GROWTH STRATEGY THEMES FOR SMART SYSTEMS SUCCESS

Successful IIoT strategy development needs to address one or more of the following themes:

• IoT and connected product technologies are enabling radically new user and customer experiences and informing equally disruptive business models (think of Apple, Amazon, GE Digital, etc.) – we believe competitive differentiation will shift away from traditional means such as product/brand position, low cost manufacturing position, channel/support capabilities or similar towards how intelligent products are experienced and how networked products foster interactions between and among manufacturers, users, technology alliances, channel partners, etc. in a networked context.
• Leveraging new digital data values inherent in connected products and systems will require new infrastructure and enabling technologies that will, in turn, inform the formation of new and different market relationships and alliance networks.
• As the complexity of these systems continues to increase, the number and diversity of stakeholders, users, sellers, supporters, etc. involved and interacting with these systems will also rise in a way that creates a “social system” comprised of diverse relationships. We believe that within this social system [or ecosystem] there will be more dominant and subordinate personas interacting with these systems.
• The corresponding development of new value networks and ecosystems of complementary equipment and device OEMs as well as third party application, services and solution providers will force players to make choices about who they create relationships with; a phenomenon we call “strange bedfellows.”
• The technical innovation driven by IoT technologies coupled with changing relationships between and among complementary players will cause changes in market structure and potentially [likely] cause shifts in the sources of profit and value creation.
• Players have an opportunity to lead and become a central organizing market player, coordinating and orchestrating the aggregation, sharing and brokering of valuable new equipment and device data which, in turn, enables a whole new range of customer experiences and optimized services.

Perhaps the most important perspective and learning we have come to is the relationship between technology and business model and the “role” of integration architecture and development platforms play in enabling new solutions.  This perspective does not just come from our own thinking; it’s from the diverse community of people we have come to know who are thinking about the scope of “architecture” that “Smart Systems” deserves.

Our evolving “thesis” goes something like this: as the complexity of these systems increases, the number and diversity of stakeholders expands, (users, sellers, supporters, benefactors, etc.), and the volume and nature of their interactions grows, the systems or “technology architecture” will become more and more tightly coupled to the “business architecture” and therefore, in turn, the required architecture and technologies to inform a radically new view of data and information-driven services must be aligned with the corresponding business and revenue models these technologies will inform.  These two “architectures” must be viewed in close proximity. The two thrusts need to be mutually supportive without inhibiting one or the other.

Many of the participants in this emerging arena we speak with are coming to see the continuously evolving relationship between technology architecture and business architecture as fertile ground for innovation.  They need to be interwoven and mutually supportive.  In fact, from our own direct consulting experiences, we believe success in either increasingly goes to the company that effectively utilizes the combined potential of both.

WHAT IS REALLY REQUIRED FOR STRATEGIC DEVELOPMENT?

It’s About Doing Things Differently

The modern business enterprise has been deconstructing for decades.

We have re-evaluated how we work with our clients and think a new approach is in order – one that balances the qualitative with the quantitative – which we feel is more revealing in markets that hold a recognizable shape barely long enough to be described or measured.  Developing new smart systems and services businesses requires abandoning traditional protocols.

Our core learnings/beliefs follow:

• Spotting Trends and Emerging Discontinuities: companies need to learn how to spot emergent trends “around corners;” staying close to customers, vigilantly tracking competitors maneuvers and tapping alliance and ecosystem partners for new insights is critical.
• Designing New User and Customer Experiences: understanding the customer experience through the user’s eyes enables a much deeper human-centered appreciation of how solutions align with needs; engaging ecosystem partners and “strange bedfellows” in participatory design fosters an acute understanding of the potential business system to support a new solution.
• Organizing Clever Combinations of Smart Systems Technologies: creative combinations of new technologies can enable sustaining differentiation and are often discovered in very unexpected and unfamiliar places – systematically searching in non-traditional industries and domains can lead to the discovery of new and novel solutions to customer needs.

