August 2020 | ISE Magazine 29
Work measurement is a fundamental build-
ing block that enables industrial and systems
engineers to understand time and build so-
lutions that optimize around it. While it is a
foundational industrial engineering tool that
supports key ISE competencies, new tech-
nologies and capabilities make timely data collection more
granular and accessible. ISEs are definitely in the sweet spot
as businesses convert this data to information that can be
used to improve and measure business processes.
As the demands of industry to deliver both efficiency and
effectiveness climb to new levels, significant headwinds have
emerged that require incredible focus and attention:
• Competitive pressures and industry consolidation require
companies to focus more on the customer. Stakehold-
ers want improved service experiences and it is no longer
enough to just improve efficiency.
• Wage and benefit levels continue to increase, resulting in a
growing shortage of skilled labor. Companies are rethink-
ing their compensation strategies to ensure appropriate
staffing levels.
• Big data capability has become an operating requirement
to thrive in the current business landscape. This evolution
can be an exciting journey, but large investments are often
needed to integrate these capabilities into business process-
es.
• Finally, companies are under mounting pressure to better
balance economic, environmental and social expectations.
This requires significant tradeoffs that affect short- and
long-term operating performance.
Threading the needle through these expectations and
headwinds is a tremendous challenge. Whether it is leverag-
ing data to deliver efficiencies, implementing a new service
model, determining optimum wage rates or balancing busi-
ness results across all stakeholders, one common denominator
is understanding time. It is what drives process improvement
and is a critical tool in every industrial engineer’s toolbox. In
essence, time is the new currency.
Feedback from the Work Systems Division Town Hall
at the 2019 IISE Annual Conference & Expo exposed how
work measurement has lost some momentum in academia
and industry. With new topics needing to be integrated into
program curriculum (i.e., data analytics), some classical ISE
topics are finding themselves under pressure as industrial
engineering departments ensure everything fits within the
credit hour limits.
In industry, there is tremendous excitement around new
modeling, simulation and visualization tools. We have all
heard the term “garbage in, garbage out” – well, it is now
more important than ever to ensure that the data feeding
those models has been properly collected and analyzed. New
technologies like GPS and time study apps provide an over-
whelming amount of data ISEs can use to improve and man-
age business processes.
A new campaign all about time
Think about how important work measurement is for the
industries around us. Airlines use it to optimize how passen-
gers and baggage flow through an airport. Grocers leverage
it to determine the best way to fulfill online orders. Deliv-
ery companies rely on work measurement to minimize the
amount of time and miles required to bring packages to your
door. The list can go on and on.
With that in mind, the IISE Work Systems Division has
launched a campaign labeled “It’s All About Time” focused
on rebuilding the awareness and reinforcing the importance
of work measurement. Key activities include benchmarking
work measurement in both academia and industry and lever-
Work Systems launches
time campaign
To help provide a new push toward work measurement, the IISE
Work Systems Division launched a campaign called “It’s All
About Time” to rebuild awareness and reinforce the importance
of work measurement. The campaign includes multichannel
touchpoints, including IISE Connect, and a heightened focus at
the IISE Annual Conference & Expo 2020 Oct. 31-Nov. 3 in New
Orleans.
The efforts included a student video contest for those in the
division. Each three- to six-minute video entry focused on the
importance of work measurement and how it has evolved with
new technologies and processes. The winners will be announced
at the Annual Conference with a first prize of $1,000 and second
prize of $500.
W
30 ISE Magazine | www.iise.org/ISEmagazine
It’s all about time: The revitalization of work measurement
aging learnings across a mul-
tichannel communication and
educational plan (Figure 1).
By understanding what work
measurement skills industry
will need in three to five years,
we can work with academia to
ensure new graduates have the
proper skills to succeed from
day one.
Some early work has uncov-
ered that there is still a percep-
tion that work measurement
means a clipboard and a stop-
watch. The reality is that new
industries, technologies and
capabilities are redefining how
work measurement can be lev-
eraged. Karen Craig wrote an
excellent article for ISE in June
2018, “Bringing Time and
Motion Studies up to Speed”
(link.iise.org/isejune2018_craig)
that shows how far the work
measurement tool set has ad-
vanced.
