Category Archives: Automation

On both an absolute and relative basis, Rockwell Automation (NYSE:ROK) stock looks expensive. As you can see below, its current P/E ratio of around 27 times earnings means it commands a premium to the electrical equipment sector.

Time to hit the sell button? Not so fast -- here are five reasons Rockwell Automation's premium rating is deserved, and why the stock might even be a good value option.

ROK PE Ratio (TTM) data by YCharts

Earnings aren't the only way to value a company. In fact, cash flow generation is arguably a better way to look at matters -- after all, it's free cash flow that's actually used to pay down debt, make stock buybacks, and pay dividends. The good news is that Rockwell is traditionally very good at converting net income into free cash flow. As the chart below illustrates, the 10-year average free cash flow conversion rate from net income is around 1.

Data source: Rockwell Automation presentations. Chart by author.

Moreover, if you look at valuations on the basis of enterprise value (market cap plus net debt) compared to free cash flow, Rockwell Automation is actually cheaper than its peers, including Emerson Electric (NYSE:EMR) and Honeywell International (NYSE:HON).

ROK EV to Free Cash Flow (TTM) data by YCharts

The Internet of Things (IoT) involves embedding internet-enabled devices into hardware and then interacting with the data produced. Rockwell's sensors and controls make it a key player in the IoT market, and management claims it's actually an industrial software company.

As such, Rockwell's stock deserves a premium due to the long-term secular growth potential from IoT. Rockwell isn't the only company investing in IoT, but peers like General Electric Company and Honeywell International have a lot more exposure to a specific set of end markets compared to Rockwell's broad-based exposure to automation spending.

In fact, Rockwell's broad exposure to industrial capital spending means it's a key beneficiary of an improving industrial economy in 2017. Emerson Electric also has heavy exposure to industrial automation, and that company has raised guidancefor the second time this year.

It's a similar situation with Rockwell. Here's how the company has raised guidance throughout 2017.

Full-Year Guidance

At Q4 2016

At Q1 2017

At Q2 2017

Organic sales growth

0% to 4%

1% to 5%

4.5% to 7.5%

Adjusted EPS

$5.85 to $6.25

$5.95 to $6.35

$6.45 to $6.75

Data source: Rockwell Automation presentations.

The substantive upgrades indicate that Rockwell is a company that benefits from an improving economy and has good earnings momentum.

Rockwell might also command a premium because investors accept that it's a business whose margin tends to move up and down with its revenue growth. In other words, it has a high amount of operating leverage. The following chart shows how operating margin does indeed oscillate in tandem with revenue growth.

ROK Operating Margin (TTM) data by YCharts

Considering that the U.S. industrial economy is recovering from recession-like conditions, the likelihood is that a combination of revenue growth and margin expansion will lead to strong earnings growth at Rockwell. Indeed, analysts have EPS growing at 11.6% and 9% in 2017 and 2018, respectively.

Finally, with an enterprise value of around $19.9 billion and its position as a leading IoT play, Rockwell Automation is often seen as a takeover target for companies like Emerson Electric, Honeywell, ABB, andSiemens. Such companies usually command premiums because investors feel that a larger company might be willing to pay handsomely in order to acquire Rockwell's product portfolio.

Rockwell Automation stock commands a premium rating, but it might be worth paying for. Image source: Getty Images.

All told, Rockwell may look superficially expensive, but for the reasons above, its stock price could continue to move aggressively higher in 2017. The cash-generating company has a lot of earnings momentum behind it, and offers investors an attractive mix of long-term growth potential from IoT and a bit of takeover potential as well.

Lee Samaha has no position in any stocks mentioned. The Motley Fool recommends Emerson Electric. The Motley Fool has a disclosure policy.

Originally posted here:

Why Investors Are Paying a Premium for Rockwell Automation - Motley Fool

Tech guru and venture capitalist Marc Andreessen said Tuesday that automation, like the technologyembedded in self-driving cars, will not take away available jobs but will actually createmore.

Its a Luddite fallacy. Its a recurring panic, Andreessen said during a conference hosted by Recode, specifically referring to the oft-professed concernthat automationis bad for the country and the world. This happens every 25 or 50 years people get all amped up about machines are going to take all the jobs and it never happens.

