Future Systems Report | Accenture...component of adaptable systems, collaborating with machines to make reliable decisions and take confident action exponentially faster. Making systems

FUTURE SYSTEMSThriving in a world of constant change

Welcome to the era of boundaryless, adaptable, radically human systems.When we envisioned the Future of Applications back in 2014,1 we defined three groundbreaking strategies for applications in a world in which technology-driven disruption had become the norm.

Centered around the concepts of liquid, intelligent, and connected applications, we predicted these strategies would transform core applications and power the high-velocity, software-driven companies of today.

We now see these strategies adopted widely. With liquid applications, companies are assembling reusable components and modular architectures with a cloud-first mindset. Intelligent applications are maximizing business data through machine learning and analytics. And connected applications are providing the technological foundation for new kinds of business, partner, and customer interactions.

The result? Companies have implemented new enterprise architectures and approaches to improve agility, manage technical debt, and harness technology innovation. And they’ve seen their applications spur new growth, shape new markets, and reach new customers.

Today, the ground is shifting once more. Machine learning and other forms of artificial intelligence (AI) are rapidly being operationalized, powered by the vast amounts of data now available to organizations. Computing power is ubiquitous and seemingly limitless. The Internet of Things is gaining ever greater traction across industries. Boundaries between applications and infrastructure are blurring to the point they’re now indistinguishable. Immersive technologies are creating new possibilities for customers and employees alike. And data is being shared within and between organizations with ever greater levels of trust and security.

WELCOME

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These profound changes create new opportunities and new challenges for today’s companies. As they continue to transform the core, how can they unlock the value still trapped in their organizations by core systems and processes? How can they build bridges from core systems to new systems? And how can they best scale innovations with the thriving systems necessary for success in a world of constant change?

First and foremost, by recognizing how today’s systems are already evolving, becoming ever more pervasive and embedded in businesses and daily lives. This seismic shift is both technological and cultural. The style of IT as we know it is simply not suited to constant change. It requires new ways of thinking and working that are much more experimental, agile, continuous, and resilient.

The reality is that applications, infrastructure, and employees are no longer discrete, standalone entities, isolated from the wider enterprise. Companies need to stop thinking of them that way. Instead, they must see them as components of complex, interconnected, living systems of technologies, applications, and people.

As they continuously morph to meet new market opportunities and challenges, these systems will create new and interesting connections between businesses and consumers, between suppliers and competitors, and between entire communities.

That’s why today we’re talking about the future of systems, rather than applications. Success in this future world will be driven by companies that can connect core systems with the new in a seamless fashion through digital decoupling—and scale the new with systems that are boundaryless, adaptable, and radically human. In this Point of View we describe these characteristics of thriving systems in detail, and how companies can use them to outperform in a world where nothing stands still. These systems call for new talent, and new holistic approaches—not just new technology.

The relentless pace of change we describe can sometimes seem daunting—for IT and business leaders and citizen users alike. Yet it is also full of possibility. Join us as we explore the characteristics of thriving future systems.

Bhaskar Ghosh Group Chief Executive Accenture Technology Services

Paul Daugherty Chief Technology & Innovation Officer

WELCOME

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WELCOME

Imagine a world in which living systems of super-smart applications, data, and infrastructure are anywhere and everywhere. Liberated from static IT stacks and legacy data centers, they use flexible enterprise architectures to give us what we need when and where we need it, adapting the way we adapt, and working the way we work. Engineered by a broad emerging talent force, these systems are created by us for us. These are future systems.

Applications are evolving into systems, merging with data and infrastructure, moving outside the boundaries of the enterprise, and embedding themselves deeply into our daily lives. Companies must be ready to respond.

It’s an evolution which is already underway, perhaps without us even realizing it. Applications, data, and infrastructure are merging into systems, blurring the boundaries of the conventional IT stack. Those systems are embedding themselves into everything, expanding their role throughout the enterprise, into the business ecosystem and beyond.

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THE CHALLENGES OF ACCELERATED CHANGE As these future systems evolve,

companies will face significant challenges in reaping the benefits.

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fuel tomorrow’s growth is a workforce tied to the technologies of yesterday. Already, 40 percent of employers report talent shortages.4 And with significant upshifts expected in skill requirements, that gap is likely to increase—dramatically. In fact, by 2020, more than a third of the desired skillsets of most jobs will be comprised of skills not yet considered crucial today.5

97%of a company’s decisions are made using data that its own managers think is of unacceptable quality.