• Extending Skills Through New Relationships and Ecosystems: new digital and smart system solutions will increasingly be comprised of coalitions of diverse self-motivated participants that pursue a common goal, not mere subcontractors tied to “command and control” schemes.
• Rapid Experimentation & Business Systems Innovation: success will depend upon understanding and choosing new or modified business models and acting quickly; continuous experimenta­tion is a must as new opportunities will often fail and re-form as learning grows.

• Aligning the “Business Architecture” with the “Technology Architecture”: as digital and Smart Systems technologies become more deeply embedded into new business solutions, the “technology architecture” will need to become more closely coupled and aligned to the “business architecture” to inform and enable new value — the two “architectures” must be viewed in close proximity and need to be interwoven and mutually supportive without inhibiting one or the other — success in either increasingly will go to the companies that effectively utilize their combined potential.

DISTILLING 35 YEARS IN SMART SYSTEMS TO A SET OF GUIDELINES

The new era of ubiquitous Smart Systems requires a new mode of operating. We’ve compiled the following guidelines based on years of consulting with the largest players and developing ongoing intelligence into our core emerging research themes.

New Business Models

• The dis-integration of traditional enterprises driven, in part, by the decades long wave of outsourcing, is restructuring businesses into three broad segments or roles: platform players, horizontally-focused providers of outsourced “professional services” and, vertically-focused “specialist” product and service businesses.
• The influence and disruptiveness of platform companies affect much of the business world these days. Platforms can come in many types, including a de-facto standard such as Cisco’s network operating system or Microsoft’s Windows (or Azure today), or the immense scale of Facebook’s (now Meta’s) user base enabled by social relationships and interactions.
• Platform business models that creatively combine elements of dis-intermediation, new relationships, shifting profit pools, new recurring services, customer transparency or other maneuvers are all disrupting existing business and operating models – just consider the scale and impact of technology-based platform models like Google, Apple and Meta.
• To date, most of the successful platform models are more consumer-focused. Few, if any, B2B markets have really embraced the “as-a-service,” consumer-focused model, but we believe the model is spreading. Freight logistics, genetic sequencing, travel, order management, customer relationship management, asset management, etc.
• The growing influence and disruptiveness of platform models is forcing all businesses to think more carefully about their future role and, since not all businesses can be platform players, which role suits them and which players can they form win-win partnerships to maximize value for customers.
• As businesses come to understand that future enterprises will all be part of ecosystems and new value delivery networks largely comprised, in varying combinations, of these new roles, they are recognizing the era of “going it alone” or “flying solo” is over and the “command-and-control” alliance and partnering strategies of the past will not be effective in the complex, instantaneous, interwoven global digital economy.

New Skills and Organization Designs

• The technical innovation driven by digital and IoT technologies, coupled with diverse and changing relationships between and among complementary players will likely lead to changes in market structure, shifts in the sources of profit and value creation and thus, new business and operating models. Identifying and designing new business models along with developing the new skills, capabilities, systems and organizational relationships they require will be critical to success.
• Both platforms and outsourcing will require huge scale, but small product and service companies will be able to use that scale to thrive as well. “Everything as a service” will be available on demand, from a mix of horizontal (cross-industry) and vertical (industry-specific) outsourcers, with the latter often set up as joint ventures by industry participants. There will be ongoing battles at the seams between the three types of companies.
• Next-generation platforms will become a material force for building community and increasing bargaining power among skilled workers, much as unions have done historically for lower-skilled workers.

New Computing and Information Architectures Inform Relationships

• As the number and diversity of ecosystem stakeholders expands (users, sellers, supporters, benefactors, etc.), and the volume and nature of their interactions grows, the systems or “technology architecture” will need to become more closely coupled to the “business architecture” to inform and enable new information-driven services. These two “architectures” must be tightly interwoven and mutually supportive without inhibiting one or the other.
• These advances require computing resources that are fully distributed, both for functional and for economic impacts (i.e. eliminating the latency involved in sending and receiving data from the cloud; reducing the costs and economic impacts on network infrastructure and computing resources; and, leveraging AI for language processing and image recognition to enable new time and context-dependent interactions between people and systems, to name a few examples).
• Just as tides shift according to the gravitational pull of the moon, the distribution of computing resources needs to shift dramatically from centralized to decentralized to fully enable large scale interactions and collaboration. Just as the extensible, technology-neutral nature of the Internet has allowed it to scale so dramatically and gracefully with minimal central administration, we need a similar approach to enabling the diverse interactions between systems, data, institutions and people.

