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00M-639 - IBM Big Data Sales Mastery Test v1 - Dump Information

Vendor : IBM
Exam Code : 00M-639
Exam Name : IBM Big Data Sales Mastery Test v1
Questions and Answers : 51 Q & A
Updated On : April 17, 2019
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00M-639 Questions and Answers

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00M-639 IBM Big Data Sales Mastery Test v1

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00M-639 exam Dumps Source : IBM Big Data Sales Mastery Test v1

Test Code : 00M-639
Test Name : IBM Big Data Sales Mastery Test v1
Vendor Name : IBM
Q&A : 51 Real Questions

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IBM IBM Big Data Sales

IBM's sales have fallen for 15 straight quarters | killexams.com Real Questions and Pass4sure dumps

Why IBM's CEO is hiring Brooklyn teens Why IBM's CEO is hiring Brooklyn teenagers The closing time IBM's earnings rose, "The Artist" had just won the Oscar for foremost photo and the big apple Giants were celebrating a super Bowl win over the new England Patriots.

on the grounds that then, IBM has rattled off 15 straight quarters of income declines. large Blue referred to Tuesday that its fourth-quarter earnings fell eight.5% from a 12 months in the past.

just over a year in the past, IBM was predicting that its income would attain $20 a share by way of the end of 2015. neatly, we simply accomplished up 2015, and IBM posted earnings of simply $14.92. or not it's no ask yourself IBM deserted that $20 goal in the third quarter of 2014.

it be a fantastic hunch for the 104-12 months ancient business. And it's best going to get worse.

IBM (IBM) estimated that a robust dollar would weigh closely on profits, forecasting that its income would be about $13.50 per share this year. Wall road analysts had anticipated profits of about $15 a share.

The enterprise become unwell-organized for its consumers' surprising heat embrace of cloud computing. Why buy massive, high priced IBM mainframes and servers in the event you pays Amazon (AMZN) or Microsoft (MSFT) to apartment your entire statistics for you -- for more affordable?

over the last a few years, IBM has tried to shift its method. it is now an important cloud player, racking up $10.2 billion in cloud sales final yr. And it has poured hundreds of thousands of bucks into massive facts analytics, mobility and safety. IBM spoke of revenue of those "strategic imperatives" grew by way of 26% in 2015.

but guidance a ship as huge as IBM takes a lot of time -- and patience that many investors should not have. Shares of IBM are already down 7% this 12 months, after falling 15% last year and 13% in 2014.

$IBM down 5% #premarket. Time for Watson to take over as CEO?

— Paul R. La Monica (@LaMonicaBuzz) January 20, 2016

Yet IBM's most popular shareholder is sticking with the aid of the business, for now anyway. Warren Buffett announced in November that he has lost $2 billion on his IBM funding, but he referred to he became assured that the stock's plunge is just "brief."

IBM's government leadership says it expects that its approach will repay quickly, but Wall street analysts are not anticipating IBM's sales to develop for at the least one other couple years.

"As we have now pointed out, this transformation will play out over time," pointed out Martin Schroeter, IBM's chief monetary officer, on a conference name with traders. "we're more and more encouraged that the approach is correct and that we're executing to radically change IBM."


IBM returns to the Charleston location as a a good deal different business | killexams.com Real Questions and Pass4sure dumps

IBM Corp. is decided to score a Wall road version of a hat trick in South Carolina.

because it approaches its 108th birthday, the ever-evolving expertise pioneer is bringing its shareholder meeting lower back to the Charleston area for the third time in the past 14 years.

The 2019 gathering might be held at the Charleston area convention core, the place traders once again will opt for a slate of directors, vote on executive pay, categorical their opinions in regards to the enterprise and hurl a number of questions at administration. 

The international Fortune 20 business called large Blue expects a turnout of at the least a few hundred in keeping with past attendance traits.

North Charleston is among the many few cities the place the IBM street display has ventured to more than twice. The old South Carolina conferences were held in 2005 and 2012, at the equal venue.

“We search for locations which have a big number of shareholders within a 50-mile radius of the area we select,” IBM spokesman Doug Shelton observed ultimate week.

It’s a tried-and-real lifestyle for the Armonk, N.Y-based company that obtained it birth in June 1911 as Computing-Tabulating-Recording Co. It switched its identify in 1924 to overseas business Machines.

“because 1961 we have moved our annual … meeting to a unique area from the 12 months before so that IBM is accessible to greater of its shareholders,” Shelton mentioned.

while it prides itself as an innovator, the enterprise hasn't joined the small but growing to be variety of organisations which have moved their annual investor summits online. Former investment banker Gary Lutin of manhattan-primarily based Lutin & Co. likes the conception of itinerant meetings as a result of they give stockholders of all stripes from diverse locations a rare possibility to size up and query decision-makers within the flesh.

“I’d analyze it as enlightened, reasonable practice," noted Lutin, who's additionally chairman of the Shareholder discussion board, which organizes workshops to aid traders pick out company governance issues.

The remaining time IBM introduced its administrators and buyers together in South Carolina, stockholders showed up from in all places. One retired couple traveled to Charleston from cell, Ala., wanting to hear what newly minted CEO Virginia "Ginni" Rometty was bringing to the desk.

Rometty — a onetime IBM engineer and the tech colossal's first feminine chief govt — laid out a plan for boom, together with a bet on the way forward for “big statistics” as an enormous profit center. She cited that her goal was to “invariably reinvent" a corporation that via then changed into beginning to circulate past hardware and private computer earnings. It changed into her first annual meeting as the appropriate boss, and for probably the most the early studies were glowing. 

“I feel IBM’s got a fine future,” an positive shareholder told The put up and Courier that day. 

Seven years on, Rometty continues to be within the nook office — she turned into paid $16.forty five million in money and inventory remaining 12 months — and has when you consider that delivered chairman to her company card. She'll be taking middle stage again at the conference center next month.

but she could face a more skeptical viewers in her encore efficiency in North Charleston. among other complaints, longtime investors are pissed off that the stock fee has below-performed the broader market whereas Rometty has been operating the reveal.

it be undeniable that the IBM of 2019 is a unique and smaller animal compared to the 2012 version, in virtually every approach. sales have skidded virtually 26 percent during the last seven years to about $seventy nine.6 billion in 2018, partly since the enterprise jettisoned its computing device division and other legacy businesses it has decided were now not a strategic fit. web profits has dropped with the aid of virtually half to $8.7 billion over the equal length. The enterprise's international workforce has been pared by using about 80,000 to about 351,000 personnel.

We're starting a weekly newsletter about the enterprise experiences which are shaping Charleston and South Carolina. Get forward with us - it's free.

The painful slog turned into enough to force off legendary buy-and-grasp investor Warren Buffett, who bought a big slug of IBM inventory in 2011. He delivered a no-confidence vote with the aid of unloading most of it via early remaining yr.

Rometty, who's generic for her mastery of MBA buzzwords, will come to North Charleston together with her revenue hat on. She'll possible urge investors to cling in there, that the transformation plan she hinted at in the actual same room in 2012 is eventually beginning to display results, as IBM makes inroads in areas corresponding to synthetic intelligence and blockchain know-how.