Or consider the limitations of existing technologies. For example, business leaders know that strategic partnerships will be increasingly critical to future growth. Eighty-five percent of business and IT executives surveyed agree the strength and impact of ecosystem relationships will rest on how well an organization’s technology can support the partnerships. Yet many are restricted by technology that wasn’t designed for the sheer scale of connections a business needs to make today.

Data, too, can be a constraint. A recent study estimated that 97 percent of a company’s decisions are made using data that its own managers think is of unacceptable quality.3

This extraordinary lack of confidence in data veracity will have ever more serious consequences. In particular, the ability of companies to use AI effectively will be severely hindered. But perhaps the biggest obstacle to scaling the innovations that will

The breakneck pace of change continues to cause growing pains, particularly for organizations which are held back by patchwork ways of working and applications built for another era. Even those who have embraced the need to make their core systems future ready face a fundamental challenge of bridging them with the new systems that allow true innovation at scale.

The risk of not meeting these challenges? Collaboration is slower and scaling innovation is that much harder. Consider that, “through 2020, more than 75 percent of organizations will have to maintain multiple different governance, delivery, and operating models to meet the changing needs of digital business.”2 That’s simply not a sustainable way of running a company.

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So how can organizations overcome these challenges and seize the coming opportunities?

Only by understanding the characteristics of thriving future systems—boundaryless, adaptable, and radically human—can they scale tomorrow’s innovations and maximize value in an era of constant change.

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INTRODUCTION

The conventional IT stack has reached its practical limit for fueling business innovation. Now, systems are breaking down barriers—within the IT stack, between companies, and between humans and machines—giving businesses near-infinite opportunities to improve how they operate. Companies must design for a world of constant disruption by decoupling the entire IT stack and moving to dynamic, “everything-as-code” systems. They must also ensure interoperability through a uniform approach to data, security, and governance, while leveraging a blend of cloud and edge computing.

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To minimize friction and scale innovation, companies need systems that seamlessly adapt to business and technology change. Advances in trusted data and intelligent technologies are powering systems that can learn, improve, and adapt by themselves. But this is not a vision of a world without people—humans are an equally critical component of adaptable systems, collaborating with machines to make reliable decisions and take confident action exponentially faster. Making systems adaptable requires flexible, living architectures, new ways to protect and nurture valuable data, and responsible approaches to AI.

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Technology interfaces are becoming invisible. Elegant and simple experiences are the new normal. Finally, machines can adapt to humans, rather than the other way around. Natural language processing, computer vision, voice recognition, and machine learning are equipping systems with the ability to talk, listen, see, and understand the way people do. Companies can now reimagine systems to empower new human–machine relationships with natural conversation, simple touches, and abundant personalization. To do so requires a culture of end-to-end ownership, exploiting human-centric development processes and a frontier spirit of experimentation.

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INTRODUCTION

On this journey to future systems, conventional thinking about how we build and deploy technology and embed it in our businesses and our daily lives must be upended. But, just as important, we must be prepared to reimagine our talent strategies for a world that will look very different from today.

Now is the time for every company to start scaling innovation in the new by building the expansive, flexible, human-centric systems necessary for future success.

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The next new normal for executing business strategies with technology

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Blurring technology boundaries create new space for business innovationThe conventional IT stack—spanning applications, data, and infrastructure—has reached its practical limit. It simply wasn’t built for today’s complex, ever-changing world containing billions of devices, petabytes of data, and countless decentralized applications scaling for millions of users. In the wake of this technology explosion, boundaries are blurring across the stack and beyond.

Computing infrastructure, for example, is no longer fixed, but rather continuously shaped by code, making it essentially indistinguishable from applications.

The result? Nimble business capabilities that allow fast and fluid reactions to market conditions and create new spaces for companies to capitalize on business innovation.

Why:

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What:

Increasingly, applications, data, and infrastructure, humans and machines, and companies and partners are becoming ever more entwined. In fact, the concept of the standalone “application” in modern system development is rapidly disappearing. Applications, data models, and infrastructure are embedding themselves seamlessly into ever more devices in ever more connected places.

Distinct layers of applications, data, and infrastructure, as well as architecture, are giving way to more componentized, decentralized platforms. The rapid adoption of AI is contributing to disappearing boundaries between humans and machines, creating new interdependent ways of working. And companies are reaching ever deeper across their networks of customer and partner ecosystems to reduce friction in their operations and customer interactions.

Innovating beyond the boundaries of the enterprise

In place of the standalone application, companies are starting to reimagine their IT stacks as boundaryless systems of complex machine, employee, consumer, partner, and competitor interconnections. Today’s platforms are already breaking down traditional barriers, enabling companies to connect together best-of-breed services to meet specific needs and solve complex problems.

