Editor’s note: Just as Cisco and IBM were announcing a partnership to push network analytics to the edge of networks as part of their Internet of Things strategy, so too did Hewlett Packard Enterprise. John Spooner, director of the Internet of Things and Devices Practice at Technology Business Research, takes a look.

HAMPTON, N.H. – Hewlett Packard Enterprise (HPE) is building its Internet of Things (IoT) business around what it sees as the rise of the digital enterprise, the result of a coming convergence of information technology and operational technology, driven by businesses’ needs to capture and rapidly assess mission-critical data from their operations and their customers.

Data capture and rapid assessment, via edge computing and analytics, is a core means of supporting both day-to-day operations and ongoing business innovation and transformation efforts for customers. Although most businesses are not likely to have all the tools in place to implement and train their personnel to leverage large IoT transformation efforts, HPE and other vendors are endeavoring to support those efforts. Edge computing and analytics capabilities provide a vital function in those and other, smaller, IoT projects.

HPE last Wednesday unveiled a partnership with GE Digital, the purveyor of the Predix IoT platform, along with enhancements to its broad-based portfolio of HPE IoT capabilities. The updated HPE IoT suit includes an edge-specific version of Vertica analytics, a pair of upgraded Edgeline servers and a series of IoT-specific services for implementing IoT in business, such as for deploying analytics or creating a predictive maintenance service.

Under these offerings, HPE will provide assessment, validation and implementation across the various use cases. The new components and services, along with HPE’s Universal IoT Platform announced in May, are all designed to work together to provide businesses with the capabilities to connect and analyze massive numbers of device or sensor connections and the data they produce.

HPE’s emphasis on bringing the components together into a virtual suite, wrapping it with use-case-focused services as well as a range of partnerships, comes as it works to differentiate from competitors by focusing on business outcomes.

  • Lowering the barriers to entry for IoT

One significant factor in securing a positive business outcome is cost and time to insight. The HPE announcement, along with the edge-focused partnership between Cisco and IBM on June 1, highlight the importance of defining business outcomes and bringing together edge analytics, for speed, and centralized analytics for generating deep insights. Integration of both types of analytics in a hybrid approach is critical to customers adopting an evolutionary IoT strategy, under which they move systematically to deploy IoT capabilities to accomplish business goals. TBR believes this evolutionary approach will become increasingly popular, as it is a proven and flexible path to unlocking the potential of IoT.

The availability of edge analytics lowers a barrier of entry to IoT for customers, benefiting HPE, IBM and Cisco alike. Customers can evolve their IoT, while maintaining flexibility, by choosing the real-time capabilities of edge analytics, the broad-reaching, deep-thinking properties of central analytics or a hybrid of the two.

When combined with centralized analytics, such as HPE’s Vertica, edge analytics can contribute to more powerful, flexible and cost-effective hybrid IoT analytic capabilities, relative to centralized platforms alone. HPE backs the approach with certain benefits as well, including ability to establish a unified approach to data capture and analysis, asset management and security, to eliminate stovepipes and/or incompatible data sets, systems or processes. Doing so can support the deployment of a single IoT strategy globally, which is important for large businesses with multiple divisions.

  • HPE is still about the hardware

HPE joins a chorus of vendors who are endorsing a hybrid, centralized/edge strategy for IoT. Most recently, IBM and Cisco announced their edge partnership. Prior to their announcement, GE Digital’s Predix platform, Microsoft’s Azure and numerous other vendor have edge and/or on-premises capabilities.

Centralized and cloud-based analytics have different value propositions and different cost structures than edge analytics. Centralized analytics aims at discovery of new value in big data repositories, while edge analytics aims at rapid response to incoming data. Centralized analytics take place in the cloud or in company data centers and incur resulting costs for data transmission, storage and processing as well as for personnel to prepare and analyze data.

The centralized approach lies at the heart of what TBR calls “big IoT.” Big IoT follows the same assumptions as other big data applications: There is strategic business value in large data aggregations, which companies can discover through analytics and cognitive computing. Centralized analytics is driven by the need to discover these new insights. However, it is not required for every IoT implementation. Edge analysis does not look for insight. It looks for actionable data patterns. The need for speed drives edge analytics. Rules specify the patterns that edge analytics looks for. Those rules can be written based on domain knowledge or generated by centralized analytics.

Compared with centralized analytics, Edge is tactical and less expensive, focused on putting processing and analytics capability as close to the data sources — sensors — as possible. The advantage becomes real-time reaction to changing conditions. These create alerts or automated responses, which prevent the failures of expensive machinery or help, ensure the safety of personnel.

Edge analytics are implemented on gateways, routers, switches and near-the-edge servers to apply insights about incoming IoT data to drive actions. Based on edge analysis, summary data may be transmitted to a central location, but in any case, data transmission, storage and processing costs are lower than with centralized analytics. This is because some, but not all, data collected can be retained and analyzed centrally, in search of other findings. Many implementations use edge to slim down the amount of data that is sent to a central function for those purposes, limiting the amount of time, bandwidth and other IT resources or costs associated with them.

HPE’s contribution to its edge customers’ needs also comes in the form of computing horsepower. HPE’s Edgeline EL1000 and EL4000 systems are configurable with as many as 64 Intel Xeon processors and incorporate rugged features, which allow them to be placed close to industrial machinery.

  • Edge and analytics are the stepping stones for IoT

HPE’s edge strategy is also an important stepping stone for its overall IoT business. Edge supports HPE’s broad ambition to provide large, IoT transformation project capabilities for customers.

Customers interested in IoT — especially strategic transformational IoT projects — often experiment with proofs of concept or tactical implementations as they evaluate their commitments to large and transformational IoT projects — big IoT. This is a costly and time-consuming process for vendors and resulted in slower IoT growth rates than expected by companies counting on big IoT.

Customers see edge-based IoT as safer, with greater assurance of a more rapidly realized ROI as, given the costs, the ultimate benefits of big IoT are less certain than that for little IoT. The ultimate value of the big IoT/centralized insights cannot be known until they are generated and used. With little IoT, ROI may be more modest, but it can be estimated with more confidence. HPE’s edge capability makes it possible for the company to move customers, including existing HPE shops as well as net new IoT customers, along the IoT adoption path in a similar manner.

  • Hybrid is the new go-to architecture for IoT

The technology paradigm underpinning HPE’s approach, therefore, is not new. However, its partnership with GE, new hardware and Vertica offerings and services all point to a more focused approach on IoT and a more cohesive strategy to walk customers through the process from initial implementation to business transformation.

Although the marketplace remains crowded and vendors such as Microsoft, Dell, IBM and Cisco all have edge capabilities, TBR believes HPE has one of the more complete sets of in-house IoT capabilities thanks to its software, services, infrastructure, security and connectivity capabilities. We also believe HPE, with its Universal IoT platform, ranks as relatively vendor-agnostic, working with a range of partners, including GE for Predix, PTC for Thingworx and SAP for HANA, in areas such as manufacturing and maintenance services.

We believe HPE’s capabilities differentiate the company from those vendors as well as would-be cloud-based competitors, such as Amazon Web Services (AWS) and Google. Although we believe that AWS, seeing the emphasis on edge, will also improve its abilities and partnerships to serve edge-centric and/or small IoT customers.

As this hybrid approach becomes more familiar, it will continue to accelerate the trend toward evolutionary IoT, where companies move to their transformative IoT goals through steps, each one providing benefits to the company. TBR believes this is the future of commercial IoT adoption.