She's additionally sure to factor out that 2018 became the primary yr massive Blue grew on the revenue side considering the fact that 2011, when sales peaked at $107 billion. 

She'll even be pitching "Chapter 2," her time period for the subsequent phase of the cloud-computing gold rush. Rometty sees massive businesses moving to a "hybrid" model that combines their personal deepest data facilities with the potential they rent from off-web site servers. IBM's function could be smack in the center, providing the technical competencies and functions for those excessive-tech infrastructure mergers.

That imaginative and prescient is driving huge Blue's planned buyout of pink Hat Inc. The $34 billion acquisition of the Raleigh-based company is asserted to be the greatest-ever acquisition within the software trade. nonetheless it's peanuts compared to the amount of money Rometty estimates is up for grabs.  

"it's a $1 trillion market, 'Chapter 2,'" she informed Fox company information in late January. '"We will be number one in what the world calls hybrid cloud. it's 'Chapter 2' and we'll be no 1."

buyers can make a decision for themselves when Rometty and IBM make their return engagement to the Lowcountry on April 30. The reveal begins at 10 a.m.

Contact John McDermott at 843-937-5572 or observe him on Twitter at @byjohnmcdermott


facts Science Market to Witness big boom via 2028 | leading Key gamers | killexams.com Real Questions and Pass4sure dumps

Apr 02, 2019 (WiredRelease via COMTEX) -- data science is a wide term that incorporates records analytic equipment, which aid the organization to make improved selections, enhance efficiency, cut back operational prices, and boost consumer capabilities. statistics science structures are used to discover frauds and are additionally effective in practise of medicines in pharma industries.

The analysis file on world information Science Market 2019 keenly analyzes big elements of the business. The evaluation servers market dimension, newest tendencies, drivers, threats, opportunities, in addition to key market segments. it is in keeping with past statistics and existing market needs. also, involve distinct business methods accredited by the determination makers. That intensifies boom and make a unbelievable stand within the industry. The information Science market will grow with a big CAGR between 2019 to 2028. The record segregates the comprehensive market on the groundwork of key players, geographical areas, and segments.

Technological advancements, principally in massive data analytics and lengthening adoption of quite a few facts analytical equipment in industries across developed nations is a major component riding growth of the international information science market. furthermore, increasing adoption of a considerable number of cloud based mostly technologies and extending statistics collection & evaluation from cellular instruments are other main elements anticipated to boost growth of the global statistics science market over the forecast duration.

The study comprises simple counsel about the product reminiscent of data Science scope, segmentation, outlook. Likewise, it comprises provide-demand static, funding feasibleness, and components that constrain the growth of an business. principally, it presents product demand, each year income and boom side of the industry.

click here To download The PDF pattern Pages Of This analysis: https://marketresearch.biz/file/records-science-market/request-pattern

different Segments of global facts Science Market:

through classification: solutions, features. by means of conclusion user: Banking and monetary associations (BFSI), Telecommunication, Transportation and Logistics, Healthcare, Manufacturing

major leaders of the realm statistics Science market are:

Microsoft supplier, IBM enterprise, SAS Institute Inc, SAP SE, fast Miner Inc, Datalink SAS, Apteryx Inc, reasonable Isaac company (FICO), Math Works Inc

Regional analysis:

presently, the market in North america accounts for highest share within the global facts science market in salary terms, due to expanding awareness about facts safety and excessive adoption of facts analytic equipment within the region. The market in Europe accounted for 2nd-highest earnings share in the global records science market, as a result of turning out to be trend of preferring cloud and massive facts technologies in the region, followed with the aid of markets in Asia Pacific, Latin the united states, and middle East & Africa respectively.

For procuring The report click on here: https://marketresearch.biz/purchase-record/?report_id=6310

Who will all get merits from international information Science market analysis record?

* Product managers, industry administrator, chief administrative officers of the industries.

* Scientists, investigators, analysis analysts, and laboratory capabilities.

* Universities, college students, interns, professors and quite a few other academic organization attracted to records Science market.

* author, journalists, editors, reporter and webmasters get to find out about records Science .

* inner most/governmental institutes, venture managers associate in records Science industry.

* latest or approaching records Science market avid gamers.

In conclusion, the records Science market record divulge analysis discoveries, consequences, conclusions. Likewise, exhibits distinctive information sources, traders/distributors, suppliers, manufacturers, revenue channel, and addendum. In a notice, the complete record is a worthwhile document for americans drawn to market.

other linked reviews:

Greenhouse Horticulture MarketGuar Gum MarketAircraft Engines MarketChromium MarketHealthcare Contract research company (CRO) MarketInsect Feed Market


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How To Choose The Best Master’s Degree For You | killexams.com real questions and Pass4sure dumps

More and more business schools are offering business masters degrees, from generalist programs in management to specialized master’s offerings covering topics like accounting, data analytics, finance, and marketing.

With so many options out there, choosing the best master’s degree to suit your career ambitions can be a challenge.

Before applying, candidates should know the answers to the following questions: Who are the different master’s programs for? What jobs do they lead to? What do you study on the course? What do you need to know to get accepted?

To answer those questions, we spoke with students and faculty from five of the most common business master’s degree options at some of the world’s leading business schools.

Read on to find out how to choose the best master’s degree for you.

You can find out more about the master’s degree that interests you most by clicking on one of the links below.

Masters in Accounting

Masters in Analytics

Masters in Finance

Masters in Management

Masters in Marketing

Find out more about business master’s degrees via webinar

Masters in Accounting

Find out more about Masters in Accounting via webinar

nini

Dr Wang Jiwei, MSc in Accounting director at Singapore Management University (SMU)

Who is a Master’s in Accounting for?

Our Master of Professional Accounting (MPA) is designed to create a pathway for non-accounting graduates working or seeking to work in a field that requires specialized knowledge in accounting.

We also have a Master of Science in Accounting (MSA) which specializes in data and analytics. It’s designed for students who already have a background in accounting or business related disciplines, but wish to further their career and skills set in this data-driven era.

What skills/qualifications do you need to apply?

The overall quality of the applicant determines admission to the program. This would include prior academic performance at university, work experience, referees reports, interview scores, and GMAT/SMU Admission Test is compulsory.

Applicants must have sufficient background in math. Applicants with post-undergraduate working experience will have an added advantage. Applicants to the MSA must also have a business or accounting background.

What will you learn on a Master’s in Accounting?

Through the MPA course, students will learn about the three pillars of accounting; the business fundamentals, accounting core and the professional services which would include the following modules: management accounting, taxation, audit, corporate financial management and financial accounting.

The MSA equips students with the essential skills to harness data for critical decision making. They learn to make use of tools such as R, Python, Tableau, and SQL for data analysis, data visualization and data management. They also can learn machine learning techniques, and understand how they can be applied to the accounting and finance work.

What jobs can you qualify for after a Master’s in Accounting?

An accounting master’s degree is versatile. Every company needs somebody who is well versed in finance and accounting. Hence, the career of an accountant is not limited to the accounting, banking and finance industry. Good accountants are in demand in every sector.

In the recent years, the role of an accountant has evolved. Many organizations are eliminating manual accounting work, because computers and robots can automatically generate accounting entries.

