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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.

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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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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Business Automation & Multi-Cloud Management: Micro and Maxi trends for 2021 and Beyond

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The year 2021 is all about transformation processes, primarily resulted by the exceptional situation we’ve witnessed in 2020. As 2020 caused a major shift in how business and IT teams operate, the development around COVID-19 was and still is a great challenge for all organizations. In addition to classic customer service, IT service, in particular, is confronted with more tasks and service requests. So that the workforce can work productively and quickly, the IT service needs intelligent tools for automation. Many changes have been on the agendas of IT departments for several years and vary from micro changes that affect the big picture to maxi changes that will affect future generations of employees.

 

In this continuously changing environment, organizations are exploring new ways to operate and drive growth. Each year, Gartner, Inc. releases a series of studies mentioning trends/predictions that will impact the business environment, IT, and technology in the coming years. Here below, we’ve gathered the most relevant trends to the IT automation market to help IT, professionals.

 

“Hyper automation is irreversible and inevitable. Everything that can and should be automated will be automated.” Brian Burke, Research Vice President, Gartner

 

  • By year-end 2025, over half of the world’s population will be subject to at least one internet of behaviors (IoB) program (private, commercial or governmental).
  • By 2025, 50% of enterprises will have devised artificial intelligence (AI) orchestration platforms to operationalize AI, up from fewer than 10% in 2020.
  • By 2025, 40% of physical experience-based businesses will improve financial results and outperform competitors by extending into paid virtual experiences.
  • By 2025, half of the large organizations will implement privacy-enhancing computation for processing data in untrusted environments and multiparty data analytics use cases. 
  • By 2024, organizations with IT teams that understand the needs of customers will outperform other organizations’ customer experience metrics by 20%.
  • 2023, 40% of all enterprise workloads will be deployed in cloud infrastructure and platform services, up from 20% in 2020.
  • By 2025, traditional computing technologies will hit a digital wall, forcing the shift to new computing paradigms such as neuromorphic computing.
  • By 2025, most cloud service platforms will provide at least some distributed cloud services that execute at the point of need.
  • By 2025, customers will be the first humans to touch more than 20% of all products and produce.
  • By 2024, organizations will lower operational costs by 30% by combining hyper-automation technologies with redesigned operational processes.
  • By 2024, 80% of hyper-automation offerings will have limited industry-specific depth mandating additional investment for IP, curated data, architecture, integration, and development.
  • By 2024, more than 70% of the large global enterprises will have over 70 concurrent hyper-automation initiatives mandating governance or facing significant instability.

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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!

 

 

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AI and Automation impact on medium-sized Companies and Organizations

 
The Business Benefits from AI and ML
  • Massive Data Consumption from Unlimited Sources
  • Rapid Analysis Prediction and Processing
  • Simplifies Time-Intensive Documentation in Data Entry
  • Handling Repetitive Jobs
  • Reduction of Error
  • Improves Precision of Financial Rules and Models
  • Easy Spam Detection
  • Interpret Past Customer Behaviours
  • Better Customer Segmentation and Accurate Lifetime Value Prediction
  • Recommending the Right Product
  • Digital Assistance and 24/7 Availability

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Hyper Automation and Artificial Intelligence (AI) are seeping into every aspect of business, from operations to production and from product development to business processes. Processes, tasks and role models – everything is changing with this revolutionizing in the commercial sector. This evolving area of Artificial intelligence (AI) and machine learning (ML) is the future for all businesses, and it’s already affecting the way we live and work today. In fact, research firm Markets and Markets estimates that the machine learning market will grow from $1.41 billion in 2017 to $8.81 billion by 2022!

 

The new digital technologies are having different impacts on jobs in the short and longer term. While automation may displace workers within a sector in the short term, studies are demonstrating that overall employment is growing when looking at a longer period comparing results from different sectors and the World Economic Forum has found that, by 2022, algorithms and other transformative technology could create more jobs – as many as 58 million. Because despite automation and artificial intelligence, people will continue to be important in the future.

 

Artificial intelligence opens up possibilities 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.

