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How machine learning and artificial intelligence are changing RPA’s Landscape

Robotic Process Automation (RPA) is a technology that allows software robots to automate repetitive and rule-based tasks, such as data entry, processing transactions, and generating reports. The integration of ML and AI with RPA has taken the industry by storm. This dynamic combination is revolutionizing the way businesses operate, making processes faster and more efficient than ever before. ML & AI are being used in RPA to streamline processes to reduce costs, increase productivity, enhance RPA’s capabilities, and enable it to perform more complex tasks.

There are diverse types of RPA solutions available on the market, each with its own unique capabilities. Below are some of the most popular RPA solutions and their capabilities:

 

  • Automation Anywhere: Offers both web-based and desktop-based bots. Capabilities include screen scraping, data manipulation, file transfer, workflow automation, etc.
  • Blue Prism: Provides desktop-based bots that can be deployed on-premises or in the cloud. Capabilities include process mining, exception handling, automatic documentation generation, etc.
  • UiPath: Offers both web-based and desktop-based bots. Capabilities include image recognition, natural language processing (NLP), process mining, etc.

 

How machine learning and artificial intelligence are boosting RPA

 

The use of ML and AI is helping to boost the capabilities of RPA, with both technologies working together to automate a wide range of processes. ML is being used to develop bots that can understand and respond to human interaction, making them more natural and efficient communicators. This is particularly useful in customer service applications, where bots can handle large volumes of inquiries without getting overwhelmed.

AI, on the other hand, is being used to create bots that can think for themselves and make decisions on their own. This is proving invaluable in more complex processes where humans may struggle to keep up with the pace. AI-powered bots can identify patterns and exceptions, meaning they can often solve problems faster and more effectively than their human counterparts.

With ML and AI capabilities, RPA bots can make more intelligent decisions based on data analysis, predictive analytics, and other advanced techniques. This can enable them to handle more complex tasks and make better recommendations. ML and AI can also help RPA bots to scale more effectively. This is particularly useful in high-volume environments where there is a need for rapid processing and analysis.

How to get started with machine learning and artificial intelligence in your RPA process

 

Machine learning and artificial intelligence are increasingly becoming essential components of RPA, enabling robots to learn from their mistakes and become more efficient as they process data. If you’re looking to get started with machine learning and artificial intelligence in your RPA process, there are a few things you need to do.

First, you need to identify what tasks in your process can be automated using ML & AI. You must also define the business problem you want to solve using ML and AI in your RPA process. This could be a task that requires more intelligence and decision-making than your current RPA bots can handle. Once you’ve identified those tasks, you need to find the right software solution that can help you automate them.

 

Also, to use ML and AI in your RPA process, you will need data to train your algorithms. Identify the data you need and where you can obtain it. There are many different ML algorithms to choose from, so choose the one that best suits your identified business problem and data. Use that data to train your ML algorithm. This involves feeding your algorithm with labeled data to help it learn and make predictions. Once your ML algorithm is trained, integrate it into your RPA process. This involves connecting your ML algorithm to your RPA bots and using it to automate more complex tasks.

Finally, you need to implement the automation solution and monitor its performance over time and refine it as necessary. ML and AI can help you automate more complex tasks if you continuously evaluate your RPA process and look for opportunities to improve efficiency, accuracy, and productivity. By following these steps, you can ensure that ML and AI will play a positive role in your RPA process.

 

Below are some examples of how ML & AI can be used in RPA:

  • Natural Language Processing: NLP is used to extract and process data from unstructured text, such as emails and chat logs. RPA bots can use NLP to understand the intent of a user’s message and take appropriate actions based on the context.
  • Computer Vision: Computer vision can be used to enable RPA bots to read and interpret images, such as screenshots of a user interface or a scanned document. This can be useful in automating tasks such as data entry and document processing.
  • Predictive Analytics: ML algorithms can be used to analyze data and identify patterns that can help RPA bots make predictions and decisions. For example, an RPA bot could use predictive analytics to identify customers who are likely to churn and take proactive measures to retain them.
  • Reinforcement Learning: Reinforcement learning can be used to train RPA bots to learn from their actions and improve their performance over time. This can be useful in tasks such as fraud detection, where the bot can learn from its mistakes and improve its accuracy over time.

 

With these examples in mind, it is clear that machine learning and AI will continue to play a key role in driving further innovation in the world of RPA. Remember that implementing ML and AI in your RPA process requires a solid understanding of both technologies. If you do not have the necessary skills in-house, consider contacting us to ensure that you will get the most out of your investment.

