38 ISE Magazine | www.iise.org/ISEmagazine
There is no question about the importance of re-
newing and improving the electrical infrastructure
in the United States. Aging structures only provide
high probability of accidents that most of the time
affect vulnerable areas. One of the key initiatives to
overcome aging infrastructure is to modernize the
electrical grid with cutting-edge technology devices that not
only provide good quality of services but also are in alignment
with where information technology is heading in terms of big
data analysis capabilities to constantly increase the value propo-
sition to customers.
Advanced metering infrastructure (AMI), or simply smart
metering, is defined as “an integrated system of smart meters,
communication networks, and data management systems that
enables two-way communication between utilities and cus-
tomers” (mordorintelligence.com). The growth in smart meters
deployment, supported by government policies and funded
incentives, has been constant for the past decade in the United
States, as shown in Figure 1 (on Page 39).
To cope with this rate of installation, projects must be de-
livered more efficiently to meet contractual requirements and
stakeholders’ expectations. In undertaking such large efforts,
all of us know that managing teams becomes complex – chal-
lenges around planning and logistics coordination are present,
project risks materialize and issues with visibility for actual per-
formance may arise.
Our client was in a situation in which the deployment of
an AMI project was delayed, the rate of installation was not
optimal and below planned. In other words, the forecast at the
early stage of the project was not prominent.
To understand the root cause of those problems and revert
the project performance, Motive Power Inc. applied Lean and
Six Sigma principles and developed tools.
Background on the project
Motive Power was contracted by a large East Coast utility
company to assist in the project execution by developing and
nding processes and tools to install smart meters efficiently in
T
How eliminating waste boosted meter
installation by 100% in New York
Plan based on Lean and Six Sigma ideals boosted efficiency, productivity
By Gerhard Baumann and Satvinder Sidhu
March 2021 | ISE Magazine 39
the greater New York City area.
The project covered the geographic area of the Manhat-
tan, Bronx and Westchester boroughs (Figure 2). Between
the three boroughs, there were approximately 2.5 million
smart meters to be installed.
In looking at the initial limited performance data avail-
able, the consultants in charge of the project identified a few
red flags that raised attention. Naturally, the first step to have
a thorough understanding of the project was to gather and
understand the historical performance data.
After the consultants analyzed the findings, the conclu-
sions suggested that the utilities company suffered at several
fronts: a lack of a robust planning process that made it dif-
ficult or impossible to develop logistics plans; the external
stakeholders’ management for building access was not in
place; the presence of large multidwelling units that was not
considered; assignment of teams and individual assignments
was ad hoc; there was no baseline for weekly targets, which
were increasing monthly; and determining which meters re-
quired special technicians was invisible.
Lean and Six Sigma concepts were implemented to drive
the desired improvements. The goals of this consulting proj-
ect that took place during July 2018 through February 2019
were enhancing profitability and reducing costs through
improved quality, productivity and efficiency. The business
driver for pursuing this project came down to cost and time.
Detailed project description
This project used the DMAIC methodology (dene, mea-
sure, analyze, improve, control) iteratively to diagnose and
improve the contractor’s meter installation process. Empha-
sis was placed on the measure and analyze stages to under-
stand the frequency of the problems while identifying their
root causes.
The process performance was measured early on to assess
the overall situation and determine project health. Various
sets of data were readily available to both the contractor and
Motive Power for usage. The sources included daily reports
on installation jobs, which included fields such as installation
time, location, technician name, start time, end time, me-
ter type and other relevant information. While all the fields
are self-explanatory, meter type was a critical measure that
needed to be accounted for since different types of meters
required advanced skills. Daily, weekly, and monthly metrics
were derived from this data.
Another measurement was conducted by plotting all in-
stallation jobs on a geographic information system (GIS)
platform. This helped to visually interpret which districts
were worked on and how productivity looked. In addition
to production data, baseline schedules, forecast metrics and
actual metrics were also available. All this data allowed for
the development of daily production trackers, which in-
FIGURE 1
Smarter meters
The growth in smart meters deployment, supported by government
policies and funded incentives. (Source: statista.com)
FIGURE 2
New York boroughs
The smart meter project covered the geographic area of the
Manhattan, Bronx, and Westchester boroughs and installation of
approximately 2.5 million devices.
40 ISE Magazine | www.iise.org/ISEmagazine
cluded technician install rate, break time and efficiency; geo-
graphical maps; and proper resourcing. Although measurement
was done throughout the project, initially it was clear that the
contractor was significantly behind schedule and it was vital to
determine how to get back on track.
