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Covid19: Things We’ve Learned About #CloudComputing, So Far

 

Things We've Learned About #CloudComputing, So Far

In a remarkably short period of time, cloud computing has moved from a marginal to a fundamental element of IT operations. Thus, in just ten years, CIOs were presented with an opportunity to break the rules and create a new model for the implementation of IT. IDC forecasted cloud infrastructure spending to grow 12.9% to $74.6 billion for 2021 and Gartner expects the cloud computing industry to grow a trillion-dollar value in 2022. While cloud computing is essential in the IT strategy, it’s good to highlight where the cloud has brought benefits and in which areas companies still have to improve.

Let’s find below which strategies are working and where there is still work to be done.

 

The practice of cloud computing to bridge gaps in services

Cloud computing should be seen as a form of flexible outsourcing. It is only one vector among others for the provision of services. In computing on demand, what matters is how the company subscribes to services and benefits, not how they are delivered.

Cloud computing has the advantage of offering a very different model from the traditional ways of purchasing enterprise computing, where an ISD would acquire hardware and software for a specific location. This may be appropriate for services limited to a regional market but can encounter problems of latency at the global level. This can be very problematic, especially if you are managing IT for a highly transactional business such as a financial institution, or if you ship large amounts of data. The cloud enables CIOs to ease these performance issues by purchasing on-demand computing to create omnipresent service delivery.

You can rely on the third party to provide the diverse service you need, while they, as an expert, have the capability to deliver peak capabilities and performance where and when you need it.  As a CIO, you can expect the platform to work and be available. Now, many IT executives will do their best to avoid possessing new physical hardware, while being assured that the service will be well provided. The cloud enables IT managers to take a step towards hosting and achieve high levels of backup and security for a defined fee.

 

Adopt a cloud computing mindset

A company must have a long-term goal to migrate as much IT capacity to the cloud as it provides a cost-effective way to gain access to new skills and expertise. It can be difficult to keep in touch with all the innovations associated with the cloud; so, make sure to spend enough time brainstorming and talking with future IT professionals to get an idea of ​​future changes. They are probably more aware of the next big phenomenon that will affect the company. The culture that surrounds IT management is evolving, and that’s why you have to take a look at the new services that are available on the market and encourage employees to adopt a mindset favoring cloud computing.

However, a migration to the cloud must be carefully managed, including governance and information security. By definition, major providers (such as Amazon and Google) should be much better at securing data. However, CIOs need to be aware that convincing the rest of the company of the benefits of cloud computing can be a slow process, particularly with regard to governance, security, and approval issues.

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Let the cloud take care of core domains

Cloud computing integration must bring a tremendous solution to your organization’s operational challenge. The starting point concerns a number of core areas that CIOs can easily deliver on-demand. If you are using products such as Salesforce and Office 365, you’d have to be crazy to want to host them yourself. Better to let someone else, an expert in this field, take charge of your operational concerns. The cloud also serves as a one-time solution to problems involving certain operational projects.

 

Finding a balance and determining how to manage legacy systems

IT managers would be foolish to dismiss cloud computing, if only in terms of the quality of the service. However, while businesses will continue to migrate on-demand services, much remains to be done. We’ve noticed that some companies are opting ​​for an on-demand model and there are others that buy more internal resources.

For CIOs, moving to an on-demand model can be a headache. You have your systems inherited and at some point, you will have to consider migrating these services to cloud computing, but it’s possible, as the momentum is in favor of computing demand, despite persistent concerns about security and governance.

 

Security and Privacy

The main challenge to cloud computing is how it addresses the security and privacy concerns of businesses thinking of adopting it. The fact that the valuable enterprise data will reside outside the corporate firewall raises serious concerns. Hacking and various attacks on cloud infrastructure are affecting multiple (potential) clients. These risks can be mitigated by using security applications, encrypted file systems, data loss software, and buying security hardware to track unusual behavior across servers.

 

Reliability and Availability

Cloud providers still lack round-the-clock service; this results in frequent outages. It is important to monitor the service being provided using internal or third-party tools. It is vital to have plans to supervise usage, SLAs, performance, robustness, and business dependency of these services.

