Category Archives: Automation

All around us, our products are getting smarter. They respond to our touch and voice and adapt to our needs. They are responsive, flexible, and intelligent. Unfortunately, the same cannot be said about the factories that make them. Our factories are mainly analog; most are still populated by hundreds of people repeating the same task. Neither the processes nor equipment is designed to respond to change, adapt quickly to customer needs, or address quality issues at scale and with ease.

An Amazon Echo Spot smart speaker photographed on a kitchen counter, taken on January 9, 2019. ... [+] (Photo by Olly Curtis/Future via Getty Images)

This outdated approach has real consequences: machines sit idle (utilization can be as low as 40%) while waiting for orders, material, or human intervention. Mistakes and misfires produce large amounts of scrap, and labor turnover can be as high as 30%.

The last big step-function in manufacturing capacity and capability was achieved via globalization more than two decades ago. Now, access to low-cost labor is diminishing, while consumer demand for authenticity, speed, and localization increases. Our manufacturing methods are reaching their limits.

The Next Big Leap

Its clear that automation is the next giant leap for manufacturing, but its deployment has been stymied for the somewhat ironic reason that automation itself isnt automated. Instead, machines have to be individually configured and independently managed by human workers. There is no connected flow of information between machines and no method of continuous improvement. This first generation of automation costs too much, takes too long to install, and depends on a small group of experts, making it difficult to scale or replicate.

In the last decade, software has evolved to address these problems. We can automate automation by connecting individual machines to a software layer that dynamically configures and continuously monitors and manages machines to improve operations, creating autonomous production lines and programmable factories. We call this approach software-defined manufacturing. It provides three clear benefits.

How Software Will Define Manufacturing

First,it makes it easier to configure, replicate and scale automation, dramatically changing the economics, speed, and flexibility of automation.

Second, by digitizing factory operations, software-defined manufacturing makes these operations more transparent and accessible, enabling the entire organization to better interact with manufacturing processes. The payoff is agility and continuous improvement.

Third, it adds intelligence. By leveraging computer vision, machine learning, and adaptive algorithms, it gives machines eyes and brains.

Artificial intelligence (AI), machine learning and modern computer technologies concepts.

With software-defined manufacturing, intelligent applications can act on production data to configure and continuously improve production lines, delivering higher quality and throughput. Production lines become autonomous, and the factories that house them programmable.

Opportunities at The Back-End

The logical place to start automating automation is at the back-end of the production line, where assembly, inspection, and testing are still primarily done manually. That requires a combination of technologies to create an integrated system of hardware (such as robotic cells, automatic conveyors, and material feeding systems) and software that leverages computer vision, machine learning, and 3D simulation. The cells provide the arms and legs, and the software provides the eyes and brains. Dexterity and variability are no longer blockers.

Microfactory for product assembly and inspection.

Take, for example, a manufacturer that needs to automate the assembly of a networking device specifically, to figure out where and how to insert screws and then to insert a high-value memory component called DIMM.

To do this, a system that truly automates automation would first take pictures of a prototype board and ingest 3D geometry describing the boards design. Using AI, it understands the features of the product, rather than mere geometric positions. Collaborating with a human, the software creates a set of instructionsa manufacturing recipeto assemble the components. The recipe is then simulated in a virtual environment with a physically and kinematically accurate robot model. This ensures that the proposed actions are safe, accurate, and successful.

Then, the manufacturer presses play and can watch the robot seek out the screw holes using optical sensors, then place and screw the heat sinks into place. The robot uses those same sensors to apply a precision level of force to insert the DIMM module.

Thats just the start. The abstraction of instructions into recipes means that once one software-defined manufacturing system learns how to assemble a DIMM module, all those systems, or microfactories, can instantly do the same anywhere in the world.

Enabling the Future-State of Manufacturing: Nimble, Local, Innovative

Software-defined manufacturing provides a holistic view and deep insights into the entire production line. It makes it easier to pinpoint quality issues and find their root causes, no matter where in the production line they may be. The software suggests corrective action, which an operator can implement. As a result, not only do operational metrics improve, but the production line becomes configurable and self-correcting. This is fundamental to reimagining the factory floor and essential to automating automation.

Software-defined manufacturing is already helping transform the industry, exceeding requirements for speed, scale, and flexibility and yielding a real return on investment. It is also enabling distributed, location-agnostic manufacturing. Customers can make better products in nimbler, smaller, and more sustainable factories. One can sense a future where products are made locally and on-demand.

Perhaps most exciting among the benefits of software-defined manufacturing is its potential to speed innovation dramatically. As factories become digital and distributed, they become transparent and accessible. Manufacturing is transformed into a capability that anyone can access, rather than a mysterious, dark art. Ultimately, its not about AI or software or increasing run rates. Its about enabling anyone to build anything anywhere, on-demand. Its about the democratization of innovationand the manufacturing infrastructure to make that innovation real.