Process mapping and visual mapping tools similar to Google
Earth, Google Maps and Excel 3D maps were used to analyze
the problem and determine the root causes. Although enough
technicians were available and everyone had their daily re-
source assignments, efficiency remained low. Everything from
the warehouse assignments of meters to technicians going out
to the field for installation seemed to be flowing, yet the data
proved otherwise.
After careful analyses, the primary root causes were identi-
How eliminating waste boosted meter installation by 100% in New York
FIGURE 3
Production obstacles
A cause-and-effect diagram showing meter installation productivity.
FIGURE 4
Results of the plan
A visual depiction of the installation patterns before and after the weekly workplan grouping show jobs grouped based on the day and
geographic location. Each color represents a specific day where the team would work.
March 2021 | ISE Magazine 41
fied to be the distance traveled between meter locations; ac-
cessibility to buildings; large skyscrapers and the challenges
faced within them; wrong technician assignments; wrong me-
ter type assignments; and lack of group assignments. Figure 3
shows the cause-and-effect diagram created for brainstorming
these causes and their relevant effects.
These root causes allowed productivity to decline. Building
supervisors required advanced notice to ensure technicians had
proper access on the day of installation. However, this respon-
sibility was not assigned to one specific individual and often
fell through the cracks, causing technicians to wait for hours.
The warehouse planners were also sending technicians to
multiple sites throughout the day. While acceptable, planners
failed to consider the distance between sites, resulting in long
walks with heavy equipment. Outside Manhattan, technicians
were driving 30 minutes between locations.
Moreover, skyscrapers brought on an entirely new chal-
lenge. Too few technicians were sent out and multiple floors
became incomplete because of it. The goal was to complete an
entire building on the day of the initial visit. However, the lack
of planning prevented this. Lastly, unqualified technicians were
assigned to advanced meters, and wrong meters were shipped
from the warehouse to the sites, causing delays of their own.
To solve these root causes, solutions in the form of dash-
boards for process feedback, solution scenario analysis and
waste elimination were created, along with various produc-
tivity reports to increase efficiency. These tools were used in
conjunction with worker narratives and root cause analysis to
identify and categorize waste events within the seven types of
waste. Waste reductions were primarily in waiting, extra pro-
cessing, transportation and motion.
To effectively eliminate waste, many process changes and
improvements had to be considered and implemented. Daily,
weekly and monthly installation plans were created first. The
installation plan took into consideration the meter type, loca-
tion and the number of meters at a specified address. It also
helped ensure forecasted targets were being met as they were
increasing monthly. After considering these variables, jobs
were grouped by each day and sent out to the warehouse and
installation teams.
This work plan established four things: 1. meter types were
matched with skill level; 2. warehouse shipping became more
organized; 3. drive and walk-time between sites was reduced;
and (4) large buildings were assigned an adequate number of
installers.
This installation plan also helped visualize where technicians
would work on a given day while being able to plan for road
closures, festivals or any other disturbances. Figure 4 shows
how the weekly installation plan looked visually with jobs
grouped based on the day and geographic location. Each color
represented a specific day where the team would work. As one
can see, keeping the area within a few blocks was essential for
productivity. In addition to technicians having this data, a list
of addresses was sent to the newly developed “Building Noti-
fication Team” responsible for calling each address at least two
weeks before the install date to ensure access was granted by
the building supervisor.
This installation plan, through various iterations, was im-
plemented throughout Manhattan for all future work. It was
a new process, and it was met with backlash. However, after
proper training and understanding of the intent, it was widely
accepted. Though all future jobs followed this newly devel-
oped process, a solution still had to be developed for the lack
of productivity in the past and for other boroughs that were
lacking productivity.
Smart grids, meters generate a buzz
The market analysis and advisory firm Mordor Intelligence
(mordorintelligence.com) forecasts annual growth of more
than 6% for the smart grid market in North America.
The goal of upgrading the grid network is to meet growing
demand by developing renewable power sources and reducing
transmission and distribution losses. Doing so requires a
considerable investment for utility companies to set up and
modernize their facilities to generate, transmit and distribute
power.
In 2017, 39 U.S. states enacted 288 policy and deployment
actions tied to grid modernization and advanced metering
infrastructure (AMI). The installation of smart meters in the
United States was expected to reach 98 million by the end of
2020, driven by the successful installation of more than 86
million by the end of 2018.