Hyper-Automation: How to achieve tactical and strategic goals by automating business processes

Hyper Automation How to achieve tactical and strategic goals by automating business processes

 

When it comes to digitization processes in companies, hyper-automation is mentioned more and more often. Zion Market Research forecasted Hyperautomation Market  is expected to grow annually at a CAGR of around 23.5 % (2022-2028), it’s was valued at approximately USD 9billion in 2021 and is projected to reach roughly USD 26.5 billion by 2028. It’s one of the big digitization buzzwords, which has come into focus not least because of Gartner’s positioning as one of the top tech trends of 2022.

 

According to the market research company Gartner hyper-automation is the combination of different approaches and technologies in order to get the maximum degree of efficiency out of digital possibilities, by automating automate as many business and IT processes as possible and create end-to-end workflows.

 

Contrary to the pure Robotic Process Automation (RPA), not only individual tasks but also complex processes can also be automated. Hyper-automation cannot be achieved without RPA, artificial intelligence (AI) and machine learning (ML). It all sounds super interesting but how can companies successfully implement this “hyper-automation”?

 

The first step requires a detailed mapping or analysis of the organization and back office processes to fully understand the existing workflows and identify where gaps, latencies and bottlenecks exist. On this basis, a strategy can then be developed to build bridges between the solutions and close efficiency gaps.

 

The next step consist of a wise selection between the different. Given the versatile requirements and complexity of many business processes, a well-orchestrated combination of different technologies is often required. A combination of artificial intelligence and machine learning to workflow tools, business process management (BPM) and robotic process automation (RPA) to low and no-code tools must be foreseen for the use of different application scenarios and problems. By linking previously mentioned technologies, the mapping of complex, cross-departmental and cross-functional workflows can be a piece of cake.

In practice, it’s equal to using process mining tools to better understand business operations & workflows, ML module to verify compliance and decision software to automate maximum tasks.

 

As companies are not only looking towards achieving early ROI but also focusing on optimizing processes, the vendor selection must be prioritized. The providers of different solutions are as diverse as the technologies. The objective must be to ensure that their solutions are easy and rapidly scalable. The cost of integration a technology is comparatively less than that of hiring and training a human. Therefore, organizations need to ensure the selected vendor offers solutions that can easily be integrated and configured in their existing infrastructure. Because every business is different, and there is no such thing as a one-size-fits-all way of doing business.

 

Before you start establishing hyper-automation in your company, you should communicate your automation initiative transparently right from the start and involve employees in the planning and implementation process. They must know how the hyper-automation is going to affect their jobs. Because you may see all the benefits, but your employees might see them differently. They may see a machine replacing them and their work. They must understand that automation increases overall productivity, lessen workload, offers the opportunity for professional growth, and can become a promoter for high-performing and efficient teams.

 

Organizations that want to stay competitive in the long term, must use suitable automation technologies in line with the speed and agility of digital transformation to reach the next business level.

How Hyper-automaton is changing the digital landscape?

In the past two years, the shift from the workplace to the home office has led to increasing demands for artificial intelligence (AI) and automation in our daily life. Hyperautomation is a term that keeps coming up while discussing digitalization processes in businesses. For some, this is simply a detailed kind of process optimization, whereas hyperautomation is the key for the long term success for others.

 

The term hyperautomation goes back to the market research company Gartner. It refers to a well-founded methodology and a disciplined approach that organizations use to automate as many business and IT processes as possible. This technique uses a variety of technologies to speed up the automation of complicated business processes; in essence, businesses are attempting to maximize the efficiency of available digital opportunities and advance their Process Excellence initiatives.

 

Hyperautomation-Enabling Software

Hyper-automation has gained popularity over the previous 18 months, which is not surprising. The industry has adopted a somewhat hopeful attitude toward the development in light of Gartner’s identification of hyper-automation as one of the main strategic technology trends and its prediction of significant progress in years to come.

 

It’s true that hyper-automation opens up many opportunities for companies, especially when it comes to process improvement initiatives, lower operational expenses, fewer mistakes, and better outcomes, such as higher customer satisfaction through tailored customer experiences. Although it may seem thrilling and promising, the implementation is always the most difficult part. Because hyperautomation only functions as a holistic approach, you need to develop a sustainable and long-term plan before you start implementing it in your business. Organizations must also deploy the effective automation tools & techniques that form the strong foundation of hyper-automation.

 

Organizations run the risk of failing on these initiatives if they don’t take essential and key steps to understand the potential of automation as well as its capacity to generate ROI through increased productivity and cost reductions. In order to automate at such a high degree, businesses must first digitize widely.

 

While hyper-automation remains a concept, technologies such as robotic processing automation (RPA) are being deployed to create more dynamic industrialization and promote seamless collaboration between humans and bots. Plus many pure RPA applications can be implemented as small islands in the company almost overnight. Because it enables businesses to enhance their workflows and use AI-based automation, RPA will continue to be a key instrument for the digitization.

