Forbes readers’ most frequent requests center on which companies are the best to work for in emerging technology fields, including IoT. The Computer Reseller News’ Internet of Things 50, 2019 list of companies is used to complete the analysis as it is an impartial, independent list created by CRN. Using the CRN list as a foundation, the following analysis captures the best companies in their respective areas today.
“The hot IoT startups today have a strong focus on data analytics and AI and are increasingly targeting industrial and manufacturing clients. It remains to be seen how much of the analytics technology that today’s startups are building will be scalable across IoT use cases and industries. For now, most of the IoT startups are adding value in specific industries or for specific use cases,” said Knud Lasse Lueth, Managing Director of IoT Analytics.
The following are the top 10 IoT Startups Of 2019 from IoT Analytics:
Arundo Analytics is a hot IoT Startup that provides analytics software for industrial and energy companies. The company has formed several strategic alliances, e.g., with Dell Technologies and WorleyParsons. Arundo has also formed a joint venture with DNV GL to provide stream data analytics for maritime companies. The board of directors includes Tore Myrholt, Senior Partner at McKinsey and Thomas Malone, the founding director of the MIT Center for Collective Intelligence. Recently, Arundo launched several applications incl. machine monitoring and fuel efficiency.
Bright Machines is currently the fastest growing IoT Startup, has grown from virtually zero at the beginning of 2018 to almost 200 employees a year later (April 2019). The firm focuses on “micro-factories” made up of its software and robot cells as well as new software tools that make manufacturing more efficient. The leadership team is filled with former executives from Autodesk, Flextronics, and Amazon including Amar Hanspal (CEO), Brian Mathews (CTO), Tzahi Rodrig (COO) and Nick Ciubotariu (SVP, Software Engineering). The company recently entered into a strategic partnership with BMW i Ventures.
Dragos (IoT Middleware & Software Infrastructure)
Dragos is a cybersecurity startup that offers a software-defined security platform for manufacturers. The company has seen a 300%+ growth in headcount the last two years and collaborates with GE, Deloitte, OSIsoft, ThreatConnect, Crowdstrike, and several other companies. The company recently acquired Atlanta-based NexDefense and collaborates with Waterfall Solution for a joint solution.
Element (IoT Middleware & Software Infrastructure)
Element (also known as Element Analytics) is a fascinating IoT Startup that focuses on industrial analytics software such as Digital Twins, particularly in heavy industries. The company counts an impressive list of investors, including Kleiner Perkins, GE, Honeywell, and ABB. Element partners with Microsoft, Uptake, OSIsoft, and Radix (consulting).
In recent years, US-based startup FogHorn has gained an excellent reputation with leading manufacturers and oil and gas organizations around the world for its real-time edge computing and analytics software. The company has seen an 89% employee growth in the past two years and has secured partnerships with 50+ industrial solution providers, OEMs, gateway providers, and consultants/SIs, including AWS, Google Cloud, Microsoft, Cisco, HP, NTT Data, and more. FogHorn is also a member of LF Edge, an umbrella organization to drive an open, interoperable framework for edge computing to accelerate deployment among the growing number of edge devices. Investors in FogHorn include The Hive, Bosch, Dell, GE, Honeywell, Intel, Saudi Aramco, and Yokogawa.
Iguazio is a hot startup that provides a state-of-the-art data science platform for various verticals, including Industrial IoT, Smart Mobility, and Telecommunications. The company recently entered into collaborations with NVIDIA, Microsoft, and Google. Iguazio markets its Nuclio platform product as a “serverless” framework for multi-cloud environments and is thus well-positioned for the next wave of cloud computing.
IoTium (IoT Connectivity)
IoTium is a quickly upcoming IoT startup from the Silicon Valley area that focuses on software-defined network infrastructure in manufacturing and related verticals. The company has seen a 100%+ growth in headcount over the last two years and now counts John Chambers, former Cisco CEO, as an investor along with other well-known corporate investors incl. Juniper, Qualcomm, SafeNet, and Wind River. The company is also very active in the EdgeX Foundry and recently joined the Siemens’ MindSphere partner program as a gold member.
