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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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Smart companies: Tips for a smooth integration of AI

AI (Artificial Intelligence) has a long history of being considered science fiction but opens up enormous potential for companies in terms of productivity, the efficiency of business processes, gain sustainable competitive advantage and customer relationships. Covid-19 pandemic is the proof of accelerated use of AI across multiple industries around the globe.

Smart companies Tips for a smooth integration of AI

According to the latest title “Global Artificial Intelligence Market” published by Facts & Factors, the global Artificial Intelligence market size is expected to reach USD 299.64 Billion by 2026 from USD 29.86 Billion in 2020, at a compound annual growth rate (CAGR) of 35.6% during the forecast period 2021 to 2026.

Most companies believe that AI is certainly one of the foremost technologies of the future even though they still aren’t making the most out of their relationship with AI. Here below are few obstacles to AI adoption and how they can be avoided.

 

The Preparation Phase

For many people, there is still something mystical or threatening about AI. Although intelligent technologies act invisibly in our everyday life, the image of AI often emerges as futuristic, emotionless robots that look amazingly like Arnold Schwarzenegger are going to hunt us down and kill us. But AI is only aimed to develop machines/computers that are capable of doing things normally done by people. The lack of knowledge is one of the main obstacles to AI adoption. The implementation of new technologies should always be seen as a long-term project. As there really isn’t a textbook on how to adopt AI at the enterprise level, people with the right mindset need to be brought into an organization to help facilitate changes and capitalize on opportunities.

In many cases, high costs and a lack of resources are also decisive obstacles. But not every company directly needs its own computing resources or expensive, in-house developed platforms. In many cases, it’s worth taking a look at third-party AI platforms or in the public cloud. They enable the use of powerful and scalable AI solutions without the need for extensive investments of your own. The experience of the major platform providers also helps to implement projects as quickly as possible.

 

Communication is the key

The challenge of scaling AI and automation often does not lie in the technology itself. Rather, the corporate culture is often important in order to implement changes in the work environment. Thus, before the introduction of the AI, timely communication with employees is essential. The benefits of AI must be well elaborated and appropriate training must be planned for all employees. Artificial intelligence requires specialists who are well educated and have to be trained. This is the only way to develop, operate and maintain intelligent systems and to handle advanced troubleshooting and continuous improvement of these solutions. Tasks and responsibilities transformation must also be openly discussed to deal with the fear of losing jobs among employees, as, AI will complement rather than replace employees.

 

Introduction of a clear AI strategy

Small and medium-sized companies, in particular, are often reluctant to implement AI because they lack a clear strategy. In the first step, however, a fully developed strategy is not absolutely necessary: ​​rather it is more important for companies to understand the technology and recognize the possibilities it offers. At this point, experts should be consulted to elaborate on the benefits of AI and how can this actually benefit the company? What are the installation process and its duration? What type of data or tools are needed to work successfully?  What can be done to achieve results? Once all questions are clarified, and a strategy has been worked out the introduction can be prepared.

 

AI technical requirements

Like a human, an AI system also needs time to learn. That is why it takes time for the first successes to be measurable. In order to have a decisive influence on the development of companies, good implementation is requisite. The AI requires various available data that it can analyze. This is the only way to generate data models that can be used as a basis for future predictions or decisions. The implementation effort depends, among other things, on the flexibility of the software that a company uses. Another factor is the specific use cases that should be automated with the help of AI and that must be taken into account as early as the implementation phase. It is possible to start individually with each communication channel, regardless of whether it is email, chat or telephone. Preferably, however, the channels are placed one after the other. As a result, a company does not lose any time, because the advantages of an omnichannel system are that the training results of one channel flow into the learning process of the other channels. Depending on the use case, the AI ​​applies different algorithms and develops certain models. The learning is based on the trial-and-error method until it has developed the right model.

 

The AI ​​promises long-term optimization in terms of profitability and efficiency of in-house processes. With the ability of self-learning, algorithms can be used to improve existing processes and products as well as develop new business models. This means that AI has the potential to change entire industries and value chains over the long term. Artificial intelligence also opens up cross-sector value creation opportunities and growth potential for small and medium-sized companies. To gain all benefits related to AI, the first step is the will to deal with the topic of AI and ultimately its implementation. Therefore a well-developed strategy is required.

