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Category Archives: Automation

The top robotic process automation companies, according to IT pros – Business Insider

Posted: October 20, 2019 at 9:50 pm

Businesses are trying to do things easier and faster with the help of software that can connect and automate the patchwork of applications and systems in their networks.

These tools, called robotic process automation, or RPA, can speed up processes and eliminate keying and other errors saving a business a lot of money. For example, RPA systems can take on basic data entry tasks or generate automated email responses to customers.

It is still a small market, with total revenue of roughly $850 million in 2018, according to analyst firm Gartner. But it is a fast growing market. Gartner estimated the RPA segment posted a year-over-growth of 63% in 2018.

IT Central Station, the review site where IT professionals are able to weigh in on the software they use, recently conducted a survey on RPA tools.

Here are the top robotic process automation companies, according to IT professionals on IT Central Station.


The top robotic process automation companies, according to IT pros - Business Insider

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Warren, Yang fight over automation divides experts | TheHill – The Hill

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Sen. Elizabeth WarrenElizabeth Ann WarrenTrump says his Doral resort will no longer host G-7 after backlash Ocasio-Cortez: Sanders' heart attack was a 'gut check' moment Ocasio-Cortez tweets endorsement of Sanders MORE (D-Mass) and entrepreneur Andrew YangAndrew YangYang cautions Democrats: Impeachment might not be 'successful' Yang defends Gabbard: She 'deserves much more respect' Super PAC seeks to spend more than million supporting Yang MORE's fight over jobs and automation at the last Democratic debate highlighted the divide over the contentious issue, including among experts.

Warren and Yang sparred at Tuesday's presidential debate over whether automation or trade were primarily responsible for eliminating jobs in key parts of the country.

Yangs campaign is centered around a universal basic income, which would pay every adult citizen $1,000 a month to combat the job loss brought on by automation. Americans, he said, are already seeing the effects of speedy technological advancement.

Their Main Street stores are closing. They see a self-serve kiosk in every McDonalds, every grocery store, every CVS," he said at the debate in Ohio. "Driving a truck is the most common job in 29 states, including this one; 3.5 million truck drivers in this country. And my friends in California are piloting self-driving trucks."

While some of Warrens plans acknowledge the role of automation, she has dismissed it as the primary driver of job loss.

The data show that weve had a lot of problems with losing jobs, but the principal reason has been bad trade policy. The principal reason has been a bunch of corporations, giant multinational corporations whove been calling the shots on trade, she said at the debate.

Warren argues that empowering workers on both corporate boards and in trade negotiations would help alleviate those problems.

Following the debate, The Associated Press issued a fact check siding with Yang, pointing to one study from Ball State University in 2015 that attributed some 88 percent of manufacturing job losses to automation.

Economists mostly blame those job losses on automation and robots, not trade deals. So the Massachusetts senator is off, the AP Fact Check wrote.

While members of the Yang Gang, Yangs devoted online supporters, expressed glee at the report, labor economists and experts took issue with the AP ruling, issuing their own fact checks on the news wire.

That fact check strikes me as incorrect, said Melissa S. Kearney, a University of Maryland economist who along with Katharine G. Abraham co-authored a comprehensive review of factors behind employment loss.

The paper, published last year with the National Bureau of Economic Research, found that two of the top factors affecting job loss were increased import competition from China and the penetration of robots into the labor market, but found competition from China had more than double the effect of automation.

Noah Smith, a Bloomberg Opinion columnist, argued that the Ball State study cited by AP was of much lower quality than research showing a big impact from China.

AP Fact Check got this one wrong,he tweeted.

In a statement to The Hill,the AP said it stood by its story.

Nobel Laureate Paul Krugman assailed both Yangs position and the AP fact check in a New York Times column, pleading with Democrats not to go down the robot rabbit hole.

As it happens, Warren was more right than the supposed fact-checkers, he wrote. As far as I can tell, [Yang is] offering an inadequate solution to an imaginary problem, which is in a way kind of impressive, he added.

Krugman argued that the effect of technological change on jobs is no different today than it has been at any other time in modern history, noting that similar anxieties existed about machines taking away farmers jobs. While technology did cause the share of the jobs devoted to agriculture to drop precipitously in the last 80 years, he noted, better, higher-level jobs replaced them.

In response to criticism from Krugman on the same issue in June, Yang pointed to the low level of labor force participation.

Former Maryland Rep. John DelaneyJohn Kevin DelaneyThe Hill's Campaign Report: Biden camp faces new challenges Warren's surge brings new scrutiny to signature wealth tax 'We lost a giant': 2020 Democrats mourn the death of Elijah Cummings MORE, a 2020 Democratic candidate who did not qualify for the most recent debate, rejected Yang's position, noting that automation had its upsides.

Krugman is right, the idea that automation will take away all the jobs is a complete fantasy. Innovation always displaces AND creates jobs, that's how progress works. What we need is massive public investment in workers and infrastructure to manage change,he tweeted.

But while the experts seemed to side more closely with Warren, they didnt let her off the hook completely either.

The primary culprit in trade-related job loss, they said, was China, which upended the global economic order when it began to open up its economy and joined the World Trade Organization in the 2001.

I want to be clear that its not to say that trade writ large is bad, but the experience of the last 20 years, with China in particular, has led to employment loss, said Kearney.

Recent studies, she noted, have shown that the shock of Chinas economic boom and integration into the global economy has begun to recede.

Ernie Tedeschi, a managing director and policy economist for Evercore ISI, argues that although the U.S. lost some jobs to Mexico following the North American Free Trade Agreement, the deal actually helped prevent deeper job losses by giving U.S.-based companies a reason to stay put instead of relocating entirely to China.

While there is still a robust academic debate, he said, research seems to indicate that automation has had more of an effect on wages than on the number of jobs.

Automation has probably allowed output and profits of firms to grow faster than pay has, he said.

The debate shows no signs of cooling off.

Zach Moller, deputy director of the economic program at Third Way, a think tank argued that policy-makers should instead focus on how to help workers, regardless of whats behind it, floating a new look at unemployment compensation and skills training.

If you ask the worker who lost their job, I don't think they care whether they lost the job from a robot or outsourcing, he said. "They care how they will support their family."

