levels to
customers, both in response time and
the ability to fix a problem right the first
time
• An experienced planning engineer
facing retirement himself in 12 months
stated that the engineers being hired in
his company are technician/clerk level
rather than qualified engineers and
“…lack the sense of what is possible
and advisable”
• Concerns over the loss of corporate
culture were expressed. This is a
significant point as older workers
may wish to preserve strong ethical
values and a heightened sense of
responsibility towards public welfare
• There was an expression of doubt
about a company’s ability to retain
employees in the wake of work
force reductions, that is, employee
loyalty has been shaken
Survey and Case Studies
Sources: UTC Analysis
Self Assessment Mitigation Other Issues
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Retirement Projections: mitigation plans should be designed around a utility’s
unique workforce needs
• Utilities should not rely on general data to understand their possible employee loss
• Before a mitigation plan can be developed, utilities should engage in a number of efforts
– Identify the number of workers that will be retiring over a certain period
– Retirement numbers can be obtained by tracking retirement patterns as well as employee age
– Identify what specific positions will be vacant and when they are likely to be vacated
– Some companies have found success through employee surveys asking employees when they
plan to retire
Source: APPA
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Projected knowledge loss involves identifying what skills retiring employees will
be taking with them
• Retirement projections should be more that pure numbers
– Utilities should develop a clear picture of the void in skill set that will occur as their older, more
experienced workers retire
– Understanding what skills will be lost is essential in accurately determining what skills must be cultivated
in the new workforce
Determining skill loss may be a matter
of asking the right questions
At least one utility has found success in
conducting interviews asking employees to
identify their most valuable contributions to
the company as well as what unique tasks
they perform
Utilities have also initiated open
meetings where employees discuss
problem-solving techniques
Such communication forums enable
management to determine what specific
skills need to be replaced with human
capitol and what should be replaced with
new technology or outsourcing
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• Benefits Packages
– Utilities should develop a clear
picture of the void in skill set that will
occur as their older, more
experienced workers retire
– Signing bonuses
– Flexible scheduling options, such as
flextime or telecommuting
– Tuition reimbursement
• Family-friendly work environments
– Utilities should develop a clear
picture
– Family-leave programs
– Workplace daycare options
– Financial counseling
– Wellness programs
As the population ages, attracting younger workers from an increasingly small
workforce pool will require competitive practices
Mitigation Actions
Source: APPA, Social Funds
• Attracts younger, more talented workers
• Encourages employee loyalty and
reduces turnover
• Reduces absences
Competitive Benefits
Implications
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Internship programs allow utilities to get a jump-start on training while giving
students an opportunity to gain work experience
• Utilities can form alliances with local communities to begin recruiting from universities as well as community
colleges and technical schools
• Internships enable utilities to train and mentor future employees
• Students also have the unique and valuable opportunity to gain work experience prior to graduation
• Certain positions open to full-time students
• When students have graduated and worked as interns for two full school years, they can be hired
without the usual competitive process facing new employees
• Since the inception of the formal internship program in 2001, no job offers extended to interns have
been rejected
Success Story: Colorado Springs Utilities
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Companies that spend significantly more than average on employee training
through “Fast Track” programs often find improved results
• Fast Track Development programs are designed to identify future leaders and groom them to take over
leadership positions
• Different from the traditional philosophy of waiting until upper management retires and hoping to fill vacant
positions, fast track development enables utilities to more quickly prepare younger employees to take over
leadership roles
• Classroom teaching and job-related assignments give hiring management an
opportunity to watch employees in action
• Management has the opportunity – and the need – to identify strong leadership
candidates
• Employees who are identified as future leadership candidates are then rotated into
further development and mentoring programs or trained to takeover specific positions
Key Issues