Andreessen used particular historical references to help corroborate his contentions.

People, especially horse and carriage workers, for example, were very worried about the ascension of cars around a century or so ago.

The manufacturing of vehicles not only created more jobs directly, according to Andreessen, but also spurred innovation in other areas, such as paved road construction. This led to the idea of suburbs and consumer establishments like hotels, restaurants and movie theaters.

The jobs that were created by the automobile on the second, third, and fourth order effects were 100 times, 1000 times, the number of jobs that blacksmiths had, he continued. (RELATED: Tech Tycoon: Silicon Valley Is Extremely Liberal, Doesnt Understand Rest of America)

Likely due to the public outcry overcomputerization and its effects on society, Andreessen defended technology. He said the three main sectors that are eating the economy and are currently undergoing a price crisis (construction, healthcare, and education) have been slow to progress technologically. In other words, Andreessen claims that the parts of American society that are struggling the most are the ones that technology hasnt changed or improved.

I think the opportunity and the challenge for the tech industry and Silicon Valley and all of us to go to figure out how to have a much bigger impact in the slow growth sectors of the economy, Andresssen explained.

Andreessen, along with his fellow speaker Reid Hoffman, co-founder of LinkedIn, cited several other potential benefits of driverless cars, including reduced roadway deaths caused by human error, less traffic congestion, and more leisure time during transit. (RELATED: Distracted Driving Is A Huge Problem, And Autonomous Cars Could Help)

However,the National Bureau of Economic Researchpublisheda study in March that found industrial robots had a significantly negative impact on U.S. employment and wages for many local labor markets between 1990 and 2007.

Ryan Hagemann, director of technology policy at the think tank, the Niskanen Center, said he finds this relatively surprising, while also adding that the analysis doesnt appear to factor inall of the potential effectsof advanced technology.

Were more likely to see humans working withand not competing against robots in many of the industry jobs imperiled by automation, Hagemman explained to The Daily Caller News Foundation. Because the authors model treats the labor market as one of competition between human labor and automated labor, it doesnt seem to account for potential productivity gains through cooperation between the two.(RELATED: Google Exec: I Am A Job Elimination Denier When It Comes To Robots)

Others, like Hagemann, argue the tangible and intangible benefits of automation, robotics, and advanced technology in general, may not transpire right away or be as easily perceptive.

The endless search for new and better ways of doing things drives human learning and, ultimately, prosperity in every senseeconomic, social, and cultural, Adam Thierer, senior research fellow at the Mercatus Center, wrote in his book Permissionless Innovation.The pessimistic critics of technological progress and permissionless innovation have many laments, but they typically fail to consult the historical record to determine how much better off we are than our ancestors.

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Andreessen: Automation, Driverless Car Will Create More Jobs | The ... - The Daily Caller

Reasons people are migrating to Spark. Image: Databricks

Hadoop and MapReduce, the parallel programming paradigm and API originally behind Hadoop, used to be synonymous. Nowadays when we talk about Hadoop, we mostly talk about an ecosystem of tools built around the common file system layer of HDFS, and programmed via Spark.

Spark is the new Hadoop. One of the defining trends of this time, confirmed by both practitioners in the field and surveys, is the en masse move to Spark for Hadoop users. Spark is itself an ecosystem of sorts, offering options for SQL-based access to data, streaming, and machine learning.

People are migrating to Spark for a number of reasons, including easier programming paradigm. Easier than MapReduce does not necessarily mean easy though, and there are a number of gotchas when programming and deploying Spark applications.

So why are people migrating to Spark? The top reason seems to be performance: 91 percent of 1615 people from over 900 organizations participating in the Databricks Apache Spark Survey 2016 cited this as their reason for using Spark. But there's more. Advanced analytics and ease of programming are almost equally important, cited by 82 percent and 76 percent of respondents.

All industry sources we have spoken to over the last months point to the same direction: programming against Spark's API is easier than using MapReduce, so MapReduce is seen as a legacy API at this point. Vendors will continue to offer support for it as long as there are clients using it, but practically all new development is Spark-based.