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The Technology Trap: More Than Automation Is Driving Inequality – The National Interest Online

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Carl Benedikt Frey, The Technology Trap: Capital, Labor, and Power in the Age of Automation (Princeton, NJ: Princeton University Press, 2019), 480 pp., $29.95.

DEMOCRATIC PRESIDENTIAL candidate Andrew Yang has declared, The automation of our jobs is the central challenge facing us today. Yangs message, echoed by another candidate, South Bend mayor Pete Buttigieg, wont win him the nomination, but it is backed up by several social scientists including Massachusetts Institute of Technologys (MIT) Erik Brynjolfsson and Andrew McAfee and Oxford researchers Carl Benedikt Frey and Michael A. Osborne. In 2013, Frey and Osborne predicted that in perhaps a decade or two 47 percent of total U.S. employment would be at high risk of being automated. That could portend what futurist Martin Ford has called a jobless future and would call for drastic measures to prevent a social and political cataclysm.

Now Frey has written a long book, The Technology Trap: Capital, Labor, and Power in the Age of Automation, putting his findings in historical context. Frey argues that automation, or what he calls the third industrial revolution, is not only putting jobs at risk, but is the principal source of growing inequality within the American economy. The failure to meet this challenge, Frey warns, is fueling populist and white identity politics, most evident in the 2016 election of Donald Trump.

FREYS BOOK is about a third longer than it needs to be. He and his publisher were, perhaps, beguiled by the commercial success of Thomas Pikettys weighty Capital in the Twenty-First Century. Freys book is highly repetitious. And before getting to the heart of the argument, which is the difference between the first, second and third industrial revolutions, you have to wade through chapters about Neolithic and preindustrial technology. But the heart of the argument is interesting and worth pondering.

According to Frey, the West has experienced three industrial revolutions that have been impelled by technology. The first, dating from the late eighteenth century, was driven by the steam engine, the railroad and the cotton gin; the second, which extends through the first six decades of the twentieth century, by electricity and the internal combustion engine; and the third, which begins sometime in the 1960s, and is still going on, by computer technology and, most recently, artificial intelligence. Each of these revolutions has had different effects on employment and equality, depending on the kind of technology that was introduced.

The effect has depended on whether the technology was enabling or replacinga distinction that is common among social scientists who write about automation. An enabling technology increases the productivity of existing workers without eliminating their jobs. A good example would be how the typewriter increased the power of a clerk without eliminating the need for clerks, or how computer design increased the productivity of architects without imperiling their jobs. But the ATM replaced and eliminated many bank tellers. Robots, combined with industrial reorganization, have replaced assembly line workers. And so on.

According to Frey, the first industrial revolution was dominated by replacing technology. Weavers and other artisans were replaced by simple machines that could often be operated by children. Some of these former artisans became low-wage farm laborers, while others were unemployed. Overall, wages and labors share of national income plummeted. Economic historians call this period the Engels Pausea reference to Friedrich Engels classic The Condition of the Working Class in England in 1844, which documented the immiseration of the peasantry and working class under the new technology. Marxs socialist politics was rooted in this first industrial revolution: it assumed a rebellious working class facing unremitting downward pressure on wages.

The second industrial revolution, Frey argues, was dominated by enabling technology. The key was the rise of the electricity-powered assembly line, the gasoline-powered engine and the new electric office. Productivity rose rapidly, but wages kept pace, and the gap between the wealthy and everyone else actually shrank. The third revolution has taken place in two stages. In the first, which featured robots, many mid-wage, routine industrial jobs disappearedamong those were the assembly line jobs created in the earlier revolution. In the next phase, based on artificial intelligence, many lower-skilled service jobs will disappear. These would include office and administrative support, sales, food preparation and serving, and transportation. Frey thinks the development of autonomous vehicles will soon have a devastating effect on truck drivers, who are the largest single occupational group in many states.

Factory workers who lost their jobs during the first phase of the third revolution (circa 19702010) often had to take lower-paid service sector jobs. The same thing will happen, Frey predicts, with workers who lose their jobs in the phase characterized by artificial intelligence. Freys prediction is dire. He writes,

A truck driver in the Midwest is not likely to become a software engineer in Silicon Valley. He might take up work as a janitor. Or he might find work in grounds maintenance, keeping parks, houses, and businesses attractive If he became a janitor he would trade a $41,340 job (2016 annual median income) for a $24,190 job. If he manages to become a ground maintenance worker, he would make $26,830 per year. Or he might get a job as a social care worker, earning $46,890 per year. But that would require him to get a college degree.

In this way, the third industrial revolution would resemble the first: it would render a mass of workers obsolete and depress overall wages. And, like the first revolution, the third could precipitate a revolt from the bottomled initially by right-wing populists like Donald Trump or Frances Marine Le Pen. The robot revolution is largely a Rust Belt phenomenon, and this is also where Trump made the greatest gains for the Republican Party, Frey observes.

SOME OF Freys analysis of the political implications of the third revolution seems overdrawn: he claims that the research he did with two other social scientists demonstrated that if the number of robots had not increased since 2012 in Michigan, Pennsylvania and Wisconsin, Hillary Clinton would have won these states and the 2016 election. Overall, however, Freys analysis of the Trump vote in the Midwest is pretty astute. Some liberal commentators have attributed Trumps votes entirely to white racism and identity politics. Frey locates it instead in a broader problem of identity created by fading opportunity in the labor market.

Frey argues that industrial male workers had to find ways of taking pride in monotonous toil on a factorys assembly line. Citing sociologist Michle Lamont, Frey writes that their solution was to construct an identity as a disciplined self. He concludes, In Rust Belt cities and townships, where joblessness is now widespread, the disciplined self identity has become harder to maintain, making dormant grievances come alive. These include the cultural resentments that liberals have focused on in explaining Trumps votes. In my own book, The Nationalist Revival, I similarly described the threat to workers way of life from a decaying industrial base, which carried with it the destruction of neighborhoods, bars, churches, union halls and of the expectation that ones children could enjoy the same lifetime employment.

Freys analysis of working-class discontent also leads him to dismiss the condescending solution favored by some wealthy Democrats for economic inequality. Yang, former Facebook publicist Chris Hughes and other one-percenters have argued for a universal basic income that would provide the equivalent of a supplementary welfare paymentfrom $500 to $1000 a month, even to those unable or unwilling to find work.

