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.
IoT Leaders are achieving cost and revenue gains of at least 15% or more, while laggards see less than 5%.
Pursuing 80% more IoT use cases compared to their peers, IoT Leaders are progressing faster down the learning curve of monetizing their application areas.
IoT Leaders anticipate that their IoT use cases will boost their gross profits by 13% over the next three years, three times as much as IoT laggards.
What IoT leaders do to excel and drive greater results compared to their peers is explored in the recent McKinsey report, What separates leaders from laggards in the Internet of Things. The study is based on interviews with 300 IoT executive-level practitioners from companies with more than $500M revenues which are implementing large-scale IoT strategies with projects that have progressed from pilot to production. Enterprises from 11 major industry segments from Canada, China, Germany, and the United States were included in the survey.
McKinsey found 16% of enterprises have IoT programs in production, delivering aggregate cost and revenue impacts of at least 15%. The study also found 16% of enterprises are lagging, attaining aggregate revenue and cost improvements of less than 5%. The following graphic compares companies by the level of financial impact from IoT initiatives:
Nine practices differentiate IoT Leaders from laggards, and the study provides a fascinating look into each based on the survey data. Key insights into IoT Leader’s practice areas is provided here:
Leaders are more aggressive about pursuing a greater number, scope, and variety of IoT applications and use cases than their less successful peers. What IoT Leaders learn quickly is how steep the IoT learning curve is, and how it’s essential to run as many IoT pilots as possible to learn more. Leaders discover the first 15 or so IoT use cases typically have a modest payback, with the average payback rising until approximately 30 use cases have been achieved. IoT Leaders anticipate that their IoT use cases will boost their gross profits by 13% over the next three years, three times as much as IoT laggards. The following graphic illustrates the financial impact per IoT use case by the cumulative number of IoT use cases enterprises initiate.
Leaders are more willing than their peers to change business processes to unlock IoT’s value. McKinsey found IoT Leaders are three times more likely than their peers to say that managing changes to business processes is one of the three most important capabilities for implementing IoT. CEOs who champion their company’s IoT initiatives make strong contributions in this area, removing barriers and roadblocks quickly to keep IoT programs moving forward.
Leaders design, pilot and move to production IoT use cases that rely on advanced endpoints far more than their peers. McKinsey finds that IoT Leaders are more visionary and aggressive than peers in developing applications with advanced endpoints. Leaders are gaining expertise and mastery of how to creatively use advanced endpoints today, reporting higher levels of satisfaction and positive results.
Leaders clearly define how IoT will create value and excel in building effective business cases. McKinsey found that IoT Leaders are 75% more likely than their peers to cite the preparation of a strong business case as a critical success factor for their IoT programs. The study’s respondents who have an IoT vision that includes a strong value proposition, a proven delivery model, and a business model that drives revenue are getting results faster than their peers. 35% of Leaders rate the importance of “strong business case and vision for value creation” as one of the top three success factors versus 20% of laggards. Leaders leave nothing to chance when it comes to defining how IoT will deliver business value either in the form of greater revenue or reduced costs.
A CEO’s involvement and support are essential for any enterprise to succeed with IoT. Based on personal experience with IoT pilots, C-level executives are indispensable in removing barriers and making process-level changes necessary for success. 72% of the surveyed executives agree. A vital catalyst of any enterprise succeeding with IoT is a clear, unequivocal time commitment on the part of the CEO. Enterprises in the Leaders quintile were 2.4 more likely than laggards to report that their CEO serves as the champion of IoT efforts as the following graphic illustrates:
Leaders credit strong alignment with IoT strategies and priorities enterprise-wide as a critical factor in their success. IoT initiatives and pilots on their way to production require executives, managers, and frontline workers to learn fresh skills and collaborate across business and functional boundaries in new ways. Enterprises need to have a strong unifying vision of where they’re going with IoT, with the CEO championing the change management required to make sure they succeed.
