Rapid Growth in Times of Uncertainty
The industrial Internet of Things (IoT) is enabling and accelerating the convergence of three key technology and business model shifts that are fueling the digital transformation of every industrial enterprise:
- Connectivity. The number of connected devices and mobile devices is growing at an increasingly faster pace, emanating massive amounts of real-time information that enables deep insight about themselves and the environment around them.
- Cloud Computing. After years of hesitation, cloud technology is finally becoming a mainstream business platform and a growth engine. New information systems and business operation constructs can be deployed and scale quickly and cost effectively, as connected assets and mobile devices deliver decision-making power to all ranks in the organization.
- New Business Models. Cloud-connected assets and customers, coupled with real-time information and decision-making capabilities form the foundation for new ways to engage the business and its customers. Businesses can deploy innovative customer-centric outcome-based engagement models and respond to changing market conditions with greater agility and flexibility.
Industry is making strides in developing Internet of Things technologies and articulating the potential business value of industrial IoT and Industry 4.0 solutions. The upcoming years of the IoT evolution will be characterized by rapid technology acceleration, as the vision of an always-connected world, in which everything and everybody is connected, is becoming an everyday reality.
And company leadership is under pressure to seize the opportunity. Eager technology vendors, enthusiastic investors and analysts, and deluge of breathless headlines, all entice corporate management to jump on the IoT bandwagon before it’s too late.
However, as technology forecaster Paul Saffo aptly observed, one should not mistake a clear view for a short distance.
Early rosy projections about growth in the number of connected devices and the economic impact of the industrial Internet of Things are proving overly optimistic, particularly about the ability of industrial companies to pursue the vision effectively. A survey by the Boston Consulting Group found that while US companies consider digital technologies critical, many lack a holistic adoption strategy and a sense of urgency. A report by KPMG reaches a similar conclusion, highlighting a growing gap between executive ambitions and the corresponding transformative action plans.
To a great extent, the excitement and promise of growth are tempered by lingering concerns about IoT network security and data privacy. Others are still uncertain how to go about articulating comprehensive business models and return on investment.
What Does the Industrial IoT Mean for Product Designers?
What does the industrial Internet of Things mean for the designers of connected products that enable new customer engagement models? Are IoT “things” just like any other industrial equipment, only connected to the Internet? or are there certain design and technical elements business planners and design engineers should consider?
To understand the relationships between the Internet of Things and product design, we need to consider three layers of responses:
Design for IoT
At its most fundamental level, designing products for IoT concentrates on incorporating basic telemetry features such as sensor electronics and Internet connectivity, and, rather obviously, the necessary mechanisms to secure these devices from rogue access and malicious hacking.
Design for the Business of IoT
A less obvious observation, often missed by IoT enthusiasts, is that the product architecture and features must be aligned with business operations. Designers should adopt a business-centric point of view and optimize features and capabilities specifically to achieve the intended business outcome.
For instance, a design to maximize system uptime requires not only remote monitoring capabilities, but could also include optimizing replaceable unit (FRU) granularity to streamline field service operations, spare parts inventory, and workforce availability and training.
Design by IoT
But there is much more to the question about the relationship between the Internet and the “things.”
Most engineering organizations lose sight of their products once they are sold or installed in the field. Always-connected products and customers provide a nonstop stream of structured and unstructured information about products, services, and user interactions. This rich feedback from diverse connected ecosystems, including social media, enable faster and precise design iterations and effective continuous improvement. In essence, the IoT is driving product design!
Seven Industrial IoT Predictions for 2017 and Beyond
1. From Connectivity to Evidence-Based Business Outcomes
The early wave of excitement over connecting “things” and disagreeing over how many millions and billions of devices are going to be connected in the not-so-distant future is finally subsiding, giving way to the pursuit of tangible business outcomes enabled by an unprecedented ability to collect, analyze and garner deep insights from data.
The coming years will see an impressive progress in data analytics, machine learning, and artificial intelligence-based automated and assistive decision-support systems. Much of the progress will come from analytics and machine learning powerhouses like IBM Watson and Google’s DeepMind, as well as scores of IoT analytic startups with lofty aspirations.