These eupeptic plans run afoul, Frey argues, of the average Americans desire to earn a living through work and aversion to those who might not share this legacy of the Protestant Ethic. He quotes his Oxford colleague, Ian Goldin, who contends that Individuals gain not only income, but meaning, status, skills, networks and friendships through work. Delinking income and work, while rewarding people for staying at home, is what lies behind social decay. Exactly right.

In a closing section, Frey enumerates his own proposals for dealing with job displacement owing to the third industrial revolution:

Addressing the social costs of automation, will require major reforms in education, providing relocation vouchers to help people move, reducing barriers to switching jobs, getting rid of zoning restrictions that spur social and economic divisions, boosting the incomes of low-income households through tax credits, providing wage insurance for people who lose their jobs to machines, and investing in early childhood education.

While by no means novel, these proposals make perfect sense.

FREY COVERS a lot of ground in his book, and I wont pretend to match his erudition. But I want to raise a few questions about his historical account of the industrial revolutions and about the overweening role that he assigns to automation in explaining economic equality and inequality.

First, the history of technology and jobs: I dont think the distinction between replacing and enabling technology fully accounts for the difference between the revolutions and their effect on jobs and economic equality.

Take the difference between the second and third revolutions. Frey acknowledges in passing that, during the second revolution, technology did dramatically replace employment, especially in agriculture. In 1850, according to some estimates, 64 percent of the countrys workers worked on farms; by 1929, due in large part to the introduction of reapers, tractors and other machinery, it was down to 18.3 percent. It is now below 2 percent, even though total production has continued to increase. During the same period, a host of crafts occupations were also replaced by assembly-line production.

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Three automation myths standing in the way of better patient care – MedCity News

Posted: at 9:50 pm

Automation has already made its mark in various aspects of business, including sales and customer service operations, and more innovation is expected in the coming years. But automation technologies often face a variety of challenges before healthcare organizations can implement and use them effectively.

In this industry, for automation to carry out its potential to save burned-out providers massive amounts of time, deliver more advanced patient communications, and streamline and improve medical workflows, we must combat a number of myths.

In many organizations, there can be an initial lack of trust due to a misperception that automation means administrators, clinicians and staff are giving up control to new and untested technology. A good technology solution, however, can offer countless benefits, including saving time, improving accuracy and increasing capacity. Through the adoption and implementation of proper reporting capabilities, the staff can maintain full visibility into the system and remain in control.

In fact, automation has already arrived in healthcare and is generating an extraordinary amount of value to organizations, allowing them to filter out time-consuming, manual tasks and focus more on the meaningful face-to-face work that matters most. As we enter the next decade of automation, it will be adopted by more systems sooner rather than later as advocates become more proficient in debunking three major myths that often tarnish the perception of automation:

Myth No. 1: Automation means handing over controlA common misperception of automated solutions is that they take over 100 percent of the work, leaving decision-makers with a lower level of control and visibility. Automation does take over a significant portion of mundane work, but this can actually help increase visibility. When staff members dont have to spend time with tedious tasks, it frees them up to do more meaningful and rewarding work.

Take automated scheduling as one example. With a system that helps schedule patients automatically via text messaging and also fill empty slots when cancellations arise staff members spend far less time playing phone tag with patients and laboring to keep schedules aligned. More importantly, smart automation solutions give professionals across the organization constant visibility into an up-to-date and accurate view of the clinics capacity and opportunities for filling any gaps. Its an example of how automation provides the foundation for accurate visibility into processes like physical calendars, which can often be plagued by human lag time.

Myth No. 2: Getting staff to buy-in is nearly impossibleIts true that meaningful change can be a hard sell into established processes and workflows, or those with legacy systems in place because theyve always done it that way. But there is one thing automation offers that makes it difficult for anyone to deny: results.

Take referrals, for instance, the foundation that many specialty practices are built on. Manually handling referrals often involve mountains of phone calls and faxes, making it easy to lose track of patients in the shuffle, let alone getting to all the patients in a timely manner. When referral management is automated, manual processing is eliminated. Practices can deal directly with referred patients via interactive text messages that guide them to automatically schedule appointments. Referred patients receive real-time notifications when an appointment is confirmed, and providers have the ability to track their status along the way.

Automating referral management makes the entire process quicker and easier text messages that include a link to schedule an appointment are immediately sent to referred patients reducing the lag time and improving response rates. After implementing such systems, the results become clear immediately: clinics with automatic referral management are able to treat 60 percent more referrals on average.

Myth No. 3: Automation makes care delivery less personalAutomated patient engagement is changing the way care is delivered. Providers can remain in regular contact with patients both before and after appointments and procedures, ensuring theyre on the right path along their care journey. This all happens automatically with custom text messages that require no additional work from physicians, creating the misperception that it makes care delivery somewhat impersonal.

The exact opposite is true. With constant engagement, providers have a better sense of a patients situation well before they step foot in the office. This allows them to have more meaningful appointments and deliver treatments designed specifically for that individual patient. From the patients perspective, this makes receiving care much more personal, because they have been engaging with their provider at every step along the way, not just at an appointment every few weeks or months.

In the end, automation doesnt replace personal engagement, it replaces zero engagement. It turns manual phone calls into automated texts and allows front office staff to focus additional outreach efforts on high-risk patients and provide a more personal and pleasant experience in the office. Physicians are able to tailor and connect with patients across a vastly higher rate of touchpoints, creating more personalized, and ultimately better, care.

Embracing technological shifts requires thoughtful and strategic implementation. In the case of life-saving industries like healthcare, allowing myths to stand in the way of better care can be downright lethal. Automated solutions have proven to streamline clinical processes getting more patients to care faster, optimizing the business of healthcare, and, most importantly, delivering better and more personal care to patients.

Photo: Andranik Hakobyan, Getty Images

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Three automation myths standing in the way of better patient care - MedCity News

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What’s the manufacturing job killer, automation or trade? – PolitiFact

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The Democratic debate in Ohio stirred up a heated exchange on a basic economic question: Did robots hollow out American manufacturing?

Sen. Elizabeth Warren, D-Mass., has said that blaming job losses on automation is a myth, and CNNs Erin Burnett pressed her to explain why workers in Ohio shouldnt be worried.