Preferred Networks is one of Japan’s IoT hotshots, focused on applying real-time machine-learning technologies to new Internet of Things applications. The company has seen a 100%+ employee growth in the last two years and now collaborates with world-leading organizations incl. Toyota Motor Corporation, Fanuc, and the National Cancer Center. The company is also very active in developing the deep-learning framework Chainer™ together with IBM, Intel, Microsoft, Nvidia.
READY Robotics (IoT Hardware)
READY Robotics is a rare robotics startup that is looking to benefit from the increasing automation and flexibility of manufacturing processes around the world. The company emerged from the cutting-edge robotics research at Johns Hopkins University to develop its industrial robotic software called Forge. The company has seen a 150%+ growth in headcount in the last two years and is now producing roughly 15 robot systems per month.
SparkCognition excels in AI-powered analytics, particularly in manufacturing and related verticals. SparkCognition has seen a 100%+ growth in headcount over the last two years. The company has launched Skygrid, a joint venture with Boeing and it has partnered with Siemens as part of its Mindsphere program. The company is also a Google Cloud Technology Partner and works with IBM as a trusted partner.
The full 62-page report (+ 1,018 line-item database) titled “IoT Startups Report & Database 2019” is available for purchase here.
Industrial Internet of Things (IIoT) presents integration architecture challenges that once solved can enable use cases that deliver fast-growing revenue opportunities.
ISA-95 addressed the rise of global production and distributed supply chains yet are still deficient on the issue of data and security, specifically the proliferation of IIoT sensors, which are the real security perimeter of any manufacturing business.
Finding new ways to excel at predictive maintenance, and cross-vendor shop floor integration are the most promising applications.
IIoT manufacturing systems are quickly becoming digital manufacturing platforms that integrate ERP, MES, PLM and CRM systems to provide a single unified view of product configurations.
The following are the key takeaways from the study:
Capturing IIoT’s full value potential will require more sophisticated integrated approaches than current automation protocols provide. IIoT manufacturing systems are quickly becoming digital manufacturing platforms that integrate ERP, MES, PLM and CRM systems to provide a single unified view of product configurations and support the design-to-manufacturing process. Digital manufacturing platforms are already enabling real-time monitoring to the machine and shop floor level. The data streams real-time monitoring is delivering today is the catalyst leading to greater real-time analytics accuracy, machine learning adoption and precision and a broader integration strategy to the PLC level on legacy machinery. Please click on the graphic to expand for easier reading.
Inconsistent data structures at the machine, line, factory and company levels are slowing down data flows and making full transparency difficult to attain today in many manufacturers. Smart machines with their own operating systems that orchestrate IIoT data and ensure data structure accuracy are being developed and sold now, making this growth constraint less of an issue. The millions of legacy industrial manufacturing systems will continue to impede IIoT realizing its full potential, however. The following graphic reflects the complexities of making an IIoT platform consistent across a manufacturing operation. Please click on the graphic to expand for easier reading.
Driven by price wars and commoditized products, manufacturers have no choice but to pursue smart, connected machinery that enables IIoT technology stacks across shop floors. The era of the smart, connected machines is here, bringing with it the need to grow services and software revenue faster than transaction-based machinery sales. Machinery manufacturers are having to rethink their business models and redefine product strategies to concentrate on operating system-like functionality at the machine level that can scale and provide a greater level of autonomy, real-time data streams that power more accurate predictive maintenance, and cross-vendor shop floor integration. Please click on the graphic for easier reading.
Machines are being re-engineered starting with software and services as the primary design goals to support new business models. Machinery manufacturers are redefining existing product lines to be more software- and services-centric. A few are attempting to launch subscription-based business models that enable them to sell advanced analytics of machinery performance to customers. The resulting IIoT revenue growth will be driven by platforms as well as software and application development and is expected to be in the range of 20 to 35%. Please click on the graphic to expand for easier reading.
Global spending on IIoT Platforms for Manufacturing is predicted to grow from $1.67B in 2018 to $12.44B in 2024, attaining a 40% compound annual growth rate (CAGR) in seven years.
IIoT platforms are beginning to replace MES and related applications, including production maintenance, quality, and inventory management, which are a mix of Information Technology (IT) and Operations Technology (OT) technologies.
