Tag: time studies

OM in the News: NASCAR’s Pit Crews and Operations

Chapter 10 of your Heizer/Render/Munson text , Human Resources, Job Design, and Work Measurement, opens with a Global Profile featuring high performance teamwork at auto races. In the case of NASCAR, races can cover up to 600 miles, with cars zipping around the track approaching 200 miles per hour. Yet races are often won by seconds, or even slivers of a second, and a slower pit stop can cost teams hundreds of thousands of dollars in prize money and potential sponsorships, writes The Orlando Sentinel (Sept. 3 , 2024).

Every second saved in a stop is worth about 20 car lengths on the track. Last season, the average margin of victory was 1.11 seconds, and it was under one second in 19 of the 36 races. The margin of victory was under one second in 10 of the 23 races so far this season.

“While you are fighting for every position on the track, you can gain multiple spots on pit road,” said the president of Joe Gibbs Racing, which has about 50 athletes in its pit crews. “It can 100 percent win you a race and absolutely lose you a race.”

The pursuit of that edge is why Hendrick, Gibbs, Penske and other big race teams invest millions of dollars to hire and train dozens of tire changers, jackmen and gas can carriers who can work in chaotic conditions on race days 38 weeks a year. Teams are building state-of-the-art gyms and hiring top trainers, chefs and yoga instructors. They are also paying hefty salaries — reaching $200,000 — to sign top athletes and lure pit crew members away from rivals.

The athletes, who included a few college lacrosse players and wrestlers, are separated roughly by body type: bigger linemen in one group, lankier receivers and defensive backs in another, and squatter linebackers and running backs in a third. They are evaluated on 12 different skills and tasks. (At a NASCAR minicamp, coaches collect 49 different data points for evaluation.)

Teams have learned that former football players often make the best prospects for 5-man crews, thanks to their strength, agility and speed. So teams scour college campuses looking for players  who didn’t catch on with an N.F.L. team and want to trade their football helmets for fireproof suits. For most of NASCAR’s 75-year history, mechanics, fabricators and others in the shop doubled as pit crews. Pit crews have become on-camera stars featured in Netflix documentaries.

Classroom discussion questions:

  1. Which tools in Chapter 10 could be used in a pit stop?
  2. What change has been made in crew sizes in the past 2 years? Why?

OM in the News: Improving Productivity at Starbucks

A barista prepares a drink at the lab inside Starbucks HQ.

In Starbucks headquarters lies a technology lab that is plotting the firm’s renewal. That includes rethinking the onerous path its baristas must take to make a Frappuccino. Inside the massive space, baristas working in a mock-up of a cafe walked back and forth between refrigerators, blenders and syrups to make a single blended coffee topped with cold foam and caramel drizzle. They asked if the company could build kitchens that bring the equipment closer together (see the topic of layout in Chapter 9) and make syrup pumps, milk dispensers and ice bins that work better.

“Starbucks, the chain that made espresso ubiquitous, now faces daily crises in dispensing it,” writes The Wall Street Journal (Sept. 1, 2022). U.S. stores designed a decade ago struggle to meet today’s consumer demand. Cafes that once averaged 1,200 orders a day are now asked to make 1,500. Workers have been pressing for better pay, staffing levels and hours. Turnover has shot up. One in 4 baristas are quitting their jobs within 90 days, up from 1 in 10 previously.

So Starbucks also has been testing how to overhaul operations to improve the experience for both employees and customers. If employees spend less time running around fetching foam and carrying 20-pound buckets of ice, maybe they will be happier working there.

As Starbucks expanded, so did its menu (see Chapter 5). It started serving Frappuccinos in 1995, and pumpkin spice latte and other flavors followed. Warm sandwiches came in 2003. It introduced cold brew and draft nitro coffee in the 2010s. In 2015, the company launched an app that allowed customers to pay for their drinks ahead of time and to customize their coffee orders in 170,000 ways!

The firm expects workers to deliver handcrafted beverages fast. A store clipboard, used to track workers’ drive-through delivery times, said “Expectations: Under 50 Seconds.” But stores are heavily restricted by design and need a remodel to cope. Starbucks has upgraded equipment periodically, including adding espresso machines that can pull 3 shots for complex orders, rather than 2. It conducted motion studies (our topic in Chapter 10) to measure how long it took baristas to walk across the floor to pump extra syrup, among other tasks.