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Is Your Automation Automated? How Software Is Opening The Door For Increased Innovation In Manufacturing - Forbes

MOUNTAIN VIEW, Calif.--(BUSINESS WIRE)--Stampli, a complete accounts payable (AP) automation platform that brings together AP communications, documentation, and payments in one place, has been named Leader in AP Automation, as well as Invoice Management by G2, the worlds leading business solutions review website.

In addition to securing its placement as an overall G2 Grid Leader in AP Automation for the seventh consecutive quarter, G2s Spring 2021 scores also mark this as the fifth quarter in a row the company was named an overall Grid Leader in Invoice Management. Stampli is also recognized as a Leader in AP Automation for mid-market businesses (companies with 51-1,000 employees).

As part of Stamplis continued success in multiple software categorizations, the company is placed as overall Leader in G2s Momentum Grid across AP Automation, Invoice Management, and Billing categories. The Momentum Grid is measured by Momentum scores on the vertical axis which represents overall company growth along with review growth, and Satisfaction scores on the horizontal axis which represents overall customer satisfaction.

As with previous quarters, Stampli received its Leader status across multiple categories based on high ratings of customer satisfaction, support and usability according to reviews submitted to G2 by Stampli users. User-contributed ratings of Stampli led to a number one overall rank in Spring 2021 for all four AP Automation Index Reports Implementation, Relationship, Usability, and Results as well as first in the same four Index Reports for mid-market companies.

From the beginning, Stampli has put customers front and center, said Eyal Feldman, CEO of Stampli. This has resulted in everything from our industry-leading response times to the way we've evolved the Stampli product (our introduction of Stampli Direct Pay being an example of this). We're thrilled to be recognized by our customers on G2 Crowd and excited to continue building the best AP Automation platform for our users.

"We hold an incredible amount of respect for the G2 Crowd because they're real-life indicators of customer satisfaction. Being able to see unbiased user feedback is invaluable. It's also incredibly fulfilling to see reviewers holding Stampli in such high regard, with things like user friendliness, fast integration times, supportive customer success and deep integrations being common themes in the reviews.

G2 reviewers praised Stampli for its intuitive design, extensive training and support capabilities, and seamless integrations with existing processes and financial systems. These traits are especially important when many AP teams are operating remotely.

According to one Stampli user in 2021:

Stampli's simple to use interface makes it easy for our employees to review, process and pay invoices. By implementing Stampli, we were able to streamline our AP process and cut down on the amount of time it took to process invoices. In addition, their on boarding process was easy and they took great care making sure we were 100% satisfied before they went "hands off". Stampli's support has been on point and they are quickly able to answer any questions that we have.

In addition to being a G2 Leader in AP Automation, Stampli was named Best Accounts Payable Solution in the 2021 FinTech Breakthrough Awards just last week.

About Stampli

Stampli is intuitive with role-specific experiences, carefully tailoring the invoice processing experience by stakeholders AP Staff, Management, Approvers, and Vendors giving each individual an experience based on their unique workflows and needs. Additionally, Stampli turns the invoice into a communication tool by offering an in-app communications hub connected to the invoice. All conversations are connected to the invoice getting questions answered quickly and available for audit.

Stampli is also payment agnostic, giving customers the freedom to choose whichever payment method or service they prefer. Stampli Direct Pay, is an optional service, where Stampli users can pay vendors directly inside of Stampli with ACH and Check payments.

Stampli seamlessly integrates with ERPs, including Oracle NetSuite, Sage Intacct, QuickBooks Desktop, QuickBooks Online, Microsoft Dynamics and more. Fast, easy setup without the need for IT. For more information, visit stampli.com.

About G2

G2, the worlds leading business solution review platform, leverages more than 1,000,000 user reviews to drive better purchasing decisions. Business professionals, buyers, investors, and analysts use the site to compare and select the best software and services based on peer reviews and synthesized social data. Every month, more than one million people visit G2s site to gain unique insights. Co-founded by the founder and former executives of SaaS leaders like BigMachines (acquired by Oracle) and SteelBrick (acquired by Salesforce) and backed by more than $100 million in capital, G2 aims to bring authenticity and transparency to the business marketplace. For more information, go to G2.com.

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Stampli Named AP Automation Leader in G2's Grid for Seventh Consecutive Quarter - Business Wire

When it comes to transforming organizations these days, automation is king. Automating IT and business processes took major leaps forward in the wake of the pandemic, and the trend is expected to roll on this year, as organizations navigate a post-pandemic business environment.

Research firm Gartner listed hyperautomation an all-out approach to automating anything that can be automated in an organization as one of its top strategic technology trends for 2021. The use of robotic process automation (RPA) platforms is on the rise, and artificial intelligence is becoming much more than a buzzword as more organizations deploy AI-powered tools and build use cases.

Automation has become such a key priority for organizations that IT leaders are creating dedicated teams to plan, execute, and maintain their automation strategies. What does it take to build an elite automation team? Here are some key traits and skills to look for.

Automation team members should have a working knowledge of the various platforms on the market that enable IT automation, such as RPA, business intelligence (BI), business process management, and other systems.

