Harbor Research IoT Technology Trends To Watch in 2018
Over the last 15 years or more, Smart Systems and IoT technology developers have largely focused their core development work and innovations on primarily serving original equipment manufacturers (OEMs) and related service providers. Digital and IoT technologies are driving many new growth opportunities and efficiencies for OEMs based on new data collection, management and analytics tools that provide a deeper understanding of a connected product or machine’s performance and usage. Because of immediate returns on efficiencies and the new applied values these systems can generate, OEMs have been the dominant adopters of new Smart Systems and Services technologies and, like “Typhoid Mary” have carried these innovations into end customers where their presence, their spread pattern and impacts are expanding like a disease.
As users and customers have become more familiar with digital and IoT capabilities, they are realizing these technology innovations will push the boundaries of how products, systems and equipment are used and managed within their operations which, in turn, has increased pressure on machine builders and equipment manufacturers to embrace these capabilities. End customers in factories, hospitals, buildings and more are coming to see how these technologies work together in new and novel ways to solve operational and business problems. As a result, specification and adoption of digital and IoT enabled equipment and systems is beginning to shift towards a “shared” set of roles between end customers and their OEMs.
How will this shift effect OEMs? How should leadership in these companies think about the impacts of evolving digital technologies on their strategy, operating models and customer value creation?
COLLABORATION TECHNOLOGIES WILL BE CRITICAL TO ADDRESSING END CUSTOMERS
We believe the shift in product and systems specification is driven by end customers wanting to integrate data from diverse suppliers of devices, machines and equipment systems in their operations. Consider the diversity of equipment in any complex operating environment like a factory or a hospital.
Today, the average 200+ bed hospital has over 250 brands of equipment and devices and the typical hospital patient comes into contact and interacts with over 75 devices per day. However, if every device and machine has its own embedded intelligence and monitoring scheme, how should a health delivery company CIO respond to say 250 equipment OEMs showing up on their doorstep proclaiming that they have the most superior digital and IoT capabilities?
The speed and scale at which OEMs are integrating digital automation and data analytics into equipment systems is rapidly expanding. The corresponding rate of end customer adoption of these systems is also growing rapidly. Connectivity alone may help the manufacturer of the machine provide more efficient service and support, but it does not allow the end user and customer to leverage very much intelligence across myriad brands, suppliers and diverse systems. This is due to several factors including technical integration complexities, networking and data standards and differing approaches to automating machines. The challenges of gathering machine data and integrating diverse data types have been big end customer adoption hurdles, particularly for industries where the range of brands and equipment types number in the hundreds.
Given all the aspects that must be addressed from the end customer’s standpoint, alliances between OEMs represents one approach to address the challenges of leveraging data across differing brands of equipment and, at the same time, create maximum value for all parties involved. However, alliances alone will not provide the end customer with the ability to integrate data from multiple brands and equipment and ultimately, utilize the data to optimize their operations. At the end of the day, all of this adds up to a huge collection of information-islands. Assuming the islands remain in existence reliably, they are still fundamentally incapable of truly inter-operating with other information-islands. We can create bridges between them, but islands they will remain. That’s what they were designed to be.
What’s required is a true shift in thinking about how data from devices, machines, people and physical systems will be integrated and how they will interact. We need an approach that is not about leveraging aging IT, telecom or automation technology into a new context; it’s about looking forward to a single, unified approach for integrating the many interactions that these systems will foster.
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Which core technologies will drive adoption and, more importantly, impact? What are the enabling technologies required to overcome these today’s many adoption hurdles? We believe the following are the critical core enablers of Smart Systems:
» Higher performance, higher quality and more reliable mission critical wireless networks that enable new smarter sensors and sensor data fusion tools;
» More “democratized” distributed data and information architecture standards to inform data sharing and data fusion for analytics and machine learning;
» Easier and less costly data management, transformation and analytics application development tools; and finally,
» A new generation of integration and equipment management platforms that enable free flowing data discovery, data aggregation, integration and fusion and collaborative application development.
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EVOLUTION OF PLATFORM TECHNOLOGIES
It is this last core enabling technology focused on new platforms that stands out for us. Next generation platforms will need to be organized around a data and information architecture where there are no artificial barriers between diverse data type and, that facilitates free flowing data discovery, data fusion and collaborative application development. Acceptance of this reality is essential to the effective design of platforms and the adoption and usage of these emerging core technologies.
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We believe there are four critical requirements for platforms:
» A fully configurable software platform architecture that enables both peer-to-peer and client-server distribution of services;
» A platform that can simultaneously and asynchronously act on any type of information from any device, storage or streaming source;
» A platform that can enable real-time temporal, spatial and state-based contextual processing; and,
» A platform that provides tools for development of real-time, state-based applications.
Demand for these types of capabilities is hardly new, but as they do converge, these technologies need to be interwoven and mutually supportive. We believe success will only go to players who effectively leverage their combined potential.
While all of the above list of required tools will contribute to OEM and end customer adoption of new Smart Systems and IoT technologies, our analysis also points to several broader market development trends and challenges in realizing the full value of new enabling technology:
» Challenges in OEMs with adopting new business, revenue and operating models;
» Complex services delivery ecosystems that require new and different relationships;
» Anticipation of smart services and systems innovation and new growth venture modes not widely adopted today;
» Fragmented digital and IoT vendor landscape – particularly the lack of understanding of how these new more “distributed” and “participatory” systems will work on the part of the IT and telecom technology development community; and,
» Requirements for more vertically-focused solutions developed from “horizontal” enablers.
The rigid and fragmented nature of software offerings available today make it extremely difficult to develop effective Smart Systems applications. Feedback from developers and adopters suggests we are reaching a critical point in market development where organizations will expect their investment in new data-centric applications that can be re-used again and again. Customers expect evolving software tools to be functional, ubiquitous, and easy-to-use. Within this construct, however, the first two expectations run counter to the third. To achieve all three, a new approach is required.
The potential scale of the Smart Systems and IoT opportunities is utterly dependent on new technology innovations.