It’s All About Time: The Revitalization of Work Measurement

It’s all about time: The revitalization of work measurement

ISE Magazine August 2020 Volume: 52 Number: 8

By Dave Hampton, Mark Burden and Laura Sanchez-Titko

https://www.iise.org/iemagazine/2020-08/html/hampton/hampton.html

Work measurement is a fundamental building block that enables industrial and systems engineers to understand time and build solutions that optimize around it. While it is a foundational industrial engineering tool that supports key ISE competencies, new technologies 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. Stakeholders 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 rethinking 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 processes.
• Finally, companies are under mounting pressure to better balance economic, environmental and social expectations. This requires significant trade offs that affect short- and long-term operating performance.

Threading the needle through these expectations and headwinds is a tremendous challenge. Whether it is leveraging data to deliver efficiencies, implementing a new service model, determining optimum wage rates or balancing business 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 passengers and baggage flow through an airport. Grocers leverage it to determine the best way to fulfill online orders. Delivery 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 aging learnings across a multichannel communication and educational plan. 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 uncovered that there is still a perception that work measurement means a clipboard and a stopwatch. The reality is that new industries, technologies and capabilities are redefining how work measurement can be leveraged. 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 advanced.

Work measurement in the Frito-Lay go-to-market system

Frito-Lay, the snack food division 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 engineers 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) model where it is responsible for delivering products to stores and merchandising them on store shelves. This DSD go-to-market 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 for all customer types and geographies. The more accurate the standards, the more efficient and reliable the service execution. 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 combination of video, stopwatches and information passively collect-ed from the picking technology have been used to determine standard times for walking, selection and container management 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 developed 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 utilization 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, subsequent 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 direct 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 observations, depending on store types. Due to this collection rate, and the number of observations required for accurate standards, the standards had to be categorized in approximately 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 observations 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 standards 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 technology to rethink the way data was collected and analyzed provided a solution

Developing a data analysis solution

A few years ago, Frito-Lay decided to leverage the GPS capabilities 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 integrated with other data to provide a massive amount of reliable time study data.

Here is how the process works: 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 developed for each account to estimate the size of the store property, including potential parking locations.

When the route sales representatives arrive for a store service, 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 delivery 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 regressions. Once standards are developed, they are uploaded to the appropriate tables for route engineering and route management 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 integrate 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 understanding 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 averages 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.

References: IISE Magazine July 2020 (https://www.iise.org/iemagazine/2020-08/html/hampton/hampton.html)