A New Era of Digital Transformation is Leading to new Business Models

In a mere two decades, the digital transformation of every aspect of human affairs has been profound enough to make silicon-based computation seem almost as important to our evolution as DNA itself. The undeniable and irreversible effects are visible everywhere.

However, somewhere along the digital transformation journey many companies have become confused.  Transformation is not monolithic nor an end unto itself. Transformation is the process that enables new growth opportunities and unlocks paths to long term value creation. Digital transformation is a means to an end, but not the end state itself.

The growth opportunities that software and digital innovations enable, what we like to call Smart Systems, are creating unimagined new solutions based on new customer experiences, new business and revenue models and new service delivery modes. As the cyber-physical world continues to dovetail with IoT, machine learning and artificial intelligence, Smart Systems will enable previously unimagined capabilities. The question is whether business leadership really understands the new dynamics driving value and are ready to grasp its potential.

Raw sensor data is not in itself actionable business information. It requires a complex process of normalization, filtering, fusion with other data sets, and serious analysis in order to become useful for business decisions. Here too the techniques have long existed to make this transformation. We live, after all, in the era of “big data.”

We now have that magic blend of mature and well-aligned technologies across many verticals, yet most of our raw data might as well not exist. This is why we insist that the perennial failure of Smart Systems to “get off the ground” isn’t a technology story at all. It’s much more a story about business models and business maturity—or the lack of them.

BUSINESS MODELS ARE SHIFTING TO ENABLE
SERVICE-BASED OUTCOMES

source: Harbor Research

THE EVERYTHING AS A SERVICE BUSINESS MODEL

Mature technologies need to be paired with mature business thinking. If we use a baseball analogy of “going around the bases,” when an equipment OEM succeeds in “sensing up” its hardware to turbo-charge delivery of services and data, they’ve reached first base. Once there, they often make more money on services than they did on the initial product sale. Unfortunately, most OEMs get drunk on the big margins at first base and never make it to second.

When a company successfully reaches the “as-a-service” phase of the story, that’s second base. At that stage, the system and service provider has made the successes of first base and a customer’s data easy for users to consume. That’s an important addition to the business model because it means that delivering value to the customer is just as important as delivering it to the provider. But oftentimes, second base is as far as the Smart Systems story goes.

SMART SYSTEMS AND SERVICES JOURNEY

source: Harbor Research

The problem with stealing third base is that our business culture does not democratize the things that make sharing risk easy, which in turn drives more assured outcomes for the customer and users. Typical business thinking remains overly risk averse and not customer-centric. Businesses want to protect IP and do things in secret.

When the idea of sharing risk becomes perceived by the business community as valuable enough (or necessary enough) to force the secrecy instinct to give way, data, ecosystems and collaboration will be added to business models and lead to a rush to third base and home plate. Open data and collaboration are essential for the success of any “as-a-service” business model, whether equipment, manufacturing, software, network, infrastructure, or data.

Equipment as a Service (EaaS) & Manufacturing as a Service (MaaS)

Manufacturing-as-a-Service (MaaS) represents a natural evolution of equipment and services models. Historically, OEMs sold machines in a one-time transaction, then began offering their equipment via a rental service with after market support. Now, manufacturing the product itself has become the service.

The value of digital transformation is gaining traction among manufacturers, but the complexity of this strategy is causing challenges across all industries. By its nature, maintenance is an ad-hoc event. It’s reliant on triggering events that by themselves are relatively straightforward.  The complexity of the event and the nature of the work are primary determining factors when deciding how to adopt these technologies, and what business models to implement within them.

As equipment and systems complexity increases, customers benefit from supplier support in three key areas:

• Design & Engineer
• Operate & Execute
• Maintain & Optimize

Examples of Services Across End Customer Operations

source: Harbor Research

Embedding intelligence and software into products and systems creates new opportunities across the value chain, driving competitive differentiation for products and services.

New sources of value for OEMs include:

Product Requirements. Apply rich new data on how products are used by customers in next generation product designs.