Engineers mocked up designs for the cafe prep area, producing prototypes with 3-D printers. Technicians studied milk dispensers, ice machines and the size of dispensers for strawberries. “Every second matters with customers waiting,” says the new CEO.

Classroom discussion questions:

  1. What do you think Starbucks can do to improve productivity? (See Chapter 1)
  2. What can they do to lower turnover?

OM in the News: Amazon’s Way of Measuring Work

Amazon warehouse workers who can’t ‘make rate’ don’t last.

Austin Morreale worked at the Amazon fulfillment center in Edison, N.J.. “It was 10 hours of pretty much mind-numbingly boring work, pretty much standing in the same position for the whole shift,” he said. “But at the end of the shift, I was drenched in sweat and aching like I hadn’t ached since I was playing competitive soccer.”  Morreale was slow, he says, and kept messing up the patterns for efficiently putting items on robotic shelves—known as “stowing.” He couldn’t “make rate”: Amazonese for keeping up with the pace of work. In Amazon’s fulfillment centers, writes The Wall Street Journal (Sept. 11-12, 2021), human productivity is measured by an overall pick or stow rate calculated for each worker at a robot-fed pick-and-stow station.

On the job, no one ever stood behind Morreale and barked at him to work faster. But twice a day at a stand-up meeting, his shift managers told the group how everyone was doing. They knew because Amazon’s software, and an assortment of sensors in the warehouse, tracked workers’ every move. Knowing that if you don’t make rate you’ll get a warning, triggered by an algorithm, and if it happens often enough your job is in danger, can be a powerful psychological spur to work harder, and possibly to exceed your physical limits. (In 2019, Amazon reported 5.6 injuries per 100 workers. The average rate for warehouses in the U.S. that same year was 4.8 per 100).

More than a century ago, Henry Ford pioneered systems for speeding up work that we take for granted today (see Chapters 1 and 10). What Morreale experienced was Amazon’s 21st-century, algorithm-driven successor to Fordism. It’s a mix of surveillance, measurement, psychological tricks, targets, incentives, sloganeering, and an ever-growing array of technologies. This system of technologically supercharged management can be benevolent, or sinister, or both.

Imagine the delight of  Ford, if he could know, to the millisecond, how long it took every worker to complete a task, every day, in every facility he owned. Imagine what early time-and-motion experts Frank and Lillian Gilbreth could have accomplished had they been able to discard their film cameras and replace them with millions of hours of video captured from the digital cameras that watch every station at Amazon’s fulfillment centers.

 

Classroom discussion questions:
1. How would the use of time studies, detailed in Ch. 10, be impacted by the Amazon approach for setting standards?

2. What are the responsibilities of operations managers in dealing with productivity and safety at their warehouses?

 

 

OM in the News: A Stopwatch in the Operating Room?

stopwatchMost businesses know the cost of everything that goes into producing what they sell — essential information for setting prices.  “Medicine is different. Hospitals know what they are paid by insurers, but it bears little relationship to their costs”, writes The New York Times (Sept. 8, 2015). Now, thanks to a University of Utah project, its hospital is getting answers, information that is not only saving money but also improving care. The cost issue has taken on new urgency as the U.S. accelerates the move away from fee-for-service medicine and toward a system where hospitals will get one payment for the entire course of a treatment, like hospitalization for pneumonia.

The linchpin of Utah effort is a computer program with 200 million rows of costs for items like drugs, medical devices, a doctor’s time in the operating room and each member of the staff’s time. The hospital has been able to calculate, for instance, the cost per minute in the emergency room (82 cents), the surgical intensive care unit ($1.43), and the operating room for an orthopedic surgery case ($12). With such information, as well as data on the cost of labor, supplies and labs, the hospital has pared excess expenses and revised numerous practices for more efficient care. Harvard’s Michael Porter called the accomplishments “epic progress.”

The hospital began by looking at how much supplies cost — bandages, sutures, medications. Then it started tracing use of those items to individual patients. It added in labor costs, a more complicated question. Porter told the hospital to go into rooms with a stopwatch and time how long each staff member spends on each procedure and with each patient.