Covid19: Evolution of the Digital Transformation within companies

Covid19 Evolution of the Digital Transformation within companies

The corona pandemic is continuously changing the framework for digitization. According to IBM 96% of leaders report that Covid-19 will accelerate their digital transformation by an average of 5.3 years. Another study by Celerity shows that 63% of leaders state that the Covid-19 pandemic prompted them to embrace digital transformation sooner than originally planned. The goal of promoting innovations faster and keeping up with the times is the most important reason for digital transformation for companies.

 

With the adoption of digital solutions, companies have greater resiliency. They can not only streamline their operations but also automate all manual processes in order to generate more revenues. With data driven insights, companies can make decisions faster and adapt or change course at any point. They are also better prepared to fight against cyber threats, also when their employees work remotely. All these advantages give companies a boost for their own digital transformation, but they also have to overcome various hurdles as the transition to a digital company is anything but easy. Limited resources, rigid legacy systems as well as unclear goals and rules – all these things delay IT departments when it comes to innovations.

 

Even tough 30% of organizations will increase innovation and reinvent their business models in order to future-proof their companies, digitization continues to be a major challenge for many companies. Companies’ IT departments are experiencing the greatest change: they are developing into a service provider who, on the one hand, strives to ensure that the IT systems and applications run properly and, on the other hand, acts as a full-service provider of IT-supported business processes. The requirements continue to increase. A total of four hurdles in particular slow down innovative projects.

 

Skill shortage:

According to the KMPG CIO survey, 54% of organizations reported that skill shortages were holding them back from pursuing their transformation goals. In particular, they were lacking expertise in the following areas: Cybersecurity, Technical architecture, Enterprise architecture, Advanced data analytics. Current IT teams are made of few people who have the essential technical skills but don’t have training time to develop the skills. But if your business is suffering from skills shortages, ignoring training is not the right solution – it’s much easier to train existing staff than to hire new employees.

 

 

Legacy systems

Legacy systems, which form the backbone of many enterprises, are holding them back from leveraging new digital technologies and creating new experiences for their customers/partners. Outdated business software consumes a lot of resources in companies. According to Forrester, companies invest 70 to 80 percent of their IT budget in maintaining rigid back-office systems. These systems are difficult to integrate or customize when it comes to supporting new digital initiatives. Slow development methods combined with legacy systems make the problem worse. Outdated networks and servers no longer meet the needs of companies. Taking the right step and modernizing the legacy is the way forward. The IT modernization promises cost savings, efficient management of IT infrastructure, efficient utilization of human capital, better security and risk management, enhanced user experience, and last but not the least, a direct impact on competition.

 

Limited resources

Digital transformation is necessary in order to become more agile, more innovative and more resilient, but often only limited resources are available for converting old processes to more modern tools. Building a business case for such investments can be quite challenging in terms of budget approval. Also, all legacy systems require modernization. Otherwise, they can be exposed to crashes anytime. Therefore, the introduction of new technologies can be introduced in steps, often with a free software test phase.

 

In order to be really successful, that means first and foremost to be economically positive, but also to recognize and use the opportunities of the future as a driver of innovation, a digital roadmap should be planned. Not the hard change, but a targeted and coordinated development in digitization should be the way in which all members involved within a company pull together. Strategic concepts that include optimal resource planning are required here. This means that a networked transfer of knowledge and experience must take place. Using the strengths of individual individuals and combining them with scientific innovations should be the path to productive and efficient profitability. The digital evolution is a permanent further development and with all step forward new opportunities become visible that can be realized through a stable foundation.

 

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

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

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

 

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

 

Automation is a complicated and complex process

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

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

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The future is automated

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

 

Automation is killing jobs

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

 

Existing systems prevent the integration of new solutions

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

 

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

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

iot IoB covid gartner xorlogics

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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Credential Stuffing Attacks: How to Protect Yourself

GLOBAL INTERNET USERE 2020

 

As we look forward to the hopefully great year ahead, let’s rewind a year that seems to have more episodes than Game of Thrones. Companies all across the globe were put into a huge test followed by a rapid shift from office working to home-office prompted by the coronavirus pandemic. Nearly overnight, organizations worldwide had to enable remote workforces to support their business requirements. COVID-19 has in many ways unleashed a new set of challenges and/or accelerated existing challenges, such as ransomware, data breaches, API attacks, cyber-fraud and unemployment frauds, within global enterprises.