For example, an RPA process discovery platform can be used to automatically identify work processes that are suitable for automation. “Automating automation” is an crucial step to achieve scalability, as only 8 percent of automation projects reach more than 50 bots. Hyper-automation at scale is impossible without RPA.

 

According to Forrester, return on investment (ROI) in the form of both cost and time savings is expected to boost the market for RPA software from $13.9 billion to $22 billion by 2025. “Hyperautomation has shifted from an option to a condition of survival”, says research vice president at Gartner. While advances in hyper-automation will no doubt continue to evolve, RPA will help leverage this technology—ultimately “to automate automation”—and support the longer-term goal of hyper-automation.

From RPA to Intelligent Automation

RPA Intelligent Automation

 

RPA – Robotic Process Automation is changing the way companies operate around the world. The global RPA market was worth $271 million in 2016, and in 2020 that number hit $2.5 billion, an enormous increase by any metric. By mimicking structured, repetitive, and rule-based processes and tasks that are carried out by employees, this innovative technology shows its strengths. This ability can be used in many business processes in various sectors. Along with the increasing spread of RPA, the integration of artificial intelligence (AI) into the corresponding RPA software offerings is also increasing. More and more processes can be automated and transformed. Intelligent automation promises more insights, financial benefits, customer experiences, and higher business value.

 

The two types of process automation: fully automated and partially automated

 

In robot-based process automation, a distinction is made between partially automated solutions on the one hand and fully automated solutions on the other. In general, the idea behind RPA is that the robots work through the processes independently so that there is as little human interaction as necessary.

 

  • Fully automated processes (unattended automation)

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With fully automated processes, the robot works completely independently without the need for human intervention or, depending on the scenario or context, only necessary in exceptional cases. The software robot carries out transaction-based activities and processes on a large scale fully automatically without human interaction, even if the employee is logged off from the system. This type of automation is often used for back-office systems when it comes to collecting, sorting, analyzing, and distributing large amounts of data to specific employees within an organization.

 

  • Partly automated processes (unattended automation)

With partial automation, the focus is on bot/human interaction in processes. In partially automated processes, the robot reacts like a digital assistant to the employee by taking on certain homogeneous tasks. His work is triggered by certain events, actions, or commands that an employee executes in a certain workflow. While full automation concentrates on independent processing with little human intervention, the idea behind partial automation is a cooperation with the employee, in which human actions are supported by smaller automated processes.

 

 

Intelligent automation for competitive business results

 

Leading RPA software providers are continuously working to make their solutions smarter. While conventional RPA technologies often require rule-based processes and therefore do not need to make decisions based on their own judgment, intelligent automation, a combination of AI and RPA, opens up completely new possibilities: Virtual robots or bots monitor transaction processing, take notes if necessary, draw conclusions and make predictions. You can even refine the process execution approach based on insights.

 

Many RPA vendors have invested heavily in developing native solutions in their workflow design modules for bots, and have partnered with other leading technology companies. In this way, they can offer numerous innovative functions for processes that can be automated using RPA – while increasing the potential for added value at the same time. For example, some existing manual processes require reading an email or a poorly scanned PDF document and performing certain actions based on the content – or inserting extracted data into a data visualization tool and predictive or prescriptive analysis. In such cases, the use of natural language processing, computer vision, intelligent optical character recognition, or even data analysis and visualization tools may be necessary. All of this is available through the leading intelligent RPA tools. Another application example: Intelligent automation detects anomalies by virtual robots reviewing large data sets of payments, invoices, medical records, or customer feedback and identifying outliers, patterns, or topics that ultimately influence decision-making.

 

Many executives are well aware of the benefits of intelligent automation and how it can be integrated into their business transformation. These intelligent systems can detect and produce vast amount of information and can automate entire processes or workflows while self-learning and adapting. Companies that are looking to implement an RPA program should think ahead and choose an RPA platform that offers cognitive capabilities, reusable elements, and comprehensive libraries that are compatible with multiple applications.

While some companies struggled with their investments in the past year, the COVID-19 pandemic has further increased the demand for strong RPA resources as part of the digitization of processes.
Companies moving from traditional RPA to intelligent automation implementations have normalized the optimization and standardization of processes and strengthened the collaboration between IT and business. Instead of concentrating on the automation of various routine tasks, an intelligent solution enables the use of bots for end-to-end business processes and the identification of automation candidates through task or process mining. In doing so, the appropriate solutions are able to understand the data read and improve their own performance over time.

 

RPA can accelerate digital transformation. However, the real future lies in intelligent automation. As RPA providers expand their native AI offerings and the integration of technology partnerships progresses, digital team members will be able to execute increasingly complex processes – which further increases the value of intelligent automation. Therefore, companies need to review all their options before implementing the right technology that can improve their overall operational efficiency and take their business performances to the next level.