"We have had a lot of problems with losing jobs, but the principal reason is bad trade policy," Warren said. "The principal reason has been a bunch of giant multinational corporations who have been calling the shots on trade."

Entrepreneur Andrew Yang shot back that the Americans he talks to are very worried about automation.

"They see a self-serve kiosk in every McDonalds, every grocery store, every CVS," Yand said. "My friends are piloting self-driving trucks. What does that mean for the 3.5 million truckers, or 7 million Americans who work in truck stops, motels and diners that rely upon the truckers getting out and having a meal? Saying this is a rules problem is ignoring the reality that Americans see every day."

The reality is that the research backs up both candidates. Trade may well have done more than automation to shrink Americas factory workforce. On the other hand, automation, computers and robots can and have cost people their jobs.

Manufacturing takes a hit

Tracking manufacturing jobs data shows the moment they nosedived in America. It was right around 2000.

The fall after 2000 was so sharp, its clear something happened at about that time. Many economists point to China winning permanent "most favored nation" trade status. Chinese imports to the United States grew rapidly, while many American firms shifted production to low-wage factories overseas.

Warren relies on a 2018 study from the Upjohn Institute that looks at the role that trade and automation played in driving down manufacturing employment. One of the explanations is that American firms invested in robots and other technology that replaced humans with machines.

But Susan Houseman of the Upjohn Institute rebutted the automation theory. If robots killed jobs, she argued, the country should have many robots. Instead "the adoption of industrial robots has been limited," Houseman wrote. "The effects of automation in manufacturing were most prominent in the 1980s and had greatly diminished by the 2000s."

As the chart above shows, after the automation surge, manufacturing employment held fairly steady through the 1990s.

Houseman also reported that apparent rises in productivity often used to explain falling factory jobs are more a statistical fluke than a real phenomenon. That might seem totally academic and esoteric, but it lies at the heart of Yangs rebuttal to Warren.

Yangs campaign pointed to a 2017 study from Ball State University economists that found that productivity gains accounted for nearly 90% of manufacturing job losses between 2000 and 2010. Houseman challenged that, noting that the study showed five times as many jobs "not filled due to productivity" in the computer industry as the actual number of jobs lost, a result she called "absurd."

We cant resolve the dispute.

Other analysts have noted that countries with a larger fraction of manufacturing workers than the United States, such as Germany, South Korea and Japan, all have more industrial robots per capita. Automation by itself, they argue, didnt seem to undercut factory workers there.

Automation as disruptor

To some extent, Warren and Yang might have been talking past each other. Yangs point had as much to do with non-manufacturing jobs, like cashiers, as factory work.

In that light, a 2018 analysis, "Will robots really steal our jobs?", from Price Waterhouse Cooper, an international accounting firm, paints a picture where many jobs could be at risk.

Their report lays out three waves of automation. The first has been going on for awhile and is more computational, like the scanners at the grocery store. The second gets into moving things around, like robots in warehouses. The third is much more complex, with decisions made on the fly in real world situations. That is the scenario where self-driving trucks replace human truck drivers.

That third wave is about 10 years off. The threat is real, though.

"In the long run, less well-educated workers could be particularly exposed to automation," the report said. "We do not believe, contrary to some predictions, that automation will lead to mass technological unemployment by the 2030s any more than it has done in the decades since the digital revolution began. Nonetheless, automation will disrupt labor markets."

In their ranking of sectors most likely to be rocked by automation, transportation and storage, followed by manufacturing and construction are at the top, with at least 40% of the jobs in those areas at high risk.

For manufacturing, strong forces will drive much of that change as low-wage countries will continue to attract new factories.

"For economically advanced countries, competing on the cost-side of production is very difficult," wrote Darrell West and Chrstian Lansang with the Brookings Institution. "In order for these countries to keep their manufacturing sectors flourishing, value unlocked through robots, artificial intelligence, and the use of Big Data is essential."

Economist Teresa Fort at Dartmouth College said the relative impacts of trade and automation change from place to place and line of business. Pointing to the steel industry, Fort said, "we dont need as many workers to create the same amount of output." Thats a technology effect.

But in other areas, such as small home appliances, the flood of Chinese imports drove the trend.

"It really is not possible to tease apart the trade versus technology channels," Fort said. "This is because technology can lead to trade, and because trade can lead firms to adopt new technologies."

So both Warren and Yang have their points. Trade shaped the past and will shape the future. Automation does put jobs at risk, but it isnt divorced from trade itself, and under the right conditions, it can bolster manufacturing jobs, not undercut them.

For Fort, the trade versus automation debate is a red herring. They both, she said, rearrange the returns for different kinds of work, and many people will end up on the short end of the change.

"If we care about peoples well-being, we should stop debating whether trade or technology led to the loss of certain jobs, and instead focus on how to recognize and facilitate the transition into new job opportunities," Fort said.

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Ono Food Co. Brings The Restaurant Industry One Step Closer To Full Automation – Forbes

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Ono Food Co.'s Ono Blends truck is powered entirely by robotic technology. Customers order via kiosk ... [+] and the technology creates the product in less than a minute.

Automation in the restaurant industry isnt necessarily new. Weve seen robots flip burgers and pour coffee for a few years now. But adoption of the technology is starting to pick up from a drip to a trickle.

Zume, for example, is rolling out its largely automated mobile kitchen fleet through a partnership with &pizza.Zume CEO Alex Garden has flat-out said that the companys priority is to automate the business as much as it can to free up repetitive jobs so employees can do more of the things they enjoy.

Now, another concept is looking to go one step further. Ono Food Co. announced this week that the first mobile restaurant powered entirely by robotic technology, called Ono Blends, will open later this month in Venice, California. Not coincidentally, the company was founded by two people who know quite a bit about robotics and automation. CEO Stephen Klein came from robotic coffee bar Caf X in San Francisco, and previously worked at Instacart. CTO Daniel Fukuba directed the engineering team at a firm that provided automation for Zume, SpaceX, Tesla, Apple and more.

Klein said the biggest objective with the Ono Blends launch is to provide healthy fast food options to customers wherever they are throughout the day, and that the biggest differentiators between Ono and other mobile concepts is that it is fully automated and its 56-square-foot space can be assembled anywhere.

