According to a recent KPMG survey of C-level executives,  92% are using data and analytics to gain greater insights into marketing.72% report their enterprises are regular to heavy users of social media data to improve customer relationships. 81% of enterprises are relying analytics to improve their understanding of customers.

[University of Pittsburgh Prof. Dave] Lebel says research has found that it can be easier to ask for help when you turn it into advice seeking. In a study published in the June 2015 issue of Management Science, researchers from Harvard Business School and Wharton School at the University of Pennsylvania found that advice-seeking differs from other help-seeking behaviors because you’re eliciting information for a course of action, retaining the decision-making process, and implying that the values of the advice seeker is similar to the adviser.

"Asking for a recommendation can feel flattering to the other person," says Lebel.

Analytics may be a young profession but it is taking off, and its growth is evident in the rapid increase in analytics patents that have been granted by the U.S. Patent Office. As an analytics professional, you may find that patents play an important part in your life -- the 40-plus patents that we co-invented at IBM were front and center for us.

Knowing the patenting process can be important for you and your company’s success, protecting your most valuable work. And if you want to learn about advanced analytics, the patent literature is an important source of information.

In a study we wrote with Troy White of Clarkson University that has just been published in the INFORMS journal Interfaces, we examined keywords relevant to descriptive, predictive, and prescriptive analytics found in U.S. patents that were issued between 2002 and 2013.

Practically, I was trained as an engineer. My degrees are all in operations research, not in economics. I gravitated to economics because I'm interested in how people coordinate and collaborate with each other. Economics studies all the ways people get along with each other.

Operations Research Analyst

National median wage: $72,596

Best Cities

5. Baltimore, MD ($97,750)

4. Washington, DC ($106,960)

3. Virginia Beach, VA ($93,620)

2. San Diego, CA ($104,880)

1. San Jose, CA ($117,530)

Worst Cities

5. Tampa, FL ($52,830)

4. Jacksonville, FL ($53,210)

3. Miami, FL ($52,870)

2. Tallahassee, FL ($43,440)

1. Baton Rouge, LA ($40,800)

Certified Analytics Professional -- INFORMS

What it's all about: The CAP certification is a rigorous general analytics certification. It certifies end-to-end understanding of the analytics process, from framing business and analytic problems to acquiring data, methodology, model building, deployment and model lifecycle management. It requires completion of the CAP exam (available at more than 700 Kryterion computer-based testing centers in more than 100 countries) and adherence to the CAP Code of Ethics.

How to prepare: INFORMS provides preview material and a Complete CAP Study Guide as an aid. It also provides free half-day CAP refresher sessions for organizations with 10 or more candidates.

Graduate school isn't like undergrad when, in theory, you could take a year or two to choose a major and poke around different career paths. The process moves a little faster as an MBA student. You don't need to set your target job in stone, but you should have a solid idea or two in mind, so you're ready to make the most of your courses – as well as networking and recruitment opportunities.

The following jobs are well-suited for MBA graduates, and the Bureau of Labor Statistics predicts hiring growth and solid salaries for each of them.

...

6. ​Operations research analyst: These analysts use statistics to identify and troubleshoot problems usually relating to production, logistics and sales. It’s possible to find an entry-level position with just a bachelor’s degree, but higher-level operations research analysts usually have an MBA with a specialization in production and operations management. Consider top schools, such as the Wharton School at the University of Pennsylvania and the Stephen M. Ross School of Business at University of Michigan—Ann Arbor.

First employed by World War II military planners, operations research has become a key tool in the big data age used by companies and other organizations to better allocate resources, develop production schedules, manage supply chains and set prices. It helps transport companies move freight and manage distribution, allows health care systems to improve the collection and processing of patient lab specimens, and lets supermarkets determine how best to organize products, for example.

It used to be that a theme park operator would pair an engineer with a business expert to improve queuing at rides and attractions, notes [INFORMS President] Robin Keller, a professor of operations and decision technologies at the University of California—Irvine’s Paul Merage School of Business. Today, that task is handled by a single person trained in operations research.

Parent trap. A third study found that investors put more money into mutual funds when the share price of the fund’s parent company is outperforming the market than they put into mutual funds run by companies whose share prices are lagging behind.

For most of the companies in the study, running mutual funds was a relatively minor source of revenue. That suggests that the inflow of investor money wasn’t driving the parent company’s share price, according to Clemens Sialm, a professor at the University of Texas at Austin who co-wrote the study—which also included fund firms such as T. Rowe Price Group and Janus Capital Group.

The study, which didn’t include companies whose shares aren’t publicly traded, such as Vanguard Group and Fidelity Investments, is due to be published in Management Science, another peer-reviewed journal.

In his CNN opinion piece, "The Big Dangers of Big Data" , Konstantin Kakaes of New America raises some interesting points about the ways that designing certain types of Big Data projects could lead to bad societal results.

Unfortunately, Mr. Kakaes' column appears to be part of a larger narrative that is skewing the perception of the importance of advanced data analytics to economies, societies and families around the world.

Big Data is not merely the accumulation of vast amounts of information, but a collection of interconnected and interrelated data points that, when analyzed carefully, helps business leaders make decisions that lead to increased profitability and job creation, assists doctors and scientists in understanding critical factors about health care, helps policymakers better protect the public from potential terror attacks, and much more.

It all starts with the sales rep. He or she is on the front line of the battle for corporate revenue. They also are the first and sometimes last contact point a customer has with the company. So who better than to turn to about advice on said customers, correct, than the sales rep? For that reason, when the sales rep urge headquarters to come down a notch on pricing, their opinion should seriously be considered, right?

Maybe, according to academic research on the subject—but first have the sales reps strenuously argue the case as to why a price should be lowered.

So found a study that ran in the November issue of Marketing Science, a publication of the Institute for Operations Research and the Management Sciences (INFORMS).

The study, called "Why do sales people spend so much time lobbying for low prices?" was conducted by Duncan Simester, the Nanyang Technological University Professor of Management Science, and Juanjuan Zhang, Associate Professor of Marketing, both at the MIT Sloan School of Management.

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.

[Adam] McElhinney said he thinks Enova's hiring practices and goals are what you'd find at most leading-edge analytics shops. So here are eight things you need to know if you're aiming to pass McElhinney's or his ilk's scrutiny and land a coveted analytics job...

2. Get involved with a professional society. The emphasis here is on involvement. Don't just show up for meetings but become involved in some way -- offer up your web development skills if you have them, or help write a newsletter or volunteer to help plan an event, McElhinney said.

3. Show continued development. McElhinney suggested three ways to make your resume stand out in this respect. One, get an analytics-related certification, be it via an independent organization like INFORMS, platform-specific from a vendor like SAS, or related to a specific domain, like finance, risk, or actuarial science. Two, enter a data analysis competition at Kaggle or the like. You don't have to win, but do be prepared to talk about the experience. Three, participate in open-source software development, maybe creating a package for R, working on a Python data analysis tool, or showcasing projects on GitHub.