Not everyone using Spark has the same responsibilities or skills. Image: Databricks

As Ash Munshi, Pepperdata CEO puts it: "Spark offers a unified framework and SQL access, which means you can do advanced analytics, and that's where the big bucks are. Plus it's easier to program: gives you a nice abstraction layer, so you don't need to worry about all the details you have to manage when working with MapReduce. Programming at a higher level means it's easier for people to understand the down and dirty details and to deploy their apps."

Great. What's the problem then? Munshi points out that the flip side of Spark abstraction, especially when running in Hadoop's YARN environment which does not make it too easy to extract metadata, is that a lot of the execution details are hidden. This means it's hard to pinpoint which lines of code cause something to happen in this complex distributed system, and it's also hard to tune performance.

Having a complex distributed system in which programs are run also means you have be aware of not just your own application's execution and performance, but also of the broader execution environment. Pepperdata calls this the cluster weather problem: the need to know the context in which an application is running. A common issue in cluster deployment for example is inconsistency in run times because of transient workloads.

Pepperdata is not the only one that has taken note. A few months back Alpine Data also pinpointed the same issue, albeit with a slightly different framing. Alpine Data pointed to the fact that Spark is extremely sensitive to how jobs are configured and resourced, requiring data scientists to have a deep understanding of both Spark and the configuration and utilization of the Hadoop cluster being used.

Failure to correctly resource Spark jobs will frequently lead to failures due to out of memory errors, leading to inefficient and time-consuming, trial-and-error resourcing experiments. This requirement significantly limits the utility of Spark, and impacts its utilization beyond deeply skilled data scientists, according to Alpine Data.

This is based on hard-earned experience, as Alpine Data co-founder & CPO Steven Hillion explained. At some point one of Alpine Data's clients was using Alpine Data Science platform (ADSP) to do some very large scale processing on consumer data: billions of rows and thousands of variables. ADSP uses Spark under the hood for data crunching jobs, but the problem was that these jobs would either take forever or break.

The reason was that the tuning of Spark parameters in the cluster was not right. People using ADSP in that case were data scientists, not data engineers. They were proficient in finding the right models to process data and extracting insights out of them, but not necessarily in deploying them at scale.

The result was that data scientists would get on the phone with ADSP engineers to help them diagnose the issues and propose configurations. As this would obviously not scale, Alpine Data came up with the idea of building the logic their engineers applied in this process into ADSP. Alpine Data says it worked, enabling clients to build workflows within days and deploy them within hours without any manual intervention.

So the next step was to bundle this as part of ADSP and start shipping it, which Alpine Labs did in Fall 2016. This was presented in Spark Summit East 2017, and Hillion says the response has been "almost overwhelming. In Boston we had a long line of people coming to ask about this".

Hillion emphasized that their approach is procedural, not based on ML. This may sound strange, considering their ML expertise. Alpine Labs however says this is not a static configuration, but works by determining the correct resourcing and configuration for the Spark job at run-time is based on the size and dimensionality of the input data, the complexity of the Spark job, and the availability of resources on the Hadoop cluster.

"You can think of it as a sort of equation if you will, in a simplistic way, one that expresses how we tune parameters" says Hillion. "Tuning these parameters comes through experience, so in a way we are training the model using our own data. I would not call it machine learning, but then again we are learning something from machines."

Pepperdata now also offers a solution for Spark automation with last week's release of Pepperdata Code Analyzer for Apache Spark (PCAAS), but addressing a different audience with a different strategy. Data scientists make for 23 percent of all Spark users, but data engineers and architects combined make for a total of 63 percent of all Spark users. This is the audience Pepperdata aims at with PCAAS.

Architects are the people who design (big data) systems, and data engineers are the ones who work with data scientists to take their analyses to production. Munshi says PCAAS aims to give them the ability to take running Spark applications, analyze them to see what is going on and then tie that back to specific lines of code.

The thinking there is that by being able to understand more about CPU utilization, garbage collection or I/O related to their applications, engineers and architects should be able to optimize applications. PCAAS boasts the ability to do part of the debugging, by isolating suspicious blocks of code and prompting engineers to look into them.