But at the same time, we also see a growing demand in other job functions, mainly in the areas of data processing, management analysis and financial analysis. In the current market, there is a demand for domain experts who understand finance, accounting and data technology and how the systems work.

Top tip for applying to SMU?

What will give our applicants an edge is whether they have the drive to excel, the gumption to overcome challenges and the passion to make a meaningful impact through their work.

Master’s in Accounting student Q&A

ry

Ryan Guo Yu Sheng, SMU MSA student (part-time), manager of Global Operating Certificates at Visa in Singapore

Why pursue a Master’s in Accounting?

I have always been a tech-savvy accountancy graduate, and most of the process and data technology applied in my work was self-taught and unstructured. After completing a specialist diploma in Business Analytics in 2017, I was looking to further my knowledge and build on the basics learned in that course.

An understanding of data analysis and usage of automation and robotics have become essential to the modern finance function and this is also part of my effort in future-proofing my own career. There is an increasing focus on the application of technology to finance processes and simply relying on our IT colleagues to fill us in on technical developments is a thing of the past.

What advice do you have for prospective Master's in Accounting students?

A candidate should be technically savvy. Dealing with data requires a highly analytical and structured skillset, along with a sense of creativity for data transformation and programming. Having a conceptual understanding of accounting is important.

Masters in Analytics

Find out more about Masters in Analytics via webinar

impp

Crystal Grant, director of admissions (pictured above), and Kalyan Talluri, MSc Business Analytics program director at Imperial College Business School (pictured below)

Who is a Master’s in Analytics for?

There's a huge range of Master's in Analytics programs available, which reflects the growing demand from candidates and employers for graduates who are able to derive business insights and competitive advantage from big data.

Some will be aimed at new or recent graduates looking to launch their career, whilst others will be suited to professionals hoping to up-skill to progress or change jobs.

What skills/qualifications do you need to apply?

Programs vary in the balance of business versus technical experience required, but if you have a passion for data analytics, quantitative skills and commercial awareness, you should be able to find a Master's in Analytics that supports your goals.

Successful candidates to our MSc Business Analytics bring a wide variety of academic and work experience. We look for strong quantitative, communication, problem-solving and team-working skills. A passion for coding is also important, as the curriculum is very practical and you should be ready to learn and use programming languages.

What will you learn on a Master’s in Analytics?

Masters in Analytics aim to help graduates and young professionals understand the content, relevance, and importance of big data problems facing businesses. Our program takes a practical approach including a variety of machine learning, statistical, and operations research techniques.

Students can expect to learn solid technical skills in programming, including R, Python and SQL, data structures, and algorithms. They’ll learn skills in optimization, econometrics and statistics, networks, and machine learning. Industry-specific application is core to the program, and students learn to apply their mastery of tools to real business problems.

What jobs can you qualify for after a Master’s in Analytics?

The most popular destination for our graduates is consulting, however others go on to work in technology, FMCG, e-commerce, finance, healthcare, and media. Graduate roles vary depending on candidates’ previous experience, but include positions like business analyst, data scientist and, consultant. Employers include Accenture, Amazon, BCG, eBay, EY, Microsoft, and Revolut.

Top tip for applying to Imperial?

Don’t just list your experience of coding and programming languages. Highlight your problem solving skills by showing how you’ve applied your technical expertise on interesting projects. Demonstrating big-picture thinking, commercial awareness, and the ability to articulate complex information in a compelling and accessible way will help your application stand out.

impald

Master’s in Analytics student Q&A

Pinelopi Chamalelli, MSc Business Analytics student at Imperial, joining the analytics graduate scheme of a major consulting firm in London after graduation

Why pursue a Master’s in Business Analytics?

Analytics is the future; every business no matter its size collects more and more data, and desires to utilize them for a more efficient decision making. So, the opportunities we have after this program are endless not only in terms of quantity but also in terms of variety, since analytics can be applied in every single industry. imp

 What advice do you have for prospective Master's in Analytics students?

Coding skills or generally the ability to learn a new programming language or a new software package quickly is crucial. Three main programming languages we use are Python, R, and SQL, since these are widely used in the industry.

Good knowledge of linear algebra and statistics also help a lot. A good business understanding is also crucial for a successful data scientist.

Masters in Finance

Find out more about Masters in Finance via webinar

Diane Jordan, associate director of admissions, MIT Sloan

Who is a Master’s in Finance for? diane-jordan

Our Master of Finance is for individuals interested in learning the fundamentals of modern finance that emphasizes a foundation in how markets work. Students of the program come from a variety of bachelor’s degree disciplines including business, economics, finance, and significant representation from the STEM areas.

What skills/qualifications do you need to apply?

We seek smart, motivated applicants who are passionate about finance. Recent graduates, early career professionals in finance, engineers, mathematicians, physicists, computer programmers, and other high-tech professionals are encouraged to apply.

We look for: Success in academic, extracurricular, and professional endeavors; Ability to collaborate to accomplish a common goal; Ability to inspire others to achieve success; Excellent communication skills; Willingness to seek alternative solutions to existing challenges; Motivation to pursue goals.

What will you learn on a Master’s in Finance?

You’ll begin with rigorous courses in finance theory, financial mathematics, and financial accounting. You’ll be required to pass the Programming Literacy Test in either R or Python programming languages.

You’ll work with analytical tools—financial modeling, portfolio and pricing theory, statistics and data analytics, and computational methods—to help tackle multi-faceted challenges that arise in finance, from capital budgeting and cash flow analysis, to dynamic asset allocation and big-data-based investment strategies, and more.

You’ll take part in project-based courses solving real-world problems with MIT's partner corporations and culminating in presentations to corporate decision makers. You’ll choose electives from financial technology, to quantitative methods, to economics, to specialized disciplines such as healthcare finance, fixed income, mergers and acquisitions and asset management.

What jobs can you qualify for after a Master’s in Finance?

Jobs at asset managers, consulting firms, investment and corporate banks, brokerage firms, financial data providers, ratings firms, hedge funds, venture capitalists, insurance companies, public institutions, fintech, and more—from Fortune 500 companies to leading-edge boutiques.

Companies who have hired Master of Finance graduates from MIT for each of the last three years include Bain & Company, BCG, BlackRock, Deloitte, Morgan Stanley, McKinsey, and Citi.

Top tip for applying to MIT Sloan?

Get to know us and the admissions process through online chats and events to help you decide if MIT is a good fit.

Master’s in Finance student Q&A

david-mit

David Smadja, student at MIT Sloan, has an offer for an associate position at a major investment bank in New York

Why pursue a Master’s in Finance?

Prior to my master’s, I graduated from a master of applied mathematics. Though I had a good understanding of the quantitative side of financial markets, I felt I was missing some important financial knowledge. To me, masters in accounting, for example, are not capable to cover everything you need to know to succeed in the field of finance like a master’s in finance does.

What advice do you have for prospective Master's in Finance students?

The role of the master’s is to teach you what’s necessary to break through the industry but I reckon that some preliminary skills are beneficial. If you’re interested in financial markets, some coding and analytics skills (statistics, optimization, AI a plus) are a minimum to have. If you’re more interested by the corporate side, a good understanding of financial statements analysis and accountability rules is crucial. 