 

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4 Cloud Computing myths, debunked

Flexibility, scalability, and long-term business resilience are the huge boost to cloud adoption. The future of the cloud is bright. Over $ 287 billion growth is expected during 2021-2025 for the global cloud computing market. Yet there are many myths surrounding the use of cloud solutions that prevent companies from taking benefits of cloud services. Even after twenty years, the use of cloud applications such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) keeps coming up against it vague fears and rejection. It’s because, in addition to data security, access and control options also play a hugely important role. Cloud solutions certainly pose certain risks for companies and their data if not managed correctly. However, many myths are way much exaggerated. In addition, many risks not only affect the cloud, but also locally operated networks.

The following misconceptions about cloud computing prevent companies from taking advantage of the cloud and have made the acceptance of cloud services particularly difficult.

 

The company will lose control over its own data

Many CIOs and IT managers or administrators often feel that they will completely lose control of companies’ sensitive data and its management once it’s migrated to the cloud. Additionally, they also carry the fear of dependence on providers as the control over the server is also given away to the cloud provider. Overall companies are particularly concerned with the location of the data and a possible loss of control over their own data. But even though they have passed the operation and maintenance of servers into third-party hands, they are and will remain the sole owner at all times and can retain all rights and control over their data and can decide independently, depending on the services used, where the company-critical backup and archiving data is stored. Because administrators and those responsible for data no longer have to worry about small details such as updates or background processes, they can spend more time optimizing the infrastructure and suitable strategies for business growth.

 

The data is not safe in the cloud

For a long time, it was believed that cloud solutions are more susceptible to attacks than the company’s own IT. Cloud services, in themselves, are exceptionally secure. However, many companies are reluctant to cloud adoption and have huge concerns about cyber-attacks, data theft, and industrial espionage. Because there is no such thing as absolute security, more and more cloud providers are creating a secure cloud for their customers. Their business model hinges on preventing breaches and maintaining public and customer trust. Additionally, all cloud providers have to comply with stringent regulations and this requires them to put robust security measures in place, including the use of strict protocols and advanced security tools. Also, the latest data centers are equipped with various security measures and offer users a guaranteed high level of security for their data.

 

Migrating to the cloud is complicated

The companies’ IT departments are often considered to be busy maintaining ongoing day-to-day operations. They don’t have enough time or know-how to modernize IT operations through the cloud. They are persuaded that migration to the cloud will come along with additional requirements, will also increase the complexity of the IT infrastructure and administrative effort. BUT every cloud provider offers their support whether it’s before or during the migration and ensures that everything runs smoothly. The greatest advantages only become visible after the conversion and cloud automation of many tasks and processes, on the one hand, it relieves computer scientists in their everyday work as they no longer have to worry about updates, backups, archiving, or the complicated maintenance of IT systems.  On the other hand, it can meet the requirements of the specialist departments faster than conventional infrastructures.

A company that plans to move its applications from a data center to a large cloud platform, must check whether their applications are cloud-ready or need to be revised before the migration. Otherwise, they’ll end up paying a high price for a platform that they cannot take full advantage of.

 

Cloud is more expensive than the in-house computing

Cloud migrations are complex projects that quickly lead to unexpected costs. As with all operating costs, it is not just the monthly cost that needs to be considered, but also the total cost of ownership (TCO). The cost of going to the cloud depends on several factors such as license obligations, data center, and the company’s ability to control and optimize cloud consumption. The big advantage of the cloud is the flexible scaling and that you only pay for the capacities that you actually use. The up-front costs of cloud migration are often significant, but the longer-term savings usually dwarf that initial cost. Choosing the right provider and achieving more performance and lower costs requires know-how and experience with the multitude of services.

 

Almost every company knows how important it is to keep up with the times in the digital age in order to remain competitive. Cloud computing is playing a vital role in responding to the challenges of these unpredictable times. The cloud is seen as a tried and tested method to achieve the necessary flexibility and agility. It has proven to be an important driver of digital transformation.