 

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Hyper-automation: The Future of Digital Transformation

When it comes to digitization processes in companies, there is more and more talk of hyper-automation. But what is it actually? For some it is just a comprehensive form of process optimization; for others, hyper-automation is the future strategic technology that is not to be ignored.

“Hyperautomation has shifted from an option to a condition of survival,” said Fabrizio Biscotti, research vice president at Gartner. “Organizations will require more IT and business process automation as they are forced to accelerate digital transformation plans in a post-COVID-19, digital-first world.”

 

Hyperautomation The Future of Digital Transformation

 

What actually is hyper-automation?

The term hyper-automation goes back to the market research company Gartner. This means a well-founded methodology for achieving tactical and strategic goals through the automation of business processes. Thus, Hyperautomation considers the automation of business processes on a large scale by combining a wide range of coordinated digital technologies.

According to Gartner, hyper-automation focuses on two aspects of business operations: The first is to automate whatever can be automated within an organization. The second is to combine different approaches, tools, and technologies to automate only individual tasks (RPA) but also complex processes with the help of artificial intelligence (AI), virtual assistants, and machine learning (ML).

 

How does hyper-automation work?

Hyperautomation is able to unlock maximum potential by combining a number of technologies that support each other and automate complex processes with unstructured data and a significant level of ambiguity. By using AI, ML, NLP, process mining, and intelligent technologies, the ability to discover processes independently is enhanced, and RPA bots are enabled to do much more than just perform the previous repetitive tasks.

Basically, hyper-automation takes on another level of human work. It’s not only a tool but a unified enterprise strategy or initiative with the ultimate goal of creating and optimizing end-to-end processes to achieve an even higher degree of automation that supports innovative new business propositions.

Hyperautomation only works if bots ultimately also perform the tasks that a machine learning (AI) has identified. Advanced artificial intelligence can better analyze unstructured data and implant it in an efficient workflow. With RPA being the fundamental part of hyper-automation, intelligent bots continue to process the data in hyper-automation and ultimately ensure that the work is done.

 

Benefits of hyper-automation

As already described, hyper-automation enables automation that goes beyond simple, repetitive process sections. With hyper-automation, comprehensive automation can cover even complex processes. Reducing costs and maximizing profits, but also conserving resources and designing a smart working environment are also considered as main benefits. When used correctly, hyper-automation leads to a higher degree of automation and higher productivity in the company. A significant increase in customer satisfaction can also be achieved by integrating the personalized customer service. The side-by-side collaboration of man and machine is the ultimate goal of hyper-automation.

 

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Automation myths debunked: Why is Automation important for your business?

Hardly any company that strategically pursues their company growth can get around automation today. Automation enables tasks that were previously slow, manual, old-fashioned, and time-consuming to be supported with suitable software and thus run independently. As a human error can be unpredictable and happen when you least expect it, with the right technology companies’ processes are more accurate and faster. Use cases of automation are, for example, employee onboarding, analyzing reports on transactions, monitoring bookkeeping activities regularly, customer service, databases updates, sending personalized emails, perform inventory, etc.

Business processes automation can not only be used to gain efficiency. Availability of modern technology, as well as enhanced software applications, have made it easier to increase employee efficiency and you can get better results when you embrace automation. A win-win situation for companies and employees.

 

But despite these benefits, there are still myths surrounding automation that keep companies from getting started. Even though automated processes create positive changes, still, many companies fear high costs, difficult implementation, and staff changes – but these are just prejudices that we would like to address here and thus show that every company can benefit from automation.

 

Automation is a complicated and complex process

Hmmm, yeah. Not if it’s done right. As is often the case, good preparation is half the work. So, before starting with automation, make sure you understand what your company’s expectations are. Your decision to automate must depend on your needs, capacity to build it, and also your customers’ requirements. Specific goals can be developed using your personal business case. This step is essential so that automation succeeds and creates benefits for the company.

These requirements should also be discussed in-depth with different automation tool providers instead of falling for fancy advertising promises or the cheapest subscription. It is advised to meet with different process automation providers for not only choosing the right tool, but also to evaluate your own requirements.

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The future is automated

‍Automated processes bring a lot of advantages in operational processes, such as improved operational efficiency, long-term cost reduction, better customer service, visibility & transparency, and an increase in productivity. However, if a company only carries a small range of products, stores a manageable amount of goods, and generally only offers a small storage capacity, there is no need to implement a fully automated system. In such cases, manual or partially automated solutions that grow with you are the better options. Companies then have to weigh up whether small order quantities can be processed more efficiently in this way.

