Trends Identified
Increasing philanthropy
Philanthropy will grow further on a global level up to 2030. Global donations and grants to Greenpeace increased consistently at the rate of 4% p.a. from 2000 to 2009; donations to Amnesty are currently ten times what they were in 1990. Global willingness to donate was not even stopped by the global financial crisis. The Haiti earthquake in 2010 led to USD 1.4 billion in donations to 96 organizations. About 30% of the world's population donates money to a charity every year, so the world will have about 2.5 billion active philanthropists by 2030. The growth of philanthropy also has a strongly emotional aspect: there is a strong correlation between giving money and happiness, with a coefficient of about 0.69.
2011
Trend compendium 2030
Roland Berger Strategy Consultants
Immersive Technologies – Enhancing the Digital Experience
Two distinct but merging technologies are behind immersive technologies: Virtual Reality (VR), computer- generated, digital environments that fully immerse users in a virtual world and Augmented Reality (AR), which overlays digital information on the physical world and augmented reality operating environments. Companies are already experimenting in pilot projects and the technology has the potential to become the next computing platform. Mobile devices are currently at the center of the implementation of AR/ VR and they could replace large parts of the PC landscape. We observe a co-evolution with digital twins and gaming. Hardware is important, but the user experience such as ease and comfort of use and real-time performance as well as a structured content are keys for success. High data quality including realtime analytics is also a prerequisite. Immersive Technologies are still in early development and are five to ten years from wide mainstream adoption. They currently show a slower adoption than smartphones but will probably experience a similar cost reduction and speed up significantly cost reduction and development speed. Hardware vendors are accelerating computing and speeding up application performance and vendors are already developing and offering enterprise-level collaboration tools and augmented reality operating environments. For now, the clumsiness of the current devices has reduced mobility and the cost for adopting content are slowing progress and cybersecurity and safety of usage remain issues. Immersive technologies promise unique user experiences including 3D interactions, new ways of data handling, and interaction with the physical world and has the potential to accelerate and simplify business practices or even invent new ones. Use cases are hands-free tasks like in field service and maintenance, digital twins for operations, architecture, real-estate etc., live media streams, and augmented information for any digital supported workplace.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
Conversational Systems and User Interfaces –Talking to Machines
Machine Learning has reached a state in which conversational systems can have increasingly engaging and human like conversations. These chatbots or digital assistants use mainly natural language processing (NLP) to interact with humans but will use sight, sound, tactile, etc. in the near future as well. Conversational systems can be viewed as a step towards true personal virtual assistants and will replace most common interfaces, simplifying human-machine interactions and replacing less interactive interfaces. The technology will probably merge in part with Immersive technologies and will also leverage the digital network of sensors, appliances, and IoT systems to interact with humans. The chatbot ecosystem is already robust, with many different third-party chatbots, native bots, distribution channels, and enabling technology companies. Messaging platforms such as Facebook Messenger, WhatsApp, Tencent’s WeChat, Google Allo, Apple iMessage, Slack and Kik all use chatbots as well as voice-controlled consumer devices like Amazon’s Alexa, Apple’s Siri, Microsoft’s Cortana, Google Assistant and SAP Co-Pilot. While the focus is on consumer applications right now, especially based on mobile technologies, chatbots will go business very fast, allowing businesses to leverage the inexpensive and wide-reaching technology to engage with more consumers and to support, simplify and speed-up many business processes. Examples are commerce applications as taxi cab ordering (such as Uber), concierge facilities (such as Sephora), B2B contract workfl ows (such as Apttus), food ordering (such as Domino’s Pizza) and others. Use cases for chatbots are helping humans to use technology without the need to know technology like in navigating and exploring, automated customer services, and supporting functions for hand-busy tasks in fi eld service, logistics, maintenance, medicine and others.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
Robotic Process Automation – Rule-Based Bots
Robotic Process Automation (RPA) refers to rule-based and easily programmed software, that promises to eliminate repetitive, easily automated tasks. RPAs are fully programmed, cannot learn and have to be updated when IT systems change. RPA is seen as a next step towards automation where machine learning is not needed. It can be tied together with machine learning to automate more complex tasks to create intelligent enterprises. Most RPA today uses text analytics, image processing, text search, or optical character recognition. Analytics will become critical as RPA will soon be developed towards more smarter versions. While we are heading towards an automated world, the process seems to take longer than anticipated and is more complex than anticipated, so RPAs could be a fast forward solution for those processes that yet do not need sophisticated algorithms. For now, a central control of bots is not fully established and changes of IT systems could lead to expensive updates. Besides that, RPA can boost productivity with minimal process change, it offers easy-to-calculate ROIs and it is an in-route to more complex automation with machine learning.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