 

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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

COVID-19: Companies Journey toward Digital Expansion to become Faster, more Productive and more Responsive

Digital transformation progress

 

Our everyday life and way of doing things are completely changed since COVID19 started. It has accelerated the global digital transformation, according to the most recent F5 State of Application Strategy survey (SOAS). The seventh annual edition of this study is based on a survey of 1,500 participants from various industries, company sizes, and positions.

 

The need to adopt digital services across industries, geographies and communities is accelerated due to the dramatic shift in remote work and social distancing so that companies can improve their connectivity to interact with customers.

Business leaders have recognized digital technology as a key driver of revenue and raced towards digital transformation within their company. Here, below, are the key findings of the F5 survey:

 

  • AI-assisted business has tripled.
  • Applications continue to be modernized rapidly, with APIs a method of choice.
  • The importance of SaaS-delivered security is rising as organizations work to unify security across distributed applications while managing more architectures than ever.
  • Architectural complexity makes multi-cloud availability an imperative, and edge deployments are increasing, too.
  • Telemetry will take us to the future—but now, nearly everyone is missing the insights they need.

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Future-ready organizations are working to improve connectivity, reduce latency times, guarantee security and use data-driven insights. There is increasing interest in public cloud and SaaS, edge computing, and seeking application security and delivery technologies that are easy to deploy and provide data for decisions.

Modernization remains the top priority when it comes to operating on both modern and traditional application architectures for more than 87% of organizations that’s 11 percent more than in 2020. Additionally, almost half of all companies – 30 % more than last year – manage at least five different architectures.

 

Since last year’s SOAS report, the growth of AI and machine learning has more than tripled to 56%. This means that more and more companies are in the late phase of digital transformation. 57 % of those surveyed have begun digital expansion, an increase of 37 % compared to the previous year. This shows an increased focus on business process automation, orchestration, and digital workflows to integrate applications. 77% are already modernizing internal or customer-oriented apps, which is 133% more than in the previous year.

 

Additionally, two-thirds of respondents use at least two methods to create modern workloads, a mixture of traditional and modern application components. Of the companies with only one method, 44% say they use modern interfaces, either via APIs or components such as containers. More than half of the respondents already use infrastructure as code. Organizations using this approach are twice as likely to deploy applications even when using automation. They are also four times more likely to use fully automated application pipelines.

 

Companies are realizing the potential of edge computing. It enables new services and better performance by placing applications as close as possible to the sources and users of data, situation may vary for each industry and business function. Of course, COVID-19 is an accelerator due to the distribution of labor. No less than 76 % of those surveyed are using or planning edge implementations. The top reasons are to improve application deployment, performance and data available for analysis. In addition, 39% believe that edge computing will be strategically important in the years to come. 15% already host technology for app security and delivery at the edge. More than a third of companies (42%) will support a fully remote workforce for the foreseeable future. Only 15% plan to bring all employees back to the office.

 

Companies are creating and collecting more data than they have at any point in the past. All this data is coming from different sources. However, according to surveys, sufficient data does not necessarily deliver the insights companies really need. More than half of the respondents already have tools that assess the current state of applications. But an alarming 95 % say that they are missing important findings from the existing monitoring and analysis solutions. Accordingly, the collected data is primarily used for troubleshooting, followed by the early detection of performance problems. Almost two-thirds of respondents (62%) measure performance in terms of response times. Less than a quarter of companies use them to uncover degradation in performance. And only 12 percent forward the data to business areas.

 

More than 80% of respondents believe that data and telemetry are “very important” to their security, and over half are excited about the positive effects of AI. Participants also named platforms that combine big data and machine learning (also known as AIOps) as the second most important strategic trend in the next two to five years.

 

In many ways, the coronavirus pandemic has challenged businesses and governments around the world. In order to rise to the challenges caused by the pandemic, businesses have modernized and distributed applications in short term. Digital technologies have allowed many organizations to avoid a complete standstill, due to unexpected and urgent shifts in work. Companies must continue to discover and implement AI and other digital technologies for the continuity of their business.