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47
Fast Track Development is increasingly seen as a critical component to ensuring
that maximum talent and capabilities are kept in house
• Identifying specific talents within the organization not only enables a company to identify who its future leaders
may be, but also provides feedback on how to improve efficiency within the organization
• Utilities that have established a fast track development program report improved communication between
supervisors and employees as well improved customer service
• Some programs focus on overall leadership skills, rather than preparation for a particular position
– They include intensive leadership study for new employees to develop such skills as problem-solving and
team building
Mitigation Actions
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48
As health care costs rise, a great majority of those nearing retirement age say they
plan to continue working to help off-set costs as well as to find fulfillment, leading to
issues concerning gradual retirement practices
• One alternative to the loss of expertise resulting from retiring employees to delay retirement or rehire certain retired
employees, enabling utilities to retain certain skill sets for a longer period of time
Mitigation Actions
Opportunity Programs
Gaining additional access to retiring
workers through mentorship initiatives
• Flexible schedules
• Part time work
• Job sharing
Preventing physical impairments from
limiting the access to valuable expertise
of experienced workers
• Technology-assisted workplace
Utilizing technology to capture decision-
making skills of more experienced
workers
• Use of automated tools
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49
Today’s discussion
• Introduction
• Topics for Discussion
o Infrastructure Condition
o Utility Personnel
o Financial Tracking
• Benchmarking Process
Agenda
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50Internal Operations
Internal operational issues addressed the potential to streamline the day-to-day
activities
Issues Raised
• Limited ability to use current system to engage in detailed system modeling
• Scheduling and logistics are limited in today’s environment
• Billing and metering operations impact distribution operations as well
Key Considerations
• Reduction in bill auditing can reduce operating requirements
• Enhanced system data can improve system modeling
• Can improve scheduling and logistics
• Reduced challenges resulting from metering delays
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51Billing
Billing issues extend beyond just the need to send accurate bills to customers
Issues Raised
• Metering delays from last February still causing drag on operations and receivables
• Bi-monthly billing a burden on water and wastewater departments as well as customers
• High degree of re-reads and audits
Key Considerations
• Reduction in read-to-bill cycles can improve organizational cash flow
• Customers would welcome switch to monthly billing
• Reduced and/or eliminated need for re-reads and audits
• No further need to catch up on metering backlog
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52Connect/Disconnect
The cost of disconnects and reconnects coupled with the risks associated with
bad debt make the continued development of solutions in connect/disconnect
appealing
Issues Raised
• Significant cases of meter theft
• Operational procedures result in repeated offenses and long cycles to address
• Potential bad debt issue present
• Significant percentage of transient customers
Key Considerations
• Reduced operational demand placed by non-pay customers
• Reduced bad debt• Reduced incidents of stolen
meters• Need to establish/refine
operational procedures• Ability to more quickly
respond to turn on/turn off
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53Customer
Each utility always strives to deliver high customer service
Issues Raised
• Customers operate on bi-monthly billing cycle today
• Limited information provided to customers on consumption or billing
• Legacy metering platform leads to certain level of read errors
• Higher than desired call abandonment rates
Key Considerations
• Establishment of customer portal to empower customers and deliver information
• Reduction/elimination of read errors
• Lower demands on call center due to bill complaints/special reads
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54On Cycle/Off Cycle Reading
In addition, we also unearthed a number of issues related to on cycle/off cycle
meter reading
Issue Notes
Potential billing on one date
Need to avoid bottlenecks; might want to stagger billing dates
Move in/move outCan use system to grab billing data on exact date
requested
System interactionNeed to consider impacts to existing systems;
need to account for portions
Deployment timingMight want to select certain routes for early
stage deployment
Bill auditsNeed to consider impacts to implausibles, re-
reads, work orders, outsorts, EMMAs
High bill inquiriesHow can we use system to make inquiries; any
changes to policy?