 

Automation is killing jobs

Nowadays it is constantly stated that automation is accompanied by a huge burden of unemployment. With the increased use of machines and automated processes, the fear of reducing or replacing staff increases. It’s true that automation is impacting various jobs in different sectors around the world. Due to automation, human intervention is certainly reduced in a business process. For instance, from production to planning, everything can be controlled by artificial intelligence or machine intelligence. It is easier to bring accuracy into the production process and increase overall productivity with machine intelligence. Every company wants to reduce the number of its employees as much as possible through technological improvements. But that does not mean that we are heading towards an unemployed society in years to come. As the machines are performing tasks previously done by humans, companies are busy transforming and redesigning jobs in a way that can make technological elements compatible with human capital development. The future workplace is where humans and machines will enhance each other’s strengths by working side by side.

 

Existing systems prevent the integration of new solutions

Automation doesn’t happen overnight – Companies are constantly faced with the challenge of proper integration of a set of services related to automation and ensuring that all expectations are aligned with business goals. Integrating your automation initiatives successfully is impossible without a flexible, scalable infrastructure. Therefore, on-premise infrastructure must be avoided/limited because of its limitation in terms of automation roll-out, scalability, and ease of use. For this purpose, cloud solutions are ideal as they let you get straight to work without wasting your valuable time on on-premise setup and maintenance.

 

So, now that you know that automation is here to stay, and can help you better run your business, it’s a safe bet that such automation can be trusted and utilized. By taking into account the myths discussed in this article, and learning the truth about each, you’ll be able to run your business more effectively.

IT automation – Top Technology trends to look for Business Transformation

IT automation is one of the biggest IT trend terms in recent years. This involves a wide variety of solutions that give IT specialists more freedom in their day-to-day business. “IT automation is certainly a worthwhile goal because it saves a lot of money through lower personnel costs” – Tony Iams, Managing Vice President at Gartner. Yet IT teams in small and medium-sized companies often struggle with budget constraints and a shortage of skilled workers. When the demand for IT services increases, they are therefore heavily overloaded and look for ways to increase efficiency.

The 2020 IT Operations & Strategic Priorities for IT Executives report from Kaseya shows that IT automation is a critical need for SBMs, 60% of IT executives worldwide plan to invest in IT automation in 2021. IT automation is their primary strategy for doing more with less. With IT automation being a top priority for businesses today, IT teams are now applying it to a wider range of business and IT functions. Here below technologies are particularly efficient:

IT Automation Technologies for Business Transformation

 

Robotic Process Automation (RPA)

Robotic process automation (RPA) is changing the way companies operate around the world. It is well known that with Robotic Process Automation (RPA) you can optimize many processes and save time and money. An immense number of processes are still carried out manually in companies and authorities, although this is actually not necessary. RPA tools use software bots that simulate human-computer interaction to automate routine tasks. RPA is rapidly growing thanks to the benefits it has to offer such as lower labour costs and less human error. RPA bots usually do not require any software customization or deep system integration. According to Gartner, global RPA software revenue is projected to reach $ 1.89 billion in 2021, up 19.5% from 2020. It goes without a doubt that RPA is accelerating digital transformation.

 

Implementation of RPA

Despite the numerous advantages this technology has to offer, most businesses struggle with successful RPA implementation. The use of Robotic Process Automation (RPA) promises a high increase in process efficiency but also brings huge implementation challenges if it’s not seen as a central building block on the way to hyper-automation but just another technology. According to a study by Deloitte, many companies have found that scaling RPA is more difficult than expected. Larger RPA implementations, when the number of bots is more than 50, often take longer and are more complex and costly than companies originally expected. Particularly when introducing Robotic Process Automation, attention must be paid to a strong strategy, right expertise, and communication with employees for the realistic expectations of Robotic Process Automation, because the software robot should automate entire processes or at least make work easier through partial automation. A lack of acceptance makes the implementation of corresponding RPA projects more difficult and leads to distrust and displeasure among employees. Rather, if the employees actively participate in the development of the robot, particularities in the processing of the process can be emphasized. Positive communication also creates trust and motivates the workforce to contribute their own ideas.

 

Predictive analysis

As the name suggests predictive analysis techniques include machine learning, data mining, and predictive statistical modelling to use historical data from various operational sources to predict the likelihood of future events. It’s an emerging technology that is helping companies acquire and retain their most profitable customers and grow the customer base to improve operations. They also help companies predict future customer needs, business needs, human resource requirements, and process improvements that they should make to their operations. It’s being used by multiple companies to improve the efficiency of production and operations, reduce risk and fraud, and create better customer experiences by mapping the likely journey of customers and the expected touchpoints. It can also improve the accuracy of supply chain management, and help organizations create marketing plans with more precision, knowledge and confidence. This technology is also helping IT security experts to identify potential vulnerabilities, determine the likelihood of cyber-attacks and work on improving the company’s security structure.