Pre-Sales Insights . Understand installed device states – end of support; end of life, etc. to drive more personalized account management, outreach and sales tactics.

Supply & Distribution Chain. Track products throughout supply and distribution chains to monitor detours, delivery, compliance and more.

Remote Support Services. Design for [remote] Servicing: diagnostics and preventive and predictive maintenance are conducted remotely to assist field technicians and support resources automatically.

Asset Tracking. Efficiently utilize & maintain expensive assets by monitoring status, health, configuration and location.

MaaS and EaaS models are rapidly evolving as virtual businesses by providing equipment and processes that are enabled by a combination of software, networked services, and partner and ecosystem development.

Beyond Software as a Service (SaaS)

Software is now in everything. It’s indisputably eating the traditional profits and revenue models across many industries.  Machine, equipment and hardware OEMs literally have no choice but to embrace the creation of code. The questions are: How, where, and to what ends?

Manufacturing companies have actually dealt with software for a long time. But their expertise has always been in hard-coded, purpose-built software embedded in their machines. You needed it to make the hardware work, so OEMs bundled the embedded software with their physical product and didn’t even charge money for it. They’d grown up in an environment that was all about physical control, and they remained challenged by software, code development, data acquisition, value and analytics.

As technologies mature and open standards become the norm, applications based on deeper, peer-to-peer interactions between devices, data, systems and people will drive new dynamic value streams. This opens new collaborative business model opportunities for OEMs that have the potential to drive much greater value for the customer. Understanding the business-model design trade-offs, organizational and relationship structures, and the key interactions and combinations of them will be critical to success.

Software architecture is quickly becoming the foundation of every technology-driven organization; not just electronics and software companies but every company building digital capabilities. However, relatively few players understand how dramatically the software development arena has begun to change and the strategies they need to maximize value. For many OEMs we have observed, just combining aging monolithic applications with new “cloud veneers” and SaaS delivery just won’t cut it.

We believe that successful market development will require established OEMs to develop new software ventures as well as new relationships with specialized innovators and developers to enable larger ecosystems and the positive synergies and values that flow from them. These new roles are progressive in the sense that the value increases with the integration of each additional player’s equipment, systems, data, and, most importantly, the increased value resulting from new and diverse interactions.

THE MIX OF CAPABILITIES & MANEUVERS
TO DRIVE NEW SOFTWARE BUSINESSES

source: Harbor Research

Network as a Service (NaaS)

Smart connected devices are a global and economic phenomenon of unprecedented scale, one that already encompasses billions, and before long trillions, of nodes. Soon, any device that is not networked will rapidly decrease in value, creating even greater pressure to be online. Devices will blend into every venue, and vast opportunities will arise for companies delivering, managing and responding to the rich media and data being generated.

Consider that the number of connected devices on the planet—almost 7.5 billion—has already surpassed the number of people. The potential number of smart connected devices could reach a potential installed base of nearly 30 billion units in 2025—over three times larger than the population—with traditional IT and telephony devices becoming a very small portion of the connected world.

Wireless technology convergence and the new world of IoT and Smart Systems are ushering in an era where people, machines, devices, sensors and businesses are all connected and able to interact with one another. Many schemes and “standards” for device connectivity already exist, but all those solutions add up to one big problem. Users don’t want many standards. They want one solution that works seamlessly for everything, and therein lies the challenge. Networks of that scale, with that application diversity, have never been successfully assembled before.

Ultimately, adoption of smart connected systems utilizing next generation wireless technologies is no longer a “luxury.” Private 5G is increasingly needed to meet the growing demands of the very competitive arenas that constitute industrial and mission critical domains.

Harbor estimates the total opportunity for private LTE and 5G networks to reach $208B in 2025, with 5G representing $113B or 54% and experiencing rapid growth at a 68% CAGR. And while progress has been made to leverage Internet of Things and Smart Systems technologies, network performance still needs to be improved for these innovations to be embraced and integrated into business operations.