Connected IoT technologies are enabling a new era of smart, connected products that often expand on the long-proven platforms of everyday products. Capgemini estimates that the size of the connected products market will be $519B to $685B by 2020.
These and many other fascinating insights are from IoT Analytics’ study, IIoT Platforms For Manufacturing 2019 – 2024 (155 pp., PDF, client access reqd). IoT Analytics is a leading provider of market insights for the Internet of Things (IoT), M2M, and Industry 4.0. They specialize in providing insights on IoT markets and companies, focused market reports on specific IoT segments and Go-to-Market services for emerging IoT companies. The study’s methodology includes interviews with twenty of the leading IoT platform providers, executive-level IoT experts, and IIoT end users. For additional details on the methodology, please see pages 136 and 137 of the report. IoT Analytics defines the Industrial loT (lloT) as heavy industries including manufacturing, energy, oil and gas, and agriculture in which industrial assets are connected to the internet.
The seven things you need to know about IIoT in manufacturing include the following:
IoT Analytics’ technology architecture of the Internet of Things reflects the proliferation of new products, software and services, and the practical needs manufacturers have for proven integration to make the Industrial Internet of Things (IIoT) work. IoT technology architectures are in their nascent phase, showing signs of potential in solving many of manufacturing’s most challenging problems. IoT Analytics’ technology architecture shown below is designed to scale in response to the diverse development across the industry landscape with a modular, standardized approach.
IIoT platforms are beginning to replace MES and related applications, including production maintenance, quality, and inventory management, which are a mix of Information Technology (IT) and Operations Technology (OT) technologies. IoT Analytics is seeing IIoT platforms begin to replace existing industrial software systems that had been created to bridge the IT and OT gaps in manufacturing environments. Their research teams are finding that IIoT Platforms are an adjacent technology to these typical industrial software solutions but are now starting to replace some of them in smart connected factory settings. The following graphic explains how IoT Analytics sees the IIoT influence across the broader industrial landscape:
Global spending on IIoT Platforms for Manufacturing is predicted to grow from $1.67B in 2018 to $12.44B in 2024, attaining a 40% compound annual growth rate (CAGR) in seven years. IoT Analytics is finding that manufacturing is the largest IoT platform industry segment and will continue to be one of the primary growth catalysts of the market through 2024. For purposes of their analysis, IoT Analytics defines manufacturing as standardized production environments including factories, workshops, in addition to custom production worksites such as mines, offshore oil gas, and construction sites. The lloT platforms for manufacturing segment have experienced growth in the traditionally large manufacturing-base countries such as Japan and China. IoT Analytics relies on econometric modeling to create their forecasts.
In 2018, the industrial loT platforms market for manufacturing had an approximate 60%/40% split for within factories/outside factories respectively. IoT Analytics predicts this split is expected to remain mostly unchanged for 2019 and by 2024 within factories will achieve slight gains by a few percentage points. The within factories type (of lloT Platforms for Manufacturing) is estimated to grow from a $1B market in 2018 to a $1.5B market by 2019 driven by an ever-increasing amount of automation (e.g., robots on the factory floor) being introduced to factory settings for increased efficiencies, while the outside factories type is forecast to grow from $665M in 2018 to become a $960M market by 2019.
Discrete manufacturing is predicted to be the largest percentage of Industrial IoT platform spending for 2019, growing at a CAGR of 46% from 2018. Discrete manufacturing will outpace batch and process manufacturing, becoming 53% of all IIoT platform spending this year. IoT Analytics sees discrete manufacturers pursuing make-to-stock, make-to-order, and assemble-to-order production strategies that require sophisticated planning, scheduling, and tracking capabilities to improve operations and profitability. The greater the production complexity in discrete manufacturing, the more valuable data becomes. Discrete manufacturing is one of the most data-prolific industries there are, making it an ideal catalyst for IIoT platform’s continual growth.