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Skills and traits of elite IT automation teams - CIO

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Graphene is touted for several applications due to its beneficial properties and the synergistic benefits brought about by utilizing its different properties. There are already many applications where graphene is having a real-world, commercial impact and there are several emerging applications. It is also thought that graphene will play a role in industrial automation in the near future.

Almost all manufacturing and industrial processes will be automated in some way in the near future in the era of the so-called Industry 4.0. The ability for many processes to become automated offers the following benefits:

There has been a drive to implement industry 4.0 on a wide scale, combining physical monitoring approaches, big data, and artificial intelligence algorithms, as well as the Internet of Things (IoT). While many industrial automation processes focus on software (as these provide the analyses and optimization protocols), the importance of the physical infrastructure that underpins the data/software cannot be understated.

In terms of industrial automations physical infrastructure, there is much potential for graphene to be used. These promising areas will be discussed below.

Sensors are one of the most important devices in any automation, monitoring, or IoT approach. While the software and data algorithms get a lot of credit, they would not be able to make predictions or optimize processes without data. This data comes from an array of sensors strategically placed around the process/manufacturing line and are in place to detect and monitor a range of factors. These can include but are not limited to, detecting different gases, temperature, humidity, strain, the optical properties of product, and the presence of harmful chemicals in the working area.

Out of all the electronic devices where people talk about graphene, sensors have the most potential and there are already a range of graphene-based sensors on the market which are designed to detect different parameters. The infrastructure is already being created using graphene, it just needs to be implemented into the automation systems.

The inherent thinness of graphene can create very small sensors. Graphene sensors are very interactive with their local environment and minute changes can trigger a detectable response thanks to graphenes high electrical conductivity and charge carrier mobility which changes in response to an external stimulus. Graphene sensors are highly sensitive and can be integrated into locations where other (bulkier) sensors may struggle.

With IoT and artificial intelligence algorithms, the more accurate the data being recorded is, the more accurate the predictions and optimizations will be. Therefore, there is a need to obtain the most accurate data possible to complement the automation algorithms, and it is likely that we will see graphene sensors being used to provide this accurate data in the future as graphene sensor commercialization and automation integration gain more traction.

The creation of graphene-based energy storage devices has seen a lot of recent commercial involvement. Energy storage devices are not applicable for all automation processes as many sensors and components are connected to the mains. However, energy storage devices can be key for monitoring processes that are more remote/in harsh processing conditions, reliable and long-lasting.

Many components and devices require batteries or supercapacitors, and both graphene-based batteries and supercapacitors are now starting to become a commercial reality. Graphenes high electrical conductivity enables large amounts of charge to be stored and released, enabling devices to be powered for longer.

Another area, which is only applicable to more remote monitoring and data acquisition methods, is energy harvesting devices. There has been a drive to create nanogenerators that convert energy from the local surroundings (be it mechanical energy, heat/thermal energy, or otherwise) and convert it into electrical energy. While the energy produced is small, it is often enough to power the sensor it is attached to.

While energy storage and harvesting devices are not applicable for all industrial industries, those that require some levels of remote or environmental monitoring could benefit from graphene-enhanced devices to power the remote sensors. There is a lot of work going into these devicesespecially energy storage devicesand the use of graphene energy storage devices is likely to extend into many industrial applications in the future (not just in terms of automation/monitoring).

One of the key things about automation systems is their ability to collect and analyze data from many locations, pick out trends, and implement an appropriate response to the data being provided. Sometimes there is no response, however, in others, it can be a warning to a human operator. An internal optimization by the software itself may also be needed. For all of this to occur, the different components need to interact and communicate with each other. In some cases, this can be through wired communications. However, for many devices to be connected around large sites (and in large monitoring systems) they need to be connected wirelessly. This tends to be via microwaves or radio frequency (RF) waves.

There have been several devices created using graphene that can act as either transmitters or receivers for both RF waves and microwaveswith RF waves being the more common approach. A lot of these have been based around creating graphene-based transistors, which can then primarily be used to build antennas (for either a receiver or transmitter) that can communicate using different electromagnetic waves.

Graphene transistors are also being used in other receiver/transmitter components, including amplifiers, mixers, switches, oscillators, and modulators that enable various forms of signal modulations.

While graphenes electrical properties are crucial in creating transistors that are highly efficient (and small), the small size, its mechanical properties, as well as the properties that graphene induces into the transistors are also vitally important. For example, many graphene transistors have been made to date already, and there has been much interest in creating RF communication systems with graphene. A lot of the devices to date have a high performance, but also exhibit a high gain and a high cut-off frequencywhich can be high into the Gigahertz (GHz) and the Terahertz (THz) range.

There is much interest in developing graphene-based wireless communication systems, but they have not reached the commercial level/market adoption phase that other graphene-based systems are at. Nevertheless, there is the potential (if research and development efforts continue) for graphene to be used within these communications systems in the near future, as there are several different components within receiver/transmitter systems where graphene can be integrated.