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55Collections/Move In & Out/Non-Pay
Collections and other issues also often plague water utilities
Issue Notes
Leak detection$1-1.5M per year in leak adjustments; could be
reduced by as much as 75%
Connect/disconnectDelays exist in cut-on/cut-off due to order
volume and geography
Retail servicesPotential to work with plumbers to deliver home
inspection services
Third party DunningProvide cut off of water service for non-pay of
sanitation fees
Stolen metersNeed to address issue of stolen and relocated
meters
InspectionsSwitch to AMI may result in lower ability to
monitor field conditions
Billing and collectionsCustomers may be able to maintain current
status better due to portal data
Billing dateAbility to select billing date could help customers
meet billing obligations
Billing date flexibilityPotential to charge customer fee to self-select
billing date
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56Project Scope Example
A number of technical, operational, and financial characteristics need to be
addressed to make sure the optimal strategy is uncovered
Technology
Drivers
•Operating Costs
•Customer Service
•Non-revenue
Water Mgt.
•Conservation
•Etc.
Vision, Goals &
Objectives
Financial
Situation
Requirements
•Interval Meter
Reading
•Data Reporting
Interval
•Tamper, Leaks,
Backflow, etc.
•RC Shutoff
Ownership and
Implementation
Plan
Deployment
Strategy
Economic/
Financial
Impact
Existing
Systems
•Meter Reading
•CIS
•SCADA
•GIS
•Etc.
MWU Presentation 9.26-28.17
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57Financial Modeling
It is always wise to develop a financial assessment of the proposed program to
make sure the system you deploy is designed accordingly
System Automation Business Model
Prepared for: Prepared by:
Business Case Results
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Benefits
Meter Reading 148,205$ 300,857$ 458,055$ 440,249$ 446,853$ 453,555$ 460,359$ 467,264$ 474,273$ 481,387$
Engineering & Planning 16,320$ 33,129$ 50,439$ 51,196$ 51,964$ 52,743$ 53,535$ 54,338$ 55,153$ 55,980$
Leak Detection 80,200$ 162,807$ 247,873$ 251,591$ 255,365$ 259,196$ 263,084$ 267,030$ 271,035$ 275,101$
Smart Pumping 4,601$ 9,341$ 14,221$ 14,435$ 14,651$ 14,871$ 15,094$ 15,320$ 15,550$ 15,783$
Total Benefits 333,998$ 977,174$ 1,651,643$ 2,382,056$ 3,180,684$ 3,590,800$ 3,678,645$ 3,758,318$ 3,838,997$ 3,913,652$
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Pro Forma Financials
Benefits 249,327$ 506,134$ 770,589$ 757,471$ 768,833$ 780,365$ 792,071$ 803,952$ 816,011$ 828,251$
OpEx -$ 132,485$ 182,831$ 233,176$ 233,176$ 233,176$ 233,176$ 233,176$ 233,176$ 233,176$
EBITDA 249,327$ 373,648$ 587,758$ 524,294$ 535,656$ 547,189$ 558,894$ 570,775$ 582,835$ 595,075$
Depreciation 132,485$ 182,831$ 233,176$ 233,176$ 233,176$ 233,176$ 233,176$ 233,176$ 233,176$ 233,176$
Net Income 116,841$ 190,817$ 354,581$ 291,118$ 302,480$ 314,012$ 325,718$ 337,599$ 349,658$ 361,898$
CapEx 1,324,855$ 503,455$ 503,455$ -$ -$ -$ -$ -$ -$ -$
Cash Flow (1,075,528)$ (129,806)$ 84,303$ 524,294$ 535,656$ 547,189$ 558,894$ 570,775$ 582,835$ 595,075$
(3,199,042)$ (653,140)$ (229,263)$ 198,876$ 659,932$ 2,074,486$ 2,086,914$ 2,083,082$ 2,094,971$ 23,887,224.37$
Financial Metrics
NPV 3,461,285$
IRR 33.9%
MWU Presentation 9.26-28.17
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58Implementation Support
The roadmap and implementation scenarios developed help to ensure project
success
Integration / Architecture Business Transformation
Customer & Stakeholder Engagement
