Las Vegas Timeshare Industry Adds $2.5 Billion to Local Economy

The Las Vegas timeshare industry contributed an estimated $2.5 billion in consumer and business spending to the local economy in 2015, according to a study conducted by Ernst & Young for the ARDA International Foundation (AIF).  Adding to this total were over 16,000 jobs, $867 million in salaries and wages, and $148 million in local and state tax revenues for the Las Vegas region.
“It is not just the vacationers that benefit from the timeshare industry,” says Howard Nusbaum, president and CEO of ARDA. “This industry has a huge impact on local economies through jobs, spending by vacationers, and taxes.”
In addition to the impact of jobs added to the market, the local timeshare industry witnessed a total of $436 million in spending from vacationers. Vacation spending was twice as much off-site or outside of the resort. An average party of four spent around $1,700 on vacation expenditures during their stay, flowing that cash revenue back into the local economy.
Employment in the timeshare-related industry in the state averaged 5.6 percent higher compensation than the same positions across the U.S. in corporate, sales and marketing, and resort operations. Direct employment associated with the timeshare industry in the U.S. was estimated to be 231,090 jobs and 280,692 jobs in indirect employment. On average, there are 2.21 total jobs created in the U.S. economy for each direct employee associated with the timeshare industry.
The overall economic impact of the timeshare industry in the U.S. last year was $79.5 billion in consumer and business spending, with more than 511,000 full- and part-time jobs, $28.1 billion in salaries and wages, and $10.2 billion in tax revenue.
Other states with significant economic contributions from the timeshare industry:
  • California: $3.6 billion economic output; $1.3 billion labor income; 24,395 jobs, $267 million in tax revenue; and $471 million in consumer spending.
  • Florida: $14.9 billion economic output; $5 billion labor income; 106,158 jobs, $865 million in tax revenue; and $2.6 billion in consumer spending.
  • South Carolina:  $2.4 billion economic output; $818 million labor income; 19,157 jobs, $130 million in tax revenue; and $534 million in consumer spending.
All data was from the American Resort Development Association (ARDA) International Foundation’s U.S. Timeshare Industry:  Economic Impact Study 2016, conducted by Ernst & Young. For details on the study, visit www.arda.org/foundation, and for details on the Las Vegas market, visit ARDA’s infographic on the “Las Vegas Timeshare Industry: Building the Local Economy”.

Machine Learning Is Revolutionizing Every Industry

Machine learning is being applied in recommendation engines, marketing automation, financial fraud detection, language translation, and text-to-speech applications. 

Apple recently announced that the iPhone 7 would use machine learning in its camera to recognize faces, imagery, and even the lighting in a room, making Apple the latest tech company to give primacy to its use of machine learning. 

But machine learning is no longer exclusive to digital companies: Businesses in every industry are utilizing this technology to improve processes.

The NFL uses machine learning to gather deep insights into player movements, positions, and passes to reorganize play style. In the medical sector, machine learning analyzes patients and predicts the likelihood of their returning. Even hiring and talent management in most companies is now handled by algorithms that dig out desired characteristics and, hopefully, remove biases.

Machine learning’s data-driven intelligence is permeating every corner of every industry, and it’s starting to disrupt the way we do business globally. As Google’s Eric Schmidt puts it, “New developments in machine intelligence will make us far, far smarter as a result, for everyone on the planet.”

The Rise of Smart Machines

Machine learning has evolved into a powerful capability underpinning a variety of business solutions, including curating interesting content for visitors on websites, helping movie studios learn about consumer behaviors, and even engaging with users through customer chatbots.

Leveraging machine learning has enabled processes to be re-calibrated automatically and optimized for reduced cycle times, created a higher quality of delivered goods, and allowed for new products to be developed and experimented. The ability to leverage data enables for more precise decision-making in place of gut feel.

Information technology is an area most often associated with the benefits of implementing machine learning, but organization-wide use is already in place:

• According to Gartner’s research vice president, Alexander Linden, “Ten years ago, we struggled to find 10 machine learning-based business applications. Now we struggle to find 10 that don’t use it.” In fact, startup watchers like Crunchbase and AngelList show more than 1,000 startups in the machine learning space.

• A recent MIT survey targeting executives of large companies found that 76 percent use machine learning to target higher sales growth.

• More than a dozen European banks have already replaced older statistical modeling with machine learning, with mostly positive results.

Machine learning is also being applied in recommendation engines, marketing automation, financial fraud detection, language translation, and text-to-speech applications. With businesses generating more and more data, simply navigating this growing archive of information effectively almost necessitates machines with analytical capabilities.

Incorporating Machine Learning on a Global Scale

Machine learning’s growth makes data an increasingly integral part of how a business makes decisions. And data is data, regardless of the country. This puts machine learning in a unique opportunity to maximize its value across borders.

As data becomes a core agent of change within a business, data scientists everywhere will take a more central role in organizational strategies. Rather than having algorithms drive the information, it’s the information that’s driving the algorithms.

Machine learning will also begin to affect which businesses are successful in a global market. Because data has no native language, organizations that are data-rich have more leverage, regardless of their locations. That changes the landscape of competition.

While developing countries have begun to realize machine learning is a challenge to their demographic dividend in terms of job prospects, the developed countries can feel a broader impact as the influence is more profound.

The U.S. does have a competitive edge here: Machine learning enables the nation to reclaim some of the jobs it lost to offshore manufacturing because investments in developing analytical skills will build a pool of qualified labor in this country. With a profusion of data in manufacturing given the prevalence of sensors and IoT adoption, the ability to leverage data will be critical to building competitive advantage.