Nuclear Decommissioning Authority (2017) The Potential Applications of Graphene (and Related Compounds) Relevant to the NDAs Decommissioning Mission. Online. Available at: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/635443/The_Potential_Applications_of_Graphene__and_Related_Compounds__Relevant_to_the_NDA_s_Decommissioning_Mission.pdf

Nassef B. G. et al. (2020) Graphene and Its Industrial Applications A Review, International Journal of Materials Engineering, DOI: 10.5923/j.ijme.20201001.01

Zhu, L. et al. (2020) 2 - Two-dimensional materials-based radio frequency wireless communication and sensing systems for Internet-of-things applications, Emerging 2D Materials and Devices for the Internet of Things, https://doi.org/10.1016/B978-0-12-818386-1.00002-3

Liu, C. et al. (2020) 10- Nanocomposite materials for nano-electronic-based Internet of things sensors and energy device signaling, Emerging 2D Materials and Devices for the Internet of Things, https://doi.org/10.1016/B978-0-12-818386-1.00010-2

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

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The Future of Graphene Nanoparticles in Industrial Automation Applications - AZoNano

IT security leaders are prioritising investments in automation, Zero Trust and API-based security to protect a rapidly transforming IT ecosystem, according to new research from FireMon.

A survey of 500 cybersecurity leaders has uncovered the key investments organisations are making, and the rationale behind their decisions. The survey found distinct priorities have emerged when it comes to responding to the needs of IT security's rapid transformation.

"The study shows that a cocktail of multiplying threats, the proliferation of hybrid and cloud architectures, blended with a pandemic-fuelled explosion in distributed and remote work has created a perfect storm for network security teams," says Satin H. Mirchandani, president and CEO of FireMon.

"It is no wonder that they are adding new technologies, architectures, and approaches to ensure their networks remain protected."

The survey identified five major areas for network security investment:

"From an automation perspective, respondents cited the need to increase security agility and accelerate responsiveness and reduce the mean time to discover and resolve security incidents as the major drivers," says Mirchandani.

"This indicates that network security's growing complexity has rendered manual processes insufficient to keep up with accelerating rates of change," he says.

"Automation is now an imperative."

Mirchandani says that based on the survey findings, it is also clear that Zero Trust Architecture will achieve broad adoption to support the transition to cloud architectures and ensure security for an increasingly remote workforce.

"Both trends were accelerated by COVID-19 and are highly unlikely to be reversed," he says.

As part of this transition to cloud-based architectures, many respondents plan to implement a SASE platform to reduce cost and complexity, and improve security for their distributed and mobile workforce.

However, there is a risk of lack of alignment in a rush to balance the transition to cloud-based environments while still managing legacy infrastructure. This is especially the case when it comes to network security operations and application development and delivery processes. This misalignment causes slower application deployment, increases risk of downtime, and creates friction between security and development teams.

To gain greater alignment among security and development processes, more than 8 out of 10 organisations are looking to better integrate their systems via open APIs. This allows them to inject security capabilities into their preferred workflows, enabling greater flexibility and smoothing collaboration between groups.

"Network security is in the midst of a tectonic shift. New technologies and approaches will rapidly become the norm, forcing security teams to rethink how they manage access policies and ensure compliance in a changing and highly heterogeneous world," says Mirchandani.

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IT leaders prioritising automation, Zero Trust and API-based security investments - SecurityBrief Asia

With the retail apocalypse showing no signs of slowing down, brands hoping to survive need to harness intelligent technologies to ensure they thrive. Retailers must look at ways to integrate innovative solutions and accept that infusing artificial intelligence (AI) through a chatbot on your website, while important, is no longer enough. Instead, retailers should use AI and automation more broadly to ensure they can delight customers, which will future proof their business.

Brands need to integrate AI more widely to provide the intelligence they need to help understand more about their customers and ensure they can meet their demands exactly when, where and how they want. However, making this mantra a reality remains elusive for many.

By integrating AI and automation, retailers will be able to solve some of the immediate challenges they face, including:

With the pandemic now entering its second-year supply chain, challenges remain a significant hurdle. These inefficiencies result in lost revenue and dissatisfied customers. Inefficient inventory management is the Achilles heel of many retailers that need to connect their digital apps directly with their back-office logistics and supply chain management systems to give users up-to-date, accurate information. This reduces friction and will ensure that customers remain on your digital sites rather than turning to a competitor. With AI, the entire supply chain, including stock, logistics, staffing and distribution, can now be managed in real time so that every customer-facing digital interface conveys precise information. With AI, brands can predict and understand demand fluctuations and trends.

AI is critical in helping deliver a personalized and seamless customer experience. It provides retailers with the intelligence they need to understand customers' shopping habits and preferences. This enables retailers to align their offerings with customer expectations. For example, AI can recommend promotions and products tailored to a customer based on the individuals social footprint, demographic data, and a variety of other data points. Those brands that have delivered personalized experiences have seen revenues increase. Retailers can't afford to mismanage customer expectations in the current economic climate. With AI, brands now have the power to offer personal shopping at scale.