The best way for a supplier or enterprise to navigate the challenges and intricacies of deploying private networks is to leverage new NaaS management platforms designed to ease the difficulties of configuration and management. Moreover, these network management platforms can also help extract more value from the diverse data collected when integrating “siloed” networks.

5G IS DRIVING A CONFLUENCE OF TECHNOLOGY INNOVATION TO ENABLE IOT VALUE

source: Harbor Research

DATA AS A SERVICE (DaaS) & THE ADVENT OF INVISIBLE COMMERCE

This cycle of technology development’s most profound impact lies in the integration of smart sensors, machines, information systems and smart algorithms to create a “digital nervous system” that smoothly interacts and makes decisions about a very wide range of situations autonomously.

“Smart Systems” should be understood as networked information and computation that will process a rapidly growing number of situations and decisions without human intervention. Inside such systems, reliable and blindingly fast microprocessors do what they are very good at doing (and what people are very bad at doing): digesting billions of data-points, talking to 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. As is always the case with maturing technologies, they “melt” into reality and we stop seeing them. The incessant stream of ongoing data interactions and systems intelligence is increasingly and necessarily “invisible” to people. Intelligence, in many ways, has moved beyond humans to systems.

Whatever we choose to call the next wave on the horizon—autonomous, robotic, self-directed, etc.—intelligent systems will increasingly become self-sensing, self-controlling and self-optimizing automatically, without human intervention.

Think of intelligent agents and virtual assistants residing inside systems and making purchase decisions defined by a set of programmed rules. Then think of machines and systems making optimized selections among competing offers based on learning and rules or, ultimately, machines deducing human needs based on rules, context and preferences.

In several industries, invisible commerce is already here—in fact, it’s already the dominant mode. We have machine-to-machine trading of stocks and energy, streaming playlists on Spotify, and algorithm-based traffic optimization. All this give us a preview of what’s coming to the rest of the economy.

As these systems evolve, we are setting the stage for numerous invisible computer-to-computer interactions that will constitute a new generation of “machine-to-machine” transactions:

• Autonomous machines making decisions about purchases on our behalf and concluding contracts.
• Multi-agent AI systems and decentralized autonomous machines enabled to lease themselves out, hire maintenance professionals, and pay for replacement parts
• Micro-payments between machines like a car looking for a specific spare part, or drones and farming systems negotiating directly with each other for services

The nature and behavior of truly distributed intelligent system are concerns that have yet to really take center stage—not only in business communities, but in most technology communities and governments as well. Understanding the technologies, markets, companies, and business models that constitute autonomous commerce will soon be a minimum requirement for businesses to compete.

Moving toward a Smart Services Future

As digital transformation results in more and more complex applications, success factors will include clever combinations of Smart Systems technologies, organizational and cultural changes to support smart services, and ecosystem relationships with “strange bedfellow” partners. The time to act is now.

OEMs must adopt new business models and business thinking, while aligning business processes with new and innovative technology architectures. Organizational and cultural change within OEM’s and ecosystems relationships with “strange bedfellows” are required when organizing clever combinations of smart systems technologies. The sharing of data across ecosystem participants is the only way to capture the true value of Smart Systems.

New data architectures will drive value for all entities involved.
A new generation of data and information architecture is required to achieve this Smart Systems future, one where data is disaggregated, structured homogeneously, and captured in real-time such that it can be used anytime, anywhere for any application. This new data and information architecture reduces solution costs while enabling tight integration of systems and businesses to generate new revenue streams for suppliers and customers.

As-a-service business models will embrace sharing data and risk.
By sharing risk across ecosystem players, customers will have more assured outcomes. Open data allows for better collaboration and more efficient ecosystems, as well as greater value and insight for the customer.

Future business processes and ecosystems will be highly integrated.
The future of Smart Systems is characterized by tightly integrated equipment, people, processes and businesses, where data from each entity is combined with data from other entities and their surrounding environments to drive value for all ecosystem participants who are organized to receive it, including OEMs, third-party service providers, and end customers.  ◆