INFORMS in the News
UPS's Orion is Lavish O.R.-based Deployment
UPS won’t say how much money it has invested in Orion. But management and information technology expert Thomas H. Davenport, a distinguished professor at Babson College near Boston, believes Orion is the largest deployment of operations research, and that UPS spent $200 million to $300 million to develop it, excluding many years of investments in underlying driver technology and communications infrastructure.
The Economics of Counter-Terror, by INFORMS Pres. Elect Ed Kaplan
How many good guys are needed to catch the bad guys? This is the staffing question faced by counterterrorism agencies the world over. While government officials are quick to proclaim “zero tolerance” for terrorism, unlimited resources are not made available to prevent terror attacks, nor should that be the case. Indeed, as with most public policy decisions, the appropriate staffing level depends upon both the benefits and costs of fielding counterterrorism agents.
How to operationalize the concepts described above is another matter, for unlike many production processes, it is not easy to observe the relationship between counterterror agent staffing on the one hand, and terror plot detection on the other. However, progress in this area has been made thanks to methods borrowed from queueing theory, which is applied widely to study staffing problems in situations ranging from telephone call centers to hospitals to manufacturing facilities to air traffic control.
Looking for Big Pay, Less Stress? OR!
Operations research analyst is another high-growth job in the business sector. These data miners can be involved in everything from logistics to manufacturing, looking to enhance a company's profitability and cost efficiency. In 2013, the typical salary was pushing $75,000 annually, but analysts in New York, San Jose and San Diego often earn more than $130,000.
Doing Good with Good OR - The CitiBike Example
Citi Bike deploys 6,000 bikes throughout the city that are often taken on more than 10 trips each day. In the morning, commuters pick up a bike near home and drop it off near their job. Near home, supplies dwindle, while midtown stations fill up, sometimes leaving few places to dock. During the day, similar imbalances occur across town. The solution is to “rebalance,” using trucks to move bikes from crowded locations to empty ones. Managing the process “is a good part of my day-to-day,” said Michael Pellegrino, director of operations for NYC Bike Share LLC, the operators of Citi Bike.
David Shmoys [above, left], the Laibe/Acheson Professor and Director of the School of Operations Research and Information Engineering, and graduate student Eoin O’Mahony [above, in grey sweater] have developed algorithms and data analysis tools to help rebalance the Citi Bike system as efficiently as possible.
O’Mahony described the system at the 2014 INFORMS Annual Meeting, “Bridging Data and Decisions,” in November in San Francisco. He earned first place and a $1,000 cash prize in the Doing Good with Good OR student competition with his paper, “Smarter Tools for (Citi)Bike Sharing.”
Air Asia Tragedy and Air Safety - Arnie Barnett Weighs In
What role, if any, the failings of Indonesia’s aviation system may have played in the crash of Flight 8501 may not be known for weeks. But in a country of 17,000 islands, where cheap flights are replacing the ferry journeys that Indonesians used to take across the archipelago, the chances of dying on an Indonesian plane, while rare, are unacceptably high, experts say.
Arnold Barnett, a [operations researcher] at the Massachusetts Institute of Technology who specializes in airline safety, said that the death rate in airplane crashes over the past decade in Indonesia was one per million passengers who boarded. That rate is 25 times the rate in the United States.
What will influence marketing in 2015?
V. Kumar, Executive Director of the Center for Excellence in Brand & Customer Management, Georgia State University and Head, Marketing Science to Marketing Practice Initiative, INFORMS Society for Marketing Science
I foresee the marketing function transforming into a more crucial role within the organization by becoming an integral part of the organizational decision-making framework. In other words, a tight-knit integration of marketing activities with the other business functions can be expected. This will create unique opportunities for marketers wherein marketing campaigns and strategies will now have to consider the interface of other business functions, and not just the marketing function. Further, interdependencies with other factors such as accountability, investment decisions, technology needs, and operational guidance will come to the fore as companies will begin to realize the power of marketing and its data-oriented analytical capabilities.
Universities Increasing Programs for Data Scientists
Capital Markets Outlook 2015: Investment in big data continues to increase, but it all means squat if there's no talent to program the tools, analyze the results, and create business value. Universities are responding by creating programs to train a generation of data scientists in technical and business capabilities.
5 Things CIOs Should Know About Prescriptive Analytics
What's the followup to predictive analytics? It's prescriptive analytics, which actually tells you the best action to take. Here are five things you need to know it.
First there was descriptive analytics, using data to describe current or past circumstances. Then came predictive analytics, analyzing data to predict a future outcome. Prescriptive analytics suggests the best option for handling that future scenario.
"Prescriptive tells you the best way to get to where you want to be," says Anne Robinson, director of supply chain analytics at Verizon Wireless and a past president of INFORMS, a society for analytics and operations research professionals. "If you want to differentiate yourself, the next step is the prescriptive tool box."