Work measurement
in the Frito-Lay
go-to-market system
Frito-Lay, the snack food divi-
sion of PepsiCo, has leaned into
this evolution and now lever-
ages GPS capabilities to enable
work measurement at scale in
its go-to-market system. Frito-
Lay continuously recruits engi-
neers to leverage their academic
understanding in a real-world,
business-driven environment.
Whether in manufacturing,
supply chain or go-to-market,
engineers play critical roles.
The company operates a direct store delivery (DSD) mod-
el where it is responsible for delivering products to stores and
merchandising them on store shelves. This DSD go-to-mar-
ket system executes more than 500,000 weekly service calls
to all types of retailers, including supermarkets, convenience
stores, dollar stores, etc.
Each week, more than 20,000 route sales representatives
and merchandisers drive nearly 4 million miles and spend
more than 1 million hours on these calls, which can include
order writing, fulfillment, delivery, shelf merchandising and
selling. Service calls can range from 30 minutes to three-plus
hours based on service model, store type, amount of product
delivered and merchandising requirements. Customers are
engineered onto fixed routes with service days scheduled to
ensure products are in stock. There are also constraints on
when deliveries can be made and when shelf merchandising
needs to be complete.
To ensure this system works efficiently and effectively, it
is critical that standard service times are properly developed
FIGURE 1
Time is the new currency
Key competencies related to time and work measurement and how it affects various industry sectors.
FIGURE 2
Work measurement at go-to-market
Frito-Lay employs a variety of techniques to plan and manage the go-to-market system.
August 2020 | ISE Magazine 31
for all customer types and geographies. The more accurate
the standards, the more efficient and reliable the service ex-
ecution. Less accurate standards would lead to missed or late
service calls and/or route sales associates working far more
or less hours than expected. Frito-Lay employs a variety of
work measurement techniques in order to properly plan and
manage the go-to-market system (Figure 2 on Page 30).
Order fulfillment is typically executed in a warehouse or
distribution center upstream of the actual stores. It supports
traditional direct observation techniques, where a combina-
tion of video, stopwatches and information passively collect-
ed from the picking technology have been used to determine
standard times for walking, selection and container manage-
ment activities.
Standard drive time involves the sales associate driving
from a depot to the day’s scheduled service calls and then
back at the end of the day. Expected drive times are devel-
oped using a comprehensive routing tool that include speed
limits, time-of-day traffic implications, commercial road
types and planned mileage. GPS devices on the trucks can
then provide a comparison of actual vs. planned drive time.
Sales management time is a key indicator of how much
time managers spend on value-added activities like selling
and the development of their sales associates. Since these
1,500-plus managers are in the market, and their activities
can vary greatly in frequency, scope and duration; their uti-
lization can be best measured via work sampling. Managers
can be randomly sampled and asked to record what activity
they are performing at that time. Data analytics can then be
leveraged to visualize how their time is being utilized. New
processes and technologies can then be developed to address
opportunities and shift more time to the key value-added
activities. When new tools or processes are introduced, sub-
sequent work sampling studies
can be executed to measure
their impact.
In-store service is a much
more complicated activity to
properly measure. Historically,
time standards were set via di-
rect observation with industrial
engineers observing the route
sales representative, recording
the start and stop times for store
service calls and some specific
in-store activities. A typical
day for an IE would produce
between three and 10 obser-
vations, depending on store
types. Due to this collection
rate, and the number of obser-
vations required for accurate
standards, the standards had to be categorized in approxi-
mately 10 limited categories.
However, the growing uniqueness and variations between
store types and geographies are now meaningful enough that
standards need to be more specific. This resulted in the need
for nearly 100 unique standards to cover the range of store
and geographical variations. Even if only 50 quality observa-
tions are required for each standard, that would mean nearly
1,000 days of IE support. That requirement would apply to
initially setting standards as well as updating them when new
tools and processes are installed. In that model, some stan-
dards could be outdated even before they were established.
The need for more detailed and flexible standards is clear,
but a cost-efficient way to collect enough observations with-
in a reasonable time frame was needed. Leveraging technol-
ogy to rethink the way data was collected and analyzed pro-
vided a solution.
Developing a data analysis solution
A few years ago, Frito-Lay decided to leverage the GPS ca-
pabilities installed on its route trucks. This allowed location
data for our assets to be passively collected and uploaded to
a large database. That data could then be cleansed and inte-
grated with other data to provide a massive amount of reli-
able time study data.