Its clear that contactless retail has now moved from fad to fact, and retailers need to adjust the in-store experience to reflect this shift. By integrating AI, retailers can automate many traditional high-touch processes, including incorporating cashier-less payments that help to reduce in-store lines, setting up contactless returns, and deploying voice-activated digital displays. In addition to supporting the shift to contactless retail, this will positively impact the bottom line by lowering in-store operating costs.

AI is a lifeline for retailers as they fight to survive. It provides the flexibility retailers need to meet changing demands and deliver operational efficiencies. By infusing intelligent automation across operations, retailers will survive 2021 and set themselves up for long-term success. Put simply, when it comes to AI in the retail sector, fortune favors the brave.

Gareth Smith is the general manager atEggplant, a test automation and monitoring platform that features deep learning and artificial intelligence.

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How AI and Automation Can Help Retailers Survive - Total Retail

Author: Anil Bhasin, Managing Director and Vice President India and South Asia, UiPath

2020 was the year that brought sweeping changes to the way we live, work, and run businesses. In the circumstances created by the pandemic, it drove home the importance of digitization and automation to ensure smooth operations. We have had several customers significantly ramp up their adoption of automation tools across enterprise functions. They have noted transformative changes including greatly improved efficiency, back-office functions performed with minimal intervention, and advanced remote working facilities. Several organizations look forward to extending automation to other business operations and scaling it effectively.

Based on the experiences and success stories shared by our customers, we have created this two-part article to share certain best practices that we would recommend to organisations as they scale their automation journeys:

1. Paint an Inspiring Automation Vision: Defining a vision for the project can help set the tone for the automation roadmap. It helps the larger group of stakeholders, specially those not involved in the technical aspects, process the project value, and actively participate in the program and drive the mindset change. As Krishna Vemugunta of Wells Fargo puts it, Our next 12 months vision is around implementing composite capabilities and building maturity around automated process discovery and human in the loop, ultimately leading to hyper automation.

2. Develop a Robust Business Case: While automation is at the centre of board room discussions, convincing stakeholders on the need to invest in automation is often challenging. Ensuring that the investment is aligned with strategic priorities helps make quick and informed decisions. This can later, also help simplify the approval process to source budgets for expanding the program at an enterprise level.

One example of this was Cholamandalam MS General Insurance Company Ltd. The companys Sr VP & Head - IT, Digital and Operations, Anubhav Rajput, said, Our roadmap is around two tracks. The first track is to move from 2-3 department to other organizational functions where we are confident that ROI will be delivered. The second track is building capability of intelligent OCR with handwritten capabilities and exploring usability of low code in the CoE.

3. Get Sponsorship and Support from the Top: Sponsorship and support from the top management is critical. The C- Suite must be aligned with the road map and should be able to support the vision. Continuous updates and involvement at this level helps instil confidence in the program and keep it on track.

This was also the experience of Sumit Srivastav, Partner and Intelligent Automation leader, PwC India, Once our intelligent automation technology solutions were implemented, our teams have become more tech savvy. This has also come with the encouragement, support, and investment in skilling from our leadership. Our operations have become more efficient, and our ecosystem has become more resilient.

4. Involve Stakeholders from the Beginning: An automation program requires a good understanding of the process involved. It requires continuous involvement of process owners as well as the IT support team to ensure seamless structuring. Like Bobby Jutley, Digital CoE, HP Inc., says, This is an interesting debate that always comes up about: Do we bring IT along? Does IT drive automation or is it business? We decided to have a clearly aligned partnership with IT forming a two-in-a-box approach.

The organisation must also enlist the support of key stakeholders including functional or department heads, process owners, the cybersecurity team, the compliance team, etc. It is especially critical that stakeholders who will be affected by automation are identified and their roles and responsibilities during and after the transition are well-defined.

5. Get Employee Buy-in: Given the impact of automation scaling on employees, change management must be made an integral part of the plan. People strategy must work in tandem with the organisations scaling strategy.

Most companies use a top-down approach to scale automation. They begin with setting up a Centre of Excellence and deploy the first automation to help their employees. The incorporation of employee feedback and ideas as well as external developer ideas gets a flywheel moving and helps accelerate the companys digital transformation process.

In part 2, we will learn more about the best practices that will help scale automation to successfully implement digital transformation.

Disclaimer: Content Produced by UiPath

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The 10 Step Roadmap to Scaling Automation Part1: Setting up success with stakeholder involvement - Economic Times

SANTA CLARA, Calif.--(BUSINESS WIRE)--ServiceNow (NYSE: NOW), the leading digital workflow company making work, work better for people, today announced it has signed an agreement to acquire Intellibot, a robotic process automation (RPA) company based in Hyderabad, India. Intellibot extends ServiceNows core workflow capabilities by helping customers automate repetitive tasks for intelligent, end-to-end automation. ServiceNow intends to build Intellibot's capabilities natively into the Now Platform to enable customers to more easily integrate with both modern and legacy systems to drive productivity and strengthen existing artificial intelligence (AI) and machine learning (ML) efforts.