With its software, the hospital is also finding simple ways to improve outcomes and reduce costs. When doctors looked at their costs per day, they were stunned to see how much they were spending on lab tests. Each was cheap, $10-$20, but the total bill came to about $2 million a year. It turned out that 20-50% of lab tests were completely unnecessary, ordered by residents with no questions asked.

Classroom discussion questions:

  1. How can stopwatch studies be used in hospitals?
  2. Why is it so difficult to control costs in hospitals?

Video Tip: NASCAR Racing and Time & Motion Studies

Jay and I spend a lot of time developing the Global Company Profiles that open each chapter. The whole idea is to motivate students as they enter the topic by providing an interesting company that uses the techniques we are about to introduce. Some of the firms highlighted are Hard Rock (Ch.1), Disney (Ch.4), FedEx (Ch.8), McDonald’s (Ch.9), Amazon (Ch.12), and Delta (Ch.15). But my favorite Global Profile (and the one that took us the longest to create) is definitely the introduction to Chapter 10, Human Resources, Job Design, and Work Measurement. Here we highlight Rusty Wallace’s NASCAR racing team and how they live and breathe  time studies in the “pit”, where tires are changed and fuel added.

We just came across a great 6 minute video to accompany the Global Profile and think it’s a nice way to kick-start Chapter 10. The video features the NASCAR team of Kyle Busch and looks at the anatomy of a pit stop. The pit crew manages an amazing 73 maneuvers in just 12.12 seconds. Even if you aren’t a racing fan, I think you and your students will be impressed by this operation. It also makes a good tie-in to discussion of flow diagrams (Figure 10.5),  activity charts (Figure 10.6), and operations charts (Figure 10.7).

Teaching Tip: Measurements That Mislead

Today’s Wall Street Journal (April 2-3,2011) has a wonderful article on the subject of work measurement (Ch.10). The question of how to deal with employees who know they are being observed for a time study arises in every class I teach.  About 30 years ago, Prof. Paul Sackett, at the U. of Minnesota, began timing the speed of supermarket cashiers ringing up a few dozen items. He found (unsurprisingly) that some were faster than others. All knew they were being observed. Today, with electronic scanners recording the pace of workers over long periods of time, it is once again clear that productivity varies greatly.

Sackett assumed these separate measures (short-time observed and longer-period with no observer) would generate similar rankings. But they yielded very weak correlations. This led him to believe that there are highly motivated, focused people who perform well  when they know they are being tested for “maximum performance”.  On the other hand, “typical performance” (how well one does over the long haul) is influenced by a whole different set of character traits.

Think of the SAT,LSAT, or GMAT. They each take just a few hours (under maximum performance) and are supposed to give a reading of an individual’s talent. Though the SAT does a modest job of predicting grades for freshmen (R-squared=.12), it doesn’t do well at predicting post-college achievement. (Same for the LSAT).

“Even the NFL Combine is a big waste of time”, says the Journal. There is no consistent statistical relationship between how well players do at the Combine and how they succeed in the NFL. Grit, on the other hand, which reflects a person’s commitment to a long-term goal, does predict levels of achievement. (It seems like one needs grit to get a PhD) . But workers, football players, and students do not reveal their levels of grit when taking a brief test. What really matters, as we all know, is what happens after the test is over.

Teaching Tip: Fun Class Exercise in Work Measurement (Ch.10)

I am always looking for a simple, fun exercise to break up class for a few minutes, and find that shuffling cards is perfect for Chapter 10’s topic of Time Studies.

The equations average observed time, normal time, and standard time are very straightforward (see Equations 10-1,10-2, and 10-3 in the text). But some bright students  usually inquire as to where the Performance Rating needed in Equation 10-2 comes from. So I bring as many decks of playing cards as I can find to class that day.

Explaining that there are some tasks for which the Normal time is already known and established, I recompute the equation as Performance rating factor=Normal time/Average observed time. Then I bring out the decks of cards and group the students into teams that measure how fast each person can deal the deck into a very neat bridge hands (ie, 4 piles of 13 cards per pile). Each student repeats the task 2-3 times, while team members time her, then compute the average. Each person takes a turn being timed.

The Standard time for this task turns out to be 30 seconds , and I point out that the dealing activity resembles other production tasks involving manual dexterity. Each person’s Performance rating is then computed (30 sec./average time) and recorded by the team on the board next to that student’s name. Students have fun seeing who has the highest and lowest Performance ratings for this type of job skill.