Machine Learning – The Algorithms to Make Everything More Intelligent
The success of Google AlphaGo in 2016 marks the rise of machine learning. It is based on the idea that machines can learn for themselves if they get access to large volumes of data and comprises deep learning, neural networks and natural-language processing algorithms. The technology has very strong connections to big data and real-time analytics but needs high quality data and a clear process to be trained. Machine learning and IT vendors will in build intelligent capabilities into business intelligence systems, analytics and into many devices, robots and machines. This is rising a number of ethical questions such as the future of our work, how machine learning will affect our behavior, how can we guard us against mistakes and unintended consequences, and how do we stay in control. Extracting the qualitative data needed for machine learning training is a challenge, as well as finding experts. Machine learning can be used to solve a tremendous variety of problems and automate tasks that had to be handled by humans before, such as translations, face, speech and pattern recognition, text analytics, analyzing large data sets and more. The technology promises to save costs and improve the quality of work by automating 80% of the roughly 50% work activities that are suitable for automation. Most of todays’ knowledge work contains the following activities: pattern recognition (99%), generating and understanding natural language (75%), optimizing and planning (30%). Furthermore, machine learning may generate faster insights and speed up decision making based on large data sets and accelerate innovation by faster prototyping. While machine learning will affect all industries, expectations are the highest for media, telecom, technology, consumer and fi nancial services. The fi rst wave of machine learning will focus on automating repetitive tasks and analyzing large data sets such as invoicing, text analysis, image recognition, and fraud detection but will be used for autonomous vehicles, virtual assistants, product intelligence and advanced robotics as well.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
Contextual Workspace – Driving Insights And Decisions
The need for faster and better innovation and improved productivity, and the shift towards high-value work will drive the evolution of improved workspaces. They will allow professionals to quickly create (virtual) project teams according to the project needs and the individual capabilities across any structural and organizational hierarchy. For now, siloed data sources, classical hierarchies and missing innovation and knowledge cultures are barriers for a more value- and project-driven work. Knowledge work will be more consumer like with contextual interfaces and new, social and open collaboration infrastructures and individuals will be able to identify the right people across all silos, networking with them more easily. The user experience will be a seamless one across devices, locations, and context. Machine learning based technologies such as immersive technologies, digital assistants and conversational bots will help with the handling, extraction and representation of data and generate new insights based on the individual roles and projects. Information and recommendations will be presented in a context- sensitive way and increase the user efficiency. The individualization of information will be used to understand knowledge and project management needs, and to support learning on the level of teams and individuals. Security and identity and access of information will be organized people-centric, to make it easier to get to information resources. Vendors are now bundling work stream collaboration with their productivity and unified communications products, which will a push towards even more unified and smart solutions. Contextual workspace will start around challenge-oriented and self-organizing project teams in research, innovation, design and engineering, and education as well as any knowledge and research heavy tasks and real-time data work such as pricing, logistics, supply-chains, maintenance etc.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
Blockchain – Decentralized Trust
Blockchain is based on distributed ledger technology, which records data (transactions, files, or information) across a peer-to-peer network. Participant can see the data and verify (or reject) it using consensus algorithms. Approved data is entered into the ledger as a collection of “blocks”, stored in a chronological “chain”, and secured through cryptography. The disruptive nature of Blockchain is its ability to move control over interactions from centralized systems to distributed users. For now, legal and institutional barriers restrict a shift away from central systems but blockchain has a high disruptive potential for all trust-bound activities. Four types of blockchain are evolving: the consortium (controlled by a pre-selected group), the semi-private (a single company granting access to any user), and private and public blockchains like Bitcoin and Ethereum. Up to now the consortium model is the most accepted model for business although the technology is still unproven in a larger business context. Blockchain might make systems more transparent, potentially more democratic and help inventing new trust models. It could improve cash flow, compliance and accountability, it could lower transaction costs and reduce fraud. Furthermore, it offers a huge potential to unify flows of payments, physical goods and information in the rather chaotic relationships among untrusted parties, like in complex supply chains. Blockchain will impact organizations and businesses firstly in a first non-disruptive, incremental change, by leaving processes unchanged and realizing cost savings and process improvements. A use case will start around verifications, smart contracting, transparency and accountability, sharing and leasing models, rights, and IP and government records. The second wave of blockchain will radically restructure existing industry sectors or business ecosystems into systems of trust.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