 

Artificial Intelligence (AI)

AI refers to the ability of a machine to display human-like capabilities such as reasoning, problem solving, learning, planning and creativity. By using machines are programmed to think like humans and mimic their actions. The AI ​​system is fed by sensors in machines, ERP systems, customer relationship management systems and even Internet data. Alexa, Siri, Cortana – the chatbots from Amazon, Apple and Microsoft are examples of how artificial intelligence makes the interaction between humans and computers easier and more efficient. Business software manufacturers are increasingly using intelligent algorithms to make life easier for their employees and customers.

 

Hyper automation

Basically, the term hyper-automation covers the combination of different technologies. From a global perspective, the focus is still on the automation of simple and complex tasks, but the combination of different technologies such as PRA, ML, and IBPMS ensures more efficient processes. In addition, there is no need for human action. Hyper-automation contributes to higher productivity in the company. According to Gartner’s, List of Top Strategic Technology Trends for 2021 – Hyper automation is a key trend that digital strategy teams should consider.

 

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HR Process Management : Why should you invest in HR Automation?

What Is RPA and Digital Labor?

The global robotic process automation (RPA) market size was valued at USD 1.57 billion in 2020 and is expected to grow at a compound annual growth rate (CAGR) of 32.8% from 2021 to 2028. Different organizations in different sectors are increasingly challenged by the growing market competition due to the shift in technology and changing consumer preferences. Additionally, the shift in company business operations due to the pandemic is expected to favor market growth over the forecast period.

 

All these challenges in today’s professional life mean one thing: constant movement. This means today’s organizations are required to comply with complex administrative procedures. One major challenge is the requirement to regularly track and manage hundreds of Human Resource (HR) onboarding and offboarding.

Robotic Process Automation is a process automation technology that allows businesses and organizations to configure software Robots to carry out routine, rules-based computer tasks in a way similar to a human employee. Robots can fill out documents, read and send emails, enter data into business applications, and much more. The ideal RPA solution uses AI and ML to automate a vast range of high-volume and repetitive tasks that previously required humans to perform. Also, the top-ranking RPA technologies also incorporate a variety of AI components to facilitate the Robot carrying out human tasks.In performing robotic process automation, many think of the RPA software robot as the “arms and legs,” and the AI components as the “brain.”Analysts from McKinsey & Company have called RPA technology a “third arm” for HR organizations as it works with HR to amplify the department’s capacities.

 

HR Automation is multi-functional and can lead to many different benefits. Some benefits include Higher productivity due to faster processing times and information sharing. Reduced storage, printing, and courier costs associated with paper-based work environments. Reduced risk of non-compliance penalties. Fewer data entry errors and lost or misplaced files associated with manual processes. Better support of organizational growth through efficient hiring and leaner operational costs. Better collaboration with executives to recruit, train and retain top talent.  More time to analyze HR data to make intelligent business decisions.

 

Before automation the Human Resource Management System (HRMS), was comprised of 1 to 10 employees, depending on the organization’s size, manually sorting and filing thousands of forms with hundreds of variations. In addition, they performed different validations in order to enter information into the HRMS. The manual tracking, management, and data entry approach was slow, confusing, and characterized by high error rates. To avoid these mistakes and benefit from the shift to automation, progressive HR teams are applying RPA to help tasks like data management and validation; running, formatting, and distributing reports; and replacing manual and spreadsheet-based tasks. Companies have automated payroll updates, sick leave certification, and employee onboarding / offboarding. Some are also exploring more advanced cognitive automation technologies, like machine learning and natural language processing, to enhance a range of HR processes from talent acquisition to benefits administration and beyond. The results of the RPA deployments studied have shown a significant decrease in process time, a major reduction in errors, and a high potential for scalability.

 

Organizations looking to get started typically ask, “Where should I start? or “Which vendor should I choose?” To help inform and steer these decisions, here below are few tips for onboarding and offboarding automation.

 

    • Redefine what digital means to the enterprise: Automated onboarding and offboarding require sensitivity from everyone involved to change management processes. As an IT department, involve your colleagues from HR and all application managers from the very beginning. Only in this way automated processes can be integrated smoothly in a larger organization. Only when your colleagues fully accept the new processes do they support them effectively. The future workforce will soon be populated with both human workers and digital workers. HR must prepare the workforce for a future where people and robots will work together.

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    • Train Staff: Switching from a manual to an automated HR process requires a significant change in employee behavior, but thorough and engaging training can help facilitate the transition.

 

    • Appoint a Chief Digital Officer or equivalent: Identifying a project owner and project champion is the next critical step toward successful HR automation. While the project owner handles daily operations, the project champion shares the vision of automation with stakeholders and gathers support.