Manufacturers are most relying on IIoT platforms for general process optimization (43.1%), general dashboards & visualization (41.1%) and condition monitoring (32.7%). Batch, discrete, and process manufacturers are prioritizing other use cases such as predictive maintenance, asset tracking, and energy management as all three areas make direct contributions to improving shop floor productivity. Discrete manufacturers are always looking to free up extra time in production schedules so that they can offer short-notice production runs to their customers. Combining IIoT platform use cases to uncover process and workflow inefficiencies so more short-notice production runs can be sold is driving Proof of Concepts (PoC) today in North American manufacturing.
IIoT platform early adopters prioritize security as the most important feature, ahead of scalability and usability. Identity and Access Management, multifactor-factor authentication, consistency of security patch updates, and the ability to scale and protect every threat surface across an IIoT network are high priorities for IIoT platform adopters today. Scale and usability are the second and third priorities. The following graphic compares IIoT platform manufacturers’ most important needs:
The majority of enterprises are prioritizing their blockchain pilots that concentrate on supply chains improvements (53%) and the Internet of Things (51%) according to Deloitte’s latest blockchain survey.
By 2023, blockchain will support the global movement and tracking of $2T of goods and services annually based on a recent Gartner
The Supply Chain Management enterprise software market is growing from $12.2B in 2017 to $20.4B in 2022, achieving a 10.7% Compound Annual Growth Rate (CAGR) according to Gartner’s latest market forecast.
Of the many blockchain and IoT Proof of Concept (POC) pilots running today, track-and-trace shows the most significant potential of moving into production.
Combining blockchain’s distributed ledger framework with the Internet of Things’ (IoT) proven real-time monitoring and tracking capability is redefining supply chains. Blockchain shows potential for increasing the speed, scale, and visibility of supply chains, eliminating counterfeit-goods transactions while also improving batching, routing and inventory control. Blockchain’s shared, distributed ledger architecture is becoming a growth catalyst for IoT’s adoption and commercial use in organizations.
Blockchain and IoT are defining the future of supply chains based on the initial success of Proof of Concept (POC) pilots focused on the logistics, storage and track-and-trace areas of supply chains across manufacturing. Supply-chain centric pilots are the most popular today, with enterprises looking at how they can get more value out of IoT using blockchain. One CIO told me recently his company deliberately spins up several POCs at once, adding “they’re our proving grounds, we’re pushing blockchain and IoT’s limits to see if they can solve our most challenging supply chain problems and we’re learning a tremendous amount.” The senior management team at the manufacturer says the pilots are worth it if they can find a way to increase inventory turns just 10% using blockchain and IoT. They’re also running Proof of Concept pilots to optimize batching, routing and delivery of goods, reduce fraud costs, and increase track-and-trace accuracy and speed. Of the many pilots in progress, track-and-trace shows the greatest potential to move into production today.
The following are the top 10 ways IoT and blockchain are defining the future of supply chains:
Combining IoT’s real-time monitoring support with blockchain’s shared distributed ledger strengthens track-and-trace accuracy and scale, leading to improvements across supply chains. Improving track-and-trace reduces the need for buffer stock by providing real-time visibility of inventory levels and shipments. Urgent orders can also be expedited and rerouted, minimizing disruptions to production schedules and customer shipments. The combination of blockchain and IoT sensors is showing potential to revolutionize food supply chains, where sensors are used to track freshness, quality, and safety of perishable foods. The multiplicative effects of combining IoT and blockchain to improve track-and-traceability are shown in the context of the following table from the Boston Consulting Group. Please click on the graphic to expand for easier reading.
Improving inventory management and reducing bank fees for letters of credit by combining blockchain and IoT show potential to deliver cost savings. A recent study by Boston Consulting Group, Pairing Blockchain with IoT to Cut Supply Chain Costs, completed a hypothetical analysis of how much a $1B electronics equipment company implementing blockchain-as-a-service, a decentralized track-and-trace application, and 30 nodes that share among key supply chain stakeholders could save. The study found that the electronics equipment company could save up to $6M a year or .6% of annual sales. A summary of the business case is shown here:
Combining blockchain and IoT is providing the pharmaceutical and healthcare industry with stronger serialization techniques, reducing counterfeit drugs and medical products. Pharmaceutical serialization is the process of assigning a unique identity (e.g., a serial number) to each sealable unit, which is then linked to critical information about the product’s origin, batch number, and expiration date. According to the World Health Organization (WHO) approximately 1 million people each year die from counterfeit drugs, 50% of pharmaceutical products sold through rogue websites are considered fake, and up to 30% of pharmaceutical products sold in emerging markets are counterfeit according to a recent study by DHL Research. DHL and Accenture are finalizing a blockchain-based track-and-trace serialization prototype comprising a global network of nodes across six geographies. The system comprehensively documents each step that a pharmaceutical product takes on its way to the store shelf and eventually the consumer. The following graphic illustrates the workflow.