We think future of food isnt mobile but modular, Klein said.

There are plenty of benefits behind such an approach, including a significantly lower barrier to entry compared to a traditional brick-and-mortar restaurant. Occupancy rates for brick-and-mortar locations typicallytake up to 8%to 10%of a restaurant's gross sales, if not higher in a market like LA.

For Ono, however, automation is the headline.

Because of that automation, (the product) is better, faster and cheaper, Klein said.

Just how Ono achieves better, faster and cheaper requires a multi-tiered answer. Klein said every step of Ono Blends assembly process is monitored by hundreds of sensors to ensure no spillage, cross-contamination or inconsistencies. He adds that Onos technology creates 60 blends per hour, versus the industry standard of about 20, and uses about 28 times less water because of its cleaning system.

Such efficiency yields cost savings. But most of those savings come from the real estate piece and the labor piece. Klein said Ono pays a livable wage by Los Angeles standards, but its Ono Blends truck has just one employee on board, sometimes two. These employees serve as Ono Guides to engage customers and educate them about the ingredients, etc.

Our goal is to serve higher quality food with a focus on sustainability and that costs a lot. Our food cost is higher than most concepts, at 35% of our gross revenue, Klein said. But we can be more efficient and save on labor and real estate and, because of that, we can charge customers two to three times less than other concepts like Moon Juice.

For context, the cost of a 20-ounce smoothie, such as the avocado and matcha, from Ono Blends is about six bucks.

How the concept works is simple. Customers order through a kiosk on the truck (and, soon, via a mobile app), which spins into motion the robotics system that creates a smoothie within 60 seconds. Ono started with smoothies because it is agnostic to the time of day, Klein said.

The companys objective is to expand into other culinary categories by 2021, including through a possible partnership with a celebrity chef.

For now, however, another narrative has taken the spotlight and that is the emergence of automated concepts and automation in general. Weve not only seen it in startups like Zume, but also with giants like Dominos testing driverless delivery, orMcDonalds testing robot fryers.

Some investors seem to like the potential of a fully (or mostly) automated concept.Zume secured $375 million in funding late last year and is valued above $2 billion. Ono has also receivedundisclosed funding and Klein is adamant about scaling into other markets in the next year.

Were very much on the ground floor here, but if startups like Ono can successfully prove efficiencies, expect automation adoption to turn from a trickle into a stream.We may not see fully automated concepts like this, but well see more automation. No question.

Automation will be commoditized quicker than most people think. Its happening already, Klein said. That being said, its hard for various establishments to set up automation, particularly for franchise owners, it can be cost prohibitive and retrofitting a restaurant is cost intensive. Automation in fast food will come through new restaurants versus existing restaurants.

The timing couldnt be better. The market is crowded and precious real estate is elusive, and were at record unemployment rates while minimum wages rise. Because of thisat the very leastback-of-the-house automation and modular formats will become more ubiquitous.

QSRs have very thin margins. If you can operate in a smaller space or save on labor, itll translate to huge savings in the long term, Klein said.

Still, he adds, none of these cost-savings or efficient technologies matter if the food isnt nailed down. It is, after all, still the restaurant industry.

Automation is just a tool, just like a Turbo Chef or a microwave is a tool. Well continue to see a lot of interesting applications with automation that will be exciting. We already are starting to see a lot of these types of modular kitchens being worked on, Klein said. But if the quality of the food and the taste isnt there, no food business will survive.

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Architect Your Automation Strike Teams – Forbes

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Hand touching a plasma ball with smooth magenta-blue flames

Emerging technologies such as robotic process automation (RPA), virtual agents, and machine learning these are those invisible robots described in the recently published Forrester book,Invisible Robots in the Quiet of the Night: How AI and Automation Will Restructure the Workforce. Invisible robots have rocketed automation to a top spot among enterprise initiatives, yet firms are dragging organizational and governance issues along as an afterthought.

To address these gaps, automation strike teams are emerging. So, what are they? Strike teams replace the automation center or center of excellence concept. This well-worn phrasing or description has two drawbacks when applied to todays automation initiatives: First, the term center implies more control (and, hence, bureaucracy and tardiness) than automation initiatives can withstand that are inherently federated, distributed, and centered in the business; and secondly, the term center implies a single instance, whereas we are seeing multiple strike teams forming that may specialize in a domain for example, operations (for RPA) or conversational intelligence for B2E or B2C use cases.

Strike teams are a reaction to these realities:

What The Automation Strike Team Does

Automation strike teams address the growing federation of business and traditional technology management expertise. Many organizations will have more than one, and each team may specialize in business or technology domains. Here is a summary of what they do:

This post was written by Vice President, Principal Analyst Craig Le Clair, and originally appeared here.

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Architect Your Automation Strike Teams - Forbes

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Democratic debate: The fight about automation and job losses, explained –

Posted: at 9:50 pm

Democrats tackled several issues on the debate stage Tuesday night that had previously gone untouched. One of those was automation the idea that robots and technology will replace workers and destroy jobs.

It prompted a confusing discussion about whether automation is actually killing jobs or whether free trade policies are. And it didnt offer up much of a clear answer.

CNN moderator Erin Burnett cited a study predicting that a quarter of US jobs will be lost from automation, then asked a few of the candidates what they would do to prevent such job losses.

Sen. Bernie Sanders said guaranteeing a federally funded job for every person is one solution. Andrew Yang pointed to his universal basic income plan. But things got testy when the moderator turned to Sen. Elizabeth Warren, who downplayed the impact of automation on jobs:

The reason is bad trade policy. The reason has been a bunch of giant multinational corporations who have been calling the shots on trade. Giant multinational corporations that have no loyalty to America. They have no loyalty to American workers. They have no loyalty to American consumers. They have no loyalty to American communities. They are loyal only to their own bottom line. I have a plan to fix that. Its accountable capitalism. You want to have one of the giant corporations in America? Then 40 percent of your board of directors should be elected by your employees. That will make a difference when a corporation decides, We could save a nickel by moving a job to Mexico.

Yang didnt like that answer. His entire campaign for universal basic income is based on the idea that robots will take away everyones livelihood.