This progress, however, will not always suffice to deploy relevant and practical business solutions. Information systems supporting outcome-based operation will need to aggregate machine-generated information with ERP-stored data and other analytics such as customer feedback from social media. The complexity of multidisciplinary data and the lack of semantic models that are needed to conduct domain-specific analysis provide effective decision support will require domain expertise and additional domain-specific software layers.
Recognizing this need, cloud-based IoT platforms such as Amazon AWS and Microsoft Azure will add increasingly capable IoT APIs as part of a comprehensive cognitive computing-as-a-service cloud, creating a strong foundation for systems integrators and manufacturing organizations alike to build industry-specific outcome-based solutions. Even SAP, which tends to have a monolithic self-centered point of view, is flaunting an Internet of Things platform touted as a cloud-based “digital innovation system” with a host of microservices for easy onboarding of IoT solution providers.
Open IoT platforms will be critical to reach the next level of industry maturity: delivering on the promise of the value of connectivity.
2. Accelerated Growth Leads to Shortage of Critical IoT Skills
As more companies restructure their product and service offerings to support outcome-based business models, they will face a shortage of critical IoT-specific skills, ranging from embedded software development to cybersecurity and big data analytics.
Organizations will compete on finding and retaining talent at all levels, and protecting against talent leakage stimulated by the continued proliferation of IoT technology and disciplines in industrial and non-industrial sectors alike.
But solving the skills gap isn’t simply a matter of finding and hiring people. Organizations will also discover that the over-emphasis of discrete disciplines such as analytics and embedded software engineering can lead to stovepiping decisions that get in the way of making effective long-term decisions. Forward-looking organizations will also have to develop a multidisciplinary decision-making culture, aided by master data management and analytic decision-support tools.
3. Software Defects and Vulnerabilities Linger
The ease and low cost in which product engineers can connect devices to the Internet and stream remote sensor information will continue to fuel the introduction of IoT products—mostly one-off and bespoke applications—but will also encourage sloppy implementations that result in system failures and security breaches. These will continue to draw attention to data security and privacy concerns, and dampen adoption of IoT-based solutions.
IoT advocates and products designers will begin to recognize the imperative to improve software development practices and tools, and employ advanced security standards rather than rely on security through obscurity methods that do not work. Major product companies will be reluctant to adopt technology from upstarts that peddle closed and proprietary “designed for the Internet” software.
The increasing density of embedded software in new products and the complexity of developing and testing hardware and software system dependencies in parallel will continue to challenge product engineering and testing. Vendors of embedded software development and application lifecycle management (ALM) software, such as Siemens Polarion, will continue to enhance the capabilities of their tools, but, in themselves, do not provide a substitute for an experienced workforce.
4. IoT Platform Market Shakeout Begins
The IoT technology platform market will continue to blossom, with hundreds of companies vying for some piece of the action as providers of connectivity platforms and analytic tools, and peddling mostly undifferentiated solutions.
The IoT platform market will remain highly fragmented and experience a heightened level of consolidation, as large IoT solution companies seek to improve market position, acquire domain expertise—directly and through partners—and accelerate revenue growth, which, thus far, despite much hype, has been quite tepid.
On the IoT network and connectivity front, telecom vendors such as AT&T, Verizon and Vodafone will continue their efforts to protect their share of the IoT market. However, business practices and culture that were forged in the telephone handset era impede organic growth in a space dominated by cloud-based network virtualization companies. Even more critically, the device connectivity space is being commoditized rapidly, and, at the same time, the IoT value realization is shifting to complex analytics and enterprise decision making. Lacking organic capabilities, traditional telcos and wireless carriers will focus on acquisitions.
The rush to acquire technologies, and more so, to capture emerging growth sectors, will inevitably lead to acquisitions not sufficiently thought through.
5. IoT Semiconductor Giants at Play
As the demand for personal computing is waning and smartphone component suppliers are victims of fierce price wars, IoT is emerging as the next big driver of demand for Industrial semiconductors, ranging from nanotechnology sensors to wireless communication components. The automotive industry is emerging as the next largest volume market for IoT semiconductor manufacturers, driving semiconductor companies to invest heavily in sensors, especially in video and solid-state LIDAR, and in high-bandwidth single-chip sensor fusion components.