Improving distribution and logistics, tracking asset maintenance, improving product quality, preventing counterfeit products and enabling digital marketplaces are the use cases Capgemini predicts blockchain will have the greatest impact. IoT’s potential contribution in each of these five use case areas continues to accelerate as real-time monitoring dominates manufacturing. Tracking provenace, contracts management, digital threads, and trade financing also show potential for high adoption. The following graphic illustrates blockchain use cases in the supply chain.
Combining blockchain and IoT is enabling manufacturers to pursue and excel at digital twin initiatives across their value chains. A digital twin is a dynamic, digital representation of a physical asset which enables companies to track its past, current and future performance throughout the asset’s lifecycle. The asset, for example, a vehicle or spare part, sends performance data and events directly to its digital twin, even as it moves from the hands of the manufacturer to the dealer and ultimately the new owner. Blockchain can be used to securely document everything related to the asset and IoT provides the real-time monitoring and updates. Microsoft and VISEO are partnering to use blockchain to connect each new vehicle’s maintenance events to the vehicle’s digital twin. The graphic below illustrates how digital twins streamline additive manufacturing.
54% of suppliers and 51% of customers are expecting the organizations they do business with to take a leadership position on blockchain and IoT. The majority of suppliers and customers expect the manufacturers, suppliers, and vendors they do business with to take a leadership position on these two emerging technologies and define a vision with them in it. Deloitte’s excellent study, Breaking Blockchain Open, Deloitte’s 2018 Global Blockchain Survey, provides insights into how supplier and customer expectations are a factor in driving blockchain and IoT adoption, further helping to shape the future of supply chains.
Consumer products and manufacturing lead adoption of blockchain today, followed by life sciences according to the latest Deloitte estimates. IoT adoption is flourishing in manufacturing, transportation & logistics and utilities. By 2020, each of these industries is projected to spend $40B each on IoT platforms, systems, and services. The following graphic compares blockchain adoption levels by industry. Given how dependent manufacturers are on supply chains, the high adoption rates for blockchain and IoT make sense. Please click on the graphic to expand for easier reading.
32% of enterprises are adopting blockchain to gain greater speed compared to existing systems, and 28% believe blockchain will open up new business models and revenue sources. The majority of manufacturers, transportation & logistics and utilities companies have real-time monitoring running on their shop floors and across their production facilities today. Many are transitioning from Wi-Fi enabled monitoring to IoT, which creates a real-time data stream that blockchain ledgers categorize and track to provide greater track-and-trace speed and accuracy. A recent Capgemini survey found that 76% of manufacturers also plan to have a product-as-a-service strategy to drive revenue in less than two years.
Blockchain has the potential to deliver between $80B and $110B in value across seven strategic financial sectors when supported by IoT, redefining their supply chains in the process. McKinsey completed an extensive analysis of over 60 viable use case for blockchain in financial services where IoT would provide greater visibility across transactions. The combination of technologies has the potential to deliver over $100B in value.