Digital Twin – Virtualized Insights
Digital twins are virtual models of physical things, products, buildings and systems and their data and information flows. Digital twins create a holistic view of products, buildings and processes and allow virtual simulations and modifications. The real power of a digital twin is the close to real-time linkage between physical and digital worlds. The building elements are: sensors, data, integration layer, analytics and the digital twin, the virtual model, itself. Digital twins promise to improve situational awareness, enable better responses to changes, particularly for asset optimization and preventive maintenance. They can help extending the lifetime of assets and optimizing the performance. Digital twins are increasingly and successfully used for product prototyping, reducing the development times and costs. The market is immature and we are still observing rather simple digital twins like virtual models of buildings, oil platforms and prototypes. The demand is increasing fast and digital twin templates, platforms and services will proliferate. Digital twins won’t stop at assets or things but will be expanded to operations, systems, people, business processes and metadata structures over time. These digital representations will be connected more tightly to their real-world counterparts and infused with more sophisticated artificial intelligence. Obstacles are the heterogeneous and disconnected sources of data and the complexity of the projects. Digital twins will start around asset monitoring, optimization and rapid prototyping. Midterm, operation of factories and companies will follow, long term, we will see generating insights around product and services use and business modelling.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
Quantum Computing – Using Particle Physics for Computation
Quantum Computing uses the characteristics of quantum mechanics, i.e. the superposition and entanglement of subatomic particles. The so-called quantum bits (qubits) allow for an exponential gain in computing power compared to classical bits and promise to solve certain problems that are intractably complex and go beyond todays computing power. Quantum computing might threaten cryptography and cryptocurrency, as the unlimited computing power could make many encryptions ineffective. Potential application areas of quantum computing are quantum chemistry, encryption and security, optimization problems, large database search and operations, machine/deep learning, cryptography, DNA and other forms of molecular modeling. Quantum computing is at the very early stage of basic research mainly on quantum computational hardware, with no unambiguous quantum speed up observed yet and with few known algorithms,. The probabilistic nature of quantum computers makes utilization challenging for now. The technology is currently driven by research institutes, big corporate players like Google, IBM, Microsoft, Intel, HP, and most recently investors. According to Gartner, quantum computing is more than 10 years away and it is questionable if we will ever realize general purpose quantum computers. We might instead see rather narrow use cases. At this stage of research, we see the biggest potential in hybrid approaches like using classical FPGA’s in a quantum inspired way. Another idea would be to use build hybrid computers where classical and quantum CPUs are co-located on the same computer. Blind quantum computing could be used to delegate the computation to a quantum server without leaking any information, which might solve some of the expected security issues.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
Neuromorphic Hardware – Using Nature’s Designs
Neuromorphic hardware is based on conventional processors that are conceptually inspired by neurobiological architectures. Neuromorphic systems are at the very early prototype stage between basic and applied research but the topic is gaining traction within the industry. Companies such as IBM, Intel, Samsung, HP and Google are using the neuromorphic concept to build energy-effi cient networks inspired by biology. Neuromorphic hardware promises new designs for diff erent ways of computing and extreme performance while using little energy. It is suitable for use cases based on machine learning, in particular for pattern recognition, event-driven vision processing, and robotics. It is in competition with quantum computing and in both cases the complexities are potential threats. For now, classical GPUs are more accessible and easily programmable than neuromorphic silicon and programming neuromorphic hardware requires new methodologies that still have to be developed. Based on our learning from the neuromorphic hardware research project within the “Human Brain Project” at University Heidelberg, but we believe that the neuromorphic approach will lead to new concepts in combination with machine learning and powerful graphical GPUs.
2018
Trend Report 2018 - Emerging Technology Trends
SAP