Senator Warren, I have been talking to Americans around the country about automation. They are smart. They see whats happening around them. The stores are closing, Yang responded. They see a self-serve kiosk in every grocery store, every CVS. Driving a truck is the most common job in 29 states, 3.5 million truck drivers in this country. My friends are piloting self-driving trucks.

Whether or not machines or free trade are responsible for destroying US jobs is an understandable disagreement. Economists have been having this same discussion for decades, ever since President Bill Clinton signed the North American Free Trade Agreement in 1994, which opened up free trade between Canada, Mexico, and the United States for the first time.

Heres the truth: Neither automation nor trade policies are responsible for overall job losses in the past few decades, generally speaking. But globalization (a.k.a. free trade) is more to blame for the decline of manufacturing jobs in the US than automation is.

Another thing: No one has any clue how many future jobs may be lost to automation; the estimates vary wildly and the methodology for trying to guess is questionable.

Lets break it down.

The reason why so many people say robots will take our jobs one day is because thats what economists and politicians have believed for the longest time. They worried that subway ticket machines would cause mass unemployment in the transportation industry. They also worried that concrete mixers would lead to fewer construction jobs. Those fears never materialized.

In the 1990s and 2000s (post-NAFTA), there was a sharp decline in factory jobs and it coincided with a huge surge in productivity. So factories were producing more or the same, but with far fewer workers. That led economists to believe that technology was displacing workers and creating more efficiencies that, in turn, made factories more productive with fewer employees. But they could never prove that automation was the direct cause.

Recent research suggests this theory of displacement is wrong. A 2018 study by economist Susan Houseman at the W.E. Upjohn Institute for Employment Research explains that the surge in productivity has been limited to the computer and electronics industry.

Without the computer industry, there is no prima facie evidence that productivity caused manufacturings relative and absolute employment decline, Houseman writes. In her paper, she also reviewed the latest research on the subject and concluded that trade significantly contributed to the collapse of manufacturing employment in the 2000s, but finds little evidence of a causal link to automation.

Just take a look at NAFTA. In the US, NAFTA didnt lower overall US wages as some feared, but it was linked to lower wages in some manufacturing jobs. The trade deal was also directly responsible for the loss of more than 840,000 US factory jobs, most of which were moved to Mexico. Just last year, Ford announced it was closing one of its auto factories and opening another one in Mexico.

US companies are still doing this because factory workers in Mexico are still making poverty wages.

Economists Scott Andes and Mark Muro at Brookings also point out that other countries with high productivity growth in recent decades havent seen a similar steep decline in manufacturing jobs as the US has seen.

The evidence suggests there is essentially no relationship between the change in manufacturing employment and robot use, they write.

This helps explain why no one seems to agree on how many jobs will disappear in the future.

Study after study is published every year warning the public about the looming threat of robots. The McKinsey consulting firm estimates that automation could kill 73 million US jobs in the next 10 years. The Organisation for Economic Co-operation and Development (OECD) estimates 13.6 million lost US jobs. Nearly a dozen separate studies say it could be anywhere from 3 million to 80 million. Thats a huge difference.

Yet the headlines that follow are always a variation of Robots are coming for your job.

But these studies are flawed, mostly because they depend on surveys of managers and business owners. They are usually asked to guess how many of the jobs at their business will likely be replaced by machines in the near future. Their answers are often just that: a guess.

Often, the studies try to predict market trends that are impossible to predict.

I have dedicated my career to worrying about the labor market. ... I am not worried about this, Heidi Shierholz, senior economist at the Economic Policy Institute told Voxs Joss Fong.

So will a quarter of all US jobs really disappear, as one of the debate moderators suggested?

No one has a damn clue.

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PPC automation will disrupt your business, but automation layering will save the day – Search Engine Land

Posted: at 9:50 pm

As a finalist for the Google Premier Partner awards, I recently had the chance to visit Googles campus in NYC. There, I spoke to a Googler about the state of agencies and he lamented the fact that a large wave of PPC agencies that got their start during the last economic downturn in 2008 are still managing accounts like they did 10 years ago hardly a strategy for success when we might be on the verge of another economic slowdown.

Considering how much Google Ads has changed in the past decade, it stands to reason that successful account management should also have evolved dramatically.

My friend and industry pioneer Andrew Goodman recently put this idea of agencies not keeping up with the times in slightly different terms and wrote that self-proclaimed PPC experts dont keep up with the nuances of all thats changed in Google Ads because they settle for good-enough rather than going for greatness.

So what follows are my thoughts on how to whip your PPC management skills into great shape for 2020 and beyond. The core idea is that using automations from Google is inevitable, so if you want more control, you can regain it by layering your own strategies on top of Googles through a concept I call automation layering.

Back in 2007, Google launched Conversion Optimizer which helped advertisers with at least 300 conversions over a 30 day period reach a CPA target for their ads. Today that strategy is called Target CPA and requires 20 times fewer conversions (15) to achieve similar results.

There are now also about 11 types of bid management strategies to choose from. Some, like Target CPA and Maximize Conversions almost seem like different flavors of the same thing, showing that things have progressed far enough that the differences in strategy can be down to nuanced differences in goals. It takes serious know-how to make sense of all those strategies and how they interact with manual controls such as bid adjustments.

The point is that there has been a lot of progress in automation for bids. And thats not even to speak of automations in creatives, targeting, etc.

The creep of automation into all areas of PPC will continue unabated due to two driving forces:

So please, figure out how automation fits into your business plan. Too often I hear its something people are too busy to figure out right now. We might get to it another day, they say Well duh! If you used some automation you might actually have time to get strategic about your own business, and maybe even for the clients who pay your bills.

Even if you dont live in California like I do, youve probably read that PG&E, the utility company, turned off power to 800,000 customers to prevent catastrophic wildfires due to aging and poorly maintained transmission lines to avoid the type of wildfire that destroyed the town of Paradise in 2018. What does this have to do with PPC? Well, it showed me how bad people are at long-term thinking and planning.

Now that the powers gone out, all of a sudden everyones upset at PG&E because households are in the dark. And while the utility company is certainly not blameless, theyve been advising customers for months that this likely would happen. But until the warnings turned into reality, few consumers took time to prepare.

Google executives, industry bloggers and industry peers have all been saying that automation is coming to disrupt us. And yet too few agencies heed the warnings and will wait until its too late to change.