Leaders begin by adding IoT capability to existing products and services first. McKinsey found that Leaders are three times more likely than their peers to make their top priority adding IoT capabilities to existing products. They focus on how to turn the current scale they’ve achieved with suppliers, selling and service networks into a formidable competitive advantage. They’re also more adept at cross-selling and up-selling IoT-enabled products by capitalizing on current customer relationships. The following graphic compares enterprises’ single highest-priority IoT effort:
Leaders excel at tapping into, scaling and relying on an ecosystem of partners for innovation versus doing it all themselves. McKinsey finds that IoT Leaders excel at scaling their partner ecosystems faster and more strategically than their peers. IoT Leaders also rely more on partners for the latest technology innovations instead of attempting to create them entirely on their own. They’re also deliberately choosing IoT platforms that support third-party developers and the advanced endpoints as the graphic below shows:
Leaders prepare for cyber attacks, so they don’t slow things down. McKinsey found that 30% of enterprises from both IoT Leaders and their peers say that they’ve experienced cyber attacks that have resulted in high to severe damage. 57% of Leaders had been the target of cyber attacks compared to 44% of their peers. The higher number of cyber attacks happening for Leaders is due to the broader threat surface their many pilots, and production-level use cases create. The more distributed and varied IoT use cases are the greater the risk of privileged credential abuse as well. Thwarting privileged credential abuse needs to start with a least privilege access approach, minimizing each attack surface, improving audit and compliance visibility while reducing risk, complexity, and costs. Leaders in Zero Trust include Centrify, MobileIron, Palo Alto Networks, and others.
26,792 startups are relying on IoT as one of their main technologies to launch new products and services and support platform-based business models according to Crunchbase.
78.4% of IoT startups Crunchbase tracks have had two funding rounds or less with seed, angel and early-stage rounds being the most common.
IoT startup funding reached $16.7B in Q4, 2018, with last years’ funding levels 94% over 2017 according to Venture Scanner.
By 2020, 50% of IoT spending will be driven by discrete manufacturing, transportation and logistics, and utilities according to the Boston Consulting Group.
The most successful IoT startups selling into enterprises excel at orchestrating analytics, Artificial Intelligence (AI), and real-time monitoring to deliver exceptional customer experiences. As a group, these top 25 IoT startups are showing early potential at enabling profitable new business models, revitalizing industries that have experienced single single-digit growth recently. Each of these startups is taking a unique approach to solving some of the enterprises’ most challenging problems, and in so doing creating valuable new patents that further fuel IoT adoption and growth.
The top 25 startups are concentrating on how to make IoT a growth catalyst for enterprises by designing in AI integration at the platform level. McKinsey found that 27% of AI early adopters are more likely to report using AI to grow their market than companies only experimenting with or partially adopting AI. 52% are more likely to report using it to increase their market share. These and many other survey results are from McKinsey Global Institute’s Artificial Intelligence: The Next Digital Frontier? (PDF, 80 pp., no opt-in).
Top 25 IoT Startups To Watch In 2019
The following list of 25 IoT startups are based on an analysis of their ability to attract new customers, current and projected revenue growth, patents’ current value and potential, and position in their chosen markets. Presented below are the top 25 IoT startups to watch this year:
Armis Security – Armis takes a unique approach to provide visibility into IoT-enabled devices that are unmanaged across an IT network. The company’s solutions treat every IoT device as a threat surface, enabling enterprises to prohibit access to IoT devices and networks based on security guidelines. Another unique aspect of this company’s approach to deployment is the ability to use an enterprises’ existing infrastructure for rapid deployments. Founded in 2015 the company has active customers in finance, healthcare, manufacturing, and high technology industries. Armis Security has raised a total of $47M in funding over 3 Their latest funding was raised on Apr 9, 2018, from a Series B round of $30M from Bain Capital Ventures and Red Dot Capital Partners. Crunchbase reports Armis Security has $2.1M in revenue annually and competes with DigiCert, Skybox Security, and Aruba Networks most often in sales cycles.