PCAAS aims to help decipher cluster weather as well, making it possible to understand whether run time inconsistencies should be attributed to a specific application or to the workload at the time of execution. Munshi also points out the fact that YARN heavily uses static scheduling, while using more dynamic approaches could result in better hardware utilization.

Better hardware utilization is clearly a top concern in terms of ROI, but in order to understand how this relates to PCAAS and why Pepperdata claims to be able to overcome YARN's limitations we need to see where PCAAS sits in Pepperdata's product suite. PCAAS is Pepperdata's latest addition to a line of products including the Application Profiler, the Cluster Analyzer, the Capacity Optimizer, and the Policy Enforcer.

The latter three are about collecting telemetry data, while the former two are about intervening in real-time, says Munshi. Pepperdata's overarching ambition is to bridge the gap between Dev and Ops, and Munshi believes that PCAAS is a step in that direction: a tool Ops can give to Devs to self-diagnose issues, resulting in better interaction and more rapid iteration cycles.

Interestingly, Hillion also agrees that there is a clear division between proprietary algorithms for tuning ML jobs and the information that a Spark cluster can provide to inform these algorithms. There are differences as well as similarities in Alpine Labs and Pepperdata offerings though.

To begin with, both offerings are not stand-alone. Spark auto-tuning is part of ADSP, while PCAAS relies on telemetry data provided by other Pepperdata solutions. So if you are only interested in automating parts of your Spark cluster tuning or application profiling, tough luck.

When discussing with Hillion, we pointed out the fact that not everyone interested in Spark auto tuning will necessarily want to subscribe to ADSP in its entirety, so perhaps making this capability available as a stand-alone product would make sense. Hillion alluded that the part of their solution that is about getting Spark cluster metadata from YARN may be open sourced, while the auto-tuning capabilities may be sold separately at some point.

Alpine Labs is worried about giving away too much of their IP, however this concern may be holding them back from commercial success. When facing a similar situation, not every organization reacts in the same way. Case in point: Metamarkets built Druid and then open sourced it. Why? "We built it because we needed it, and we open sourced it because if we had not, something else would have replaced it."

The AI lock-in loop: great investment begets greater results begetting greater investment. Image: Azeem Azhar / Schibsted

In all fairness though, for Metamarkets Druid is just infrastructure, not core business, while for Alpine Labs ADSP is their bread and butter. As for Pepperdata, they are toying with the idea of giving free access to PCAAS for non-production clusters to get a foothold in organizations. The reasoning is tested and true: get engineers to know and love a tool, and the tool will eventually spread and find its way in IT budgets.

Either way, if you are among those who would benefit from having such automation capabilities for your Spark deployment, for the time being you don't have much of a choice. You will have to either pay a premium and commit to a platform, or wait until such capabilities eventually trickle down.

The bigger picture however is clear: automation is finding an increasingly central role in big data. Big data platforms can be the substrate on which automation applications are developed, but it can also work the other way round: automation can help alleviate big data pain points.

Remember the AI lock in the loop? First mover advantage may prove significant here, as sitting on top of million telemetry data points can do wonders for your product. This is exactly the position Pepperdata is in, and it intends to leverage it to apply Deep Learning to add predictive maintenance capabilities as well as monetize it in other ways.

Whether Pepperdata manages to execute on that strategy and how others will respond is another issue, but at this point it looks like a strategy that has more chances of addressing the needs for big data automation services.

Read more:

Spark gets automation: Analyzing code and tuning clusters in production - ZDNet

Automation In The Oil Industry: What's Next For One Of The Big Players Forbes Automation is everywhere; even industries where some may least expect it, such as oil and gas. According to Craig Clark, VP of Finance at National Oilwell Varco (IntelliServ), the last two years for the oil and gas industry have been difficult and as a ...

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Automation In The Oil Industry: What's Next For One Of The Big Players - Forbes

In January I wrote about three major shifts on the horizon for accountantscollaboration, automation, and triple-entry accounting. Recently, automation in particularhas created a lot of industry chatter, and I would like to explain what exactly the impact will be on your firm ... specifically, your workflow.