So if its inevitable that automation is here to stay, a modern account manager better figure out how to make it part of their routine. But if for some reason, you still believe that you can compete against automation and win, listen to this advice from Hal Varian, Googles Chief Economist.

He said:

If you are looking for a career where your services will be in high demand, you should find something where you provide a scarce, complementary service to something that is getting ubiquitous and cheap. So whats getting ubiquitous and cheap? Data. And what is complementary to data? Analysis.

You know whats getting ubiquitous in PPC? Automation. Many of these automations are not just cheap, theyre free and available to all takers in Googles own Ads management interface. Sounds exactly like the type of thing Varian was talking about. Heeding his advice, to me it seems smarter to become a great complement to automation than to fight it by continuing to do the same old things manually.

The reality of PPC automations is that results vary from one advertiser to the next so not everyone will see case-study-worthy results when deploying the latest Google smart feature. But on average, automated tools deliver better results with less effort, so if you find yourself as an outlier whos not successful, you have to first determine why. Then you can plan a strategy to get on the right side of the averages.

For now a lot of the automation we see solves very narrow problems. There is one system for automating bids, another for optimizing ads, and yet another for matching those ads to likely prospects. The role of the agency is to piece the right solutions together and ensure they work well together. For a more in-depth look at this, check out my post about how the wrong combination of automations can destroy an account.

Through the example of making the mistake of using an attribution model like last-click that wont work well with other automations, it should be clear that the results of automation can be extremely dependent on the knowledge and skill of the account manager. If you dont see the results others are achieving, consider that the fault may not be with the tool but with the person using the tool.

As someone who builds PPC tools for a living, I know that even if the user is to blame for bad results, its still the tool creators problem. A tool that is amazing at automating ad testing is useless if its too difficult for the average advertiser to use without making mistakes. But the best advertisers dont let shortcomings of technology get in their way and will work to produce amazing results with whats out there.

Theres this interesting cycle that tools from Google often seem to go through. They start out manual, then become automated, and eventually, some new controls are added. In essence, this turns the automation into a new type of manual tool.

Bid management is a good example. First, we managed CPCs and bid adjustments manually. Then it became automated as a smart bidding strategy like target ROAS. But then Google added the ability to set ad group level targets, mobile bid adjustments, and seasonality bid adjustments. If you will, the automated target ROAS bid strategy is pretty manual if you consider all the settings you can now control.

Just the mere fact that there are several settings and controls for automated tools should be a dead giveaway that the automations can be optimized if advertisers are motivated enough.

I recently asked advertisers the last time they had an account with a single CPC bid. Or the last time they had manual CPC bids that they never changed. The answer for most was: never! Target CPA and target ROAS goals should likewise not be the same for the whole account, nor should they be static. They should be managed for better results, and certainly not treated as a set-it-and-forever-it tool.

Curious why I say target CPA and target ROAS should be monitored and managed rather than left alone? We should do this because there are factors in everyones business that affect conversion rates that Googles prediction systems may not be picking up on. The automation only detects a change in metrics and in its narrow scope of what it can do, may very well use this data to do entirely the wrong thing for the business.

Heres an example that Ive personally encountered Automated bidding one day noticed that conversion rates dropped significantly and so bids were reduced in an effort to maintain the target CPA. As a result of the much lower bids, the advertisers conversion volume went off a cliff and never automatically recovered.

Heres what happened. The bidding automation correctly saw a decline in conversion rate and adjusted bids downwards. But as a dumb automation, it never asked why the conversion rate dropped. The humans knew it was because a new landing page launched. Humans would have known the correct response to this event was to revert back to the previous landing page rather than decrease bids.

Machine learning is bad, very bad at explaining why and how. Show it a picture of a cat, and it knows its a cat. But good luck getting it to explain why its a cat.

In my book on the future of digital marketing, I explain that one of the roles humans need to play is that of PPC pilot, someone who monitors the automations and can make course corrections if bad data is causing bad actions to be taken.

Understand what the machine is doing and make sense of the data it is using to make its decisions. That is pretty much what Hal Varian said in the quote I mentioned before.

If you believe that automation will become even more pervasive in PPC in the future, then it makes sense that we must learn how the automations given to us by the engines work so that we can optimize them by managing their settings.

Its the simple premise that humans + machines are better than machines alone. But I think in PPC theres an additional meaning to that premise. Perhaps the equation should be:

Human (account manager at my company) + machine (automation created by Google) is better than machine alone.

An advertisers worry is not just that the machines are taking over our jobs, but its that the machines are built by Google, who also collects many of our advertising dollars. As an ex-Googler, I trust that Google tries to do the right thing, but theres nothing wrong with wanting some guarantees and putting oversight in place, especially when even Googlers cant really explain exactly how their machine learning automations are arriving at their decisions.

So thats why PPC managers want to be in the equation rather than letting machines do PPC on their own. Humans can monitor the machines decisions and provide corrections and guidance when those decisions appear sub-optimal.

But adding manual human labor to the mix is counterproductive to efficiency and economic growth. Automation would be better. So what account managers should really strive for is to have their own automations to monitor and optimize the automations from the engines. Thats automation layering.

So instead of striving for:

Human + machine

We should strive for:

Advertiser controlled automation + engine controlled automation

But as enthusiastic as marketers are about building their own automation (thanks to everyone whos been downloading my scripts over the years), the truth is it doesnt always come naturally. Thats when third-party tools can be helpful.

They help advertisers control what automations do to their accounts. Ive explained how to use automation layering to monitor and control close variants that can muddle the meaning of exact match keywords. The following graph tries to explain it more conceptually but check out my previous post if you want a more tactical guide.

Close variants allow Google to target ads for exact match keywords (the small circle in the middle) to a much larger set of search terms (the big outer circle). Google is in control of how big they make this outer circle. If they want more revenue, they can literally change some settings in the code to make the circle bigger to make ad auctions more competitive. Advertisers want more certainty and control. So with automation layering where they control the automation, they can scale back the search terms (the dotted circle) to a level they feel comfortable with.

Automation from the engines is already disrupting PPC agencies and will continue to do so more. Anyone whos been coasting and doing PPC like its 2008 needs to come to terms with the fact that this is not a future-proof strategy. Figure out how to bring automation into the mix of what you do. And if you havent because you dont trust it, know that techniques like automation layering can restore some level of control.