Implementation Services
MWU Presentation 9.26-28.17
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59Benefits
Cumulative ten-year benefits come to $11.5 million
AMI, $5,168,337
Prepaid Metering, $3,128,199
Electric Operations, $2,849,775
Water Operations, $324,273
Gas Operations, $0
Ten Year Benefits
MWU Presentation 9.26-28.17
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60Earnings
The forecast calls for strong earnings impact
$-
$200,000
$400,000
$600,000
$800,000
$1,000,000
$1,200,000
$1,400,000
$1,600,000
2017 2018 2019 2020 2021 2022 2023 2024 2025 2026
Net Income
Total Benefits
Total OpEx
EBITDA
Net Income
MWU Presentation 9.26-28.17
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61Cash Flow
Annual cash flow turns positive after the deployment period and full payback is
achieved in year 8
$(4,000,000)
$(3,000,000)
$(2,000,000)
$(1,000,000)
$-
$1,000,000
$2,000,000
$3,000,000
$4,000,000
2017 2018 2019 2020 2021 2022 2023 2024 2025 2026
Cash Flow
Cash Flow Cum Cash Flow
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62CapEx
Total CapEx over the deployment period is estimated at $7.3 million
$-
$200,000
$400,000
$600,000
$800,000
$1,000,000
$1,200,000
$1,400,000
$1,600,000
2017 2018 2019 2020 2021 2022 2023 2024 2025 2026
CapEx
AMI
Prepaid Metering
Electric Operations
Water Operations
Gas Operations
MWU Presentation 9.26-28.17
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63Business Case
By targeting only programs that offer positive value, we can reduce CapEx by 21%
and increase program value by 67%
Full Deployment Optimized Deployment
Ten Year Benefits $12.3 $11.5
Ten Year CapEx $9.8 $7.7
NPV $2.4 $4.0
IRR 15.8% 24.2%
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64Direct Benefits
Benefits can be evaluated over the life of the forecast period based on the
characteristics of program design
AMR AMI Enhanced AMI
Internal Operations
Meter Reading Labor 7,002,295$ 14,004,590$ 14,004,590$
Smart Pumping -$ -$ 425,521$
Leak Detection - System -$ -$ 93,331$
Displaced Capital 7,140,000$ 7,140,000$ 7,140,000$
Meter Accuracy 9,148,001$ 9,148,001$ 9,148,001$
Accidents 709,202$ 2,836,810$ 2,836,810$
Salvage 465,888$ 465,888$ 465,888$
Billing
Read-to-Bill 324,385$ 648,770$ 648,770$
Bill Audit Reduction 298,858$ 398,477$ 398,477$
Re-Read labor -$ 597,716$ 597,716$
Connect/Disconnect
Bad Debt Reduction -$ -$ 1,202,807$
Field Collection Reduction -$ -$ 1,772,628$
Cash Flow Acceleration -$ -$ 4,525$
Customer
Call Center Support 2,608,821$ 3,261,026$ 3,261,026$
Leak Detection - Customer -$ -$ -$
Total Direct Benefits 27,697,450$ 38,501,278$ 42,000,091$
Direct Benefit Comparison (Twenty Years Cumulative)
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65Deferred Direct Benefits
This water utility also recognized the potential to avoid the forecasted costs
associated with moving from bi-monthly to monthly reads
AMR AMI Enhanced AMI
Deferred Direct Benefit 13,316,958$ 13,316,958$ 13,316,958$
Deferred Direct Benefit Reduction 304,111$ 608,222$ 608,222$
Net Deferred Direct Benefits 13,012,847$ 12,708,736$ 12,708,736$
Deferred Direct Benefit Comparison (Twenty Years Cumulative)
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66Indirect Benefits
We also considered the potential to augment the business by evaluating “soft”
benefits
• Increased system modeling capabilities
• Network support for planned smart city effort
• Enhanced technology development in support of city strategic plan and economic development
• Enhanced employee safety/reduced claims
• Others?