In customer experience, for instance, SAP Hybris and Accenture are creating a new ‘experience conductor’ platform that orchestrates a range of vendors, data sources, and functions in a single integrated solution, offering companies the optimal mix of tools and insights to help them quickly create differentiated omnichannel e-commerce solutions.6

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Consider, too, how companies like Filament are opening up the network edge. Their platform is challenging the cloud status quo—using blockchain and the Internet of Things (IoT) to enable secure and autonomous edge-computing transactions through a decentralized network stack—independent of underlying infrastructure. Distributed edge devices on the Filament platform can exchange value between themselves in the form of data, network access, cryptocurrencies, compute cycles, and trusted introductions to other devices.7

Rail is a great example of an industry where this kind of boundaryless decentralized system could be transformational. Locomotives, cars, switch motors, and other infrastructure would be able to leverage real-time data, run preventive analytics, enable more targeted maintenance, and greatly reduce the risk of dangerous and costly derailments.8 The consensus around these trends is growing. Industry analysts predict that “by 2022, as a result of digital business projects, 75 percent of enterprise- generated data will be created and processed outside the traditional, centralized data center or cloud (up from less than 10 percent in 2018).”9

The blurring boundaries of the IT stack are breaking down barriers between enterprises and reducing the friction that inhibits the effectiveness of business ecosystems. Consider that in the food industry, fierce rivals Nestlé, Unilever, Tyson, Kroger, and Walmart have come together with IBM to solve a business problem common to them all: ensuring food safety within their highly complex supply chains. In creating a secure blockchain-based system for sharing data, they’re improving transparency and tracking food products far more efficiently.

In a pilot deployment, Walmart showed they could dramatically reduce the time taken to trace in-transit mangoes back to their place of origin. A task that once took a week was performed in just 2.2 seconds.10


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Boundaryless systems are a new paradigm for most of today’s businesses. Many companies simply don’t have the right culture to partner at scale. What’s more, their legacy business processes and systems weren’t designed to support boundaryless expansion.

Both of these factors will hinder future growth. Here are some practical steps every company can take to capitalize on business innovation through boundaryless systems and convert the breakneck pace of technology into an opportunity to outperform the competition.

Next steps for architecting a boundaryless tomorrow

How:

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For some, applications in the cloud may seem like yesterday’s news. But for many, there is still much to do to truly exploit the transformative potential of cloud services. That’s because cloud isn’t the finish line—it’s the starting point, with edge computing right behind. Cloud is a mandatory foundation for the boundaryless future.

Moreover, the most successful companies treat the cloud not just as a cost-effective data center, but as a source of continuous business innovation. Consider how Salesforce is benefiting from its own cloud-based AI technology, Einstein, to improve business performance. It creates a smart layer to support sales forecasting, as well as pipeline and sales organization management.

Break through the cloud ceilingThe message for today’s businesses is clear: If you’re not making pervasive use of cloud services already, you should be. IDC predicts that, by 2021, 80 percent of application development will take place on cloud platforms using microservices and cloud functions.11

Thanks to the countless new possibilities that a blend of cloud services and edge computing opens up, embracing cloud is a crucial first step in capturing the value of boundaryless systems.


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Constant disruption is now a fundamental part of today’s business landscape. Companies simply cannot expect static technology investments to continue returning value. Systems built today will inevitably be disrupted tomorrow. To ensure maximum flexibility in this ever-changing world, companies must design interoperable systems by applying a uniform approach to data, security, and governance. Just as protocol standards were critical to scaling and globalizing the Internet, uniformity of design will enable interoperability of boundaryless systems.

What does this look like in practice? Take mobile app development tool Amazon Cognito, a lynchpin for consistent identity and state management across competing, third-party platforms. If an app supports multiple identity providers (Google, Facebook, Amazon, etc.), Amazon Cognito can bind them into a single uniform

identity, enabling developers to provide flexible and interoperable authentication without disrupting an app user’s overall experience.12

Or, consider online payments. Stripe, a payment- processing startup, has established new standards to handle the complexities of numerous payment methods, off-site redirects, checkout flows, international sales requirements, and a myriad of languages and country-specific regulations. Stripe’s simplicity and flexibility mean any website can handle e-commerce with just seven lines of code—reducing weeks of work to mere seconds.13

By helping companies design for disruption, elegant and flexible architectures like these anticipate and insulate against change. Crucially, they obviate the need to “replumb” entire systems as disruption inevitably occurs.