 

It’s clear-cut that technology and security teams struggled in 2020 to respond as quickly to the changing environment as did the cybercriminals, who took advantage of an environment of unexpected change, extraordinary shifts in employees’ working process, and technology used by governments and worldwide companies.

 

Akamai reports that global internet traffic has grown by as much as 30 percent in 2020, while Statista observed that only in October 2020, online traffic across 20 different industries increased by 1.5% compared to the reference period in January 2020. Online transactions increased by 26.7 % compared to 2019. Another report from Cisco predicted there will be 5.3 billion total Internet users (66 percent of the global population) by 2023, up from 3.9 billion (51 percent of the global population) in 2018. That’s nearly two-thirds of the global population with Internet access.

 

The internet has gained more popularity in 2020, internet users are currently growing at an annualized rate of more than 7%, equating to an average of more than 875,000 new users each day. With this massive increase in the global internet traffic, Akamai is seeing over a hundred million of these attacks every day, with a peak of nearly 300 million a day, only in its own customer base. On the one hand, the internet is serving humanity, on the other hand, it has become the best place of like phishing, fraud, identity theft, Email Spoofing, bullying, cyberstalking, Malware, computer viruses.

 

In the history of cybercrime, the global coronavirus pandemic has added the credential stuffing problem to it extend. For those who don’t know, in this attack method, a cybercriminal tries a large number of stolen credentials on multiple websites. In order to gain unauthorized access to as many user accounts as possible to carry out attacks or fraudulent activities.

 

Transactional bots are getting popularity among hackers, as they act as agents on behalf of hackers. Bots aren’t typically created to compromise just one individual computer, they’re designed to infect millions of devices. An attacker first identifies websites with valuable accounts such as credit institutions, online shops, etc. In the Darknet, he then acquires lists of stolen login data and rents a botnet to automatically check the account list on the advised website. If a credential stuffing attack is successful, the attacker either sells the new, validated access data in the darknet or uses it himself. With the stolen data, fraudsters can then, for example, log into third-party accounts and carry out financial transactions.

 

Attacks like these often have very unpleasant consequences for the concerned companies and institutions, Application failures due to impaired web performance (73%) and recovery costs (63%) are among the greatest burdens, but also lower customer satisfaction, lost sales and financial losses (all-around 40%) have a significant weight (Akamai).

 

Here below are the few possible ways to protect yourself against credential stuffing attacks.

Protecting yourself from credential stuffing is pretty simple if you use the same password security tips that security experts have been recommending for years. For effective protection against bot attacks, it is recommended in the first step not to reuse the passwords, use a password manager, enable two-factor authentication, and get your leaked password notifications.

 

By using a unique password for each online account, you can protect all of your accounts at once. Because even if one of your passwords gets leaked, it can’t be used to sign in to other websites. As remembering strong unique passwords, for each account you have, is a nearly impossible task, the use of a password manager is recommended. It can not only remember your passwords but also generate strong unique passwords. Additionally, don’t ignore the 2-factor authentication. It is much more difficult to hack your account if you’re using two-factor authentication on it. As it adds an additional layer of security to the authentication process, it harder for attackers to gain access to your devices or online accounts.

 

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Industry 4.0: Future of Manufacturing

Industry 4.0: Future of Manufacturing

The concept of Fourth Industrial Revolution was first introduced in 2015 by Klaus Schwab, executive chairman of the World Economic Forum. It’s characterised by the increasing digitization and interconnection of products, smart machines, value chains and business models. Since connected machines collect a tremendous volume of data that can not only analyse that data to identify new patterns and insights but also inform maintenance, performance and other issues, that are impossible for a human to do in a reasonable timeframe. Today, Industry 4.0 offers the opportunity to factories across the globe, the opportunity to optimize their operations quickly and efficiently by knowing what needs attention.