AMR AMI Enhanced AMI
Customer Satisfaction 3,535,573$ 7,071,145$ 7,071,145$
Carbon Impacts 20,209$ 50,522$ 50,522$
Leak Detection 5,673,620$ 14,184,049$ 14,184,049$
Conservation 465,081$ 1,162,703$ 1,162,703$
Total Indirect Benefits 9,694,483$ 22,468,420$ 22,468,420$
Indirect Benefit Comparison (Twenty Years Cumulative)
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67
Two of the more important functions of a utility are billing and operations
• It is inefficient and risky to have multiple sources of data floating from more than two applications
• These should either be consolidated into one, more robust application or chose multiple applications that all pull from one main
database of information
Information Management – Minimize Complexity
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After defining the information architecture and adopting standards for
interoperability, it will be important to evaluate the future framework for a utility’s
systems
Information Management – Future Applications
• GIS – Trimble
• MDM – MPower
• SCADA
• Electric – Survalent
• Water – Land
• Gas – None
• CIS – local system
The ultimate systems approach will depend on the vendor(s) chosen. Nevertheless, a likely scenario
will involve continued use of Survalent for electric SCADA and Trimble for GIS. MPower (MDM) may
be usable, but will need to be determined.
MWU Presentation 9.26-28.17
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69Information Management - Mobile Data
With the increased use of mobile workforce applications comes the need to
ensure a number of elements in wireless data networks
Security
Data encryption to protect data from being read by an
unintended recipient
Authentication
Only valid users are allowed on the
network to prevent eavesdropping and unauthorized use of
the data network
Mobility
Seamless and automatic roaming
between a number of wireless networks
IP Connectivity
The ability to establish and maintain
IP connectivity in a mobile environment
MVPN (Mobile Virtual
Private Network)
A secure tunnel
between the client and
customer enterprise
network that persists
as the user roams
Application Steering and Blocking
Steer or block applications from specific networks
Data Compression
Enables higher
bandwidth data or
capacity for more
users on the network
Application Session
Persistence
Maintains TCP/IP
sessions if user loses
coverage, or during
PC device power
savings mode
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70
Today’s discussion
• Introduction
• Topics for Discussion
o Infrastructure Condition
o Utility Personnel
o Financial Tracking
• Benchmarking Process
Agenda
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71
We have developed a seven-step process that allows for the effective
benchmarking of different utility functions across a diverse set of comparisons
Project Methodology
Internal Data
Collection
Benchmark
Method
Cost
Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
Method
Cost
Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
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72
The first step involves interviews with XYZ and XYZ staff to collect data on key
processes, work functions, and output levels
Internal Data CollectionInternal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Key Issue: Identify performance levels and key tasks performed at XYZ
Approach: Conducted interviews with all subject matter experts, including specialists in short term planning,
long term planning, network maintenance, digital network, land mobile radios, network monitoring, network
provisioning, engineering, and finance. Collected data from each and identified key organizational
responsibilities.
Rationale: In order to complete the benchmarking process, it was necessary to start with the XYZ’s data
points. Furthermore, in order to assure the delivery of the best comparison possible, we needed to fully
understand the nature of the job requirements associated with the way in which XYZ worked. Furthermore,
this step was critical in providing initial hypotheses regarding the establishment of appropriate cost drivers.
Result: A thorough understanding of XYZ’s organizational structure was gained, which led us to focus on the
network monitoring function.
Internal Data Collection
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73
Detailed headcount data was collected to start the process
Internal Data CollectionInternal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Organization HC Cost Driver(s)
Second Level Support 8• Number of projects
• Size of network
ITMC 11• Number of projects
• Number of network elements and network size
Field Team 4• Number of projects
• Size of network
Land Mobile Radio Maintenance 6• Number of sites
• Size of network
Project Management 10• Number of projects
• Number of network elements
Provisioning 3• Number of circuits
• Number of network elements
System Design 21• Number of projects
• Size of network
Engineering, Planning 59• Number of projects
• Number of network elements and network size
Contract Labor 92.5• Number of projects
• Size of network
Engineering 4• Number of projects
• Number of network elements
3• Number of projects
• Number of network elementsOutside Plant
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74
Once the initial data is gathered, it is then important to determine the correct
benchmark approach
Benchmark Method
Key Issue: Identify the appropriate way to compare work loads of very different utility telecommunications
operations
Rationale: The initial goal involved benchmarking total costs; however, it was quickly determined that there
were too many variables that came into play – some of which were controllable and others not. Due to the
potential differences in labor rates, cost allocation methodologies, and burden factors outside the control of
XYZ, we chose to determine efficiency levels based on full time equivalents (FTEs) of work load rather than on
pure dollars.