For the record, in our space we have seen:

So, lets explore automation more deeplyand look at what it means to you, your practice, and your workflow.

The Age of Automation

Today, automation rests in the hands of the major online accounting software providers. With their access to enormous amounts of data from more than 3 million online subscribers (2.2 million from Intuit QuickBooks Online and 1 million from Xero), they are aggregating their customer data to build algorithms to auto-categorize, auto-configure, auto-alert, and auto-complete many of the tasks within their products.

This is changing your day-to-day by simplifying data entry and tasks. Specifically, client services, such as tax, bookkeeping, and payroll, are most impacted, and soonmany of these underlying data-entry tasks in these client services will be eliminated altogether.

Extending the Ecosystem

A constantly growing ecosystem of products surrounding the online general ledgers is making it easier to extend the workflows for your accounting system. Working with specific vertical industries or within your practice is becoming more seamless.

In some cases, additional workflows are being embedded inside general ledger software, such as the extension of QuickBooks Online with time tracking (viaTSheets) and AR/AP management (viaBill.com). In other cases, applications and their subsequent workflows are being stitched together by savvy practitioners using programs like Zapier and Workato.

In the medium-term future, you will be able to use broader APIs, notification proliferation, and easy-to-configure connectors to create cross-application custom workflows. These sophisticated workflow objects will manage, coordinate, and complete a set of predetermined tasks without you needing to lift a finger.

Your Workflow, Your Way

With the advent of online practice management applications and lightweight offerings like QuickBooks Online Accountant Practice Management, many firms are already documenting, deploying, following, and completing the necessary workflows that support their practice and complete the work for their clients.

An essential starting point for all practices is to identify key processes to document and standardize across the team. A central place that outlines how work is done will ensure quality, consistency, and efficient delivery. To fully take advantage of workflow automation, this must be done today.

Automation by the large players like Intuit, Xero, and Sagewill make your client work and other workflows easier by auto-completing or eliminating steps through learned, repeatable behavior. The reach of your existing workflows will be expanded with greater insights, real-time information, proactive vs. reactive actions, and more control over what can be done across other industry and small business applications. This is all evolving right now.

But what practice automation can you leverage today? Within your accounting application like Xero, you can map your clientschart of accounts to one common ledger to automate your report production via a standardized set of reporting templates. Intuit's recent release of auto-categorization will auto-recognize the vendor and present recommended categorization for the transaction based on similar crowdsourced behavior.

As for your small business clients, TSheets and its GPS functionality can track when and where people clock in and out. Hubdoc can automate the process of fetching documents and parsing bank statements and utility bills. Or vehicle mileage can be auto-captured for clients withExpensify's mileage tracking feature.

The list of apps, activities, and automation is growing every day. It is a matter of learning what your core apps are capable of doing and leveraging the technology to simplify the workflow of your firm.

We are already experiencing the effects of automation in the accounting industry, and this is only going to shift further and more rapidly. The challenge for you and your practice is to embrace this now, get a jump on your competitors, and make technology do as much heavy lifting as it is capable of.

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The Age of Automation and the Impact on Your Workflow - Accountingweb.com

DIGITIZE.AI May 30, 2017 | Views:

Digitize.AI is an investor backed start-up technology company headquartered in Charlotte, NC. We are currently in stealth mode and our team is growing quickly prior to our launch. Digitize.AI will use automation and artificial intelligence to help organizations create a digital workforce. Digitize.AI offers competitive salary, bonus and equity options.

Automation Developer Consultant role: Comprehensive and evident understanding of Microsoft Technology (VB .NET, Windows, Internet Explorer, SQL Server, Web Services) and ideally some background in Java. The ability to methodically solve business and technical problems using innovative and well-planned approaches. The ability to learn quickly and progress rapidly from theoretical exercises to real world delivery and mentoring tasks. The aptitude to contribute to the evolution of methodologies and procedures in a controlled manner to continually improve a rapid and repeatable delivery channel. The ability to work with a structured and methodical approach, combined with an enquiring mind. An understanding of, and a willingness to adhere to, formal change control procedures and disciplines.