Established Technology Developers and Suppliers Fall Short

• The three primary technical development communities supporting enterprises – the wireless carriers, the IT systems suppliers and the automation and control community – have failed to re-evaluate their relationship to advancing technology and to the evolving enterprise of the future. The technology and business paradigms to which these groups cling today are far too rigid, too cumbersome and too expensive to foster the data interactions and new collaborative business relationships we are discussing here.
• From a technology standpoint, even though we have witnessed a centralizing movement driven by the adoption of cloud storage and cloud computing (Amazon Web Services, Microsoft Azure, and Google Cloud, etc.), rapid decentralization of computing resources is a minimum requirement to extend and enhance the ways we share and interact with data to support new relationship structures and collaboration.
• A handful of startups are accelerating the pace of development in distributed computing, catching larger established rivals off-balance and threatening to effect fundamental shifts in technology markets. Their strategies reflect the increasing importance of the convergence of truly distributed computing and information systems with large-scale collaboration and ecosystems in creating new growth opportunities.

The New Rules of the New Economy

• Aligning and leveraging the respective roles of technology architecture and business architecture often creates contention, but we believe we are entering an era where success in either will increasingly go to the ecosystems and companies that effectively utilize their combined potential.
• The technology and business solutions we are describing will have much less managerial hierarchy, command and control decision making or proprietary ownership of ideas; new data and information architectures will change the very nature of relationships and collaboration.
• Ecosystems and value networks will be self-organized by people who are motivated to explore and develop ideas they care deeply about. Collaborative innovation will extend beyond ideas about new products and services to the very manner in which business is conducted.

Since all that we are describing is a radical departure from current offerings and business practices, and is driven by a very unique set of needs, it stands to reason that this type of solution does not fall within the narrow specialties of most existing players.  In fact, the innovation being described is probably best viewed as an entirely new chapter in the marketplace.  This is particularly true given the disjointed patchwork of solutions presently in place and the apparent lack of vision from existing players of what’s required in the future.

Alliances, collaborative systems, and distributed computing are hardly new but as new developer communities embrace new computing architectures that leverage distributed intelligent sensors, devices and assets, radical new modes of value creation are emerging.  Only those who grasp the new rules of Smart [distributed] Systems and collaborative market creation can win key positions. The opportunity to lead in developing and shaping this market looks wide open for creative players.

These tech superpowers are reshaping how businesses engage with customers and compete. The cloud delivers previously unimaginable scale. Mobile technology provides unprecedented reach. AI can bring intelligence to everything, gleaning insights from massive data sets to complement human intelligence. And IoT connects the physical and digital worlds, bringing technology into every dimension of human progress.

Over the next decade, these technologies will propel innovations that will change the ways we learn, work and live, and will help us address the truly daunting challenges of our time, from climate change to economic inequality. We believe the era of Smart Systems requires a new approach to growth and innovation, but if implemented correctly, it has the potential to transform society and drive humanity forward.

EMERGING RESEARCH THEMES

it’s not a lie that all these isolated phenomena—machine learning, blockchain, nano-medicine, robotic prosthetics, quantum computing, etc.—have come up over the horizon and are hurtling toward us. But after reading these yearly trends wrap-ups, we never believe that we’ve seen a convincing portrait of the future.

Spotting real trends is like watching waves break on the shore, one after the other, while remaining unaware of the deep currents and invisible undertows that cause this surface-reality. The specific trends change from year to year but the impact of the stories is very predictable. They always focus relentlessly on the technologies alone, whereas the real future clearly lies in the complex inter-relationship of many technological, human, business, and societal forces.