Result: A view toward comparing the work loads of network monitoring functions for benchmarking was
developed.
Benchmark Method
Internal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Approach: Interviews with XYZ Telecom and some of the early stage benchmark companies were held to
determine the commonality of group functions and overall work structure and process flow
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75
Based on the initial interviews, we were able to identify a set of specific definitions
for the network monitoring function that were common to all electric utilities
involved in the benchmarking effort
Cost Drivers / Activity Definitions
Key Issue: Identify a common denominator dealing with benchmarked companies.
Rationale: Once it was determined that an activity-based benchmark approach was needed, it was important
to identify the appropriate way to segment work function. Given that there appeared to be six key areas of
activity for each company (planning, maintenance, network monitoring, provisioning, engineering, and land
mobile radio), those tasks were defined.
Result: Specific definitions for each task were developed.
Activity Definitions
Approach: Extended primary research was conducted based on common areas of focus – labeled as key
activity areas – that served as unifying work functions.
Internal Data
Collection
Benchmark
Method
Cost
Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
Method
Cost
Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
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76
Monitoring activities are focused on ensuring seamless operation of the
distribution network
Network Monitoring Definition
Network Monitoring Characteristics
• Ensuring physical and logical security of network
• Conducting remote fixes of network when available
• Major alarm investigation
• Client services associated with network monitoring
• Monitoring technology platforms within network
Internal Data
Collection
Benchmark
Method
Cost
Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
Method
Cost
Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
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77
In order to establish benchmarks and compare values, data needs to be collected
from each of the target utilities
External Data Collection
Key Issue: Collect information from benchmark companies for comparison to XYZ.
Rationale: In order to ensure collecting the proper depth of information, it was important to have discussions
directly with each of the target utilities. Furthermore, in order to ensure access to as much information as
possible with as many of the key people needed, meetings at the utility locations were arranged.
Result: Data was collected from each of the three utilities in each of the areas sought. Follow up discussions
focused primarily on the network monitoring activities.
External Data Collection
Approach: Interviews with subject matter experts at three utilities were conducted at the utilities’ offices.
Additional discussions regarding changes and updates to operations or network monitoring activities since the
original benchmarking effort will continue with each iteration of this report.
Internal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
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78
Besides XYZ, three other utilities have been selected for comparison
• They were selected for their scope of operations and number of electric customers served
External Data CollectionInternal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
ABC DEFXYZ GHI
68,972 58,958150,000 61,861Customers
1,535,843 1,294,441640,000 283,350
Service
Territory (sq.
km)
166,700,000 54,000,000153,200,000 32,144,000System
Capacity
Note: While an attempt was made to select utilities that offered comparative value, none of the
utilities profiled provided an exact match to XYZ
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79
External data was gathered to support the benchmarks
• This type of organizational data helps to develop algorithms for comparing different types of operations
• By looking at overall workload, network size and complexity, we can establish calculations to balance the
research data prior to analyzing the results
External Data CollectionInternal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Hydro OneManitoba
Hydro
Hydro
QuebecBC Hydro
Number of Large Projects 15 3 28 13
Number of Medium Projects 30 10 38 6
Number of Small Projects 250 150 5 1
Network Elements 3,255 2965 13,462 1250Cate
gory
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80
Weighting factors will be applied prior to comparing values in order to normalize
the data
Weighting FactorsInternal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Key Issue: Establish weighting factors in order to make comparisons across companies’ activity levels.
Rationale: Since the number of network elements and the number of projects were deemed to provide even
contributions to overall workloads, the weighting factors preserved that 50/50 relationship while using an index
to tie it to a single value. The resultant weighted values will be more meaningful when compared against one
another because they are all indexed off a single value.
Result: Values appropriate to compare the work loads of other utilities to XYZ’s operations.