Traits of a successful candidate: Desire to be trained in the latest automation technology and then work with clients to help them. The skills to design and author well documented, supportable and extensible developments and the ability to support and maintain the work of other consultants, partners and clients. Good communication skills with the ability to present technical details to a non-technical audience. Good written skills with the ability to produce clear and concise documentation. An aptitude for problem solving, with the ability to take a logical route to the source of an error. A self-starter who delivers high quality work and can adapt to new challenges, either on their own or as part of a team. Ability and willingness to travel as required.

To apply: Please send resume to careers@digitize.ai.

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Automation Developer Consultant - Charlotte Agenda

The Canada-EU trade agreement is "a blueprint for future ambitious trade deals in an age of automation where job security is threatened, Prime Minister Justin Trudeau says.

Trudeau, in a speech to lawmakers and business figures in Rome, lauded the pact as a model in an era of protectionism. The speech comes as Trudeau faces a lengthy trade battle with Donald Trump over lumber, airplanes, steel, aluminum and the North American Free Trade Agreement.

QuickTake Free Trade and Its Foes

"Leaders who think we can hide from these changes or turn back the clock are wrong," he said Tuesday in the ornate Sala della Regina room at the Chamber of Deputies in Rome. "The pace of change has never been so fast, and yet itll never be this slow again."

The trade deal, known as CETA, has what Trudeau called "unprecedented provisions on labor protection, responsible investment, food and consumer safety, management of natural resources and environmental stewardship.

Trudeau was joined at the speech by his trade minister as Canada pushes European Union member states to ratify the trade deal as quickly as possible.

We need to make CETA real for people, Canada Trade Minister Francois-Philippe Champagne told reporters after the Trudeau speech. The best way to convince those who may not be convinced is to show them the benefits such as 9,000 tariff lines set to drop to zero when the deal is provisionally enacted, expected early this summer.

The deal comes as automation makes traditional stable jobs more difficult to find as the "twin forces" of technology and globalization remake the world, Trudeau said. "There are those in Canada and here in Italy who feel uncertain and anxious about what the world holds," he said.

CETA will soon be considered by the Italian senate, Italian Senate President Pietro Grasso said in introducing Trudeau.

Trudeau lauded Italy for recognizing same-sex civil unions and pushed for greater numbers of women to be elected as lawmakers or appointed to corporate boards, calling Canadas current ratio of female Members of Parliament "not acceptable."

Excerpt from:

Canada-EU Trade Deal Is a Model in Automation Era, Trudeau Says - Bloomberg

Automation prompts fiercedebatesat the moment. Manyof the larger conversations around automation focuson whether it will create jobs or destroy them, what it will do to our economy, and how its helping or hurting various industries. But there are manyother smaller conversations happening around automation, and many IT leaders are just looking for simple ways to improve productivity, increase speed, and reduce manual work in their day-to-day operations.

Of course, I believe that automating something is better than having to keep doing it manually. But I dont overlook the opportunity to ask the important question: should we automate or should we obliterate?

If a process can be automated, its often automated without taking a step back to ask whether you should continue doing it in the first place.

Think about how many times youve questioned a process or approach only to be given the maddening response, This is the way weve always done it. The era of automation gives us a similar problem. If a process can be automated, its often automated without taking a step back to ask whether you should continue doing it in the first place.

Taking the time to ask that important question provokes a different type of thinking kind of like a zero-based analysis. You are no longer assuming that whats in the base has to remain in the base. Sure, it can be automated, but if it doesnt have to exist in the first place, why not just eliminate it?

At CVS Health, we conduct surveys on an annual basis that ask colleagues hundreds of questions about the company, the work environment, the type of work they do, and more. We analyze their responses and choose themes that enable us to continually improve the work environment and experience year over year. One of the themes that emerged from the annual survey this year was the opportunity to reduce what is perceived to be red tape by our employees. This prompted usto put manyprocess improvements onto our priority list areas where we could automate or eliminate steps, processes, and functions in different parts of the IT organization, to reduce work and increase speed.