 

The full report can be downloaded here: The State of Application Strategy in 2021

DMS: Intelligent Workflows Integration to Streamline your Business Processes and Increase Productivity

STREAMLINING BUSINESS PROCESS THROUGH DMS

Our everyday life is shaped by digitization. Nevertheless, numerous documents go through our hands every day in the office as at many workplaces there is still more paper in circulation than necessary. Appropriate management of company documents is extremely important to an organization. It’s a process that can be easily automated but in many cases is carried out manually. If, on the other hand, you are a Paper-less Office (mostly digital), you still have to manage documents and possibly scan, save and organize them beforehand.

 

However, in order to keep up with the rapid changes in the modern business world, companies nowadays have to rely on lean processes, transparency, and efficiency. A future-proof company cannot avoid digitization. Efficient management of documentation can allow employees to collaborate on tasks and save businesses significant amounts of money. A document management system (DMS) can make this process much easier for you so that you can concentrate fully on the business operations. Digital document management in connection with automated process management is one of the steps towards the digital transformation of your company. With a DMS you can automate your workflows, keep track of things and are no longer exposed to the risk of losing sight, stop shuffling paper and streamline your business processes.

 

Here below are some considerations that you should take into account when implementing a DMS.

 

Plan the DMS implementation:

Deciding to implement a DMS is one of the first great steps towards becoming a Paper-less Office. A well-thought strategy and planning is essential to ensure a successful implementation of DMS. Only when you know what you want to achieve with the DMS, you can pay attention to the corresponding functions and features. It is therefore essential that you get a clear picture of the company’s current situation, possible problems, new opportunities, goals, and future needs. All of these elements need to come together in order to find out the best DMS to satisfy your company’s needs.

 

Essential features package:

If your company is growing steadily, you should also consider future requirements when planning to embark on a DMS implementation project. Don’t just think about the present, but also keep an eye on tomorrow to achieve long-term gains. The following features are essential for a smooth working day:

  • Usability: Clear user interface and simple operation.
  • Digitization: Scan documents and save them in various formats such as PDF or Word.
  • Document input: Should allow inputting files through various sources such as scanner, Email, manual upload, mobile applications, web services, etc.
  • Versioning: Always use the latest version of a document and restore an older version in an emergency.
  • Full-text search: should be able to find documents quickly by allowing users to locate any word or phrase that appears in the document.
  • Automatic workflows: Self-definable forwarding and processing of documents.
  • Archiving: Safe storage of documents.

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Industry-leading document management system providers, always go beyond the basic features and provide to their customer’s innovative features and solutions that will improve their overall business productivity. So, all other features and functions are also welcome, but if they are associated with considerable additional costs and are not absolutely necessary for your business, then you shouldn’t choose them in your package. This saves you a lot of unnecessary costs and allows you to concentrate on the essentials.

 

On-site vs Off-site DMS:

When looking for a suitable DMS, you can opt for on-premise or off-premise depending on the amount of data your organizations handle. With an on-site DMS, then you can transfer gigabytes of data in a matter of seconds. On the other hand, if you are running a company that has a large number of users to manage and your investment in IT is not convincing, then you need to go for the cloud or off-site DMS. It’s also suitable if you have a work from home of off-premise working culture within your company.

You should also pay attention to integration options whether new DMS can be integrated into the company’s existing systems such as BPM, CRM, or ERP, so that there is no need for a major changeover.

 

Service of the provider:

There are a lot of DMS providers on the market, they differ with their individual user interfaces as well as with their range of functions. That’s the reason why, in addition to extensive and solid document management software, you should choose the provider that best fulfills your requirements and most importantly when it comes to DMS implementation.

A serious DMS provider should be able to provide a transparent presentation of the costs incurred, such as for setting up and maintaining the software, through to any other services that may arise. These include, for example, training courses such as:

 

  • Introduction to document management software
  • Correct handling and use of the DMS
  • Establishment of automatic workflows
  • Assistance in any undesirable emergency situation. A permanent contact person in such a case can be helpful to resolve any issue that occurred. A DMS usually works perfectly, but in an emergency, it can never hurt to have a good connection to the manufacturer.