Design for disruption Step 2:

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Decoupling is another crucial step toward boundaryless systems. By going modular and decoupling infrastructure, data, architecture, and applications, companies can remove unnecessary dependencies across all layers of the solution stack. This approach creates a series of manageable, modular components that can be assembled in a flexible system to address business requirements at the point of need. It’s a crucial step, not just in freeing the value locked in legacy systems, but also in bridging core and new digital systems, and paving the way for innovation at scale.

There are three principal ways to establish modularity through decoupling. First, decoupling data and applications. This means enabling a real-time, continuous stream of valuable company data and events, including data trapped in legacy applications or from outside the enterprise. Uber uses such an approach, making its data accessible internally to any consuming service. It enables the company to rapidly adapt to a global patchwork of different laws, rides, payments, traffic patterns, and human resources.14


Decouple the entire IT stackStep 3:

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Second, decoupling applications from legacy infrastructure. By migrating to a cloud platform, companies can achieve scale and seamlessly accommodate different application workloads. This eliminates high fixed costs and shifts IT expenditure from capital to operational budgets. With a cloud platform in place, companies are well positioned for the inevitable shift from virtual machines to containers and to a serverless architecture, where infrastructure management is automated and invisible. This allows businesses to focus on “what an application does” rather than “where and how the application runs.”


Third, decoupling tightly integrated systems into loosely coupled systems, layering and modularizing those systems using APIs, event streams, containers, and microservice patterns, while continuing to decouple data and infrastructure. This is exactly what MetLife accomplished when it used Docker’s secure container platform to develop and manage microservices and “wrap” decades’ worth of legacy systems with modern and open-source components. The new system can pull data from multiple sources and be deployed anywhere globally, on-premise or in the cloud, to provide a consistent, efficient, and secure online customer experience.15

For more detail on the value of digital decoupling, read Accenture’s point of view, “In the Blink of an IT”.

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When boundaries disappear, new spaces open up. This creates a new landscape—one where new ideas and unconventional partnerships can flourish. It lets companies come together in new ways to solve significant business, consumer, and societal problems. It means they can piggyback on technology advances to reduce the friction in today’s processes, transactions, and business models. And it means they can scale innovative ideas with new speed and agility. The not-for-profit company set up by Amazon, Berkshire Hathaway, and JPMorgan to resolve the seemingly intractable issue of ballooning healthcare costs is one example of what becomes possible when boundaries fall away.16 The success of disruptive business models like Uber’s, founded on a new technology landscape of pervasive mobile connectivity, is another.

Leading companies are taking every opportunity to explore the contours of these new uncharted spaces. Goldman Sachs, for example, is redesigning its entire business to transform the company into the “Google” of Wall Street. Their approach

is founded on the idea that helping clients manage risk is at the core of what the bank does today and is fundamental to their future. Capitalizing on the valuable data they collect and store, their vision is to run that data through analytics engines, and then make it available to a wider audience on a digital platform, much like Google’s search and analytics services are available on a self-service basis.17

What about streamlining global trade? Few challenges come any bigger. The World Economic Forum thinks reducing barriers within international supply chains could increase global trade by nearly 15 percent, boosting economies and creating jobs in the process. This has inspired Maersk to form a global trade joint venture, using blockchain and other advanced technologies to develop a digital open trading platform for use by the entire global shipping ecosystem. The ultimate goal: greater transparency and simplicity in the movement of more than $4 trillion in goods across borders and trading zones each year.18


Explore new, unconventional business models

Step 4:

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Boundaryless systems create near-infinite opportunities for leaders to scale innovation in the new.


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Eliminating the friction that hinders business growth

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Adaptable systems can offer organizations an ability to seamlessly adjust to persistent change. Using data and machine intelligence, they can minimize the friction that hinders a company’s ability to operate efficiently and scale new innovations with speed.

At the heart of adaptable systems is a cooperative, transparent partnership between humans and machines—one that fosters truly reliable decision-making —to harness disruptive change for positive and material business impact.

Adapting to business and technology change is harder than ever

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Why:

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Advances in trusted data and intelligent technologies are powering systems that can learn, improve and adapt by themselves. But this is not a vision of a world without people—humans are an equally critical component of adaptable systems, collaborating with machines to make more reliable decisions, and take more confident actions, exponentially faster.

Adaptable systems start with living architectures. As each company’s portfolio of systems and partnerships grows, traditional architectures simply can’t keep pace with the sheer scale of business and technology connections. In their place, adaptable, dynamic, “living” architectures, including microservices and serverless architectures, are fostering new levels of organizational agility and scale.