 

Here below technologies that are the significant driver for the advance of Industrial Internet Solutions aka, IIOT:

  • The Internet of Things (and services)
  • The Digitization and Interconnection of products and services
  • Virtual and Augmented reality
  • Cloud Computing
  • Intelligent machines and autonomous Systems
  • Big data and Analytics
  • Cybersecurity

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The Internet of Things is nothing new. It is already present all around us and is growing strongly. Every day new things are linked together. This growing list of objects includes everything from your thermostat to the parking meters, household appliances, heating and cooling systems, vehicles, health and fitness monitors, environmental sensors, and more. Many of these devices can already observe their surroundings, exchange information over internet and report this data back to the user.

 

The adoption of IOT in the world of production is also increasing at an exponential rate. By 2025, Industry 4.0 –the Fourth Industrial Revolution–is expected to generate close to $1 trillion in economic value, much of it is unlocked by continuous operational efficiencies through traditional cost-cutting measures, significant transformation in the way goods are produced and delivered and large manufacturers are becoming more streamlined, efficient, and agile.

 

Whether we call it Smart Industry, Factory Automation or Industry 4.0, the goal remains the same, enable companies to produce more efficiently, which translates into an increased efficient manufacturing and production. The aim of Industry 4.0 is to make factories “smart factories”, producing “smart products with autonomous machines that will self-monitor and organize their own maintenance.

 

More and more companies are using the IIOT to capture new growth through increasing production and creating new hybrid business models, exploiting intelligent technologies to fuel innovation, and transform their workforce. It’s quite clear that the Fourth Industrial Revolution represents a fundamental change in the way we live, work and relate to one another. There is huge potential for digitization and innovation to add value to factories and to contribute to the environment and biodiversity.

 

However, to unlock the true potential of this revolution, companies must digitise and integrate their processes vertically across their entire organisation, from product development and purchasing, through manufacturing, logistics and service. Factories and warehouses must adapt and implement a digital mindset, leverage the IIoT and digitalization to become much more agile and efficient in their production lines around the world.

What is Edge Computing and why does it matter for the Internet of Things

 

What is Edge Computing and why does it matter for the Internet of Things

Possibilities are that you have already heard the term “edge computing” as many organizations use it in their daily business when it comes to handle, process and deliver data from millions of devices around the world. Multiple definitions of edge computing can be found on the internet, but I like the one from Gartner.

 

Gartner defines edge computing as “a part of a distributed computing topology in which information processing is located close to the edge – where things and people produce or consume that information.” “The emerging category of edge computing has been steadily rising in importance and maturity, and 2020 will be the most interesting year yet for vendors and users in this exciting space,” Forrester  said on Forbes.

 

The IoT is having a significant role in the digital transformation of organizations and industries. The explosive growth of IOT, mobile computing along with new applications that require real-time computing power, either to receive information from the cloud or deliver the data back to the cloud are the main reason of edge-computing systems’s growth.

The amount of data generated by digital devices is escalating day by day as 127 new IoT devices are connected to the web every second. The installed base of active Internet of Things connected devices is forecast to reach 21.5 billion units by 2025. IoT applications important growth place challenging demands on the IT infrastructure. It requires the lowest latency with the highest scalability, reliability and availability. This explains the fact that edge computing has become a special and increasingly important discipline within a network infrastructure.

 

One of the biggest benefits of edge computing is the ability to process and store data faster, enabling for more efficient real-time applications that are critical to companies. As the distributed, open IT architecture of Edge Computing processes a lot of data in real time directly on site and thus drastically reduces the bandwidth requirements and the latency times that inevitably arise during data transmission and data processing in a data center. And regardless of whether an in-house or a cloud data center is used.

 

At the same time, the high and constantly growing data volume and the increase in critical applications at the endpoints (edge) mean that the quality features typical of a data center such as scalability, reliability and high availability are also indispensable for edge infrastructures. Therefore, edge computing and the IOT are the perfect match for several reasons.

Apart from simplifying the data processing at the edge of a network, close to the sensors, and thus avoids the issues of sending all the data directly to the cloud, edge computing in the IoT environment is characterized by these four advantages compared to cloud and data center-centered approaches:

 

Speed

The longer it takes for data to be processed, the less relevant it becomes. Not only, edge computing reduces the total volume of data traffic and thus increases the performance of applications and services, but also makes latency-sensitive applications possible, for example autonomous driving, which would not be possible with data center-based data processing or in areas with insufficient network coverage.