Four Ways to Grow Analytics Intelligently in the Year Ahead
As analytics continues to capture the attention of the business world, we contemplate a distinct field that uses newly available data to make better decisions. In the coming year, we must pay attention to our university analytics degrees, our continuing education, certifying competent practitioners, and organization-wide evaluations to make sure that our field grows and we bring greater benefit to those who seek our insights.
With McKinsey’s now famous forecast of a shortage in analytics professionals ringing in the ears of CIOs and executives, my fellow academics and business leaders must plan now to make sure that the supply of trained professionals remains high and that those who currently use analytics stay up to date in a fast-changing world.
Four types of preparation are necessary...
Predictive Analytics: Harnessing Insights from Text and Network Data
The predictive analytics landscape covers a wide variety of techniques and methods designed to derive insights from data. These techniques, which include statistical modeling methods, classification rules, forecasting techniques, simulation models, machine learning tools, and so on, have been used successfully for many years on structured data (data that consists of numeric or categorical attributes, where the number of categories is limited). In recent times, the volume and variety of data available for analysis has exploded, and most of this data is in non-traditional forms, which the traditional techniques were not designed to handle.
This article describes how you can transform non-traditional data, such as unstructured data (text) or semi-structured data (networks), into a structured form that you can then use to augment traditional data. Combining both types of data provides greater opportunities for actionable insight...
Radhika Kulkarni, Ph.D. is SAS Vice President for Advanced Analytics R&D, and a 2014 INFORMS Fellow. She may be reached at editor@ScientificComputing.com
Survey shows most organizations don't have plan in place to assess their analytics maturity
According to a new INFORMS survey of 230 business, government and academic representatives released today, the concept of "analytics maturity" is important or very important to their businesses (65 percent). Yet, 82 percent of those same respondents admitted they do not have a plan, model, or any other mechanism in place for measuring the efficacy or maturity of their analytics best practices over time.
Some 47 percent of those surveyed attributed the lack of analytics maturity modeling to the fact they don't believe it will help their businesses thrive, while 21 percent said they cannot afford an analytics maturity model solution.
"The ability to fully assess the maturity level of an organization's analytics best practices is paramount to their efficacy," said Aaron Burciaga, senior manager, operations analytics at Accenture. "With more access to information than ever before, organizations must have a strategy in place for how they leverage data and analytics, and assess the maturity of their programs to empower decision making and drive organizational strategy."
A Private Jet to Your Kidney Transplant with some O.R. help
The supply and demand imbalance between organs and the people who need them means that wait lists in New York or San Francisco might be twice that of, say, Kansas or Tennessee. The problem was brought to public attention in recent years by Steve Jobs, who used his resources to travel across the country for a liver transplant. For decades, doctors and policymakers have debated how to move organs or change allocation maps in an effort to eliminate these disparities.
Now, Tayur proposes to turn the problem on its head. OrganJet, his brainchild, is a company that uses an online app to help patients find out where in the country they could go to get a liver or kidney the fastest, and then promises a private jet to fly them there at a few hours’ notice when the organ becomes available.
It might all sound a bit crazy. At 49, Tayur doesn’t have any training in healthcare or in the field of medical ethics. He is a Carnegie Mellon University-chaired professor of operations management with a Ph.D. in operations research, a field that uses mathematical modeling to solve business problems.
Ebola and O.R.-style airport screening
An MSNBC interview with 2015 INFORMS Treasurer Sheldon Jacobson.
Marketing Science Study: Skillfully Use Product Placement
Consumers have become highly adept at avoiding television advertisements. We switch channels, divert attention to our tablets and phones, and of course fast-forward through ads on our DVRs. Partly in response to this loss of attention, marketers are increasingly focused on product placement as an alternative way of exposing us to their brands. After all, product placement is innately much harder to skip given its integration into the actual program content.
Most academic research on product placement has primarily considered it as a separate persuasive technique independent from the commercial break advertising. That is, mirroring early research on TV advertising, research has focused on how product placement influences viewers’ recall of and attitude toward brands. However, this overlooks the possibility that product placement in a show might influence the likelihood of viewers watching an advertisement for related products at the next commercial break.
Executive Pay: The final reckoning
IN HIS book, “Capital in the Twenty-First Century”, Thomas Piketty argues that it is impossible to find an “objective basis” for the high salaries of senior executives in terms of their individual productivity: they pay themselves such exorbitant sums simply because they can. However, in a forthcoming paper in Management Science, an American journal, two academics claim to have found such an objective measure, and conclude that most bosses are not overpaid.
In their study, Bang Dang Nguyen of the University of Cambridge’s Judge Business School and Kasper Meisner Nielsen of the Hong Kong University of Science and Technology looked at how firms’ shares react when the chief executive or another prominent manager dies suddenly. They identified 149 cases of this happening at American companies between 1991 and 2008.