ServiceNow is the platform of platforms for the workflow revolution, offering powerful end-to-end automation capabilities that allow customers to streamline business decisions and unlock new levels of productivity, said Josh Kahn, SVP of Creator Workflow Products at ServiceNow. Our customers represent nearly 80 percent of the Fortune 500, and the vast majority are trying to drive automation across a mix of legacy and modern applications. With Intellibot, we will extend ServiceNows ability to help customers connect systems so they can easily automate workflows and drive productivity.

ServiceNow recently delivered the Now Platform Quebec Release to help enterprises accelerate their digital transformation by innovating quickly, being more agile, and operating more productively within a new world of work hastened by COVID. Intellibot will complement these capabilities, extending ServiceNows existing AI and ML, integrations, low-code development, process mining, process automation, NLX, chatbot, and virtual agent capabilities.

We are proud to join forces with ServiceNow as it continues to invest in powerful end-to-end automation capabilities to make the world of work, work better for people, said Srikanth Vemulapalli, CTO and co-founder of Intellibot. Our RPA combined with ServiceNow workflows will help businesses better connect disparate systems to accelerate innovation and thrive in a new world of work.

Expanded footprint in India

This acquisition supports ServiceNows broader commitment to the Indian market, which represents one of the companys fastest growing markets. The company plans to develop two new data center facilities in India by the first quarter of 2022. These new data centers will meet local data residency requirements, form part of ServiceNows advanced high-availability architecture, and will continue to support the scalability of the companys cloud services. India hosts ServiceNows second largest research and development center and is a growing talent hub for the organization. ServiceNow plans to double its staff in the country within the next three years.

Intellibot was founded in 2015 by CEO Raghu Alekh Barli, CTO Srikanth Vemulapalli, and COO Kushang Moorthy. ServiceNow expects to complete the acquisition of Intellibot in Q2 2021. Financial terms of the deal were not disclosed.

To learn more about ServiceNows automation capabilities, visit the ServiceNow blog.

Use of Forward-Looking Statements

This press release contains "forwardlooking statements" about the expectations, beliefs, plans, intentions and strategies relating to ServiceNows acquisition of Intellibot, general business direction and plans for expansion in India, and growth markets. Such forwardlooking statements include statements regarding future data centers, growth, expansion, product capabilities and offerings and expected benefits to ServiceNow. Forward looking statements are subject to known and unknown risks and uncertainties and are based on potentially inaccurate assumptions that could cause actual results to differ materially from those expected or implied by the forward-looking statements. If any such risks or uncertainties materialize or if any of the assumptions prove incorrect, our results could differ materially from the results expressed or implied by the forward-looking statements we make. We undertake no obligation, and do not intend, to update the forward-looking statements. Factors that may cause actual results to differ materially from those in any forward-looking statements include, without limitation, the inability to assimilate or integrate Intellibot's technology into our platform; unanticipated expenses related to Intellibot's acquired technology; potential adverse tax consequences; disruption to our business and diversion of management attention and other resources; potential unknown liabilities associated with Intellibot's business; unexpected delays and difficulties in opening and maintaining the data centers; changes in the competitive or regulatory landscape in India; and uncertainty whether sales will justify these investments. Further information on factors that could affect our financial and other results is included in the filings we make with the Securities and Exchange Commission from time to time.

About ServiceNow

ServiceNow (NYSE: NOW) is making the world of work, work better for people. Our cloud-based platform and solutions deliver digital workflows that create great experiences and unlock productivity for employees and the enterprise. For more information, visit: http://www.servicenow.com.

2021 ServiceNow, Inc. All rights reserved. ServiceNow, the ServiceNow logo, Now, and other ServiceNow marks are trademarks and/or registered trademarks of ServiceNow, Inc. in the United States and/or other countries. Other company names, product names, and logos may be trademarks of the respective companies with which they are associated.

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ServiceNow to Acquire Intellibot to Help Businesses Automate Any Workflow - Business Wire

With its stock down 9.9% over the past week, it is easy to disregard Brooks Automation (NASDAQ:BRKS). But if you pay close attention, you might find that its key financial indicators look quite decent, which could mean that the stock could potentially rise in the long-term given how markets usually reward more resilient long-term fundamentals. In this article, we decided to focus on Brooks Automation's ROE.

Return on equity or ROE is a key measure used to assess how efficiently a company's management is utilizing the company's capital. Simply put, it is used to assess the profitability of a company in relation to its equity capital.

Check out our latest analysis for Brooks Automation

ROE can be calculated by using the formula:

Return on Equity = Net Profit (from continuing operations) Shareholders' Equity

So, based on the above formula, the ROE for Brooks Automation is:

6.3% = US$79m US$1.3b (Based on the trailing twelve months to December 2020).

The 'return' is the amount earned after tax over the last twelve months. One way to conceptualize this is that for each $1 of shareholders' capital it has, the company made $0.06 in profit.

Thus far, we have learned that ROE measures how efficiently a company is generating its profits. We now need to evaluate how much profit the company reinvests or "retains" for future growth which then gives us an idea about the growth potential of the company. Generally speaking, other things being equal, firms with a high return on equity and profit retention, have a higher growth rate than firms that dont share these attributes.