 

If you have carefully studied the use of a DMS within your company and know what you want to implement with it, you can specifically pay attention to urgently needed functions. A right DMS accrues significant benefits to the organization. Hence it is imperative to choose the correct DMS to makes your day-to-day work easier.

If you are interested in a DMS, we would be happy to work with you on your company’s digitalization project and accompany you step by step with the introduction of a DMS in your company. We look forward to hearing from you and would be happy to answer any questions you may have.

 

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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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How can Digital Marketing benefit from Artificial Intelligence?

AI in Digital Marketing xorlogics

 

AI is now more accessible than ever with it’s potential to change business forever. With its positive impact, and being a lot more affordable than before, both big and small companies are able to benefit from the insights and automation options it provides. With the integration of AI brands can not only leverage customer’s data but also anticipate their customer’s next move, understand sales cycles better, correlate their strategies for converting prospects into paying customers and improve the overall customer’s journey with machine learning efforts.

 

As a subset of AI, machine learning involves the analysis of historical data from various business interactions with customers / prospects (for example: when and what was the last time the customer ordered?). As ML has the ability to analyse extremely large sets of data, its being used in the digital marketing departments around the globe to identify sales patterns and increase success factors. Algorithms for ML generate insights via predictive analytics, based on these insights, marketers can either take actions individually or automate AI to do the job. For example, they can automate emails that are aimed at re-targeting your audience, giving you a better chance of a higher ROI.

 

ML is also playing a major role in SEO. Even tough SEO algorithms change across major search platforms, with AL and ML tools, the insights from searchable content may become more relevant than specific keywords in the search process. In order to maintain a high-ranking place on search engine result pages, consider the quality of your content rather than simply the keywords included. By doing so, you’ll be ahead of the game when it comes to future-forward content creation and SEO.

Marketers can also benefit from ML tools to analyse what type of content, keywords, and phrases are most relevant to your desired audience. Once they have the key insight, they can optimize their dialogue and develop engagement across multiple online platforms, to drive brand awareness and create meaningful relationships with leads, prospects, and customers alike

 

The key difference between modern AI-based and traditional outbound marketing strategies is the integration of contextual data, i.e. information that results from the interaction with the customer is not stored in labour-intensive and time-consuming data warehouses but is available in real time and can be used for decision-making. With these customer profiles and interests recorded in parallel to the interaction, the previously defined decision strategies are fed in order to achieve high planning security for high, profitable conversion rates.

 

Artificial intelligence opens up possibilities in marketing domain far beyond currently available functions. PwC estimates that business could save $2 trillion globally by applying intelligent automation to many activities that were previously processed by humans and making employees more productive. In addition to that, AI, robotics and other forms of smart automation will bring great economic benefits and contribute up to $15 trillion to global GDP by 2030.

 

With AI integrated marketing, business can forecast customer behaviour and run data-based campaigns to have remarkable results. It helps them to save a lot of money on marketing and sales efforts by bringing them valuable leads. Not only business can achieve valuable leads and turn them into customers but they can also maintain a good relation and provide a better service to these customers by introducing a 24/7 customer service with the help of AI equipped chatbots. These chatbots are able to handle customer enquiries and provide customer support on time and appropriately, based on the needs of customers. Business are creating value through transforming customer journeys by providing immediate response to consumer’s queries or issues. According to McKinney’s study, 75% of customer demand NOW service within 5 minutes of online contact. If business can beat this time, they can convert a ‘visitor’ into a ‘paying’ customer.

Here below are some interesting statistics of AI in marketing:

 

  • According to research from Callcredit, 5 hours and 36 minutes is the amount of time that the average marketing professional spends collating data and getting it ready for presentation. An AI integrated marketing dashboard can do the collating in minutes and give you more time for reporting process. Statwolf
  • 97% of leaders believe that the future of marketing lies in the ways that digital marketers work alongside machine-learning based tools. QuanticMind
  • By 2020, 30% of companies worldwide will be using AI in at least one of their sales processes. Gartner
  • By 2020, 85% of customer interactions will be handled without a human. Gartner
  • For 61% of marketers AI is the most important aspect of their data strategy. MeMSQL
  • 80% of business and tech leaders say AI already boosts productivity. Narrative Science
  • When AI is present, 49% of consumers are willing to shop more frequently while 34% will spend more money. PointSource
  • Large businesses with more than 100,000 employees are most likely to have an AI strategy – but only 50% of them currently have one. MIT Sloan Management Review
  • Netflix is saving $1 billion per year by using machine learning to make personalised recommendations- Artelliq
  • 44% of consumers don’t even realise they’re already using AI-powered technology platforms. Pega
  • 45% of end users prefer chatbots as the primary mode of communication for customer service inquiries. Grand View Research