Masters in Management

Find out more about Masters in Management via webinar

eric-ivey

Eric Simard, associate director, MSc admissions at Ivey Business School, University of Western Ontario, Canada

Who is a Master’s in Management for?

It’s for ambitious, recent graduates who want a specialized Master’s degree, that will hone their skill-set, develop their leadership abilities and accelerate their career success. Students are admitted from a variety of disciplines, backgrounds, cultures.

This creates a unique experience in classrooms which is meant to help students understand, reflect on, and challenge their tendencies, preferences and biases.

At Ivey, students apply to a specific field of study which will allow them to focus their learning in one of three areas; Business Analytics, Digital Management, or International Business.

What skills/qualifications do you need to apply?

We evaluate applicants on a number of dimensions including; Relationship management; Leadership orientation; Openness to learning; Adaptability; Program readiness; Academic performance in their final two years of their undergraduate degree; Motivation for joining the program; Short and long-term career objectives; Pre-program experience; and International exposure/experience.

What will you learn on a Master’s in Management?

Master’s in Management programs are designed to help students bridge the gap between a solid theoretical foundation received in undergraduate studies and the practical and soft skills needed to make a difference in the early stages of their career.

Through Case-Method approach to education, Ivey MSc students are put in the position of the decision-maker and are asked to analyze data, develop alternatives and then make and defend their recommendations. We are focused on creating the next group of business leaders who are able to walk into a new role and take action.

What jobs can you qualify for after a Master’s in Management?

Graduates take positions in a variety of industries including; Technology, Management Consulting, Financial Institutions, Telecommunications, Consumer Packaged Goods, and more.

The majority of our graduates take starting positions in leadership rotational programs or in consulting firms focused in Risk, Technology or Human Capital. Many have titles such as data science associate, area manager or data analyst, and they work in a variety of organizations such as PwC, Scotiabank, Amazon, Walmart, Deloitte, Proctor & Gamble, Accenture, Sun Life Financial, BMO, Bell, EY, and Morgan Stanley.

Top tip for applying to Ivey?

Candidates should connect with our admission and recruitment team before submitting their application. They should spend time learning about what our programs have to offer by attending webinars, talking to current students, and reaching out to our MSc alumni. And they should consider and reflect on how the Ivey MSc in Management can support their short and long-term career goals.

Master’s in Management student Q&A

deanna-ivey

Deanna Hamilton, student at Ivey Business School, starting a consulting career after graduation

Why pursue a Master’s in Management?

I wanted to pursue a career in business and a Master’s in Management seemed like the perfect way for me to develop my knowledge as I did not study business during my undergrad. I also aspire to work internationally one day. Ivey’s Global Lab opportunity offered an eight-week, hands-on, international in-company experience which allowed me to immerse myself in an unfamiliar environment and work cross-culturally.

What advice do you have for prospective Master's in Management students?

Aside from the obvious skills of being a hard worker and passionate about the program, I think it is crucial for students to be open to learning and willing to adapt. It is essential for you to be willing to step out of your comfort zone to really take advantage of every opportunity on the program. Interpersonal and communication skills are also necessary for most jobs and, coming into the program, many of my classmates already had exceptional communication skills.

Masters in Marketing

Find out more about Masters in Marketing via webinar

Ning Li, academic program director of the MS in Marketing at Johns Hopkins, Carey School of Business

Who is a Master’s in Marketing for? ning-li

For students looking to continue in their marketing studies or students looking to pivot into marketing from another field. Those who are looking to become marketing experts will receive training in business foundations in addition to numerous high-level marketing electives.

What skills/qualifications do you need to apply?

Candidates will need undergraduate level communication and analytical skills.

What will you learn on a Master’s in Marketing?

Students will learn behavioral and quantitative methods and best marketing practices to address the most critical issues facing today’s marketer, including the impact of data and social media on marketing strategy, consumer behavior, social responsibility, competitive economics, business-to-business marketing, and more.

What jobs can you qualify for after a Master’s in Marketing?

Students can pursue careers in Marketing and Business Analytics, Marketing and Sales, General Management, Consulting, and more. Some employers who have hired our recent graduates include Amazon, China Telecom Americas, IBM, Johns Hopkins Medicine, P&G, and Tencent.

Top tip for applying to Carey?

Be Honest. No applicant is perfect and if there is a part of your application you are concerned about, be honest. Be open to why this program appeals specifically to you. This is important because honestly addressing concerns is important in marketing roles.

Master’s in Marketing student Q&A

msmarketing

Charlie Wang, MS in Marketing student at Johns Hopkins, Carey School of Business

Why pursue a Master’s in Marketing?

I value a program with a multi-disciplinary scientific approach to business where I’m exposed to a range of subjects, such as economics, psychology, and data science. Compared to other programs, Master’s in Marketing students explore a wider range of theories and models, and are able to quickly adapt to work in a variety of industries.

What advice do you have for prospective Master's in Marketing students?

Two skills that are essential are curiosity and fast learning skills. You don’t need to have all the answers, but you do need to be curious. You are expected to quickly adapt to the multi-disciplinary curriculum at a fast pace.

My advice: Start making friends now! Marketing students should be aware of the importance of relationships. Developing deep and enduring relationships with not only clients but also organizations will directly or indirectly affect one’s success.

Are you interested in a business master’s degree?

Register now for the Master’s Week webinar series held by the Graduate Management Admission Council (GMAC).

Running from 8-to-12 April, different business schools will talk about a different master’s program each day.

Monday: Accounting; Tuesday: Business Analytics; Wednesday: Finance; Thursday: Management; Friday: Marketing


7 Digital Marketing Marketing Trends You Can’t Afford to Ignore | killexams.com real questions and Pass4sure dumps

7 Digital Marketing Trends You Cant Afford to Ignore

“I would have written you a shorter letter but I didn’t have the time.”

This quote attributed to many different sources sums up what we are facing in this now very complex world. But keeping it simple and short takes time and effort. Distilling the complex into something that makes sense in one sentence or even a six second video is an art form that is to be treasured.

But as marketers that is what you are confronted with. Increasing complexity. It is just one of the trends that will impact your business in the years ahead.

We also need the right tools, platforms and technology to help us scale the huge amounts of data and noise that now confront us online. Here are 7 digital marketing trends that you need to keep your eye on.

1. Increasing complexity

Tech is largely to blame for making marketing complex. But it’s also the answer. Making sense of tons of data, always on marketing and the many forms of splintered media is something tech platforms do well.

Right alongside that sits different categories of complex. Facebook advertising is a discipline on its own that requires focus. Then add the dark science of “Search Engine Optimisation” and understanding the many moving parts that require mastery.

The types of media we need to master includes live streaming, Facebook videos and GIFS and Infographics. Then you need to master marketing automation and artificial intelligence tools and platforms.

2. Marketing technology

Marketing technology (sometimes called Martech) is continuing to grow. According to Venture Beat there has been over $134 billion invested in this category in startups in just 5 years. In 2018 IDC is predicting that CMO’s will spend $32 billion on buying and implementing Martech solutions.

But the category has 3 core categories. B2B marketing, B2C marketing and advertising technology. It should not be seen as one size fits all.

According to Ajay Agarwal in an article on TechCrunch there is an interesting divide between spending on marketing versus sales between B2B and B2C. B2B companies spend much more on their front end sales than on marketing at a ratio of 10:1. B2C spends a lot more on marketing than sales with an inverse ratio of 10:1.