The multiple parallel technologies behind the trends have not evolved in isolation. In fact, they have grown up so inter-related and inter-dependent that they not only reinforce each other but create completely new compound effects.

This phenomenon is not just about the impacts of technology on people, business, and societies. It’s also about the impacts of people, businesses and societies on technology development. Networks and information technology’s most profound potential lies in its ability to connect billions upon billions of smart things and people in a way that will stretch the boundaries of today’s business and social systems, and create the potential to change the way we work, learn, innovate and entertain.

So, rather than focusing on “point” technology trends, we are highlighting what we like to call “emerging research themes” that examine the many reciprocal impacts that are occurring between and among technologies, people and society.

COMBINATORIAL INNOVATIONS

In his book, The Nature of Technology: What It Is and How It Evolves, Brian Arthur introduced the idea of combinatorial evolution. Very simply, each of our technologies is a system assembled from earlier technologies. For example, the GPS and navigation systems we take for granted in smartphones combine the predecessor technologies of satellites, computing, radio receivers, transmitters and atomic clocks into a new unified and infinitely more valuable technology.

Today, multiple parallel technology developments appear to be increasingly reinforcing and accelerating one another. Cloud infrastructure resources are providing unprecedented computing scale. Mobile computing devices are extending the reach of computing itself. Machine learning and AI are bringing intelligence to diverse things, and embedded systems and IoT technology are connecting and integrating a broad array of physical and digital applications.

Each of these technologies is powerful on its own, but “catalytic” combinations of these capabilities are multiplying their impacts. Human-connected devices and machine-connected IoT devices enable exponentially more data. The cloud then enables us to capture, analyze and model many phenomena through its computational capacity. This in turn sets the stage for AI and machine learning tools to analyze and capture new insights.

Interestingly, the value of a new technology lies not just in what it does, but also in what future technologies it leads to. Every new technology becomes a building block for new innovations.

INVISIBLE BUSINESS AND INFORMATION AUTOMATION

Digitization, AI, and machine learning are creating an economic and business world that’s vast, automatic, and invisible. Information technology’s impact on “autonomy” is moving ahead quickly. Business that once took place primarily among computer-assisted humans is now being executed by ever more complex adaptive systems without human intervention.

Inside such systems, reliable and blindingly fast processors do what they are very good at doing (and what people are very bad at doing): digesting billions of data-points, interacting with each other about the data, and controlling each other based upon the state of the data. All in a matter of nanoseconds. Human beings cannot do this, nor should they. This incessant stream of ongoing data is becoming automated. Business is increasingly being conducted in an “invisible” unseen digital domain that is quietly creating a parallel economy.

The nature and behavior of this new invisible economy are concerns that have yet to really take center stage—not only in business communities, but in most governments and institutions, too.

THE DECENTRALIZATION OF EVERYTHING

We’ve experienced hundreds of years of volatility around the cycle of centralization and de-centralization of resources and decision making. In recent years, it seems a long wave of centralization has reached its peak in social, industrial, financial, technology and geopolitical spheres. We can now see the emerging scale and influence of centralization in new digital businesses that collect and sell data on behaviors. (Consider how large, powerful, and intractably indivisible businesses like Google and Facebook have become.)

As we end the second decade of the 21st century, many of our biggest challenges in society and business still originate directly from our inability to creatively collaborate to solve many significant and very threatening cross-border problems (pandemics, climate change, availability of water and food, and many more).

But just as tides shift according to the gravitational pull of the moon, we also are seeing the emergence of a cycle of de-centralization and distribution of resources. Powerful distributed technologies such as IoT, edge computing, blockchain and more are once again demonstrating the power of decentralized systems, relationships and interactions, and potentially setting the stage for a new era of large-scale collaboration and problem solving.

Just as the extensible, technology-neutral nature of the Internet has allowed it to scale so dramatically and gracefully with minimal central administration, we need a similar approach to enabling problem solving at scale for our most intractable problems.