 

Like business of all sizes, SMB are also flooded with data gathered from different sources such as, customer data, supplier data, market data, operations data and many more. AI can quickly pull out insights from these databases and extract valuable data. Managers can get valuable insights on business process from workflow management and/or make sales predictions easily by using data from ERP systems. As AI is able to pull out insights from data easier than human workforce and run the routine tasks to add value to existing business, company can use its human resources to solve potential problems, spend time on creative tasks and boost business ability to innovate.

 

SMBs can also benefit from AI to identify, understand and better target their customers. Business can forecast customer behaviour and run data-based campaigns to have remarkable results with the use of big data and artificial intelligence. 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.

 

Not only in customer service, artificial intelligence is demonstration it’s capacities in accounting, finance, auditing and tax controlling, fraud detection as well. Instead of recurring routines, data analysis, process control and optimization by automating procedural tasks would be on the agenda of SME by allowing employees to make even more valuable contribution to corporate management. As AI can decipher data and draw actionable insights easily from complicated situations and eliminate/reduce errors, it’s totally transforming and changing the way accounting and tax firms used human intelligence to perform same tasks. With an accurate integration of AI empowered workforce, accountants and bookkeepers can build a value-based business, attract more customers and increase revenue by spending less time that they were used to spend.

 

Customer service and accounting are not the only 2 departments getting aids from AI, sales and marketing are also getting their potential customer’s pipeline faster than ever before by finding interesting leads in their databases as contact information is available for the market you want to target.
By engaging each potential lead in a very personalized way, sales person can turn the lead into a paying customer and recommend the right product with the help of gathered data on the customer.

 

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IT Trend 2020: Hyper-Automation

IT Trend 2020: Hyper-Automation

Gartner Top 10 Strategic Technology Trends for 2020 have listed Hyper Automation as one of the biggest trends for 2020, as more and more enterprises are adopting automation in their work processes. Forrester has predicted that the global market for RPA services will hit US$7.7 billion next year and is expected to grow to US$12 billion in 2023. AI is increasing productivity through automation and is helping organizations derive meaning from ever-larger data sets.

 

Hyper-automation is the mixture of automation technologies that exist to expand and increase human capabilities by allowing organisations to automate more complex work with the help of robotic process automation (RPA) at its core, with artificial intelligence (AI), process mining, analytics, and other advanced tools that strengthen the ability to automate work. As defined by Gartner:

 

“Hyper-automation deals with the application of advanced technologies including artificial intelligence (AI) and machine learning (ML), to increasingly automate processes and augment humans.”

 

The adoption of Automation is helping organizations, that are data-driven, to be able to better respond to their customers’ demands, identify new business opportunities, improve their service delivery, eliminate all human errors, and reduce costs.  The idea is to automate more and more knowledge work, and engage everyone in an organization to be part of the transformation.

 

How is hyper automation important for enterprises in 2020?

 

Over 1 million knowledge-work jobs will be replaced in 2020 by software robotics, RPA, virtual agents and chatbots, and machine-learning-based decision management, predicts research firm Forrester in their new report, “Predictions 2020: Automation.”

Data Science, Analytics and Cognitive technologies are feeding RPA with the intelligence which is revolutionizing software automation in industries. Hyper automation offers 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 tasks, they can be educated to work with automation tools, wisely and with intention, and learn the latest business and marketplace information through machine learning. They can also to taught how to interpret AI-enabled decision-making, find creative solutions to resolve problems and get more engaged with their jobs.

 

Simply put, once Hyper automation is incorporated into your business it will help to reduces human effort by doing a lot of work in lesser amount of time, reduce the risk of human errors as machines are calibrated for precision, improve the quality of jobs by eliminating deadly, exhausting, and dangerous for humans processes and leads to increased productivity and higher output.

 

But before any implementations, business must think and identify areas and processes where automation is really needed.  Business leaders must make a business plan and estimate the the return on investment, and of course train existing personnel to make the most of automation instead of thinking that automation will take their job.

 

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5G Technology – The Future of Connectivity

What New Services Will 5G Enable

The introduction of 5G is getting closer. Fifth generation technologies are fast approaching, and they have tremendous transformational potential to make our lives better. Better health care, smarter cities, a much more efficient industry; all of this becomes possible as the IOT grows and comes with a wide range of innovative solutions that drive our modern economy. However, without 5G networks, none of these elements can express its full potential. Service providers and telecommunications companies thus receive new opportunities – but also challenges such as investment protection for their 4G systems. But, the fact that 5G is at a growing stage of its evolution, provides a huge opportunity to apply the lessons learned from the implementation of the 3G and 4G / LTE systems.