Maybe we will expect to see Salesforce dominate B2B marketing tech as it is the dominant sales tool for B2B globally.

He sees the key trend and opportunity as one in which a B2C marketing company can create a B2C system of record from the start of the customer journey to sale.

3. The rise and rise of algorithms

The beauty at the the birth of social media networks was their simplicity. They flowed past you unfiltered.

Twitter was a distilled stream of unfettered consciousness. Facebook was a flowing page of diverse ideas and people. And some sat outside your tent of ideas and interests.

But things have changed.

The need to make money from the platforms meant that algorithms needed to be programmed to ensure that the social networks could start to monetise their distribution. The organic reach that initially excited marketers, writers and entrepreneurs has been dialled back.

Also the volume of data has also exploded in the last 10 years driven by the two obsessive technologies of social media and smartphones. To make sense of that as finite humans means we need help from the machines. And they run on algorithms.

Why do we need algorithms?

The amount of data that confronts us each day needs filters to help us make sense of it. Here is the global digital snapshot of the size of the ecosystem that confronts us.

These platforms, devices and networks are producing this avalanche of data.

  • 5.97 billion hours of YouTube are watched every day
  • 4.3 billion Facebook messages are posted each day
  • 67 million images posted on Instagram every 24 hours
  • 269 billion emails are sent 24/7 each day
  • How algorithms are applied

    Algorithms also help marketers and entrepreneurs break through the clutter. And they are used to reach your target markets on Amazon, Tripadvisor, search engines and even in email marketing .

  • Amazon – products or books you might like based on past activity and other secret codes.
  • Search – Content and information you want to find.
  • Social – People you want to hear from or see.
  • Emails – Gmail now uses an algorithm that sorts it into tabs and also sends it automatically to spam based on its filters.
  • GPS – Help us navigate a city or find our way to a hotel.
  • Choose a restaurant – Reviews on Yelp or on Tripadvisor.
  • So we need to keep studying how they work and learn to work with them as they continue to change and shape shift.

    4. Platforms and apps

    The web is moving away from an Internet of websites to an Internet of apps and platforms. You may not have noticed it but it is happening right before our eyes. In 2014 more people accessed the Internet though mobile apps than desktop computers for the very first time.

    In 2017 over 86% of our time is spent on apps on our mobile phones.

    This big trend is something that can’t be ignored and marketers are going to need to work out how they reach consumers via apps and platforms. The obvious answer to this in part will be the rise and rise of Facebook advertising from the platform and also applying marketing tactics to apps like Messenger and WhatsApp.

    5. Artificial intelligence

    There are two things that humans aren’t good at. Collating and making sense of the vast amounts of data and also scaling our humanity. That is what machines excel at and artificial intelligence allows humans to amplify themselves.

    Watson, Einstein and Rank Brain are just three of the big players battling out for world domination in artificial intelligence . Watson is owned by IBM, Einstein by Salesforce and Rank Brain by Google. But underneath these giants who mostly use it for internal use sits a growing range of apps and platforms that are using AI for niche marketing optimization.

    Chatbots were maybe the first obvious use of AI for marketing with their abilities to handle initial enquiries without the need for human inervention. But what are some of the other ways AI is being used and imagined for improving marketing performance and scaling?

    Robert Allen from CITU lists 15 ways in which AI can be used for marketing.

    But let’s take a closer look at just 3 ways you can use artificial intelligence .

    Content creation

    An AI program called WordSmith produced 1.5 billion pieces of content in 2016. The other challenge is not just creation but curation of content at scale. An AI tool like Rocco can recommend content from social media that your followers are likely to love.

    Pay per click advertising

    Making sure that you are making the best use of your budget when performing paid ad campaigns with millions of dollars in spend means AI becomes an attractive option.

    Albert and Frank are two marketing platforms that use machine learning to buy media and deliver ads for the best results. And this is done at scale and speed that no human could ever hope to achieve.

    Email marketing

    Making email smarter instead of a blunt tool for just broadcasting is something that AI can offer. AI can improve the delivery time for achieving the best open rates, target customers with the right emails and even product recommendations that they want to buy.

    McKinsey research estimates that Amazon generated 35% of its revenue with email product recommendations driven by AI.

    6. Video

    Video continues to emerge as a visual marketing trend that sits in a variety of buckets. For simplicity we can place them in 3 categories. Traditional 30 second ad style, live and social pre-recorded for social.

    Traditional

    The traditional 30 second ad style video 20 years ago was typically created 4 times a year with a 2 million dollar budget for each. This continues but the 2 trends that are transforming video today are driven by social media realities of live streaming and 6 second videos.

    Live streaming

    Live streaming is the hot new trend with Facebook (Facebook Live), LinkedIn, Twitter with Periscope and YouTube with its “Live Events”

    According to Globalwebindex.net “As ad-blocking continues to grow in popularity it’s more important than ever for brands to engage consumers via entertaining content and native advertising”

    And live streaming is one of those forms of content.

    Image source: GlobalWebIndex

    But the challenge with any form of video is doing it well.

    The 6 second pre-recorded video

    According to AdAge, Facebook has already been telling its video advertisers to hit people with faster messages. The 6 second video emerged as an ideal ad length in a recent test conducted with Tropicana.

    Tropicana compared the results from Facebook ads that were 6, 15 and 30 seconds long. The shortest saw “higher brand metrics across the board,” Sandberg said.

    Companies like Shuttlerock are using technology to scale 6 second Facebook video ad and are riding the wave of what the data is telling us is the most effective length for a video.

    But the challenge for all video is still the messaging. Video is now often watched in silence with subtitles running so people can read while viewing.

    7. Influencer marketing

    The rise of ad blocking means that reaching your audience via influencers is on the rise. A study by PageFair and Adobe shows that online consumers are becoming more and more frustrated with adverts interrupting their browsing experience. As of June 2015, 198 million people used ad-blocking browser extensions.

    Today’s consumers prefer to make their purchasing decisions based on either recommendations from friends and family, or from online influencers they admire and trust.

    Also the reason influencer marketing trend is becoming entranced is its performance. Just check out these stats on the effectiveness of influencer marketing:

  • Businesses earn approximately $6.50 for every $1 they spend on influencer marketing.
  • 81% of marketers who have used influencer marketing deemed it to be effective.
  • 86% of women turn to social media platforms before making a purchase.
  • Influencer marketing delivers 11 times higher ROI than traditional forms of digital marketing.
  • There are also 2 distinct categories of influencer marketing. B2C which is generally about building brand awareness and B2B which often is more about lead generation and measurable results.

    8. Storytelling

    Despite all the tech there is a real movement to making our marketing more human. Companies are backing causes. Taking a stand whether it is for equal opportunity, ageism or sexism. Marketers and entrepreneurs are using “live” video to share their ideas and insights.

    But the trend that I am enjoying is seeing the rise and application of storytelling being woven back into the digital marketing landscape. It is being used more in blog posts and online presentations. It is being written into emails to stand out from what is often an ocean of bland information and data.

    We have been distracted too long by the shiny new tech toys and forgotten some of our humanity in the process.

    It’s also time to tell better stories.