For instance, the time and steps that it took to get approval on staff augmentation was perceived by our employees as red tape, and they were right. We were able to reduce that time from weeks to one day. But we didnt achieve these results through automation: It was through obliteration.

Just because something is there now, that doesnt mean it needs to be there tomorrow.

We looked at these opportunities holistically, taking into consideration both the administration and the technical aspects and processes in play. We reduced the number of project approvals by 41 percent and the technical design artifacts by 60 percent. By eliminating these steps altogether, we were able to reduce friction in the administrative processes of managing staff, projects, and programs.

If we had just focused on automation as a way to solve the problem, we would have ultimately been automating work that was unnecessary in the first place. Just because something is there now, that doesnt mean it needs to be there tomorrow.

There are excellent tools to help IT organizations answer their own automate-or-obliterate questions. You can use Pareto analyses, for instance, to determine where time is spent in order to pinpoint improvement targets. Most importantly, dont lose sight of the problem you are trying to solve. Start there, and use proven methodologies to scientifically analyze where your opportunities are, whatever they are, and then act on them.

Automation may seem like your teams secret weapon to finding more time and productivity throughout the day. But, in the constant quest to find ways to move faster in IT, its important to sometimes slow down, pause, and ask yourself, Why do I even need to do this?

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CVS Health CIO: An overlooked alternative to automation - The Enterprisers Project

Enterprise investment in robotic process automation (RPA) is set to soar in Australia and New Zealand, according to new research from analyst firm Telsyte.

Based on insights provided by 302 CIOs and IT decision makers, the Telsyte ANZ Robotic Process Automation Study 2017 predicts the ANZ RPA market will grow at a compound annual growth rate (CAGR) of 45 percent from AU$216 million in 2016 to AU$870 million in 2020.

The analyst firm said RPA -- which enables software robots to replicate the actions of human workers for routine tasks -- is now being used or investigated by six out of 10 ANZ organisations with more than 20 employees.

Additionally, 38 percent of organisations with more than 500 employees have active RPA programs in place.

The finance and insurance industries are expected to be the fastest adopters of RPA in the short term, according to Telsyte, although RPA can also be applied to industries with large customer support and request processing requirements, such as telecommunications and government.

Telsyte managing director Foad Fadaghi said RPA is not just about cutting overhead costs; it can also change the way organisations operate.

"A proof of concept is important for organisations to first understand the nature of processes that can be best solved through RPA, before progressing to an enterprise-wide strategy," Fadaghi suggested.

"Equally important is the use of pilot programs to understand the change management requirements before a further rollout."

Telsyte also recommended that organisations assess the processes they would like to automate by their level of complexity.

"Complexity has a positive correlation with automation costs, and targeting lower-complexity processes initially can result in better initial returns," Telsyte said.

Fellow analyst firm Gartner has previously referred to RPA tools as "gateway technologies" or "surface tools", because they simply skim the surface of the larger intelligent automation services market.

"The attraction is the RPA tool just sits on top of the legacy system" such as enterprise resource planning (ERP), and there is no need for any special integration, Gartner research vice president and analyst at Frances Karamouzis told ZDNet.

"They're also easy to use and have a relatively low cost. For all those reasons [RPA] has by far the highest adoption of automation tools that we've seen," Karamouzis added.

With the increase in enterprise investment in RPA, DXC Technology, a New York Stock Exchange-listed IT services company, announced the introduction of 60 new RPA experts in Australia and New Zealand.

"Organisations are looking for a way to bridge the gap between large funded digital transformation projects and the long tail of business processes attached to aging systems. RPA can achieve this with a virtual workforce that streamlines existing processes, lays the foundation for intelligent automation, and frees up employees for more engaging work," said Seelan Nayagam, managing director at DXC Technology ANZ.

The IT services company is now actively expanding in the ANZ region to guide clients implementing RPA.

"We are seeing a shift in our client's focus from cost reduction and labour arbitrage, offered by more traditional outsourcing models, to driving business value through innovation," Nayagam said. "This includes RPA, and as a case in point, we have implemented RPA within DXC for automating our own shared service processes."