Other growth metrics in AMI include:
Smart meter installation share is expected to reach 80%
among U.S. electricity customers by the end of 2024.
United States’ electricity production had grown steadily in
recent years, increasing from 4,363 terawatt hours in 2014
to 4,460 TWh in 2018.
• Demand for smart grids has increased with the development
of variable renewable energy sources, like wind and solar.
The capacity rose from more than 81 gigawatts in 2014 and
to 145 GW by the end of 2018.
Smart grids are better able to coordinate response efforts
and visibility to the distribution grid during outages. Such
recovery efforts following hurricanes Harvey and Irma in
2017, Hurricane Michael in 2018 and Hurricane Dorian in
2019 emphasized the need for such speedy recovery efforts.
According to an estimate, Mexico is expected to invest $6.3
billion in smart grid infrastructure and $2.1 billion in LED
and smart street lighting by 2027.
42 ISE Magazine | www.iise.org/ISEmagazine
How eliminating waste boosted meter installation by 100% in New York
FIGURE 5
Solution scenario dashboard
Various triggers to increase productivity are indicated, on the left, by a gray and yellow line representing baseline targets and a blue and
orange line representing actual installations.
FIGURE 6
Finding waste
The project plan identified and eliminated waste and improved efficiency.
March 2021 | ISE Magazine 43
The solution scenario
analysis dashboard was a
tool used to figure out the
proper strategy. The dash-
board, as seen in Figure
5, was used to test various
triggers that may increase
productivity. On the left,
the gray and yellow line
represents baseline targets
and the blue and orange
line represents actual instal-
lations. Triggers such as in-
creasing efficiency, increas-
ing meters and increasing
resources were placed with
higher” and “lower” buttons to test out the solution.
After much deliberation, a new technician team was formed
to target the old jobs that should have been completed origi-
nally. This team was also assigned weekly targets and was go-
ing to use the same installation plan as the rest of Manhat-
tan. The only caveat, however, was that building access was
not guaranteed. Building supervisors only guaranteed access
when the entire building was going to be serviced, as it re-
quired a shutdown of electricity; thus, individual units in the
building were not a priority.
For this reason, a weekly area was established for teams to
work on instead. If technicians were not able to gain access to
a building on a Monday, there was a high probability of gain-
ing access on another day in the week.
Another change was rather than working individually, tech-
nicians would work in groups, each with an electric and gas
technician. This allowed for collaboration while holding one
another accountable for weekly targets. Installers were also
incentivized for completing more than their weekly targets.
Measuring the project benets
The various solutions implemented throughout this project led
to an increase in productivity of more than 100% and achieved
the required schedule to avoid penalties. Different boroughs
throughout Greater New York all benefited from the strat-
egies that were first tested in Manhattan. Through multiple
iterations, time wasted during travel, accessibility and material
coordination, planning and logistics was significantly reduced.
As mentioned earlier, the primary sources of waste reduction
were in wait, extra processing, transportation and motion.
Directly, the process became more proactive rather than re-
active through identification and elimination of these wastes.
Figure 6 displays the waste contributors and the solutions im-
plemented for improvement.
Figure 7 portrays the outcome of continuous improve-
ment and process implementation on a monthly basis. By the
end of the contract, the number of meters being installed, per
month, rose to 23,000. Through the identification of these
wastes and continuously working through eliminating them,
the team was able to increase productivity by more than 100%
in a short period.
Gerhard Baumann is a project management consultant at Motive
Power Inc. in San Francisco. He earned a masters degree in industrial
engineering from École Polytechnique de Montréal. He works primar-
ily improving project management processes in the renewables energy
sector. He is an IISE member.
Satvinder Sidhu is a project management consultant at Motive Power
Inc. in San Francisco. He earned a masters degree in industrial and
systems engineering from the University of Michigan-Dearborn and an
MBA. He works primarily with data to strategize solutions in making
operations more efcient in the utilities sector.
FIGURE 7
Manhattan progress
The outcome of continuous improvement and process implementation on a monthly basis.
Go Lean at fall IISE conference
Mark the date for the newly renamed IISE Lean Six Sigma
& Data Science Conference, led by the Operational
Excellence Division. The event is scheduled for Sept.
20-22 and will include presentations and discussions
on how Lean Six Sigma and data science have impacted
applications and industries ranging from manufacturing
and healthcare to logistics, supply chains and retail.
To learn more, stay tuned for updates at
iise.org/LeanSixSigma.