    Automation and Technology Increase Living Standards | killexams.com real questions and Pass4sure dumps

    Many Americans worry that automation will significantly reduce the need for human employees. Historical experience should help to alleviate many of these concerns. Technological advances have eliminated specific jobs and reduced prices, but the historical record shows this has left consumers with more money to spend elsewhere, increasing the demand for human labor in other sectors of the economy. Some prominent economists suggest that this time is different. They fear that advances in computer technology will substantially reduce the demand for human labor, especially less-skilled labor.

    The data suggest that these concerns are similarly misplaced. Productivity growth has slowed over the past decade. The less-skilled employees who are often seen as endangered by automation have seen their employment and compensation grow at above-average rates. Automation is changing the type of work Americans do, but not the overall need for human labor. Technological progress continues to enable Americans to attain higher living standards.

    Long-Standing Concerns

    Many analysts fear that technological advances will soon make much human labor redundant.[1] They predict that many employers will soon lack productive tasks for less-skilled Americans. Historically, these concerns surface most often when cyclical unemployment is high. During the Great Depression, British economist John Maynard Keynes predicted impending mass “technological unemployment”:

    In quite a few years—in our own lifetimes I mean—we may be able to perform all the operations of agriculture, mining, and manufacture with a quarter of the human effort to which we have been accustomed.…

    …We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come—namely, technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.[2]

    After World War II, the American and British economies recovered and those fears subsided. They resurfaced in America again after the 1957 and 1960 recessions. In 1961, Time magazine reported:

    How much has the rapid spread of technological change contributed to the current high of 5,400,000 out of work? Labor Secretary Arthur Goldberg last week set up a special group to find an answer. While no one has yet sorted out the jobs lost because of the overall drop in business from those lost through automation and other technological changes, many a labor expert tends to put much of the blame on automation.…

    In the past, new industries hired far more people than those they put out of business. But this is not true of many of today’s new industries.... Today’s new industries have comparatively few jobs for the unskilled or semiskilled, just the class of workers whose jobs are being eliminated by automation.[3]

    Shortly afterward, the economy began a prolonged expansion that raised incomes and created millions of new jobs. By 1968, the unemployment rate fell to 3.4 percent.

    Lump of Labor Fallacy

    Fears of mass technological unemployment are predicated on a “lump of labor” model of the economy—the belief the economy needs a roughly fixed amount of work performed.[4] In this economic model, machines automating work formerly done by people reduce the total amount of work remaining for humans, reducing total employment. Keynes forecast an impending crisis of unwanted leisure. He suggested future societies would establish three-hour workdays to give everyone enough work to avoid boredom.[5]

    Almost all economists reject this model today. Economists have found that an almost unlimited amount of potential work exists in the economy because people’s material desires continue to expand. Virtually all Americans today enjoy material living standards vastly better than the wealthy of 1900. Nonetheless, most Americans today would purchase additional goods and services if they received a raise or bonus.

    Automation does reduce the human labor needed to produce particular goods and services, but it also reduces production costs. Competition forces firms to pass these savings on to their customers through lower prices. These lower prices lead consumers to buy more of the now less-expensive product and leave them with more money to spend elsewhere, increasing the demand for labor in those sectors of the economy. The amount of work in the economy expands to use the available labor supply.

    Economists strongly agree on this point. The University of Chicago recently asked a panel of prominent economists whether they agree that “advancing automation has not historically reduced employment in the United States.” Over three-fourths expressly agreed with that statement, and only one of the economists disagreed.[6]

    America’s economic history illustrates how technology reallocates—but does not eliminate—human labor. In 1910, approximately one-third of all Americans worked on farms,[7] food was expensive, and the typical family spent almost half its budget on food. By 1960, technological advances such as the tractor had reduced the proportion of Americans working on farms to well under one-tenth.[8] This transition did not lead to mass unemployment. Instead, former farmhands began working in offices and factories. They enjoyed less expensive food and newly available manufactured goods.[9]

    Since then the manufacturing sector has also found new ways to automate tasks. Between 1960 and 2014, the proportion of Americans working in factories fell by two-thirds even as output dramatically increased.[10] Former manufacturing workers moved into the service sector. They enjoyed even more affordable food, less expensive manufactured goods, and newly available services. As of 2003 the average family spent just one-eighth of its budget on food.[11]

    Greater Living Standards

    Technological progress enables employees to produce vastly more goods and services with their labor. This increases their compensation because competitive labor markets compel employers to pay employees proportionately to their productivity. Technological advances would only reduce aggregate employment if Americans stopped spending their increased earnings on new goods and services—something that has yet to happen.

     

    Chart 1 illustrates this, showing average U.S. hourly labor productivity between 1973 and 2014. Over this period, technological advances enabled employees’ average hourly productivity to increase by 108 percent. During that time period, the average hourly compensation of American employees increased almost as much—85 percent.[12] Chart 1 also shows the employment-to-population ratio for prime-age workers (25-year-olds to 54-year-olds).[13] The huge increase in automation and technology had little effect on employment rates. Instead, employers found jobs for the millions of women who entered the labor force in the 1970s and 1980s. Historically, technological progress has increased wages with little effect on total employment.

    Is This Time Different?

    In the aftermath of the Great Recession, fears about automation have resurfaced. Most notably, MIT Professors Erik Brynjolfsson and Andrew McAfee have raised these concerns. They and likeminded economists worry that advances in computer technology mean this time may be different. They believe technological advances will enable computers to eliminate most of the workforce. McAfee argues:

    When I see what computers and robots can do right now, I project that forward for two, three more generations, I think we’re going to find ourselves in a world where the work as we currently think about it is largely done by machines.[14]

    In particular, McAfee and Brynjolfsson worry about automation eliminating the jobs of unskilled and middle-skill employees. They agree technological progress creates opportunities for highly skilled employees who build and operate machines, but they fear that the economy will hold far fewer opportunities for less-skilled employees. As Brynjolfsson puts it:

    There are lots of examples of routine, middle-skilled jobs that involve relatively structured tasks and those are the jobs that are being eliminated the fastest. Those kinds of jobs are easier for our friends in the artificial intelligence community to design robots to handle them.… [Technological advances are] always destroying jobs. But right now the pace is accelerating. It’s faster we think than ever before in history. So as a consequence, we are not creating jobs at the same pace that we need to.[15]

    Labor market statistics do not support this concern. Productivity data show that the pace of automation has actually slowed in recent years. Over the past generation the earnings of less-skilled Americans have risen faster than the economy-wide average.

    Slow Productivity Growth. Businesses do not appear to be automating human tasks at a faster rate than before. If they were, this would increase measured labor productivity growth. The Bureau of Labor Statistics estimates productivity by dividing U.S. economic output by the total hours worked in the economy. A substantial increase in the pace of automation would allow businesses to produce as many or more goods with fewer hours of human labor. This would appear in the labor statistics as faster productivity growth.

     

    This has not happened. Chart 2 shows the year-over-year percent change in labor productivity for the non-farm business sector over the past four decades, as well as a four-year moving average that smooths annual fluctuations. Productivity growth increased noticeably in the late 1990s and the early 2000s. From 2003 onward, however, productivity growth trended downward. Average productivity jumped in 2009 as businesses going through layoffs tried to lay off their least productive employees. That surge immediately subsided. Since 2010, productivity has grown at an abnormally slow rate. In the most recent year of data, labor productivity actually fell 0.1 percent. Although employees are more productive now than in the past, overall productivity is increasing more slowly.