 

Security

The number of IoT devices is constantly growing. This makes them increasingly targets for potential network attacks. Due to the centralized structure, cloud computing is vulnerable to DDoS attacks and failures. Edge computing, on the other hand, distributes applications and processes across different devices, making it much more difficult and complex for attackers to infiltrate the network. Edge computing can also filter sensitive information and, if necessary, only transmit uncritical data in order to meet security and compliance requirements. This means that less data can be intercepted, which makes compliance with security standards easier.

 

Cost

By its nature, the edge is closer to the IoT device than the core or cloud. For IoT use cases, connecting thousands or even millions of devices directly to the cloud is often not feasible due to costs, privacy, and network issues. But, with edge computing, the data can be filtered at the point of origin and does not have to be sent to a data center. Companies therefore have the choice of using the perfect mix of local services and cloud-based applications for a cost-effective IoT solution. Data processing and storage in edge devices reduces the expensive bandwidth requirements and thus optimizes the overall costs.

 

Scalability

Edge computing enables companies to expand their capacity requirements at any time and efficiently by combining IoT devices and edge data centers. The use of edge devices optimizes the scaling costs because processing is decentralised and each additional device is associated with a far lower bandwidth with less load placed on the network.

 

Source :

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IOT – Business Transformation by 2025

 

Internet of Things connected devices installed base worldwide from 2015 to 2025

 

By 2025, International Data Corporation (IDC) estimates that worldwide data will grow to 79.4 zettabytes (ZB), generated by 41.6 billion connected IoT devices, or “things,”. To be noted that there were an estimated 22 billion internet of things (IoT) connected devices in use around the world by the end of 2018.

 

This exponential  growth in the amount of data is explained by the growth in the number of connected devices, no matter of what size they are, they are everywhere in our daily life such as smart appliances (stoves, refrigerators, washers and dryers, coffee machines, slow cookers), Smart security systems, smart locks, and smart doorbells), Smart home hubs (that control lighting, home heating and cooling, etc.), Smart assistants (like Amazon Alexa or Apple’s Siri), Fitness and health trackers, sleep trackers, and smart scales, videos surveillance cameras etc. Thus, the link between the data creation and smart devices is obvious. Data is not only being gathered by smart home and smart surveillance but also via industrial and medical IOT as well by creating an increasing demand of the IT infrastructures, therefore more and more enterprises and service providers are now looking at IoT as a powerful source to drive digital transformation and to unlock the operational efficiencies.

 

IDC forecasts that the amount of data created by these connected IOT smart devices will reach to an annual growth CAGR (Compound Annual Growth Rate) of 28.7% between 2018-2020. This data is sent directly by sensors or via gateways to centralized platforms that gather, process, store, analyse and visualize this data to create insights and improve operational efficiencies of processes. Advances in AI and real-time communication are the main cause of this exponential growth in IOT. Enterprises are extracting a maximum of advantage from the data generated by IOT for better and faster decision-making, predictive analytics and automation of workforce. These digital transformations are bringing them numerous benefits such as higher productivity, GDP growth, improved corporate performance, and new prosperity.

 

IOT is not only shaping our lives but changing the traditional legacy business at a rate of change never seen before in history. Empowered by exponential increase in AI, computing power and availability of large amount of data, machines are fast learning to become workforce of future in several areas. As machines and products have started communicating with each other without any human intervention, the real value of data is getting generated and helping business leaders in better and faster decision-making, predictive analytics and automation.

 

In addition to that, 5G will reshape IOT and smart devices by boosting the speed, coverage and responsiveness of wireless networks. According to Aleksander Poniewierski, EY Global IoT Leader and partner, “IoT cannot thrive without effective and affordable wireless connectivity, interoperability and common standards. We believe 5G has the potential to make a ground-breaking impact on the way in which future IoT ecosystems are designed, especially in the areas of scalability, latency, reliability, security and the level of individual control on connectivity parameters.”

 

As IOT adoption in enterprises will reach to 65% in 2020, a 35% increase from 2017, IT and business leaders need to consider the extent to which they can use IOT to improve ROI, market competitiveness, and brand differentiation. They must be able to build digital security around potential sensitive personal and corporate data.

 

Sources:

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