Using data and AI to smooth out business friction


Consider Nordstrom, an established company with a wealth of valuable data in a fast-changing retail market. They became an early adopter of a serverless architecture to achieve an advantage over emerging competitors by dramatically improving their ability to provide personalized, real-time shopping experiences. Their serverless architecture also allows them to dynamically adapt and scale in response to real-time retail events associated with a particular product, customer, or salesperson.19

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Today’s spectrum of new and intelligent technologies is also a vital part of adaptable systems. Whether it’s robotic process automation, virtual agents, natural language processing, machine learning, advanced analytics, or other forms of AI, companies have a host of opportunities to substantially upgrade how they do business once their architectures are ready to make AI an integral part of the transaction flow. By finding a responsible, transparent balance between human and machine intelligence, and combining it with more basic forms of robotic process automation, adaptable systems can create value in ways that have never been possible before.

Take online shopping service Stitch Fix, which uses both human and machine intelligence to match the right products with the right customers. The company uses AI to sift through mounds of customer preference data that helps their human stylists confidently choose products customers will love, while giving stylists more time to release their natural creativity.20


Adaptable systems are fueled by trusted data. Systems that can adapt and improve by themselves—such as conversational interfaces that continuously learn new speech patterns—rely on vast amounts of high-quality, trusted data. Unverified data is now a serious business vulnerability for companies who depend on adaptable systems to plan, operate, and grow. Every organization must ramp up its data integrity efforts to tackle the inaccurate, manipulated, and biased datasets that lead to corrupted business insights. Moreover, today’s near-infinite security risks demand new adaptive approaches to protecting that data and keeping systems resilient.

Think about how blockchain is enabling tamper-proof data sharing across a business ecosystem. By allowing different systems to talk directly to each other—and trust each other’s data from the outset—this technology is creating completely new types of adaptable and frictionless interaction. The blockchain-based food tracking system Provenance is a prime example. By letting food suppliers create a secure digital record for any of their products, it ensures authenticity throughout the supply chain. This system is already being used to help consumers in the UK know exactly where their food comes from.21

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With flexible, living architectures, with new ways to protect and nurture valuable data, and with responsible approaches to AI, an organization can eliminate its greatest points of business friction. Here are some practical steps companies can take to put the building blocks of adaptable systems in place.


Becoming a data-guided, adaptable business

How:

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The era of the three- to five-year architecture roadmap is over. To truly reimagine the way a business transacts today, architectures can no longer be set in stone. Instead, companies must create architectures that can constantly flex and adapt to an ever-changing set of requirements.

That’s the approach Zalando, a German e-commerce fashion giant serving 15 European countries, took when faced with substantial scaling challenges. Their engineers were telling them they “couldn’t update anything without updating everything.” But thanks to the adoption of an

API-first approach and microservices-based architecture, they can now maintain highly stable interactions between systems that are constantly evolving.22

We call this step an architectural intervention because letting go of old practices requires a careful process of persuasion, bringing others in the organization along on the journey to achieve both cultural and technological change.


Stage an architectural intervention

Step 1:

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To smooth out the friction in business transactions and create more direct connections with partners and customers, companies can leverage technologies like AI, blockchain, and microservices to make their systems self-healing and adaptive. In parallel, they must also recognize that organizational change may be a necessary precursor to solving their most significant business challenges. Where to begin? By prioritizing the systems that are most critical to the bottom line.

Consider the Bank of New York, which deployed more than 200 bots across its business to drive efficiency and cut out costly errors. This cadre of robotic assistants is accelerating the bank’s critical payment processing by reducing the time spent by employees identifying and dealing with data mistakes. Organizational change has been a key part of this innovation. Many of the bank’s bots originate from its new global innovation centers, where teams are organized around solving particular problems—with the freedom to reimagine ‘the art of the possible.’23

Or what about the State Bank of India? In deploying a blockchain system that allows each of its banks to maintain a copy of all transactions, it has sidestepped the need to maintain its own database. As each new transaction occurs, the system updates all records simultaneously, obviating the need for reconciliations between different banks.24

AI can be used to identify as well as eradicate friction points. Startup Anodot’s software uses machine learning to analyze operational data and automatically predict potential pain points. It means, for example, a retailer can detect if a competitor’s new campaign could cause a drop in sales, giving them the opportunity to quickly respond. Machine learning can also help applications learn to defend themselves from attack, using algorithms to continuously identify vulnerabilities and then triggering self-healing or protective mechanisms.25


Identify the biggest friction points in your business

Step 2:

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To be effective, AI must gain the trust and confidence of the humans it works with. First and foremost that means being transparent in explaining the decisions and actions AI takes. But it also means allowing humans to step in and take back control when necessary. That’s essential in avoiding the risk of adverse effects on business performance, brand reputation, regulatory compliance, and, above all, human beings themselves.

