Organizations from all sectors are gearing up for their digital transformation. They are doing so by investing massively in data-centric and eco-system-oriented platforms. And most of these developments are taking place in a public cloud. No more than 25% of the organizations surveyed do not use public cloud services. But almost 85% of this group plans to use them.
With a 70% confirmation rate, application development and testing is, by far, the most established use case for public cloud services, followed by hosting web-based or mobile applications.
Over one-third already host application software products such as ERP on public cloud platforms. And the massively increasing importance of public clouds for complex application hosting is confirmed by another 37% planning and 27% at least discussing it – meaning that no participant excludes this scenario.
And the public cloud is not only considered as a software development and hosting platform but increasingly as a launching pad to accelerate innovation. For 24%, deploying cloud-native features and functions to drive innovation is well-established, 29% have concrete plans, and 37% are at least discussing the possibilities for their innovation strategies.
But the public cloud is not necessarily the best solution for all workloads; data-heavy AI applications, for example, might be cheaper to operate and with lower latency on-premises. More so, there is a growing fear of untransparent or excessive costs (or both) due to complex cloud pricing. Accordingly, organizations are extending the concept and basic technologies of cloud computing to a diverse range of deployment models, including customer data centers, edge locations, and third-party locations.
In most cases, public cloud services did not entirely replace traditional IT infrastructures. Over 60% of those surveyed still own an in-house data center or private cloud, and almost one-third use externally hosted but dedicated resources.
A surprisingly huge share of organizations, 48%, indicated they already use sovereign cloud solutions, with another 42% either discussing or planning on doing so. On the one hand, these numbers reflect the great importance of public clouds for digital innovation. And on the other hand, that 89% of those surveyed consider “appropriate solutions for data sovereignty” for digital innovation as a very or somewhat important aspect of a service partner.
But narrowly defined ‚sovereignty solutions‘— i.e., public cloud combined with add-on services for ensuring compliance that usually come with a surcharge— are not necessarily relevant to all clients and use cases to the same degree. Organizations‘ willingness to invest usually depends on regulatory requirements, the sensitivity of workloads, or both. We can, therefore, assume that not all respondents referred to a strictly narrow definition of ‚sovereign cloud‘. Instead, they meant one of various alternative cloud deployment models on the market, ranging from additionally secured hyperscaler solutions to public cloud services from European vendors.
Edge or distributed cloud resources, i.e., IT infrastructure resources outside of a data center but close to or inside a factory or office, are used by 28% of the surveyed organizations. A whole further two-thirds are planning or at least discussing using these resources. Distributed models such as edge computing offer advantages in terms of latency and availability. In case of failure, only a few local edge servers are usually affected. The latency times in a cloud are often too long for operating real-time systems, making edge systems the better choice here.
At PAC, we don’t expect the trend toward cloud migration to stop soon, not least because a cloud environment is a nurturing ground and an important basis for a great variety of digital technologies that support transformation.
The most important drivers of digital innovation were the better use of data, improved customer experience, and more resilient and transparent supply chains. To achieve this, a combination of internet-of-things (IoT), cloud and edge computing, artificial intelligence, analytics, etc., are required to drive the desired levels of data insight. Let’s take a tour of some of the technologies that accelerate transformation.
The Internet of Things (IoT) brings digital innovation to many industries' production processes and organizations' end products. By adding local intelligence to products and machines and using holistic platforms for data aggregation and analysis, organizations can transform their business models and offer new high-value services to their customers. The use cases for IoT are manifold, spanning connected vehicles, smart homes and buildings, smart energy, digital government, smart cities, digital health, and digital factories.
5G marks a new era for the Internet of Things and presents organizations with a significant opportunity to improve their operations. 5G is an innovative radio technology that provides an extended frequency spectrum.
In the consumer market, 5G is positioned around faster connectivity and more bandwidth for consumer-based entertainment, media, and gaming services. In the professional arena, 5G networks combined with IoT or artificial intelligence help deliver new technologies and services in a broad range of industries, such as manufacturing, automotive, logistics, smart cities, utilities, and healthcare, that are not feasible with traditional Wi-Fi and wired networks.