When you first look at it, Brooks Automation's ROE doesn't look that attractive. A quick further study shows that the company's ROE doesn't compare favorably to the industry average of 12% either. In spite of this, Brooks Automation was able to grow its net income considerably, at a rate of 47% in the last five years. We reckon that there could be other factors at play here. For example, it is possible that the company's management has made some good strategic decisions, or that the company has a low payout ratio.

Story continues

We then compared Brooks Automation's net income growth with the industry and we're pleased to see that the company's growth figure is higher when compared with the industry which has a growth rate of 14% in the same period.

past-earnings-growth

Earnings growth is a huge factor in stock valuation. The investor should try to establish if the expected growth or decline in earnings, whichever the case may be, is priced in. This then helps them determine if the stock is placed for a bright or bleak future. If you're wondering about Brooks Automation's's valuation, check out this gauge of its price-to-earnings ratio, as compared to its industry.

Brooks Automation's significant three-year median payout ratio of 71% (where it is retaining only 29% of its income) suggests that the company has been able to achieve a high growth in earnings despite returning most of its income to shareholders.

Besides, Brooks Automation has been paying dividends for at least ten years or more. This shows that the company is committed to sharing profits with its shareholders. Upon studying the latest analysts' consensus data, we found that the company's future payout ratio is expected to drop to 32% over the next three years. As a result, the expected drop in Brooks Automation's payout ratio explains the anticipated rise in the company's future ROE to 10%, over the same period.

Overall, we feel that Brooks Automation certainly does have some positive factors to consider. That is, quite an impressive growth in earnings. However, the low profit retention means that the company's earnings growth could have been higher, had it been reinvesting a higher portion of its profits. That being so, a study of the latest analyst forecasts show that the company is expected to see a slowdown in its future earnings growth. To know more about the latest analysts predictions for the company, check out this visualization of analyst forecasts for the company.

This article by Simply Wall St is general in nature. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.

Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team (at) simplywallst.com.

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Should Weakness in Brooks Automation, Inc.'s (NASDAQ:BRKS) Stock Be Seen As A Sign That Market Will Correct The Share Price Given Decent Financials? -...

For the past decade, schools have placed significant emphasis on getting students ready for careers. The problem is that its not clear what kind of jobs will be available in ten or 20 years. So what should that mean for K-12 teaching?

Daniel Susskind, a fellow in economics at Oxford University, tackled that questionand many othersin his recent book, A World Without Work: Technology, Automation, and How We Should Respond. In it, he describes a possible future where liberal arts education would take on increasing importance as people look for meaningful ways to spend their time in a world where machines take on many of the tasks humans do today.

Education Week caught up with Susskind on Zoom for his thoughts on where the world of work is headed. This transcript has been edited for brevity and clarity.

What do you expect the world of work to look like when todays 2nd graders are entering it?

Every day, we hear stories of systems and machines that are taking on tasks and activities that until recently we thought only human beings alone could ever do. Making medical diagnoses and driving cars. Drafting legal contracts and designing buildings. Writing news reports and composing music. What does this mean, not only for the vast majority of us at the moment whose job is our main, if not our only, source of income, but for also all those young people out there who are looking ahead to the future of work? Its important to be clear [that if readers] pick up the book expecting an account of some big technological bang after which theres no work left for human beings to do, the robots have taken all the jobs, theyre going to be bitterly disappointed. Work is going to remain for some time to come.

The argument Im making is a slightly different one, which is that as we move through the 21st century, because of these technological advances, more people might find themselves unable to make the sorts of economic contributions to society that they might have hoped, or indeed, expected to make in the 20th century.

So it sounds like we dont really know what the world of work is going to look like for todays 2nd graders, but machines will probably replace many jobs, or at least a lot of the tasks.

Technologies dont destroy entire jobs in an instant. If you were to ask me what jobs you think are most at risk of automation, I am reluctant to give you a list because that isnt what technology does. What it does is, in a far more bottom-up, gradual way, it displaces people from particular tasks and activities, but it can also make some tasks and activities more valuable and more important for human beings to do.

Theres a sense that what technology does is it takes on the boring stuff and leaves us human beings with the interesting stuff. But, actually, thats not right. And just one example, if you look at many of the tasks and activities that are currently hardest to automate, many of them involve some kind of interpersonal interaction and as a result, many are found in pretty low-paid service roles. Retail assistants. Waitresses. Baristas. Receptionists. Security-guards and so on. So theres not always as comfortable a correlation between how fulfilling we find those tasks and how readily they can be automated. And yet sometimes thats how its talked about.

In your book, you note that policymakers, including former President Barack Obama, called for more people to attain post-secondary education in order to compete with machines. Do you agree that this is our best response at the moment to the idea of technological unemployment?

Its useful to distinguish between two very different worries we might have about the future of work. One is the dramatic one that you often read about in popular commentary, which is where there just arent enough jobs to be done, full stop. And that I call structural technological unemployment.

Theres also another type of technological unemployment, where people dont necessarily have the skills and the capabilities to do [available] jobs. Theres a skills mismatch. Education responds to one of the main frictions in the labor market, which is that people just might not have the right skills and capabilities to do the work that needs to be done.