Take Drive PX, NVidia’s AI-infused self-driving car platform. Even for the company’s own engineers, explaining exactly how Drive PX was teaching itself to drive was proving a challenge. So they developed a way for the machine to explain its driving style visually. By using video of recently driven streetscapes overlaid with the areas prioritized

when making driving decisions, Drive PX is opening up the “black box” of AI learning and taking a step forward for explainability.26

AI decision-making can have regulatory consequences too. The European Union’s General Data Protection Regulation gives individuals a “right to explanation” for decisions made by AI and other algorithms. For example, this gives consumers the right to understand how a car insurer calculated the premium they were offered. If the information used in the calculation is wrong, it gives consumers the opportunity to flag and fix it. This is just one example of how humans need to work hand in hand with machines to keep AI systems from drifting into incorrect or undesirable decision-making.


Understand the need for responsible AI

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Good data yields confidence in adaptable systems. So companies must start with quality data and apply a data-centric approach to their most important business decisions. Seventy-nine percent of business and IT executives surveyed agree that organizations are basing their most critical systems and strategies on data, yet many have not invested in the capabilities to verify the truth within it. These organizations are missing opportunities to generate more value from their data, and build a strong foundation for other strategic initiatives.27

Consider Salesforce CEO Marc Benioff, who uses data and AI to help him run his staff meetings and eliminate the effect of internal politics. He says having purely data-based forecasting and modeling has transformed him as a CEO because it comes without bias.28 Consider also Kensho’s machine learning systems, which are helping some of the largest trading desks in the world crawl through reams of data and market-moving information, searching for correlations between world events and their impact on asset prices.29

Data should be at the core of software development as well. Companies should be defining data-driven development and testing processes that account for the data-dependent nature of adaptable systems. Take Panoply, a data platform company using machine learning and natural language processing to model and automate activities performed by data engineers, server developers, and data scientists. By automatically aggregating data as it streams in, the platform allows organizations to analyze everything in seconds, regardless of scale and without the need for data configuration, schemas, or modeling, it saves thousands of lines of code and countless hours of debugging.30


Let data be your captainStep 4:

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Adaptable systems empower people to thrive in the face of changing requirements and environments.


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Talking, listening, seeing and understanding—just like we do

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3: RADICALLY HUMAN SYSTEMS

The breakneck pace of technology evolution means we can now do something we’ve long dreamed of: build systems that talk, listen, see, and understand the way we do.

Radically new and elegantly simple experiences can be centered around our true needs and desires. It means tomorrow’s advantage will go to those who design systems that adjust to people—not those who continue to expect people to adjust to systems.

Creating advantage through systems that truly work for people

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Radically human systems emerge when new kinds of human–machine interaction come together with data, intelligent technologies, and whole ecosystems centered around the user. They understand and serve the unique needs of every individual, sensitive to their particular social and cultural context. This is now the frontline of competitive differentiation. Every organization should be striving to build elegantly simple interactions that elevate human–machine experiences through technology, personalization, and partnerships.

Natural conversation and simple touches are already overtaking the laborious physical manipulation of technology, making the keyboard and mouse increasingly obsolete tools, freeing us from passwords, and driving a

Elegant simplicity in every individual interaction

rapid evolution in how we interact with the screen. As they do so, the technology—whether voice, smart hardware, or visualization tools—is becoming ever more “invisible” as it fades into the fabric of our lives.

Voice interaction is now everywhere, from HSBC’s mobile banking app to Apple’s Airpods. It lets us bank, dictate documents, or perform numerous other tasks easily without interrupting what we’re doing, whether that’s riding a bike or getting a massage. And when voice is blended with biometrics, even more possibilities open up. Mizuho Bank, for instance, is working with Sensory and Fujitsu to fuse voice and facial recognition into its mobile banking app, creating an experience which is both more secure and more accessible.31

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Extended reality—which refers to the spectrum of experiences, including virtual and augmented reality, that blur the line between the real world and the simulated world—is also taking hold at pace. Gartner expects that “by 2021, 25 percent of large businesses in mature markets will be piloting and deploying mixed reality solutions (up from just 1 percent today).”32 Take DHL, which is already using augmented reality glasses to display order picking and placement directions for operators, freeing their hands from paper instructions and allowing them to work more efficiently and comfortably. Extended reality has helped the company boost average productivity by 15 percent—while also improving accuracy.33