Reducing product waste and perishable foods’ product margins while increasing traceability is attainable by combining blockchain and IoT.IBM’s Food Trust uses blockchain technology to create greater accountability, traceability, and visibility in supply chains. It’s the only consortium of its kind that connects growers, processors, distributors, and retailers through a permissioned, permanent and shared record of food system data. Partners include Carrefour, Dole, Driscoll’s, Golden State Foods, McCormick and Co., McLane Co., Nestlé, ShopRite parent Wakefern Food Corp., grocery group purchasing organization Topco Associates The Kroger Co., Tyson Foods, Unilever and Walmart. An example of the Food Trust’s traceability application is shown below:
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The metrics comprising the index are designed to interpret where companies are on their journeys to becoming Intelligent Enterprises. The following are the 11 metrics that are combined to create the Index: IoT Vision, Business Engagement, Technology Solution Partner, Adoption Plan, Change Management Plan, Point of use Application, Security & Standards, Lifetime Plan, Architecture/Infrastructure, Data Plan and Intelligent Analysis. An online survey of 918 IT decision makers from global enterprises competing in healthcare, manufacturing, retail and transportation and logistics industries was completed in August 2018. IT decision makers from nine countries were interviewed, including the U.S., U.K./Great Britain, France, Germany, Mexico, Brazil, China, India, and Australia/New Zealand. Please see pages 24 and 25 for additional details regarding the methodology.
Key insights gained from the Intelligent Enterprise Index include the following:
86% of enterprises expect to increase their spending on IoT in 2019 and beyond. Enterprises increased their investments in IoT by 4% in 2018 over 2017, spending an average of $4.6M this year. Nearly half of enterprises globally (49%) interviewed are aggressively pursuing IoT investments with the goal of digitally transforming their business models this decade. 38% of enterprises have company-wide IoT deployments today, and 55% have an IoT vision and are currently executing their IoT plans.
49% of enterprises are on the path to becoming an Intelligent Enterprise, scoring between 50 – 75 points on the index. The percent of enterprises scoring 75 or higher on the Intelligent Enterprise Index gained the greatest of all categories in the last 12 months, increasing from 5% to 11% of all respondents. The majority of enterprises are improving how well they scale the integration of their physical and digital worlds to enhance visibility and mobilize actionable insights. The more real-time the integration unifying the physical and digital worlds of their business models, the better the customer experiences and operational efficiencies attained.
The majority of enterprises (82%) share information from their IoT solutions with employees more than once a day, and 67% are sharing data in real-time or near real-time. 43% of enterprises say information from their IoT solutions is shared with employees in real-time, up 38% from last year’s index. 76% of survey respondents are from retailing, manufacturing, and transportation & logistics. Gaining greater accuracy of reporting across supplier networks, improving product quality visibility and more real-time data from distribution channels are the growth catalysts companies competing in retail, manufacturing, and transportation & logistics need to grow. These findings reflect how enterprises are using real-time data monitoring to drive quicker, more accurate decisions and be more discerning in which strategies they choose. Please click on the graphic to expand to view specifics.
Enterprises continue to place a high priority on IoT network security and standards with real-time monitoring becoming the norm. 58% of enterprises are monitoring their IoT networks constantly, up from 49%, and a record number of enterprises (69%) have a pre-emptive, proactive approach to IT security and network management. It’s time enterprises consider every identity a new security perimeter, including IoT sensors, smart, connected products, and the on-premise and cloud networks supporting them. Enterprises need to pursue a “never trust, always verify, enforce least privilege” approach and are turning to Zero Trust Privilege (ZTP) to solve this challenge today. ZTP grants least privilege access based on verifying who is requesting access, the context of their request, and ascertaining the risk of the access environment. Designed to secure infrastructure, DevOps, cloud, containers, Big Data, and scale to protect a wide spectrum of use cases, ZTP is replacing legacy approaches to Privileged Access Management by minimizing attack surfaces, improving audit and compliance visibility, and reducing risk, complexity, and costs for enterprises. Leaders in this field include Centrify for Privileged Access Management, Idaptive, (a new company soon to be spun out from Centrify) for Next-Gen Access, as well as Cisco, F5 and Palo Alto Networks in networking.
Analytics and security dominate enterprise’ IoT management plans this year. 66% of enterprises are prioritizing analytics as their highest IoT data management priority this year, and 63% an actively investing in IoT security. The majority are replacing legacy approaches to Privilege Access Management (PAM) with ZTP. Enterprises competing in healthcare and financial services are leading ZTS’ adoption today, in addition to government agencies globally. Enterprises investing in Lifecycle management solutions increased 11% between 2017 and 2018. Please click on the graphic to expand to view specifics.