- Next chapter of DX: Technology-driven transformation altering business and society
- Sense, compute, actuate: Turning data into value
- Emerging autonomy: Learning to live with AI
- Rising customer expectations: More convenience, customization, and control
- Reimagining the material world: Revolutionized processes expand technology reach
- The future of work: Bridging the digital talent gap
- Legacy inertia: Retrofit the old into the DX world
Description: Digital transformation, the continuous process by which enterprises adapt to or drive disruptive changes in their operations, customers, and markets, has entered the next chapter — multiplied innovation. Now, competition is driven by platforms and ecosystems; innovation feeds off of itself. Ubiquitous changes affect business in markets, customer expectations, and operational efficiencies, while society sees improvements in daily life. But many businesses are implementing DX without success, and some will fail entirely. Societal impacts include disturbed trust, jobs, alliances, and new inequities. Companies that achieve multiplied innovation can thrive in the next chapter of DX.
Context: In the past few years, we have witnessed the evolving of DX and the disruptions and opportunities it poses for business and society. Organizations of every size and in every industry must adapt to new technologies, new players, new ecosystems, and new ways of doing business. IDC predicts that, by 2021, at least 50% of global GDP will be digitized, with growth in every industry driven by digitally enhanced offerings, operations, and relationship. While most organizations are attempting DX, only a small percentage are getting it right. Early attempts are met by subsequent challenges of change management, budget, talent, platform, scale, and sustainability.
Description: Today, data and intelligence represent a unique opportunity for creating unimaginable value. IoT, mobile devices, big data — combined with historical data, systems of record, and global information — continually sense an environment and put it into new contexts. Combined with AI and machine learning, organizations are spreading intelligence from the edge to the core to turn data into value. However, it is harder than it appears. Winners are differentiated by the ways they leverage data to deliver meaningful, value-added predictions and actions for personalized life efficiency and convenience, improving industrial processes, healthcare, experiential engagement, data monetization, or any enterprise decision making.
Context: By 2020, in over half of G2000 firms, revenue growth from information-based products and services will be twice the growth rate of the balance of the product/service portfolio. Data as a service (DaaS) presents an expanding market for both providers and consumers. The volume, velocity, and variety of data and large and diverse data sets create new challenges, but when combined with AI technologies and exponential computing power, they create ever greater opportunities. Any application, process, service, or organization that isn’t part, or all, of the new “sense, compute, and actuate” paradigm is missing the boat with digital transformation.
Description: AI is actively impacting experiential engagement, business and manufacturing processes, strategies, and more — autonomously creating a significant portion of new innovations. Many future applications will be developed by AIs without human supervision. Beyond that, augmented humanity — the fusion of digital technologies and humans — for improved mobility, sensing, and cognition will start to become routine. Unfortunately, the “ethics of AI” have yet to catch up with the technology, leaving potential for bad AI as well as good. Bias in AI models is just beginning to get attention. Regulations are even farther behind. There will be a long period of augmentation before autonomy takes over. Unfortunately, society is unprepared; however, there is still time to adapt. As AI is changing the way people live, work, and play, learning to live with AI is essential.
Context: Intelligent applications based on artificial intelligence and continual deep learning are the next wave of technology transforming how consumers and enterprises work, learn, and play. By 2027, 10%+ of applications will be developed by AI without human supervision. Automated customer service agents, increased public safety, preventative maintenance, reduction of fraud, and improved healthcare diagnosis are just the tip of the iceberg driving spend today. IDC forecasts AI solutions will continue to see significant corporate investment over the next several years, achieving a compound annual growth rate (CAGR) of 46.2% through 2021, when revenue will be more than $52 billion.
Description: As disruptive organizations leverage breakthroughs in cloud, mobile, social, and AI to deliver personalized, rewarding, and immediate experiences, customers have more choices than ever. New devices and interfaces, wearables, AR/VR, home automation, information, and connectivity are combining to instill a belief that people can have what they want, when, where, and how they want it — and at the same time, be in control of the data and their experience. Yet AI-based consumer reputational scoring may be at odds. Emerging economies are bringing hundreds of millions of new customers that businesses are competing to win. Enterprises live and die by Net Promoter Scores, apps, network integration, and more.
Context: With new customer expectations being set by thriving companies that disrupted markets, the previously accepted levels of customer service are no longer good enough. New platforms and business, operational, and organizational models are required to meet consumer expectations. Customers now expect real-time support with answers to complex questions ready at the click of a button. More people are willing to share personal data in exchange for better service, but they also want more control around their personal data.
Description: New technologies are revolutionizing industrial processes and ushering a “golden age” of new materials. Nanotechnologies and atomic-level materials create entirely new applications. IoT, robotics, and 3D printing are mainstream technologies in industrial and commercial applications. AI is used to design products that could only be manufactured by 3D printing techniques. Supercomputers are being used to help slice chromosomes and drive the pharmacogenomics revolution. “Generative design” improves strength and removes weight. Technology is driving “de-materialization” — the use of fewer raw materials to produce products and growth — and the obsolescence of outmoded devices and processes in a whole new world of products, production, and materials.
Context: Traditional CAD/CAM vendors and new upstarts are rolling out generative design frameworks leading to new generations of lighter, stronger products. Genetically targeted drugs and treatments have the potential to effectively combat cancer in our lifetime. New aircraft structures already have significant 3D printed composition, and that’s just the beginning. By 2019, generative design and biomimicry will be used by 25% of G2000 manufacturers resulting in 30% improvement in product development cycle time. IDC forecasts that, in 2021, 3D printing investments will exceed $19 billion, worldwide spending on robotics will reach $230.7 billion, and spending on cognitive and AI systems will grow to $52.2 billion.
Description: New talent management techniques and technology accelerators are fundamentally changing the concept of work and how it is done. The future workspace will be a mix of physical and virtual. Work culture will be more collaborative, while the workforce will be a combination of people and machines working together. But until that vision materializes, the demand for digital talent outpaces the supply and trends to limit free flow of workers localizes the problem. Platform providers are under pressure to address the talent crunch with new productivity environments such as low code/no code. AI may help increase efficiency for some tasks, but this is not the talent in short supply. Organizations need to equip up-and-coming generations for the future while they bring current workers up to speed to address workforce needs.
Context: The demographic shifts led by millennials entering the workforce and technology advances are driving fundamental changes in the workplace. The future of work is humans and machines, instead of human versus machines. This impacts organizations’ culture, required skills, talent sourcing, and workspace and the nature and makeup of the workforce itself. It requires organizations to leverage digital technologies, attitudes, and behaviors to reinvent the way businesses engage with their employees, partners, and customers to drive higher efficiencies and deliver superior experiences.
Description: Technology has been enabling business for decades, and refreshing deployed systems has always been problematic. While new technologies are transforming some aspects of the business, legacy systems are holding others back, limiting innovation, opportunity, and engagement. Every company in every sector is faced with balancing traditional and next-generation systems and technologies: transformation at scale demands the replacement of outdated systems. Mergers and acquisitions challenge industry leaders as they struggle to incorporate acquired technologies. Many organizations are retrofitting the traditional systems and technologies to meet the new requirements, while trying to create the flexible and adaptable DX platform of the future.
Context: DX is becoming a competitive requirement and the source of a massive wave of new investments in digitizing business operations, communications, and services. Many organizations are facing the challenges of simplifying the current technology environment. Legacy systems and processes and change management issues often derail DX initiatives. Organizations should evaluate systems against business, financial, technology, and operations measures and create a road map for modernization.