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.
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."
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.
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.
In research just published in Marketing Science, my colleagues David Schweidel of Emory University and Natasha Foutz of the University of Virginia and I began to explore whether such synergies exist.
Much like the definition of big data, the job description for data scientist is definitely a work in progress. What skills are required? Well, in addition to possessing a strong math and computer science background, including the ability to devise algorithmic solutions to complex problems, data scientists need to be good communicators -- people capable of grasping business issues and explaining data-driven insights to executives and managers.
Fair enough. But how does an organization know that the data scientist it's just hired has all of these skills? The Institute for Operations Research and the Management Sciences (INFORMS), a 10,000-member international organization of analytics professionals, believes its recently launched Certified Analytics Professional (CAP) program provides the rigorous certification needed in the burgeoning big data field.
"We realized that there were a lot of people putting themselves out there as analytics practitioners, but no real defining body on what that meant," INFORMS president Anne Robinson told InformationWeek in a phone interview.
Ashley Smith
Public Affairs Coordinator
INFORMS
Catonsville, MD
[email protected]
443-757-3578
An audio journey of how data and analytics save lives, save money and solve problems.
Can we really trust AI to make better decisions than humans? A new study says … not always. Researchers have discovered that OpenAI’s ChatGPT, one of the most advanced and popular AI models, makes the same kinds of decision-making mistakes as humans in some situations—showing biases like overconfidence of hot-hand (gambler’s) fallacy—yet acting inhuman in others (e.g., not suffering from base-rate neglect or sunk cost fallacies).
The genetic testing company 23andMe, which holds the genetic data of 15 million people, declared bankruptcy on Sunday night after years of financial struggles. This means that all of the extremely personal user data could be up for sale—and that vast trove of genetic data could draw interest from AI companies looking to train their data sets, experts say.
Robert F. Kennedy Jr., as the new secretary of Health and Human Services, is the nation’s de facto healthcare czar. He will have influence over numerous highly visible agencies, including the Centers for Disease Control and Prevention, the National Institutes of Health and the Food and Drug Administration, among others. Given that healthcare is something that touches everyone’s life, his footprint of influence will be expansive.
Health insurance has become necessary, with large and unpredictable health care costs always looming before each of us. Unfortunately, the majority of people have experienced problems when using their health insurance to pay for their medical care. Health insurance serves as the buffer between patients and the medical care system, using population pooling to mitigate the risk exposure on any one individual.
During this podcast Handfield addressed various topics, including: the current state of the supply chain; steps and actions shippers should consider related to tariffs; how the supply chain is viewed; the need for supply chain resiliency; and supply chain risk mangement planning, among others.
Oklahoma State University's Sunderesh Heragu joins LiveNOW's Austin Westfall to discuss the evolving economic landscape after President Trump implemented tariffs on some of our biggest trade partners. Most tariffs have been halted for now -- but not with China. Beijing and the White House have levied steep tariffs on each other. Trump announced that tariffs on China would reach 145 percent. In response, China imposed 125 percent tariffs on U.S.-imported goods.
Twenty years ago, few people would have been able to imagine the energy landscape of today. In 2005, US oil production, after a long decline, had fallen to its lowest levels in decades, and few experts thought that would change.
In the case of upgrading electrical and broadband infrastructure, new analysis from the University of Massachusetts Amherst reveals {that a} “dig once” strategy is almost 40% more economical than changing them individually.