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.

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How immigrant workers are preparing for automation in agriculture – PRI

Posted: at 9:50 pm

Inside Taylor Farms massive, 120,000-square-foot warehouse in Salinas, California, millions of pounds of lettuce, cabbage and spinach are processed each day. Its loud, and the temperature is kept at 35 degrees, so workers wear earmuffs and multiple layers of clothing.

Vegetables from nearby fields are sent hereto get chopped, washed, dried and packaged. When theyre ready for packing, a yellow robotic arm called a Quik Pick & Pack uses suction to pick up a 5-lbbag of greens and carefully place it in a box with the help of cameras and sensors. This job used to be done by humans.

In another room, nine large robotic arms stack boxes into pallets, which are then shipped off to restaurants, schools and commissaries. Just two years ago, people did the stacking. But now, humanworkers are monitoring the robots.

Ana Gutierrez, an immigrant from Guadalajara, Mexico, has worked for Taylor Farms for 23 years. She has seen big changes in the agriculture industry since she started working in the fields as a teenager in 1984. Back then, she harvested vegetables by hand.

Today, American agriculture businesses are turning to automation using computerized machines to take on tasks in production that used to be done by humans as a way to alleviate a nationwide farmworker shortage. And immigrants like Gutierrez are getting education and training to ensure they wont be left behind.

Gutierrez remembers when she first saw what the robots can do.

I thought that it was something good because I thought it would make work easier, she said.

The work has gotten easier, to an extent: Now, machines do most of the heavy lifting. Gutierrez welcomes the changes and signed up for trainingto learn how to run the robots. But she saidother workers are concerned automation will eliminate the need for their jobs.

I see that many people are worried that this is the future, she said.

As many as 800,000 farmworkers are employed in California, according to some estimates. Automation is changing the way they work. Job security for this largely immigrant workforcehinges on people'sability to change with technology and become a new type of worker, one who is more technically skilled. One survey from the US Department of Agriculture found that 90%of crop workers in California are foreign-born. Many have not completededucation beyond high school.

The machines, they don't run themselves, said Marcus Shebl, vice president of operations at Taylor Farms. We don't want [employees] to feel in any way threatened [by the new technology].We want to bring them along for the ride.

That means major US farm businesses, including Taylor Farms, are investing in preparing their workers.

The turn to automation in the agriculture industry has been spurred, in part, by worker shortages. A recent survey of California farmworkers found that 56%of businesses reported difficulty recruiting workers to harvest and process their crops. Existing farmworkers are getting older, and there isnt a younger generation in the US willing to replace them. Meanwhile, the flow of immigrants from Mexico, historically a major source of farm labor, is decreasing.

To alleviate the shortage, companies have increased wages. But the work both in the field and inside plants is not attractive: Its tedious, difficult and often seasonal. And while more agriculture businesses are usinga visa program that allows them to bring in temporary overseas workers, its not enough.The Trump administrations restrictions on immigration arecompounding the problem, according to industry experts.

Thats where machines and robots come in, said ChristopherValadez, president of the Grower-Shipper Association of Central California.

Automation may be another tool that will help you as the employer get some handle onto these tasks that must be performed in a way where you're not as dependent on labor to perform each and every job, Valadez said.

But there are concerns that automation will displace workers. Crescencio Diaz, president of Teamsters Local 890, a union that represents workers in the Salinas Valley, including at Taylor Farms, said he understands why companies are depending more on technology: Its harder to recruit workers under the Trump administrations anti-immigrant policies, and companies have to stay competitive in a world where consumers demand cheaper goods.

But he is skeptical that automation will create enough new jobs for everyone.

They will eliminate hundreds,thousands of jobs.

There's going to be a job for two or three mechanics, five or six technicians, but that's about it, he said. I mean, they will eliminate hundreds,thousands of jobs.

Shebl said no Taylor Farms employees have lost their jobs because of automation. Instead, he said, jobs are changing.

Related:Automation could have a disproportionate effect on women's jobs

Agriculture researchers and industry experts say education is one way to ensure workers are not left behind. Some companies are providing in-house training and development, while colleges and universities are creating programs to help students of all experience levels.

Automation is happening about four times as fast as we can keep up within education, said Clint Cowden, dean of career technical education and workforce development at Hartnell College, a community college located four miles from the Taylor Farms processing plant.

Cowden said the college educatestwo primary groups of people. Theres the younger generation thatis being introduced to computer and plant science for the first time. Then there are programs for experienced farmworkers, who are learning electric theory and basic hydraulics.

So when the plant changes, we don't have to do a complete retooling of the employee with a complete retraining but only small amounts, to keep them moving forward, Cowden said.

Last year, Taylor Farms created its own training facility next door to its processing plant. The idea is for longtime workers to gain new skills and become operators and technicians.

Matias Ramrez, director of facilities and automation at Taylor Farms, recently conducted a training on automation. About 25 workers sat behind long desks while listening tohim go through a powerpoint in Spanish. Afterward, these employees took a close look at a Quik Pick & Pack, the machine that puts packaged vegetables into boxes.

In the past you rode a bike. Now you drive a car, you better [know how to] check your air pressure, your oil levels, maintain the equipment, Ramreztold them. As we've been through this technology change in our business, you need a lot more tech-savvy people. Or someone that knows the [production] line has been that's been there for a long time that could adapt to a more tech-savvy piece of equipment.

Gutierrez wants to be one of those workers who can adapt. Though she never went to college,she said she likes to learn and wants to keep training.

It wasnt difficult learning about the new robots, she said. Because Ive seen how they work, and I can learn by watching.

At age 50, Gutierrez is now an operator, manning the Quik Pick & Pack robot and another machine that puts the vegetables in a bag. She makes about $22 per hour.

The pay isnt a big jump, considering shes been at the company for more than two decades. She started at Taylor Farms making $11 an hour. But her job today is less physically demanding, and she said she sees herself working for the company for a long time.

Gutierrez said she wants to keep looking ahead.

I want to learn, I want to move forward, I dont want to get stuck, she said. If you set your mind on something, you can achieve them, and transform for yourself and your work.

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