 

    • Setting up clear processes: The transition from manually controlled to automated processes involves both technical and cultural change. Therefore, well-defined, documented processes on how to initiate delivery of HR services through an identity management solution are highly recommended. This phase will certainly take some time. However, it is indispensable for successfully implementing automation based on coordinated processes.

 

    • Build and optimize agile delivery: Build a development environment for all critical applications. In this way, you will be able to develop new automated processes step by step. Such a development environment offers rapid testing and continuous improvement.

 

    • Focus on platform capabilities and include Security Issues: Cyber ​​threats are driving IT and security teams to work more closely together. Integrate identity management with access control systems. Ensure control over privileged accounts and be able to quickly adjust access privileges in case of onboarding – offboarding.

 

    • Acting fast: A close cooperation between IT and security also allows the rapid withdrawal of rights when an employee leaves. With automatic access control, IT is immediately able to revoke access once an employee has quit. With a real-time dashboard as part of an identity management solution, IT and security teams can instantly see who leaves the company and when. Automatically created permissions can also be quickly revoked using automation.

 

 

A changing landscape means HR must frequently adapt better strategies and seek out better processes and tools to deliver high performance. In today’s changing era, if HR departments still rely on manual, paper-based processes will be left behind if they won’t re-examine their infrastructures and won’t adapt automation technology in order to benefit from better productivity, cost containment, and compliance, awareness of employee and candidate.

As they begin to identify opportunities for HR automation, they must not forget that HR will always be about the people, and automation technology should serve those people, not replace them. As such, not every single aspect of HR can or should be automated; rather, automation should help HR professionals find and retain more talented individuals, collaborate with the organization, and spend more time evaluating their workforce.

 

Source :

–      Robotic Process Automation (RPA) Market Size, Share & Trends Analysis Report By Type (Software, Services), By Application (BFSI, Retail), By Organization, By Services, By Region, And Segment Forecasts, 2021 – 2028

–      Robotics and cognitive automation in HR Insights for action 

–      Artificial Intelligence in HR: a No-brainer 

–      Robotic Process Automation (RPA) On Entering an Age of Automation of White-collar Work Through Advances in AI and Robotics

2021: IPA- RPA & AI a Perfect Combination for your Organization

2021 IPA- RPA & AI a Perfect Combination for your Organization

 

Robotic Process Automation (RPA) is one of the most popular technologies for automating business processes. In recent years, many companies have decided and introduced RPA to drive process optimization and enabled fast and, above all, efficient automation of their standardized processes. In 2021 the trend towards RPA will not stop, because excellent results are possible with little effort. According to a Gartner forecast, the “global Robotic Process Automation (RPA) software revenue is projected to reach $1.89 billion in 2021, an increase of 19.5% from 2020.

 

A great advantage of RPA is that it does not require deep integration into different systems, but works via the existing user or desktop interfaces of the respective applications. Also known as the bridging technology, RPA supports the automation of numerous processes and thus lower costs without having to change or replace existing applications. RPA is used, among other things, for repeated data entry functions as well as for downloads and uploads in the Enterprise Resource Planning (ERP) area.

 

The key driver for RPA projects is their ability to improve and accelerate work process quality. Mimicking rule-based human actions, RPA automates all repetitive manual processes by lowering cost and time while improving quality. However, in this technology, the range of applications is limited by the need for structured data and programmable decision-making. Unstructured data is the main reason why technology is reaching its economic and technical limits. Thus, it becomes more difficult for many companies to find suitable processes for automation with (RPA) after a certain period of use. But this shortcoming can be overcome through the use of artificial intelligence as Intelligent Automation enables companies to take their existing automation strategies to a new level.

 

In the following, we will show you how artificial intelligence can help RPA bots to become smarter.

 

RPA and AI are two key technologies on the way to the intelligent automation of processes. Both technologies complement each other perfectly due to their different focus, so that from the user’s point of view they merge into an intelligent automation (IA).

As mentioned above, RPA need structured data as input, from different sources. It’s one of the biggest limitations of RPA. This means that the data must first be viewed, validated, and put into a structured form. If the input data is unstructured / semi-structured, artificial intelligence can be used to convert the data for the robots into a structured converted format.

 

Where RPA is weak, AI takes over. AI does all the initial work before data is transferred to the RPA. By using natural language processing, AI, extract the relevant data from the available text, even if the text is written in freeform language or if the information in a form looks or is distributed completely different each time. With semi-structured data, the AI ​​is able to extract the data from a document, even if this data is stored in different places on the form, in a different format or only appears occasionally. For example, on the invoices, the date could appear one time in the top right corner and another time in the top left. The invoice may or may not include a VAT rate, etc.

 

Once trained, the AI ​​is able to cope with this high variability with a high degree of confidence. If it doesn’t know how to process the file on its own, then the AI ​​can assign the task to a human who can answer the question, and the AI ​​, in turn, will learn from this interaction so that it can do its job better in the future.