Jacobson: Use O.R. Airport Screening Methods for Ebola
"Screening for Ebola is more difficult than screening for threats to the air system" from terrorists, said [2015 INFORMS Treasurer] Sheldon Jacobson, a computer science professor at the University of Illinois at Urbana-Champaign, who has written extensively about aviation security. He said more needs to be done to vet passengers, perhaps including blood tests for the Ebola virus and some sort of trusted-traveler program for people considered low-risk.
Aviation Operations Research to Screen for Ebola
U.S. airports have used risk-based security since then, but instead of looking for that needle, the TSA now identifies passengers who pose no risk to the air system – about 60 percent to 70 percent of travelers. The remaining passengers, for whom there is not enough information to rule out their threat, are subject to increased screening. That strategy focuses the right security resources on the right people. The result is a more secure air system at a lower cost, with less inconvenience to the majority of travelers. Can the same concept be applied to screening for Ebola? The simple answer is yes. Screening passengers before they get onto an airplane is the best weapon available for limiting the spread of Ebola.
With a nod to Bayesian Statistics
Some historians say Bayes developed his technique to counter the philosopher David Hume’s contention that most so-called miracles were likely to be fakes or illusions. Bayes didn’t make much headway in that debate — at least not directly.
But even Hume might have been impressed last year, when the Coast Guard used Bayesian statistics to search for Mr. Aldridge, its computers continually updating and narrowing down his most probable locations.
The Coast Guard has been using Bayesian analysis since the 1970s. The approach lends itself well to problems like searches, which involve a single incident and many different kinds of relevant data, said [INFORMS member] Lawrence Stone, a statistician for Metron, a scientific consulting firm in Reston, Va., that works with the Coast Guard.
At first, all the Coast Guard knew about the fisherman was that he fell off his boat sometime from 9 p.m. on July 24 to 6 the next morning. The sparse information went into a program called Sarops, for Search and Rescue Optimal Planning System. Over the next few hours, searchers added new information — on prevailing currents, places the search helicopters had already flown and some additional clues found by the boat’s captain.
The system couldn’t deduce exactly where Mr. Aldridge was drifting, but with more information, it continued to narrow down the most promising places to search.
Just before turning back to refuel, a searcher in a helicopter spotted a man clinging to two buoys he had tied together. He had been in the water for 12 hours; he was hypothermic and sunburned but alive.
Even in the jaded 21st century, it was considered something of a miracle.
Continuing Ed Preview: Harness the Predictive Power of Simulation
One important question that arises with simulation experiments is whether a Monte Carlo simulation or a discrete-event simulation is appropriate. A Monte Carlo simulation is appropriate when the passage of time does not play a significant role in the events being simulated. Estimating probabilities, expected values, etc., in problems associated with dealing playing cards, rolling dice, and flipping coins, for example, can be addressed by a Monte Carlo simulation. In order to estimate the probability of a specific event, a Monte Carlo experiment is conducted repeatedly, often several million times, and then the number of times that the event of interest arises is identified. This serves as an estimate of the true probability of the event of interest.
Although the concept is simple, the real-world implications are profound. Monte Carlo simulations are used in varied contexts, such as stock-price predictions, sports outcome predictions, and even to explore various molecular conformations of antibiotics…
Authors Larry Leemis, a Professor in the Department of Mathematics at The College of William & Mary, and Barry Lawson, an Associate Professor of Computer Science in the Department of Mathematics and Computer Science at the University of Richmond, will conduct Introduction to Monte Carlo and Discrete-Event Simulation, a continuing-education course offered by INFORMS, October 16-17 in Chicago.
Dr. Larry Leemis, a Professor in the Department of Mathematics at The College of William & Mary, and Dr. Barry Lawson, an Associate Professor of Computer Science in the Department of Mathematics and Computer Science at the University of Richmond, will conduct Introduction to Monte Carlo and Discrete-Event Simulation, a continuing-education course offered by INFORMS, October 16-17 in Chicago. Click here to register. - See more at: http://data-informed.com/harness-predictive-power-simulation/#sthash.8OB6WOYJ.dpuf
Training Healthcare Analytics Experts
A well-trained data scientist is often called a unicorn: elusive, desirable, and more than probably mythical. Even as healthcare joins a slew of other industries in its transformation into a technology-reliant ecosystem built on data analytics, finding and retaining qualified analytics and informatics staff members is easier said than done.
At Georgia Tech’s Stewart School of Industrial and Systems Engineering (ISyE), a group of professors led by Nicoleta Serban, ISyE Coca-Cola Associate Professor, and Julie Swann, ISyE’s Harold R. and Mary Anne Nash Associate Professor, has brought together an interdisciplinary collaboration of healthcare analytics experts, including many members of INFORMS, the largest analytics professional society, to train the new generation of data scientists.