Weighting Factors
Approach: Initial interview results identified project related work and the number of network elements were
both significant factors in determining work load for the network monitoring function. Weighting multiples were
then established to arrive at an expression of relative workload whereby each factor accounted for 50% of the
total.
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81
Weighted
Projects
Network
ElementsInitial Units Final Units
BCH 350 1250 455 1.00
MTB 244 2965 493 1.08
HQC 857 13046 1954 4.29
HON 745 1250 850 1.87
484 5754
Initial Weighting 1 0.08
Final Weighting 0.00220 0.00018
Org
aniz
atio
n
Network Monitoring
For network monitoring activities, it was concluded that 50% of the work load
stems from projects and the remaining 50% by the number of network elements –
applying appropriate weighting factors accomplishes this
Weighting FactorsInternal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
A) Weighted projects
are calculated based
on time allocations
B) Information on the
network elements is
collected
D) Initial units are
calculated based on
weights
C) Weightings are calculated so that
average values are driven to the
desired ratio based on interviews
with target utilities
E) Final units are
based on
recalibrations
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82
Weighted
Projects
Network
Elements
Initial
Units
Final
Units
BC Hydro 350 1250 486 1
Manitoba Hydro 244 2957 566 1.16
Hydro-Quebec 857 13046 2279 4.69
Hydro One 580 1375 730 1.5
Average 508 4657
Initial Weighting 1 0.11
Final Weighting 0.00206 0.00022
Network Monitoring
HC UnitsUnit
Cost
HC at
HOT
HC in Excess of
HOT Efficiency
Level
BC Hydro 11.75 1.00 0.09 15.84 8.99
Manitoba Hydro 6.71 1.16 0.17 8.09 1.24
Hydro-Quebec 16.81 4.69 0.28 7.26 0.41
Hydro One 6.85 1.50 0.22 6.85 0.00
Network Monitoring
Scaling factors are also used to compare differing levels of activities
• The original interviews we conducted identified the network monitoring job functions at each of the utilities
• The procedures from Step 5, where we calculated weighted project values, established the amount of work
completed by each group
• With these two pieces of information the unit costs – headcount per work unit – can be calculated
• However, before comparing the values they must be adjusted to account for differing efficiency levels, which
is accomplished through the use of scale curve calculations
Scaling FactorsInternal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
MWU Presentation 9.26-28.17
CONFIDENTIAL
83
The use of scale curves allows us to make comparisons even when operating
volumes differ widely
Scaling FactorsInternal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Network Monitoring Efficiency Levels
8.00
10.00
12.00
14.00
16.00
18.00
20.00
0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00
Work Units
FTE
s/W
ork
Uni
t
HON
HQB
BCH
MTB
MWU Presentation 9.26-28.17
CONFIDENTIAL
84
Finally, revisions are made where collected information seems suspect
ValidationInternal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Internal Data
Collection
Benchmark
MethodCost Drivers
External
Data
Collection
Weighting
Factors
Scaling
FactorsValidation
Network Monitoring Benchmarking Model
Prepared for: Prepared by:
Company A Company B Company C Company D Company E
Large Projects 50 7 33 17 5
Medium Projects 122 16 11 140 17
Small Projects 231 265 4 18 78
Network Elements 5,892 3,876 1,852 4,500 1,750
Ntwk Mntr Headcount 14.95 8.00 14.75 15.61 13.43
Weighted Projects 1,969 504 873 1,003 271
Network Elements 5,892 3,876 1,852 4,500 1,750
Initial Units 3,492 1,506 1,352 2,166 723
Final Units 4.83 2.08 1.87 2.99 1.00
Initial Weighting - Projects
Initial Weighting - Elements
Final Weighting - Projects
Final Weighting - Elements
Unit Cost 3.10 3.84 7.89 5.21 13.43
Comparable FTEs 9.35 9.30 18.57 13.88 26.81
FTEs above Industy Avg. -4.00 -4.05 5.22 0.54 13.46
% from Industry Average -29.93% -30.31% 39.14% 4.02% 100.83%
1.00000
0.25853
0.00138
0.00036