While technology giants like Intel, Qualcomm and Avago/Broadcom, which have been investing heavily in the past few years, may not have an appetite for additional megadeals, the semiconductor market will see activity and growth, resulting in falling semiconductor pricing, which, in turn, will accelerate adoption and drive growth in the overall IoT market.
Among the several industrial sectors benefiting from this trend will be the automotive industry, which will accelerate the deployment of active safety features and autonomous driving technology. On the other hand, the manufacturing equipment sector, which has a slower natural cadence, will continue to lag, delaying the inflection point IoT vendors are yearning for.
Innovation and growth in the IoT device space, especially in automotive, will result in growth in ALM, embedded software development, and simulation tools market.
6. Market Leaders Are Members of a Dynamic Ecosystem
While strong and vocal presence of horizontal IoT platform vendors will continue to capture headlines, mature product companies will realize that the business value of IoT cannot be delivered by a single solution from an IoT platform company. Industrial IoT solutions require deep domain expertise that the software vendors usually do not possess.
Winning companies will establish and nurture an active ecosystem of partners and solution providers that leverage connected products and customers to provide value through collaboration that benefit all value-chain participants. These companies will invest in developing cross-industry and pan-ecosystem solutions that are scalable and responsive to rapidly changing customer needs, geographic dynamics, and the competitive landscape.
The growing strength of newly formed ecosystems and partnerships between cloud infrastructure providers, IoT platform vendors, and domain experts will become a major threat to small IoT software vendors that fail to develop deep domain expertise and a business partnership ecosystem.
7. 2017 Will Not Be the Year in Which IoT Became Mainstream
The first wave of the Internet of Things produced a plethora of connected product ideas and promises. Granted, many early IoT products—especially in the consumer products space—are not worthy a mention. But there are numerous examples of meaningful IoT implementations such as the predictive maintenance application by Siemens at the Spanish rail system Renfe, and the craft beer tracking system built by Ovinto at B. United International.
But while the long-term vision of the industrial IoT is promising, and despite pressure from executive boards and Wall Street analysts to jump on the IoT bandwagon, business transformation and project implementation will be, as often is the case, slower than the rosy expectations.
2017 will not be the year in which IoT became mainstream.
There will be many impressive IoT successes. Yet, by and large, these will represent islands of success: unique implementations that deliver value, but cannot scale or be replicated easily. Furthermore, many use cases will entail projects executed by large corporations with deep pockets and business transformation wherewithal.
For many others, digital transformation will be a more arduous process. Continued concerns about data security and privacy will continue to linger for a while, as will difficulties to articulate the business value of IoT to satisfy the bean counters.
Seven Actions to Take
Sustained leadership in industrial IoT will require companies—both product companies and providers of IoT-based solutions—to plan prudently and take deliberate action to accelerate the maturation of outcome-based business solutions leveraging IoT technology.
- Reimagine Industry Models: implement outcome-based solutions that seek growth opportunities on top of efficiency improvements. Redesign business and operating models to support new product-service hybrids and customer engagement models.
- Enable IoT-infused Innovation by incorporating business considerations in early design phases to ensure alignment with outcome-based operations. Managing IoT generated data across different solutions in the enterprise master data management (MDM) system will drive agility and efficiency in your innovation process.
- Partner for Success: Build and nurture a business ecosystem. Partner within your supply chains and cross-industry to spawn new opportunities that focus on business outcomes.
- Leverage Data: Invest in analytics to harvest new insights from meshing data from IoT devices, enterprise systems, and customers, and drive better and faster decisions across the value chain. Focus on creating a rich multidisciplinary context from multiple existing sources before investing in complex and fragile analytics methods.
- Prepare for the Future of Work: Invest in skills and organization processes that improve product development and drive collaboration and better decision-making across the extended supply chain.
- Deploy Open Standard-based IoT platforms that accelerate time to value and reduce risk in IoT development. Look for open, standard-based architectures that support the entire value chain from connectivity to operations.
- Align Architectures: Align business and IT architectures. Invest in standardizing data and knowledge processes and tools that improve process and information interoperability.
Image: The Fortune Teller (Georges de La Tour c. 1630)