But this doesn’t mean the labor market will look as it did before outsourcing hit. Manufacturing jobs will be far more technology- and data-driven now than in previous generations. Machine learning’s impact implies that the nation has even more reason to focus on science, technology, engineering, and math education.

Machine learning shouldn’t be seen as a technology subject, and it clearly isn’t a short-term trend. It has already transformed industries by upending business models and, with growing maturity, will continue to be the single driver in changing how businesses across industries and nations relook at their customer engagement approach and their internal enterprise processes. In a growing global market, whether a business incorporates machine learning into its practices plays a key role in its success in the coming decades.

Guha Ramasubramanian heads corporate business development at Wipro Technologies and is focused on two strategic themes at the intersection of technology and business. Guha played a key role in the cyber resilience initiative and has led workshops for the World Economic Forum. He is also working on developing platform capability using machine learning and leads the Apollo Anomaly detection platform.

What This GE Exec Is Hiring For In 2017 (And Why)

Today’s GE is a different place from the GE you may have known 10 or even five years ago. I’ve just helped open a new site in Cincinnati that houses our Global Operations Center for the U.S. and Canada. More than just another location for a global tech company, it reflects what we’re working hardest at as we head into 2017, and how we want to get there. We’ve built open coworking spaces, we’re streamlining our shared services (HR, legal, accounting, finance, supply chain, and commercial operations), and now we’re looking for entrepreneurial problem solvers who can find new, efficient ways of getting things done.

Data is the most valuable language you can speak today.

It wasn’t always that way. The GE your parents and grandparents remember was a company made up of regional offices reporting to a central headquarters, with management responsibilities laid out in a neat corporate hierarchy. These days, we’re becoming more streamlined, simpler, and faster. As our business changes, we need to hire a workforce that’s comfortable with this new way of working. With that in mind, here are some of the key traits and job skills we’re looking for in new hires right now.

1. Comfortable Crunching Data

Not everybody is a software engineer, but every single person at Global Operations understands their part in GE’s transformation into a digital industrial company. Whether you’re in HR, accounting, or operations, being able to analyze and understand data is critical. We produce massive amounts of data every day and need to use it as efficiently as we can.

For example, our HR leader in Cincinnati is a chemist by training. She’s able to harness the immense amounts of data at her disposal to make informed decisions around recruitment and retention. It’s not the traditional career path we might’ve looked for in an HR leader a generation ago, but it’s a skill set that couldn’t be more valuable right now, and the organization benefits from her expertise.

So even if you don’t have a degree in engineering or your job description doesn’t include data processing, we want to see how you use data every day. I look for candidates who can explain how they turn their work into actionable insights—or who can tell us how they think data might help them do their jobs better. Data is the most valuable language you can speak today.

2. Humility And A Willingness To Experiment

Startups are known to encourage failure in the search for solutions, but we’ve learned that big companies need to do the same. Structurally, we’re a flatter organization these days—we knew we needed to be in order to generate better ideas, work more collaboratively, and retain the best talent. And culturally, we’re now more accepting of failure in the pursuit of an idea.

We’re more likely than we’ve ever been to hire someone who fits our culture and shows promise, even if they aren’t traditionally “qualified.”

The result is that the kind of person who succeeds at GE is humble. We want people who are comfortable being a little uncomfortable, who thrive in the ambiguity of a less hierarchical structure, and are prepared to fail—repeatedly—because we know it takes trial and error to bring ideas to life.

Don’t be afraid to talk about a time you failed at something. We want to hear the thought process that led to that setback and what you did next. Tell us about the time you had a great idea but weren’t sure how to make it happen, and the way you eventually did.

3. Proof Of Promise (Including Unconventionality)

At all of GE’s Global Operations sites, our interest in people who take risks is matched by a willingness to take risks on others. We’re more likely than we’ve ever been to hire someone who fits our culture and shows promise, even if they aren’t traditionally “qualified.”

Maybe you don’t have an MBA, or you aren’t fluent in spreadsheets. But if you’re a curious team player and an innate problem solver who isn’t afraid to mess up now and then, we want to talk to you. To be sure, plenty of companies like to say this, but not all of them can walk the walk. At GE, that often means helping people make lateral moves that wouldn’t have been open to them within the company years ago.

Shane Fitzsimons is a senior vice president and leads GE’s Global Operations, the company’s global multifunctional shared services operations.

Samsung’s Galaxy S8 might not have a headphone jack

I’m not excited about a new phone announcment from Samsung or how they hook up the headphones. Just tell me if it has a battery and if I’m ever going to be safe with your products again.

You were probably hoping the whole no headphone jack thing was just a 2016 fad, right? Sorry, but SamMobile thinks it’s here to stay, as Samsung is reportedly preparing to release its Galaxy S8 sans jack. The S8 is also expected to ship with a USB Type-C port for charging and listening to music. The Note 7 featured a USB-C port, too, but we all know where that phone ended up. (The trash.)

SamMobilenotes a few other rumors, like that the phone might ship with stereo speakers as a result of no headphone jack, and that it won’t feature a home button. It might also have a fingerprint sensor embedded in its 2K Super AMOLED display. SamMobile says the new screen will have the same resolution, but will no longer have a PenTile layout, which should improve sharpness, especially in VR.

Samsung has a lot to prove with this device. Are these rumors building up to an exciting announcement? I’m not so sure, although I guess when the bar is set at “just don’t blow up,” maybe it’s better to stick with safe product decisions.