THE PHYSICAL GETS METAPHYSICAL

As more and more companies delve into developing smart networked systems, they are quickly finding that competitive differentiation is shifting away from unique, vertically focused product features to software that enables systems to automatically adapt and foster interactions between and among users in a networked context.

As our technologies become easier to use and economically more attractive, domain-fluent practitioners are becoming a new, more aggressive force in how software gets developed and utilized, and in the scale of its impact. We no longer need specialized people in white lab coats to do specialized things. Climate scientists who are not “software people” can now model complex weather systems with no need for direct involvement by computing technologists.

As this shift occurs, every man, woman, child, citizen and business becomes a software developer. Software is infiltrating virtually every market and niche, and displacing hardware, labor and services amidst this significant shift in how smarter solutions will be realized.

DIS-INTEGRATION ENDS THE ERA OF FLYING SOLO

The modern business enterprise has been deconstructing for decades. Companies used to develop the logistics, tools, and processes they needed right inside their four walls. Today, no one thinks of a company as bound by the four walls of a building. Companies are ecosystems now, value delivery networks consisting of a disassembled set of business functions and entities—some owned directly, many sub-contracted, but all requiring orchestrated data and information.

The dis-integration of traditional enterprises that has been driven, in part, by the decades long wave of outsourcing is restructuring businesses into three broad segments or roles: platform players, horizontally focused providers of outsourced “professional services,” and vertically focused “specialist” product and service businesses.

Future enterprises will all be part of ecosystems and value delivery networks composed of new and novel roles and interactions. This will bring an end to the era of “command-and-control” alliance and partnering strategies with a dominating “host” company at the center dictating rules to “parasitic” partners. Collaborative communities and new value networks will be self-organized by people who are motivated to explore and develop ideas they care deeply about. The technology and business solutions we are describing will have much less managerial hierarchy, command and control decision making or proprietary ownership of ideas.

CREATIVE CONTENTION

Our last research theme focuses on the complexity of Smart Systems. As the number and diversity of stakeholders expands (users, sellers, supporters, benefactors, etc.), and the volume and nature of their interactions grows, the systems or “technology architecture” will inevitably become more tightly coupled to the “business (model) architecture” and, in turn, the so-called platform becomes the central organizing mechanism required to deliver new data and information-driven services.

Platform development decisions must be aligned with the corresponding business and revenue models these technologies will inform. These two “architectures” must be viewed in close proximity. Technology architectures and business architectures need to be mutually supportive without inhibiting one or the other.

However, trying to coordinate and leverage the respective roles of technology architecture and business architecture often creates contention. Many of the participants in this emerging arena that we speak with are coming to see the continuously evolving relationship between these two dimensions as fertile ground for innovation. They need to be interwoven and mutually supportive. In fact, from our own direct consulting experiences, we believe success in either—technology architecture and business architecture—increasingly goes to the company that effectively utilizes the combined potential of both.

SMART SYSTEMS REALLY MEANS COMPLEX ADAPTIVE SYSTEMS

For quite a few years now, Harbor Research has focused on what we call “Smart Systems”—the convergence of pervasive or embedded computing with the packet-switching “network of networks” called the Internet. We use the term “Smart Systems” to describe a new generation of computing and data architecture that looks very different from classical information systems and computing technologies.

What does this all mean?

The many “nodes” of a network may not be very “smart” in themselves, but if they are networked in a way that allows them to connect effortlessly and interoperate seamlessly, they begin to give rise to complex, system-wide behavior. This allows an entirely new order of intelligence to emerge from the system as a whole—an intelligence that could not have been predicted by looking at any of the nodes individually.

In Smart Systems, the physical world dovetails with machine learning and artificial intelligence to produce previously unimagined capabilities for both the B2B and B2C worlds. After years of frustrating fits and starts, the technology is here to integrate people, processes, and data in ways that enable collective awareness and better decision making. The question is whether business leadership is ready to make the leap and grasp its potential. ◆