    Concerns about rapidly accelerating computing power increasing productivity so much it reduces total employment are fears about a future possibility. Over the past decade, productivity growth has slowed even as computer power has increased exponentially.

    The Earnings of Less-Skilled Employees Increase. Concerns about automation eliminating employment opportunities for less-skilled employees also do not show up in the data. Over the past generation their total compensation has increased rapidly.

    The Congressional Budget Office measures total labor market compensation—cash wages, salaries, and non-cash benefits, such as health care and retirement contributions—for each quintile of the income distribution.[16] Chart 3 shows the percent growth in total inflation-adjusted labor compensation for non-elderly childless households between 1979 and 2011 (the most recent data available).[17]

     

    Since 1979, labor market compensation grew the fastest in the top quintile of these households—up 69 percent. Contrary to popular impression, the next fastest growth in labor market compensation occurred in the bottom quintile. The average labor market compensation of households in the bottom fifth of non-elderly childless households grew 58 percent between 1979 and 2011—more than 25 percentage points faster than any of the middle three quintiles.

    Chart 4 shows a similar dynamic at work. It comes from the research of MIT economist David Autor. The chart depicts income growth for the 10 major occupational groupings in the U.S. economy, with those occupations ranked from left to right by the required level of skills. This figure looks only at wages, not total household compensation. Consequently, it is not directly comparable with Chart 3. Nonetheless, it shows the same pattern of the fastest earnings growth occurring in high-skill and low-skill occupations, with slower wage growth in moderately skilled jobs.

     

    Over the past generation, individuals at the bottom of the income distribution have seen their economic opportunities expand significantly. This is hard to reconcile with hypotheses that automation is eliminating the least-skilled employees’ jobs. Instead, it points to more complex effects of technological progress on the labor market.

    Limits of Automation

    Computers have both more and less power than most people perceive. Autor explains that machines are incredibly good at doing repetitive tasks that do not require any judgment or variation, such as calculating sums in an accounting spreadsheet or fitting a bolt in place on the assembly line. Computers typically do these tasks faster and more accurately than humans can. Employment has fallen rapidly in such “routine” occupations as automation has replaced human labor.

    However, computers have great difficulty performing non-routine tasks. Although more fluid algorithms that take into account computer “learning” possibilities are being refined, computers still do what their program tells them to—and nothing else. Computer programmers must specify in detail every contingency that the machine might encounter. What often looks like computers adapting to their surroundings is in fact them following very detailed operating instructions.[18]

    Consequently, computers cannot handle many non-routine activities that most people find straightforward. They are simply too complex for their programs to account for every possibility. For example, Autor points out that Amazon.com and other online retailers use human “pickers” to identify, retrieve, and pack the goods that they ship their customers. The shape and size of goods being shipped changes constantly from package to package. Amazon has not been able to develop robots that can perform these seemingly simple but not entirely routine tasks. Instead, online retailers use large numbers of robots to bring palettes of particular goods to their human employees. Humans do all the labor involved in handling individual items, then the robots move the palettes away.[19]

    Even some of the apparent successes of automation are far less than they appear. Google’s advances in self-driving automobile technology have made headlines. However, the Google Car operates by comparing its location to very detailed maps of the road, street signs, and all known obstacles. Google employees must enter these data manually. The Google Car cannot operate over unfamiliar terrain. If it faces an unmapped road closure or detour, it shuts down and requires a human driver to take over. It will ignore newly erected stoplights not in its database. Google Cars have safely driven more than 700,000 miles—by driving over the same already mapped miles time and time again.[20] Computers can do routine tasks incredibly well, but struggle when confronted with non-routine work.

    Labor Market Polarization

    Autor’s research shows that this dynamic explains the counterintuitive pattern of compensation growth shown in Charts 3 and 4. Computers have automated many routine white collar and blue collar jobs. Excel spreadsheets and Outlook calendars have dramatically reduced the need for accountant and secretarial labor. Machines now do the work that was once performed by millions of manufacturing employees. These routine jobs tend to lie in the middle of the skill and income distribution. Non-routine tasks tend to lie at the top and bottom of the income distribution. As a result, employment demand and, consequently, earnings have risen more rapidly in non-routine jobs, particularly in the service sector.[21]

     

    Chart 5, reproduced from David Autor’s research, illustrates how increased automation has affected employment patterns. Since the late 1970s, employment has grown rapidly in high-skilled non-routine jobs, such as professional and technical occupations. It has grown rapidly in low-skill non-routine jobs, such as food preparation and personal care. Yet employment has grown more slowly—or contracted—in routine occupations requiring moderate skill levels, such as manufacturing or administrative record-keeping jobs. These are precisely the jobs that machines can perform.

    Many on the left blame the slower growth of middle-income jobs on U.S. policies. They point in particular to insufficiently pro-union labor laws.[22] However, Autor’s research shows that this is a global phenomenon. Relative employment in middle-skill jobs has shrunk in nearly every developed country. Chart 6 comes from Autor’s research and shows changes in low-skill, middle-skill, and high-skill employment for 16 European Union countries between 1993 and 2010. In almost every country, relative employment increased in high-skill and low-skill jobs and decreased in middle-skill jobs. Most of these EU nations have far higher taxes and far stronger unions than the U.S. does. Nonetheless, they experienced the same employment patterns. This evidence points to factors, such as technological advances and globalization, that cut across national boundaries and public policy choices. Robots have not eliminated work, but they have somewhat changed the types of jobs that humans do.

     

    Technology Can Increase the Need for Human Labor

    The relationship between technological progress and jobs is more complex than computers simply eliminating routine work. Many jobs incorporate both routine and non-routine tasks. Employees in these jobs do not necessarily need to fear automation. By eliminating routine tasks technological advances reduce the time and cost of completing their work. This increases output and can leave the overall need for human labor unchanged or even increased.

    The construction industry demonstrates this effect. Technology has made today’s construction workers vastly more productive than their predecessors two generations ago. Cranes and backhoes have replaced shovels and elbow grease, but those machines need human operators. Too many unpredictable events take place on a construction site to allow computers to operate the equipment autonomously. The lower cost of constructing buildings has also dramatically increased the quantity of construction work demanded. As a result, total construction employment has remained a relatively constant share of the overall workforce since the mid-1940s. From 1946 onward, construction employment has never constituted less than 4 percent or more than 6 percent of the U.S. workforce, despite enormous technological progress.

    A more modern example of this phenomenon comes from restaurant tablets. Applebee’s, Chili’s, and other casual restaurants have installed tabletop tablets for customers to order and pay for their food. The new technology might reduce payrolls by allowing each server to cover more tables. However, the tablets also boost sales. Customers are more likely to order appetizers and desserts when the tablets constantly display them. The ability to pay immediately also cuts the average meal time by about five minutes. Consequently, tablet-equipped restaurants can serve more patrons during busy periods. This increases demand for employees who cook the food to order, appetizingly plate it, interact with customers, and bus the tables afterward.[23]

    Whether or not these tablets will reduce the total need for human labor remains unclear. Applebee’s announced that it has not reduced total staffing since introducing the tablets.[24] Furthermore, tablets also increase tips by setting the default option to 20 percent, boosting servers’ take-home pay. Automation will change—but not eliminate—many jobs that combine routine and non-routine tasks.