Personalization, powered by data and AI, is at the core of these radically human systems. Consider how a large organic grocery store used data, AI, voice, and augmented reality to transform its stores built for the masses into curated experiences for individual shoppers. With an understanding of a customer’s diet preferences (Paleo, low sodium, gluten-free, organic, etc.), the store uses augmented reality to highlight relevant items on the shelf. In doing so, it’s creating a new kind of one-to-one interface which is both scalable and differentiated for the shopper and the brand.34

While companies are focused on acquiring as much customer data as they can, many still struggle to use it effectively. Breakthroughs in AI will be the key to unlocking unique personalized experiences at scale. Take Affectiva, a company using computer vision, speech analysis, and deep learning to classify a person’s emotions in real time. It can detect when a driver is tired, for example, and could thus be used to intervene and dramatically improve safe driving experiences.35

Radically human systems are about more than just the technology, however. They also require new partnerships within and between organizations to support a complex web of user needs. Consider how AI and voice technologies can be combined with human services to help the elderly live independently for longer, assisting with day-to-day activities and helping prevent the heartache of loneliness. Eldercare HomeCare, for instance, is a system designed by and for the elderly which integrates events, activities, and relationships—bringing the whole support ecosystem of health, medical, financial, food, social, home services, and security partners together in one easy-to-access platform.36

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Radically human systems are already upending decades of conventional thinking about human–machine interaction, along with many adjacent processes. Just consider that the main interface we use today—the keyboard—has been around since commercial typewriters were first introduced in 1874. Now, that’s all about to change. Here are some practical first steps that fast-moving companies can take to start reimagining personalized experiences around humans’ true needs.

Putting humans at the center of everything

How:

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To stay ahead of rapid disruption, smart companies are turning to human-centric design to better connect with customers and find competitive advantage. They’re recognizing that data and technology are not, by themselves, the solution to every problem. Rather, that designing successful user experiences ultimately comes down to empathy—truly understanding the needs of the people using the system. So it’s time to master design thinking, agile practices with multidisciplinary teams, and continuous user feedback, and help bring order and coherence to our chaotic, complex, hyper-connected world.37

Look at how Capital One is using customer-centric design and continuous feedback to combat a commoditizing market with differentiated user experiences. The company took time to speak directly with customers and overcome the preconceived beliefs of some of its analysts. New user-centric processes are helping the company define and solve the most important customer pain points in a way that is data-driven, repeatable, and agile.38

Or consider how major automakers are leveraging real user insights to fine-tune features. In bringing popular apps like Spotify, Yelp, Facebook, and Wikipedia to the dashboard, they must balance the new interactive services with the need to avoid too many driving distractions. BMW, for example, worked with Applause to crowdsource a testing community that provided real user insights, helping them validate the viability of new customer experiences.39


Master human-centric development Step 1:

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Companies should be scrutinizing whether their organizational or cultural boundaries are hindering the speed and accountability needed for developing radically human systems. They should also be assessing their products, services, and business models holistically, embedding an end-to-end ownership culture from initial idea all the way through to user experience.

Consider how the Republic of Estonia has streamlined citizen experiences by enabling fast, secure data sharing between 52,000 government organizations and private enterprises. All public data, from medical records to residency information, is exclusively stored by local offices. But, when completing a task that requires cross-departmental information—creating a birth certificate or filing a police report for instance—government employees can quickly execute the transaction by automatically authenticating identity or verifying access to deliver a seamless user experience.

By breaking down organizational boundaries, the solution addresses citizen needs quickly and saves Estonians 800 years of working time every year.40

Change on this scale can sometimes seem alarming to the workforce. Establishing an ownership culture that promotes trust and transparency is another important step in overcoming any inherent anxiety about new technologies, especially with respect to job displacement. To foster positive experiences, companies should make it clear to employees and customers how new tools and technologies can make everyday interactions more engaging. At Stitch Fix for example, stylists don’t see AI as a threat, but consider machine co-workers their “new BFFs,” helping the stylists do their job better and faster by algorithmically winnowing down the vast number of possible clothing and accessory recommendations.41

Break down organizational and cultural barriers

Step 2:

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Radically human technologies like AI, extended reality, and voice will grow explosively over the next few years. According to IDC, augmented and virtual reality headsets are set to show a CAGR of 51 percent through 2022.42

Early experimentation and hands-on experience are the best ways to start socializing and imagining the commercial possibilities of these technologies as they mature.