Crate.io – Crate.io’s open source SQL database features integrated search for storing and analyzing machine data in real time. The company was founded in 2013 with the purpose of providing SQL developers with an open source SQL database to capture, analyze and manage their machine learning and AI-based data. CrateDB is an open source distributed database offering the scalability and performance of NoSQL with the power and ease of standard SQL. The CrateDB Cloud for Azure IoT is a turnkey data layer, offered as a hosted cloud service on Azure, enabling faster development of IoT platforms and data-driven smart factories. Most CrateDB customers use it for operational analytics workloads, performing fast time series, geospatial, text search, machine learning queries against streams of data and data at rest in Industrial IoT, enterprise cybersecurity & systems monitoring in all industries, smart city and building infrastructure, Vehicle fleet tracking & management and marketing analytics. The company has raised $17.9M in funding over 4 rounds.
Dragos – Dragos specializes in industrial (ICS/IIoT) cybersecurity. Their cloud-based Dragos Platform collects, detects, and automates asset inventorying and visualization, threat detection through threat behavior analytics, and security operations and incident response workflows. Dragos also has a Threat Operations Center that provides customers access to dedicated ICS incident response and threat hunting services as well as industrial specific intelligence reporting on vulnerabilities, threats, and community events. Dragos has raised a total of $48.2M in funding over 3 Their latest funding was raised on Nov 14, 2018, from a $37M Series B round with Canaan Partners.
Drayson Technologies – Drayson Technologies provides an IoT platform startup that is combining wireless charging technology and machine learning software to create smart sensor networks that deliver greater energy and cost efficiencies to its customers. Drayson is known for its expertise in energy-efficient and cost-effective IoT data collection and analysis, which also contributes to their customers’ ability to reduce the cost of deploying, owning and running IoT networks.
Element Analytics –Element Analytics is rapidly establishing itself as a startup to watch in the fields of chemicals & refining, manufacturing, metals & mining, pulp & paper, and upstream oil & gas. Their Element Platform helps industrial organizations easily and rapidly use industrial time-series data to improve production efficiency and product quality. Their platform prepares time-series data, enriches it with analytically relevant context, creating greater contextual insights. The Element Analytics platform also enables machine-learning modeling to surface reliability, productivity, and sustainability insights for operations. Element Analytics has raised a total of $22M in funding over 3 Their latest funding was raised on Jan 8, 2018, from a Series A round. Kleiner Perkins participated in the first two rounds, funding a total of $7M.
FogHorn – FogHorn is a fascinating startup to watch because they excel at embedding real-time analytics and machine-learning support into size- and space- constrained commercial and industry IoT application areas. Realizing that industrial manufacturing and distribution sites often have unreliable Internet connections if they have any at all, Foghorn has designed a miniaturized, scalable complex-event processing (CEP) software engine that is capable of producing analytics in real-time. The FogHorn Lightning™ platform includes the CEP software engine, enabling high-performance edge computing, advanced analytics, Machine Learning, and AI to be implemented highly constrained environments of IIoT. The company has also created a new class of high-performance programming language called Vel ™ which transforms any gateway, programmable logic controller (PLC), industrial PC, or another edge device into an advanced edge computing system. FogHorn has raised a total of $47.5M in funding over 4 Their latest funding was raised on Oct 4, 2017, from a Series B round. The FogHorn Technology Platform is shown below:
GEM – GEM specializes in providing IoT, analytics, and machine learning platforms and solutions for the manufacturing industry, with a specific focus on Overall Equipment Effectiveness (OEE) and predictive maintenance. The company has been able to gain customers in energy, retail, and GEM’s value proposition is based on their ability to increase manufacturers’ OEE levels through greater real-time insights. The GEM Precare platform captures operational data and KPIs in real-time including availability, OEE, performance, quality, MTBF, MTBA, machine statuses, status reasons, and alarms. The following is an example of the GENM technology platform:
IoTium – This is a fascinating company to track due to their patented technology that enables secure connections between Network as a Service (NaaS), legacy onsite systems and cloud-based applications. Customers include CBRE, Emerson, Intelligent Buildings, Obernel, Rexnord, and Sunbelt Controls. IoTium is well positioned to gain new customers in building and industrial automation, oil & gas, manufacturing, transportation, and smart city industries. IoTium has raised a total of $22M in funding over 2 rounds with investors GE Ventures, March Capital, and Juniper Networks. Their latest funding was raised on Sep 19, 2018, from a Series B round.