    Future Developments

    Historical experience shows that individuals respond to technological changes by finding new jobs, typically jobs that pay more than before automation was introduced. However, technology will probably eliminate some existing occupations. Programmers will almost certainly learn how to render “routine” many tasks computers cannot currently handle. Many jobs that once appeared out of reach for automation are now being performed by machines:

  • Cleaning hotel rooms has long required human labor, supplemented by technology such as vacuum cleaners and washing machines. The tasks of making a bed or removing dirty laundry from the floor were sufficiently non-routine to frustrate attempts to automate them. However, a soon-to-open Japanese hotel will use robots to perform reception duties, carry luggage, and clean rooms. The hotel will charge $60 a night.[25]
  • Engineers have invented a machine that cooks 360 gourmet hamburgers an hour. The Alpha custom grills hamburger patties to order, sears the outside to maximize flavor, and cooks them in an internal oven. It then adds freshly sliced toppings and the desired condiments, places the cooked burger in a bun, and bags it. Humans only stock the ingredients and perform maintenance. The Alpha could save the typical fast food restaurant more than $100,000 per year in labor costs. The inventors are currently prototyping it at individual restaurants.[26]
  • Computers have begun writing routine news articles. Many events occur with little variation in the structure needed to report on them, such as economic news releases and sports events. Computer algorithms now analyze pertinent information for readers and translate it into prose. For example, Forbes.com uses such algorithms to summarize corporate earnings announcements. Computers cannot handle more complex stories and are unlikely to develop that ability, but they can summarize regularly recurring events well.[27]
  • IBM’s Watson computer is so sophisticated that it can detect correlations among research papers that human researchers have yet to discover. For example, in the field of cancer research, Watson analyzed more than 70,000 academic articles in 2014, leading to the discovery of six proteins that should be targeted for new research. One scientist noted that Watson made connections that he would have needed 38 years to make and only by reading five academic papers per day.[28] By making these types of groundbreaking causal links, Watson has demonstrated a marked technological advancement. However, it represents technology’s ability to find connections quicker than humans, not an ability to generate original research and new ideas.
  • Technological advancements like these will reshape the way that millions of employees do their jobs. Some jobs will disappear, but new tasks—primarily non-routine tasks—will replace jobs that have been automated. Such changes do not happen instantaneously, and most people will have time to adapt. Those who cannot adapt could be hurt, but automation will lower prices and raise living standards in the economy overall. Most Americans will prosper as a result.

    Responding to Technological Innovation

    Technological innovation will continue. Policymakers should respond to these challenges by promoting policies that make it easier for Americans to find new jobs.

    For example, one-third of jobs in the economy require a government license.[29] In some occupations this makes sense. Few customers would want an untrained pharmacist filling their prescription. Yet in many other occupations public safety does not require stringent licensing; it primarily exists to restrict access to a profession. For example, every state licenses barbers, requiring an average of more than a year of training before prospective barbers can cut hair.[30] These requirements have no obvious safety rationale: A bad haircut threatens no one’s life. Such excessive licensing makes it difficult for employees who lose their jobs to automation to switch occupations. State legislatures should restrict mandatory licensing to occupations with serious health and safety considerations. Potential cosmetologists, florists, interior designers, bartenders, and drywall installers should not need the government’s permission to change careers. Reducing these artificial barriers would make it easier for employees to adapt in a changing economy.

    State and federal policymakers can also make it easier for employees to switch jobs by eliminating unnecessary paper credentials for government positions. The K–12 education system is a large employer and continues to use paper credentials, such as master’s degrees, to structure compensation and determine access to the classroom. States should make it easier to enter the classroom by removing barriers to entry such as teacher certification requirements, but evaluate teachers more rigorously once they are in the classroom.

    Education Reforms

    Beyond helping individuals switch jobs, policymakers should reform the education system to help tomorrow’s employees gain the skills necessary to work in higher-paying non-routine jobs. Policymakers can do this in several ways.

    States should move toward competency-based learning for both K–12 and higher education. Competency-based learning enables students to progress in their education as soon as they can demonstrate content mastery, instead of using seat time as a proxy for learning. It also enables students with professional experience or training to test out of courses and expedite their entry into the workforce.

    Public policy reforms are needed to allow innovation to flourish in high schools, colleges, and career and technical fields. One of the keys to unlocking innovation is to get the federal government out of the higher education accreditation business and to hand that responsibility back to the market. The current regulatory barriers make it prohibitively expensive for most potential new education institutions to teach students. To foster a competitive marketplace of higher education content providers—be it academic or career-technical—federal policymakers should free the higher education regulatory environment so that businesses, industry, nonprofits, and colleges and universities can deliver content to prospective students from all walks of life to give them the skills needed to be successful in an ever-changing economy.

    Specifically, Congress should decouple federal financing (federal student loans and grants) from accreditation and enable states to allow any entity to accredit and credential courses. Senator Mike Lee (R–UT) and Representative Ron DeSantis (R–FL) have introduced companion proposals known as the Higher Education Reform and Opportunity Act (H.R. 1287 and S. 649), which would allow states to determine who can accredit and credential courses and, importantly, would allow individual courses to be credentialed. Reforms to remove the “gatekeeper” function of accreditation could also be achieved by amending the Higher Education Act to decouple federal financing from accreditation. As Senator Lee explains:

    [A]ccreditation could also be available to specialized programs, individual courses, apprenticeships, professional credentialing, and even competency-based tests. States could accredit online courses, or hybrid models with elements on- and off-campus… businesses, and trade groups could start to accredit courses and programs tailored to their evolving needs. Churches and charities could enlist qualified volunteers to offer accredited classes and training for next to nothing.[31]

    The current regulatory system stifles innovation and makes it harder for individuals outside the traditional college demographic to improve their skills. Such reforms would make higher education less bureaucratic and more responsive to individual’s needs.

    Conclusion

    Automation reduces both labor costs and prices. Lower prices leave customers with more money to spend elsewhere, increasing the demand for labor elsewhere in the economy. Automation changes where and how people work, but it has not historically reduced the overall need for human employees.

    Little empirical evidence suggests this time is different. Productivity growth slowed over the past decade after increasing in the late 1990s. The wages of the lowest-earning employees have also increased rapidly over the past generation. Instead of eliminating human labor, technological advances are reducing the need for humans in routine jobs and increasing the need in non-routine jobs. This pattern has occurred in America and around the world.

    Policymakers should respond to these changes by making it easier for displaced workers to switch jobs, such as by relaxing occupational licensing requirements and moving toward policies that allow for a more nimble K–12 and higher education system to flourish.

    —James Sherk is Research Fellow in Labor Economics in the Center for Data Analysis, of the Institute for Economic Freedom and Opportunity, at The Heritage Foundation. Lindsey M. Burke is the Will Skillman Fellow in Education Policy in the Institute for Family, Community, and Opportunity at The Heritage Foundation.



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