Look at the way a sense of experimentation helped Domino’s Pizza in their successful recent transformation. The company acknowledges it took a risk when it introduced voice ordering on its app more than four years ago. But, as Chief Executive J. Patrick Doyle explained, it was worth it: “We fundamentally believe that voice is a far more effective and efficient way for people to interact with technology… What we do

with it is going to be refined over time, but we need to get into this and start learning.”43 Accenture has the same aspiration for its Tech4Good initiative, which uses technology to help solve critical challenges faced by business and society.

Drishti, for instance, is a solution designed with the National Association for the Blind in India which provides help for the visually impaired through smartphones. Using AI technologies such as image recognition, natural language processing, and natural language generation, the solution narrates to the user the number of people in a room, their ages and genders, and even their emotions based on facial expressions. It can also be used to describe text from books, documents, and currency notes, as well as to identify physical obstructions like glass doors.44


Don’t wait to experiment with emerging technologies

Step 3:

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Radically human systems combine leading-edge technology and human -centric design to create tomorrow’s advantage.

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As systems evolve, so must the IT workforce. In fact, a workforce tied to the technologies of yesterday is one of the biggest obstacles to creating the expansive, flexible, human-centric systems necessary for future success. Companies must be prepared to reimagine their talent strategies for the next era of human–machine collaboration.

To do so, they’ll need a workforce of renaissance system engineers—multidisciplinary talent which can bridge infrastructure, development tools, programming languages, and machine learning, while also being deeply immersed in how the business works and how it makes money.

The single most important investment a company can make to support boundaryless, adaptable, radically human systems—their talent.

They’ll also need to combine their human talent with a growing army of smart machines to create the entirely new kinds of hybrid IT roles that can drive a business forward on innovation and profitability. And they’ll need to develop new ways to continuously evolve their workforce, using ongoing learning and organizational transformation to adapt to the relentless pace of technology advances.

OUTPERFORMING WITH FUTURE TALENT

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FUTURE TALENT

But how? There are five distinct steps to build future talentBy addressing each of these five steps, an organization can put itself in the optimal position to build thriving systems in a world of constant change.

Define the new organizational model and key roles, evaluating individual tasks not just jobs.

Describe the skills and competencies needed for the new organization, including those best performed by machines.

Assess the skills of the existing workforce and identify gaps.

Explore dynamic approaches and new channels for sourcing talent, using crowdsourcing and machine resources where appropriate.

Prioritize the skills to be developed, reskilling and retooling the existing workforce using collaborative learning.

For additional reading, see Human + Machine: Reimagining Work in the Age of AI by Paul R. Daugherty and H. James Wilson and Accenture’s Reworking the Revolution research.

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CONCLUSION

How can an organization build thriving systems to scale new innovation in a world of constant change? First and foremost, by recognizing how today’s systems are already evolving, becoming ever more pervasive and embedded in businesses and daily lives, changing the very nature of human–machine relationships.

With an agile and flexible approach to enterprise technology, tomorrow’s leaders will build the boundaryless systems that create new spaces for ideas and partnerships to flourish. They’ll engender new levels of agility with adaptable systems, exploiting trusted data and breakneck

advances in AI to eliminate business friction. And they’ll elevate human–machine interactions with natural, elegant, simple, and radically human systems, helping technology become ever more “invisible” to its end users.

Along the way, they’ll reimagine their approaches to finding and developing their talent. They’ll use new sourcing strategies, new kinds of human–machine interaction, and continuous learning to create multidisciplinary “renaissance” engineers whose expertise spans applications, infrastructure, machine learning, and business purpose.

Be boundaryless. Be adaptable. Be radically human.

As they do so, they’ll be building the future systems that can truly meet the needs of their markets, customers, and communities. And with the ability to innovate at scale, they’ll be positioned to lead in a world where nothing ever stays the same.

Is your business ready to join them?

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About AccentureAccenture is a leading global professional services company, providing a broad range of services and solutions in strategy, consulting, digital, technology and operations. Combining unmatched experience and specialized skills across more than 40 industries and all business functions—underpinned by the world’s largest delivery network—Accenture works at the intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders. With approximately 459,000 people serving clients in more than 120 countries, Accenture drives innovation to improve the way the world works and lives. Visit us at www.accenture.com

About Accenture ResearchAccenture Research shapes trends and creates data-driven insights about the most pressing issues global organizations face. Combining the power of innovative research techniques with a deep understanding of our clients’ industries, our team of 250 researchers and analysts spans 23 countries and publishes hundreds of reports, articles and points of view every year. Our thought-provoking research—supported by proprietary data and partnerships with leading organizations such as MIT and Singularity—guides our innovations and allows us to transform theories and fresh ideas into real-world solutions for our clients. Visit us at www.accenture.com/research

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