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The ways that ML is being used in digital marketing practices helps organizations to expand their understanding of their target consumers and how they can optimize their interactions with them.  So, when developing appropriate AI applications for marketing purpose, the collaboration between software developers and domain expert’s must not be neglected. The ultimate decision-making competence when it comes to the all-important question of which next best actions are to be implemented in order to achieve the greatest possible marketing success usually belongs to the domain experts. You should have the experience and expertise to incorporate the right NBAs into the self-learning models for decision-making strategies.

 

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RPA – Robotics Process Automation Trends and Statistics for 2020

RPA Robotic Process Automation XORLOGICS

 

This year, many companies found their business growth through the smart interaction between human resources and supporting software robots as the direction is set towards digitalization and automation. The combination of RPA with artificial intelligence (AI) and machine learning (ML) is playing a huge role in the global economic environment.

According to a new report by Grand View Research, Inc. 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. In addition to that, in Gartner Top 10 Strategic Technology Trends for 2020, hyper-automation, autonomous things and AI security were at the top 3.

 

RPA is a type of IT solution that allows organizations to automate many of their tasks through the use of specialized software programs. Many business executives believe that RPA enables their companies to automate structured tasks that take just a few work steps and repeat themselves frequently – like transferring data from one IT system to another. RPA can relieve employees of tasks that consume a lot of time but do little to add value and are prone to errors – keyword typing errors. It also helps to automate routine jobs on the computer and processes to increase efficiency, improve service and save costs.

 

One should not think that RPA is similar to BPM. RPA only simulates human data entry and helps with simple and recurring tasks, to save time because the software does things in parallel that an employee can only work through one after the other. Such an application needs simple rules with few exceptions – and the biggest advantage is that, unlike humans, it runs around the clock. Unlike BPM which stands for describing, contolling, modeling, and optimizing the processes that are present in an organization.

 

Here below are the statists and trends of RPA that shows it’s worth:

 

    • 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

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    • The RPA industry will grow from $250 million in 2016 to $2.9 billion in 2021. This is one industry that is growing at a lightning speed. It was already worth $1.7 billion in 2018 – Forrester

 

    • RPA will achieve “near universal adoption” in the next 5 years – Deloitte

 

    • By 2025, the market for collaborative robotics is expected to reach $12 billion – MarketsAndMarkets

 

    • By 2024, organizations will lower operational costs by 30% by combining hyperautomation technologies with redesigned operational processes. Gartner

 

    • The RPA fast adoption is helping business to reduce the operational costs and enhance overall customer satisfaction, improve transparency and visibility for service functions and reduce of manual efforts – Reportlinker

 

    • 11,214 results This is the number of open positions produced by a recent search for “robotic process automation”on LinkedIn’s jobs site. Titles vary within this growing IT jobs category, but “RPA developer” (and variations of the same) is an increasingly common one – reflecting the need for IT pros who can build the bots that enable organizations to offload repetitive, time-consuming tasks – LinkedIn

 

    • RPA deals with the application of advanced technologies including artificial intelligence (AI) and machine learning (ML), to increasingly automate processes and augment humans – Gartner

 

    • RPA is offering a lot of benefits to the business by giving access to collaborative intelligence where humans and technology works side by side so that they can perform their roles optimally. As employees don’t need to perform repetitive tedious tasks, they can be educated to work with automation tools and learn the latest business and marketplace information through machine learning – Xorlogics

 

    • The market for RPA in Healthcare is driven by the increasing demand to automate claims and process management. RPA vendors are focusing on developing best-in-class intelligent process automation bots – Research and Markets

 

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