InfluxData – InfluxData created InfluxDB, their Open Source Platform specifically designed to analyze metrics and events (time series data) for DevOps and IoT applications. Whether the data comes from humans, sensors, or machines, InfluxData enables developers to build monitoring, analytics, and IoT applications at scale, delivering measurable business value quickly. The company reports having 400 customers including Cisco, eBay, IBM, and InfluxData has raised a total of $59.9M in funding over 4 rounds. Their latest funding was raised on Feb 13, 2018, from a Series C round.
Karamba Security – Karamba Security is focused on solving the security challenges of connected vehicles. The company offers Electronic Control Unit (ECU) endpoint security to protect any vehicle with an IoT connection or IP address. What makes this startup so interesting is how they are using patented technologies to reduce IoT-based attacks on vehicles by blocking them autonomously. Internet connectivity or extensive developer work is not needed to implement Karamba across a vehicle fleet. Each device can be reset to its factory settings, eliminating the threat of a vehicle being hacked. Karamba Security has raised a total of $27M in funding over 4 Their latest funding was raised on Apr 10, 2018, from a Series B round.
MachineMetrics – What makes MachineMetrics an interesting company to watch is their innovative approach to using Artificial Intelligence (AI) to discover new insights into manufacturer’s data that improve product quality and performance. It’s one of the first startups to combine Industrial Internet of Things (IIoT) and AI and provide a scalable platform for discrete manufacturers and heavy equipment builders. They’ve also developed an expertise at edge connectivity in manufacturing environments that have enabled greater real-time visibility and more meaningful manufacturing analytics than has been possible in the past. They’re using AI to drive their prescriptive and predictive alerts. MachineMetrics has raised a total of $13.4M in funding over 3 Their latest funding was raised on Dec 11, 2018, from a Series A round. The following is a Workstation View from the MachineMetrics Production platform:
MagicCube – MagicCube is a device independent IoT security platform that protects against on-device, cloud, and network attacks. The MagicCube solution secures digital transactions on any device, in transit, and in the cloud with the same level of security as device hardware solutions without the complexity and cost associated with hardware deployments. MagicCube, Inc. has raised a total of $10.7M in funding over 2 Their latest funding was raised on Aug 8, 2017, from a Series A round.
Myriota – What makes Myriota a fascinating company to watch is their innovative advances in ultra-low-cost satellite Internet of Things (IoT) connectivity and the alliances they are creating, including on with SpaceX. Myriota’s nano-satellite was launched into space aboard the SpaceX Falcon 9 rocket in December 2018. Myriota uses exactEarth’s Low Earth Orbit (LEO) satellite constellation for its connectivity solutions. Myriota is a global leader in low-cost satellite IoT connectivity, providing aggregated sensor reading, environmental sensing, and online tracking and condition monitoring of remote assets. The company has raised a total of $15M in funding over 1 round. This was a Series A round raised on Mar 26, 2018.
Particle – Particle is an Internet of Things (IoT) device platform that enables organizations to develop and fine-tune connectivity across operations using scalable APIs and software development resources. Particle’s development platform is designed to provide organizations with the tools they need to prototype IoT solutions to scale quickly and securely. Over 150,000 product builders in more than 170 countries and half of the Fortune 500 have deployed connected IoT devices powered by Particle. Particle’s customers include NASA, SpaceX, consumer hot tub manufacturer Jacuzzi, and Venture-backed by Root Ventures, Spark Capital, Qualcomm Ventures, and Particle is based in San Francisco, CA and Shenzhen, China. Particle has raised a total of $35.8M in funding over 7 rounds. Their latest funding was raised on Jul 19, 2017, from a Series B round.