 

The second limitation for RPA is that it cannot make complex decisions. RPA bots cannot make decisions based on their gut feeling. They need a clear set of rules according to which they operate. Some decisions are relatively straightforward and can certainly be handled by RPA, especially when it comes to applying rule-based scores to a small number of specific criteria. But if the required judgment is more complex, then another type of AI commonly referred to as “cognitive reasoning”, can be used to aid and improve the RPA process.

“Cognitive reasoning” programs work by mapping all knowledge, such as facts and experience that an expert has about a process in a model. This model, a kind of knowledge map, can then be queried by other people or by robots in order to make a decision or draw a conclusion.

 

As we’ve seen, RPA can provide some significant benefits on its own, but the real magic doesn’t come into play until the two work together. AI opens up many more processes for Robotic Process Automation and enables a much larger range of processes to be automated, even when complex and well-thought-out decisions have to be made. Everything is positive about this collaboration between RPA and AI: Investing in RPA is absolutely worthwhile. Existing system landscapes can be retained. AI intervenes flexibly and only where processes can be further improved in a targeted manner. A perfect combination of a leading company!

 

 

Sources

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Business Process Automation Trends 2021

As 2020 is slowly drawing to a close, it is time to discuss future trends in (industrial) automation that are likely to have a significant impact in 2021. Based on the current facts, conclusions can be drawn that artificial intelligence and automation will bring steady innovation for companies of all sizes and from all sectors. During 2020, automation technologies have experienced a substantial boom especially due to the covid19 pandemic. Industrial and manufacturing operations have been massively evolved with the integration of machine learning and robotics. In fact, companies and industries are no longer fully dependent on a human workforce for simple, complex, manual, and repetitive tasks. They are gaining a competitive advantage with digitalization and IoT.

Here below are the top emerging trends to watch in automation for upcoming years:

 

  • RPA and business workflows

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RPA isn’t new, many companies use this technology to automate their routine tasks. RPA as an industry is growing exponentially– the global robotic process automation market size is expected to reach USD 10.7 billion by 2027, expanding at a CAGR of 33.6% from 2020 to 2027 – Grand View Research. RPA used in the automation of manual and low-value repetitive tasks, such as data entry (order, invoice, etc), looking up information in databases, typing in updates, prepare a template, run and download reports, read and reply email, send emails to follow up with customers, etc. is passed. During the pandemic, organizations realized their technological backwardness and the risks associated with a further delay in digitization.

In 2021 everything will revolve around business workflows. The call for digital transformation is growing and ensuring streamlined, smooth processes that delight both customers and employees. To achieve this, companies are increasingly targeting intelligent RPA solutions. Because many processes in companies are still only partially automated – if at all. It will therefore be about making RPA technology even better usable in the future. With the integration of Cognitive RPA along with other intelligent components, business processes that require human reasoning or decision-making can be automated.  A robot cannot, therefore, decide on its own to add a new dimension to the process that has not been precisely defined before. This is the only way to automate business-critical workflows end-to-end, for example.

 

  • Automation and Cyber-Threat

In order to protect against automated modern cyberattacks, organizations will be incorporating automation into cybersecurity efforts. Automation plays an important role in defense against threats. Modern automatisms will increasingly develop their effect in the fight against the threat by reducing the volume of threats and allowing faster prevention of new and previously unknown threats.

If implemented appropriately, providers of cloud platforms can take action against cybercriminal groups that use trusted services for malicious attacks. In the past, it has been observed how legitimate websites – for example, Microsoft365 or Google Drive – have been imitated in order to steal data entered by unsuspecting victims. With the right tools and validation technologies, automation can aid in the prevention of successful cyberattacks and track down such fake login pages – with the aim of counteracting the risk.

 

  • Digital employees

As the ongoing global pandemic, has triggered an acceleration of a digital working environment, business leaders are learning lessons to apply to their futuristic organizations. Remote work is here to stay; thus, many organizations were forced to tap into their technologies and pushed creative ways of leveraging them to ensure business continuity. Businesses around the globe are exploring how they can implement and strengthen their digital strategies and unleash the true power of Technology – not just from a technology and environment perspective but from leadership, change management, and career-growth perspectives, as well. Companies are preparing themselves for the hybrid future or work by investing heavily in the tools needed to work remotely and prioritizing tech and digital infrastructure investments that support sustainable remote/hybrid work.

While no one knows exactly what the future holds for us, according to Forrester, companies are investing a lot in an “anywhere-plus-office hybrid” model in which more people will work outside the office more of the time. Therefore, it’s certain that remote working will play a major role in how the workplace will evolve in the coming years and will continue changing the way we work.

 

Sources:

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