Tag: Mod.F

Good OM Reading: A Million Random Digits With 100,000 Normal Deviates

million random digitsJay just called from the snowy Denver POMS meeting, asking me to review the new edition of this classic book that we reference in Module F, Simulation. The book is Rand Corp.’s 600-page paperback, “A Million Random Digits With 100,000 Normal Deviates” (which delivers exactly what it promises), selling for $64.60 on Amazon.com. Exhibiting the great sense of humor that OM profs have, 400 people have submitted online Amazon reviews, writes The Wall Street Journal (May 1, 2013). Most of them mocked the 60-year-old reference book for OM professors, pollsters and lottery administrators.

“Almost perfect,” said one reviewer. “But with so many terrific random digits, it’s a shame they didn’t sort them, to make it easier to find the one you’re looking for.” Five stars from this commenter: “The first thing I thought to myself after reading chapter one was, ‘Look out, Harry Potter!’ ”

Several reviewers complained that while most of the numbers in the book appeared satisfactorily random, the pages themselves were in numerical order. Rand said its long list of random numbers, first published in 1955, is one of its all-time best sellers. “It’s a tool of some sort, but it’s beyond my clear understanding,” a Rand spokesman admitted.

One Amazon reviewer panned a real-life copycat publication called “A Million Random Digits THE SEQUEL: with Perfectly Uniform Distribution.” “Let’s be honest, 4735942 is just a rehashed version of 64004382, and 32563233 is really nothing more than 97132654 with an accent.”

“We are always amazed by the creativity of our customers,” said an Amazon spokeswoman.

OM in the News: Calculus for Truckers

As a former math major, it was hard to skip over the article by this title in Forbes (Sept. 12,2011) which describes the multimillion dollar simulation software created by Schneider National to manage its massive trucking business. With 13,000 drivers, 10,050 trucks on the road at any one time, and over 33,000 trailers waiting to be hauled, this 76-year old, $3.1 billion company faces many daily decisions regarding scheduling of drivers and equipment. For example, drivers are on the road between 4 days and 3 weeks at a time, and then must be back home by a certain date. The government regulates driver breaks and hours per day at the wheel (11 max). And customers are only open during certain hours.

Prior to hiring Princeton prof Warren Powell to build its fleet-wide “tactical planning simulator” (which is actually based on dynamic programming algorithms), Schneider relied on pilot projects to answer key logistical questions. A group of, say 20, drivers was carved out, experimented with, and results were drawn–at a cost of $100,000’s each time. But too often a system that worked well on the small sample did not scale well for the whole company. Sometimes the pilot even cost more than the money saved with the policy change.

The simulation model works like this: it runs forward in time 3 weeks to set the value of having a truck and driver at a certain location at a certain time. Then it runs backward in time to the “present”, reconciling the results with those that happened in the simulated future. It runs forward 3 weeks again and then backward, continuing to improve its estimate. When the schedule “converges” after hundreds of thousands of  decisions, the process is complete. Schneider has saved tens of millions of dollars with the new system, which not only schedules, but helps determine price hikes, hiring patterns, and fleet size.

Discussion questions:

1. What other aspects of OM can Schneider use the simulator to analyze?

2. Why is simulation such a valuable tool in OM?

OM in the News: Marriott’s Simulation Game Lets Students Run the Hotel

Marriott International has just rolled out a new hotel-themed online game this week, which it hopes will attract students to positions in the hotel industry. The Wall Street Journal (June 6, 2011) describes “My Marriott Hotel”  as a realistic game that puts the player in charge of running the hotel kitchen (the company will roll out games depicting other aspects of the hotel business next year). The social media game, debuted on Facebook, puts the player in charge of buying ingredients, after being given an array of options in quality and price. The player also hires staff (based on experience and salary), and buys kitchen equipment. The players have to direct tickets to cooks and inspect orders before sending them to the customer.

Unlike  commercial simulations, like “Farmville” (by Zynga), Marriott is using computer gaming as a recruiting tool– to help fill  50,000 hotel positions this year. “Our game is so appealing”, says a Marriott exec. “Not only am I having fun but I am actually getting an understanding what it takes to run a kitchen”.

The model follows the  wildly popular “America’s Army”, introduced a decade ago by the US military. This effective recruiting tool cost little and led to a whole genre of industry simulation  games generally played on a mobile device. Siemens AG just bought “Plantville”, which simulates  being a manager for a bottling facility, a vitamin factory, or a plant that builds trains. Similarly, PlayFirst owns “Hotel Dash”, which simulates luggage delivery, room service orders, and hotel renovations. Marriott claims its game “will be more realistic”. But a Wharton prof says creating an effective game to help recruit “so far remains elusive”. It has to be both fun and realistic.

Discussion questions:

1. How can these games be effective OM learning tools?

2. Why did Marriott decide to provide this simulation at no charge?