The level of digitization needed for a wide range of facilities is asserting pressure on organizations from a connectivity perspective. 5G can be considered the backbone for various use cases by providing consistent, fast, and scalable data connectivity services. It is expected to have a significant impact on direct and indirect customer service functions, as well as on supply chain, logistics, and distribution operating processes.
Depending on requirements, a 5G network can be self-operated as a separate campus network, used via a public mobile network operator’s network, or in hybrid scenarios.
Typical 5G use cases are as manifold as the IoT. For example, in industrial IoT, cyber-physical production systems rely on stable and high-performing digital infrastructure. This infrastructure must meet demanding communication requirements to enable people, machines, devices, and products to interact flexibly, securely, and reliably. Similarly, autonomously operated forklift trucks and other autonomous vehicles in intralogistics centers. Or doctors, patients, and medical equipment in digital health scenarios. In contrast to Wi-Fi, 5G provides more users with information simultaneously, which benefits smart sports, entertainment, events, media, etc.
Low-code/no-code platforms are software development environments. They allow users to ‚drag and drop‘ existing pre-built application components and connect them to create applications without requiring comprehensive coding. Such platforms give businesses the ability to develop software quicker and at lower costs, and not least, to meet the challenges of the omnipresent skill shortage in IT.
Analytics and data management directly address our survey participants' most-stated goal of digital innovation: better use of data. Data is at the heart of any digital transformation and, at the same time, an essential basis for a range of other important technologies, including artificial intelligence and machine learning.
AI combines algorithms, knowledge bases (big data sets), and neural networks/ deep learning techniques to mimic and complement human abilities in various domains. These include perception and understanding, reasoning and problem-solving, learning and training, and interacting with surroundings and people. AI techniques can enhance and augment multiple solutions, such as robotic process automation (RPA) ) and robotic desktop automation (RDA), expert systems designed to perform specific tasks, chatbots, assistants helping consumers and employees with various tasks, and autonomous systems such as industrial robots and cars.
The importance of cyber security remains consistently high. The premise behind Zero Trust is simple: companies should not automatically trust devices or users inside or outside their perimeters. Instead, they should verify every access request to their systems before granting it. It is a way of thinking rather than a technical concept. It comprises a comprehensive consideration of an organization’s environment, including identities, applications, networks, data, and devices. Zero Trust approaches are becoming more popular, but - so far, the final stage is rarely achieved.
Blockchain technology is another investment topic for many industries. At its core, a blockchain is a distributed database. The broad distribution of information is the most important feature of blockchain solutions, as it promises maximum transparency, immutability and protection against manipulation, and security. So-called smart contracts can ease collaboration between partners and can be used to create workflows and business process automation. Payment services and traceability were the most-mentioned use cases of the survey participants, but there were many others.
Augmented and virtual reality have risen significantly in popularity in the past decade. While virtual reality (VR) refers to a digital image of reality created on a computer, augmented reality (AR) is the interaction of digital and analog life.
A digital twin is a virtual representation of a physical product, space (e.g., building, factory), or process (e.g., production). Organizations can use it for simulations before touching its real-life twin. The ultimate goal of the metaverse is to create a seamless world without interruption, similar to the real world. It includes elements of both AR and VR. While the B2C metaverse focuses very much on consumption, the enterprise metaverse addresses virtual collaboration, immersive learning, virtual collaborative design, and AI training.
One of the reasons for the excitement around quantum computers is how they can scale for complex tasks like modeling. Real quantum computing is still a long way off. But the development of these computers is a process of evolution, and annealer technology is here already. It can shift tasks currently done as batches, such as scheduling and fleet movements, in real-time. The survey participants mentioned various interesting use cases grouped around route optimization, real-time matching of supply and demand, forecasting, and simulation.
In future dedicated blog posts, we will cover analytics and data management, IoT, AI/ML, blockchain, AR/VR, and quantum computing in more depth.
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