Another reason that people might not want to be able to do the work that has to be done is place mismatch. People just dont live in the same geographical place that work is being created. [Thats] particularly important for blue collar roles, rather than white collar roles. Many blue collar workers rely on being in a particular place and for that place to be succeeding economically and creating the kind of opportunities that will lead to you finding employment. Its not obvious how more education necessarily engages with that place mismatch.

And then the sort of final mismatch is what I call the identity mismatch. People very often have a very particular conception of themselves and they might be willing to stay unemployed in order to protect the identity. And a good example of this is if you think of men of working age in the United States displaced from traditional manufacturing roles by new technologies. There are some who would say they would rather not work at all than take up so-called pink collar work. Many of the jobs that are hardest to automate and where theres a lot of job growth are disproportionately done by women, whether its social care, whether its nursing, whether its pre-school and kindergarten teaching. So, there is an issue of identity there. There is work available but for various reasons these men dont want to do it. Its not obvious to me how education, traditionally understood, engages with these identity mismatches between your perception of yourself and the work thats available to be done.

Theres also just the more general problem, which is that if we look deeper into the 21st century, and we think its true that the problem might not be that theres enough jobs and people cant do them, but just there arent enough jobs full stop for various reasons. If we take that seriously, then again, its not clear to me that more education is necessarily the best response to that challenge.

But I dont think thats the challenge we currently face. So for now, the challenge is frictional technological unemployment and I think the main source of it is skills mismatch and thats why education is still, to my mind, so important.

If you were advising a high-schooler on the future job market, what careers are fields are a relatively safe bet to escape automation?

Very broadly, theres two strategies. Either you want to become the sort of person who can compete with these systems and machines, who can do the sort of things they cannot do yet. Clearly, there are large domains of human activity that remain out of reach of even the most capable machines. Interpersonal faculties. Creative faculties. Problem-solving faculties. Communication faculties. Even though machines are indeed making inroads on each of these things, by and large, if you look at the labor market, jobs that involve those sorts of faculties are among the hardest to automate.

The second strategy is that instead you become the sort of person who can build these systems and machines, who is capable of designing and operating and understanding how these systems and machines work.

Were not taking seriously enough the challenge of either teaching people to compete or teaching people to build.

You write that schools need to stop teaching algebra in ways that apps like Socrates can do kids homework for them. Can you elaborate what you mean by that?

[With some apps], you can take a photo of quite complex math problems and it will scan it, use character recognition technology, and it just gives you an answer. And it just strikes me that in a world where these sorts of technologies are increasingly available, that ought to be an implication for how we teach math. We shouldnt be teaching math in a way that people can be able to just take a photo of a question and come up with an answer and thats it. We should be pushing math instruction in a way that takes advantage of these technologies, in much the same way that the calculator revolution did the same for the way in which we taught math a few decades ago.

Its not, lets stop teaching math. Its how can we use these technologies to teach math in a different and more useful way, given where the technologies are.

In your book, you are enthusiastic about the potential of technology to personalize learning for students. You write that teaching to the middle ability level is essentially, teaching to no one. But theres still a lot of skepticism among educators about personalized learning. They feel like it overemphasizes technology. They dont necessarily feel like their students are doing any better than they were before using personalized learning approaches. Given that skepticism, why are you a fan?

Im a fan for two big reasons. We know that an average student who receives one-to-one instruction from a human being is going to outperform about 98 percent of ordinary students in a traditional classroom. So we know that one-to-one instruction with a human being is incredibly effective. But of course one-to-one instruction, with a human being, is not affordable or scalable. So what do we do? Well, this is the promise of these technologies, they offer us a glimpse of how we might replicate that one-to-one interaction in a way that is scalable. That promise is what makes me excited.

The technologies we have today are the worst they are ever going to be. Ive seen [problems] that reflect the skepticism that youre describing. But for me, thats not a reason to stop, its a reason to continue to iterate and experiment and try and settle on a model or technology that does better than what we currently have.

Near the end of the book, you argue that we may return to a liberal arts education, to make sure people can still lead meaningful lives. But right now, schools are focusing much more on STEM than the humanities. When and how should a greater emphasis on a more liberal arts education occur?

I suppose I want to avoid there being a discreet switch. I think both of these strategies are going to become increasingly important. In my view, the challenge should be focused more on how can we avoid teaching young people to do all the routine activities that machines already do. I wouldnt want to rule out either of those strategies, in part because there is a huge amount of uncertainty about what skills and abilities are going to be valuable and important.

If you take seriously the idea that we might be approaching a world with less work for people to do, full stop, if you think that that might be a challenge for the 21st century, then there is a kind of bigger challenge for education in thinking whats the purpose of education? At the moment, in large part, its preparing people with the skills and capabilities so they can flourish in the working world. In a world in which there may be less work for people to do, how does an education system prepare people to flourish in that world instead. That, to me, is one of the big and under explored questions.

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What's the Purpose of K-12 Education in the Age of Automation? - Education Week