Samsara – What makes Samsara noteworthy is their prioritizing how sensor data can increase the safety and efficiency of physical operations, contributing to productivity gains while reducing costs. Samsara is attracting customers from the transportation, logistics, construction, food production, energy, and manufacturing industries with their ability to improve the safety, efficiency, and quality of operations. Samsara builds sensor systems that combine wireless sensors with remote networking and cloud-based analytics. As of February 2019, the company has over 5,000 customers and has a run rate of 200,000 new devices being added every year. Samsara has raised a total of $230M in funding over 5 Their latest funding was raised on Dec 28, 2018, from a Series E round. An example of the company’s Fleet Summary is shown below:
SCADAfence – SCADAfence provides cybersecurity solutions designed to ensure the operational continuity of industrial (ICS/SCADA) networks. The startup excels at integrating Industrial IoT, analytics, realtime monitoring and machine-to-machine connectivity to provide scalable cybersecurity solutions for production networks. As of February 2019 the company has customers in the pharmaceutical, chemical, food & beverage and automotive industries. SCADAFence offers a solution suite that includes continuous real-time monitoring of the industrial environment as well as lightweight tools designed to automate the process of security assessment. The suite provides visibility of day-to-day operations, detection of cyber-attacks and forensics tools designed to improve responsiveness. SCADAfence has raised a total of $10M in funding over 3 Their latest funding was raised on Nov 21, 2017, from a Series A round.
SequoiaDB – SequoiaDB develops and provides commercial support for the open source database SequoiaDB, a document-oriented NewSQL database that supports JSON transaction processing and SQL query. Their database can either be a standalone product to interface with applications providing high performance and horizontally scalable data storage and processing functions or serve as the frontend of Hadoop and Spark for both real-time query and data analysis. It is designed to integrate with Spark, Hadoop/Cloudera. SequoiaDB has raised a total of $40M in funding over 3 Their latest funding was raised on Sep 19, 2018, from a Series C round.
Sight Machine – This is a fascinating startup to watch, I’ve been tracking Sight Machine for several years. The company is succeeding at attracting Fortune 500-level manufacturers as clients by providing them with AI-driven insights into how they can improve operations. Sight Machine’s AI and analytics platform, purpose-built for discrete and process manufacturing, uses artificial intelligence, machine learning, and advanced analytics to help address critical challenges in quality and productivity throughout the enterprise. The platform is powered by the industry’s only Plant Digital Twin, which enables real-time visibility and actionable insights for every machine, line, and plant throughout an enterprise. Sight Machine is optimized to run on the major cloud platforms including AWS, Google Cloud Platform, and Microsoft Azure. The company has raised a total of $30.5M in funding over 5 Their latest funding was raised on Dec 23, 2017, from a Series B round. An example of a Sight Machine dashboard is shown below:
Splice Machine –. Splice Machine provides an open-source dual-engine RDBMS for mixed operational and analytical workloads, powered by Apache Hadoop® and Apache Spark™. The Splice Machine RDBMS executes operational workloads on Apache HBase® and analytical workloads on Apache Spark. Splice Machine is known for its ease of development and use for IoT-based applications and is successfully offload operational and analytical workloads from Oracle, Teradata, and Netezza legacy systems. The company excels at ETL, operational reporting or real-time applications and use cases. Splice Machine has raised a total of $40M in funding over 4 Their latest funding was raised on Dec 20, 2017, from Salesforce Ventures.