In this blog post, I will try to explain what 5G is and why it offers such promises.

 

What is 5G? 5G is the term used to describe the next-generation of mobile networks. There isn’t any “official” definition of 5G; but it stands to fulfil the demand for continuous connectivity by creating an agile, purpose- built network tailored to the different needs of citizens and the economy. Unlike the previous three generations of public mobile network technology, 5G is targeting delivery of more than just “higher speed mobile broadband” for consumers – 5G brings an expectation of greater interconnectivity between a wider range of existing telecommunications networks and services, and an improved version of end-user experience by offering new applications and services through gigabit speeds, and significantly improved performance and reliability.

In addition to that, 5G, wireless technologies open up enormous opportunities in the field of IoT, for example in connected vehicles or smart city concepts. However, it takes some time and a lot of work to use these opportunities as well as there’s a huge investment challenge and the fear to not fall behind in the transition to 5G.

 

Features of 5G:

 

Main features of 5G Network technology are as follows:

  • 5G technology offer high resolutionit means up to 10Gbps data rate which represents 10 to 100x improvement over 4G and 4.5G networks
  • Offers bi-directionallargebandwidth; in numbers it represents 1000x bandwidth per unit area
  • 5G technology is providinglarge broadcasting of datainGigabitwhich supporting almost 65,000 connections with 99.999% of availability and 100% of coverage
  • The uploadingand downloading speed of 5G technology touching the peak.
  • The remote diagnostics
  • Through remotemanagementofferedby 5G technology a user can get better and fast solution.
  • The 5G technology also supportvirtual private
  • The 5G technology network offering enhanced and available connectivity just about the world
  • The 5G promises to offer better battery life for devices

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The creation of new career line:

 

Not only 5G is a revolution in networking, it also brings a cultural shift in business. For example, the new technology requires new skills in organizing and managing. In order to create and advance the underlying networks companiesneed employees who can understand and use the interaction and dynamics of all these software components.

A study estimates that in 2025 benefits from the introduction of 5G will create jobs in automotive, health, transport and energy. 5G deployment will bring millions of jobs and billions of euros benefits.

Automation-driven increases in productivity have already helped in many tasks for humans, such as the evaluation of data capacity, the monitoring of the network for operation limits or the search for harmful traffic. Instead, the focus of employees shifts to the results. So far, an engineer must plan a new service, get the hardware, set up the hardware, wire it, and then start the project. In this way, changing existing or deploying new services takes weeks or even months. In an automated environment, this work can be done in minutes or completely eliminated. But the success of the transition to new technologies depends on the decision-makers having a clear concept for this and the employees understanding this concept and being able to implement it.

 

The ear of Hyper-Automation

 

Automation is probably the most significant element of moving to 5G.With a new virtualized 5G technology layer, it is clear that automation is no longer a luxury option but more an essential and mandatory aspect of managing and leveraging increasingly complex networks. For a while, service providers will need to manage different bandwidth and connectivity requirements in parallel. Unfortunately, the platforms of many 4G networks are simply not designed for the scaling required. That’s where automation comes in: virtualized and cloud-based technologies allow existing networks to scale as needed, facilitating and optimizing migration to 5G services.

 

In highly distributed environments, the challenge is to gain meaningful infrastructure analysis and performance data. Switching to virtualized, automated, cloud and network-spanning environments gives service providers a comprehensive view of applications, user experience and performance. Therefore, hyper-automation is fast becoming the new paradigm in the effective management of complex heterogeneous networks and holds the answer to the challenges that lie ahead. It incorporates smart and rapid automation driven by advanced analytics and machine learning.

 

In the coming months-years, Communication Services Providers (CSPs) across the globe will be busy rolling out the 5G network. As it promises data rates 100x of 4G, network latency of under 1 millisecond, supports 1 million devices/sq. km., and 99.999% availability of the network, 5G is fundamentally different from 4G, LTE, or any other network the telecommunications (telecom) industry has ever seen before. In order to capitalize on this opportunity, your organization needs to operationalize fast data and make informed business decisions in-event and in real-time.

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