Here is how the process works (Figure 3): Every one of
Frito-Lay’s 250,000 retail customers are geocoded using
their latitude and longitude coordinates. This information is
also required for developing service routes and determining
planned drive time and mileage. Geofences are then devel-
oped for each account to estimate the size of the store prop-
erty, including potential parking locations.
When the route sales representatives arrive for a store ser-
FIGURE 3
High-tech stopwatch
Measuring store service time at Frito-Lay involved leveraging GPS capabilities installed on route
trucks to collect data for a reliable time study.
32 ISE Magazine | www.iise.org/ISEmagazine
It’s all about time: The revitalization of work measurement
vice, the on-truck GPS device captures a time stamp when
their truck penetrates the geofence. Once the store service is
completed, another time stamp is captured when the truck
exits the geofence. These time stamps are then uploaded to a
database where an analytics engine takes over.
The first analytical step is to integrate the GPS time
stamp information with sales ticket information from the
sales representatives’ handheld computer. This verifies that
a service call was made to the same latitude/longitude and
around the same time as reported in the time stamp. The
sales ticket information also provides store details and de-
livery size, which is used as an independent variable when
calculating the standard.
The next analytical step is to cleanse the data. There are a
few examples where observations are removed because they
are invalid. Examples include if two deliveries are made from
one parking location (the GPS time stamp cannot determine
when one service stops and the other starts) or if no valid sales
ticket matched time with time/location data from the time
stamp (the sales representative could have just stopped in to
the account rather than make a service call). These exclusions
are rare and account for a small percentage of the 500,000
potential data points each week.
Once the data is cleansed, standards are created for the
targeted store type/geography combinations. Delivery size is
the key independent variable used in developing the regres-
sions. Once standards are developed, they are uploaded to the
appropriate tables for route engineering and route manage-
ment processes.
Since this process runs continuously, standards can more
easily be updated when tools and processes change. Also, the
data can also be mined to further refine standards to specific
chains or tighter geographies.
Work measurement is a critical industrial engineering
building block that enables all key ISE competencies. It has
recently come under pressure in academia as ISE programs
continuously balance classical topics with the need to inte-
grate newer material, such as data analytics. However, the
need for ISEs to understand the importance of time and how
to integrate it into business processes is as strong as ever. E-
commerce fulfillment, transportation, delivery, ride sharing,
restaurants and theme parks all require a solid understand-
ing of time in order to deliver against efficiency and service
expectations.
Work measurement often is associated with a stopwatch
and a clipboard. That image is being redefined to one that le-
verages today’s new technologies and processes. Capabilities
like GPS and time study apps can provide an overwhelming
amount of data in a fraction of the time previously required.
Converting that data into information that improves and
manages business processes is right in the ISE sweet spot.
Dave Hampton is a 1986 graduate of the California Polytechnic
State University, San Luis Obispo industrial engineering depart-
ment. He has served on the Cal Poly IME Industry Advisory Board
since 2005 and served as its chair from 2008-2017. He recently
retired after 32 years with Frito-Lay Inc. where he led the Go-To-
Market Organization that innovated and deployed strategies, tools
and processes that supported the 15,000 route Direct Store delivery
system. He is also a member of the IISE Work Systems Division
Board and the IISE Industry Advisory Board.
Mark P. Burden spent a 30-plus year career with Frito-Lay Inc., a
division of PepsiCo. In the early part of his career, he concentrated on
supply chain management and material handling equipment design.
Over the past couple of decades, he has focused on last-mile Direct
Store Delivery Route Optimization, specializing in work measure-
ment and labor forecasting. He is a 1989 graduate from Purdue Uni-
versity with a bachelor’s degree in industrial engineering.
Laura Sanchez-Titko began her career at Frito-Lay Inc. after a short
stint in the telecommunication industry. Over the last 19 years, she
has been working with fleet, operations and sales under the Go-
To-Market Organization to identify and develop tools to deliver ef-
ficiencies across a 15,000-route direct store delivery system. Within
the organization, her work has won many awards, including one
of Frito-Lay’s most coveted, the Chairman’s Award. She graduated
from Texas A&M University with a bachelor’s degree in mathematics
and a master’s degree in industrial engineering.
Work measurement often is
associated with a stopwatch and
a clipboard. That image is being
redefined to one that leverages today’s
new technologies and processes.