While organisations in the ANZ region are believed to be at the "basic stages of adoption", a 2016 Deloitte report indicates that enterprises internationally have begun to employ RPA together with cognitive technologies such as speech recognition, natural language processing, and machine learning to automate perceptual and judgement-based tasks once reserved for humans.

"The integration of cognitive technologies with RPA makes it possible to extend automation to processes that require perception or judgement," David Schatsky, managing director at Deloitte, previously said. "With the addition of natural language processing, chatbot technology, speech recognition, and computer vision technology, for instance, bots can extract and structure information from speech audio, text, or images and pass that structured information to the next step of the process."

Additionally, machine learning can identify patterns and make predictions about process outcomes, helping RPA prioritise actions.

"Cognitive RPA has the potential to go beyond basic automation to deliver business outcomes such as greater customer satisfaction, lower churn, and increased revenues," Schatsky said.

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Robotic process automation market to reach AU$870m in ANZ by ... - ZDNet

At the World Government Summit in Dubai, our real-world Tony Stark, Elon Musk, was throwing around some big and important ideas about the future of humanity. Musk says that Universal Basic Income or an economic idea where everyone gets a paycheck from the government to spend how they wish is one of the only solutions to the rise of robotic automation.

Automation on large scales will absolutely change everything. The going term right now is the rise of the post-scarcity economy. And, while I know that sounds boring as hell, for you it means that in the not-too-distant future, money wont matter and all of our economies will totally collapse. And yeah, Im serious.

Post-scarcity is something that we should all be able to at least kind of understand. Traditional economies work because things are rare. Food, for example, isnt infinite. If it was, itd be free. After all, how could you charge for something that is unlimited? Like air? Or the sun? Theres no practical way to do that.

Thats essentially why the Star Trek universe abandoned money. After you have replicators, which are basically magical boxes that make anything from anything in seconds, stuff doesnt have intrinsic value. You cant control the supply or demand of anything because the demand is whatever and the supply is unlimited. In that system, as you can already tell, nothing about traditional economics works. Whats a supply and demand curve even mean under those circumstances?

Obviously, humanity is a long way from replicators. And, as a result, we wont have true post-scarcity systems for a long time yet. But, we are about to take a couple of major leaps forward. Here is a list of all the places robots are likely to steal jobs in the future. If you just account for self-driving cars, though, you can take as many as 20% of all jobs away in one swoop. The transportation sector employs that many people.

But thats not the only industry that will get a jolt. Many service industry jobs are easy to automate. That could wipe out tens of millions more job. Even if it takes twenty or thirty years, Musk rightly notes that no economy can sustain that.

And while many of you might think that sounds like a bunch of leftist hippie bullshit, this is actually about as politically neutral as it gets. Again, think about it if you have 30 or even 40% unemployment, then the economy, as weve traditionally structured it has nothing to do but collapse. If that many people are unemployed, they wont have enough money to buy anything, really. That, in turn, shatters demand for goods and then everyone else suddenly becomes unemployed. If this happens, inflation is screwed, money has no meaning and the entire system weve created would utterly cease to function.

Most plans for universal basic income start by suggesting a tax robots. The goal here is to replace revenue lost from the mass numbers of unemployed and keep it coming in from the bots. Plus, this is still a net gain for businesses they get money flowing into pockets so people can keep spending, and even conservative estimates suggest that robots will be able to pay for themselves dozens of times over. So companies wont really be losing any money there, either.

This is a set of ideas that Ive tossed around with friends for a while. Unless something huge changes, this is probably the only viable solution. It keeps most markets and corporations intact, while still working with the complex reality posed by infinite labor from bots. Its weird to think, but, honestly, Musk is almost certainly spot on here.

We will, of course, have some time to adapt to this. But its something we should all start familiarizing ourselves with now. Robots can replace you. No, your job is not safe. Not even if youre a doctor or a lawyer. Theres a great video from YouTuber CGPGrey above that runs through the best case scenarios here, and, honestly, its not good.

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Elon Musk: Automation Will Force Universal Basic Income - Geek.com - Geek