SWIM.AI – Swim provides edge-based software that executes real-time analytics and machine learning for enterprises, equipment manufacturers, smart-cities, and IoT and IIoT businesses. Its software locally processes and analyzes massive volumes of streaming data from devices/sensors/equipment where it is created, reducing network volumes, and generating real-time machine-learning business insights. Swim deploys its software at the edge to transform data into insights in real-time and delivers them to businesses, staff, operators, and customers. Swim has successfully been deployed and is in use in existing equipment and brownfield environments. In manufacturing customers’ operations Swim is improving real-time synchronization across multiple systems, reduce project implementation costs, optimizing efficiency using machine learning insights from full resolution edge data and making insights available via real-time APIs. Swim.ai has raised a total of $10M in funding over 2 rounds. Their latest funding was raised on Jul 17, 2018, from a Series B round. Swim’s model is shown below:
Tulip – Tulip was started by a team of engineers out of the MIT Media Lab, and the company’s platform is based on over ten years of research in digital manufacturing. Their self-service technology fills the gap between rigid back-end manufacturing IT systems and the dynamic operations taking place on the shop floor. Tulip’s Manufacturing App Platform combines research in intelligent hardware sensors, computer vision, assistive user interfaces, and applied machine learning. Tulip was launched to bring these latest technological developments from the lab to the factory floor. Today, Tulip’s Manufacturing App Platform is deployed at dozens of global customers in six countries across multiple industries including Electronics, Aerospace & Defense, Medical Devices, Footwear, Pharmaceuticals, and Contract Manufacturing. Tulip Interfaces has raised a total of $13M in funding over 3
Tuya Smart – Tuya Smart is an IoT solution provider for device manufacturers. Their platform enables fast, agile app development, allowing smart device manufacturers to bring their product to market quickly and at competitive prices. Tuya Smart is founded by Jerry Wang, a founding executive of AliYun, Alibaba’s cloud division, along with a group of veterans from Alibaba, Baidu and Haier Electronics. With extensive knowledge in cloud computing, software development, and hardware and supply chain management, Tuya Smart’s team is enabling manufacturers to produce next-generation smart, connected products. Tuya has raised a total of $200M in funding over 3 Their latest funding was raised on Jul 24, 2018, from a Series C round.
Uptake – Uptake Technologies provides a predictive analytics and asset performance management (APM) platform gaining traction in key industrial IoT market segments today. The Uptake platform analyzes data from inside a company and from third party sources to predict and prevent failures, uncover hidden profits, and discover new opportunities to healthcare, insurance, locomotives, construction, manufacturing, and other industries. Uptake Technologies offers a platform for equipment monitoring, diagnostic troubleshooting, event, and condition prediction, and task management to improve uptime, streamline operations, and spot growth opportunities. Key customers include Caterpillar, Progress Rail, Berkshire Hathaway Energy, and the U.S. Army.
VDOO– VDOO has developed a platform of automated solutions to help IoT makers put the right security in their devices before release and enable post-deployment security. The end-to-end platform takes the maker from security analysis to implementation guidance to certification and enables IoT makers to quickly add the right security to their devices with minimal resources. VDOO’s solution is built upon a comprehensive taxonomy of IoT devices and consists of five interrelated and integrated products including the Security Requirements Generator, Security Gap Analysis, Actionable Security Plan, Certification, and Post-Deployment Security Enablement. VDOO has raised a total of $13M in funding over 1 round. This was a Series A round raised on Jan 17, 2018.
Xage Security – Xage provides decentralized security services for industrial manufacturing and distribution businesses including oil and gas, transportation, and utilities. The Xage architecture relies on blockchain to provide a distributed, scalable and highly reliable data store that prevents hackers from attacking and gaining access through any threat surface in an organization. Xage takes a unique approach to using blockchain to thwart hacking attempts at scale, by simultaneously protecting every active ledger in an organization. Xage Security has raised a total of $16M in funding over 2 Their latest funding was raised on Dec 28, 2018, from a Series A round.
Sales, Marketing and Operations are most active early adopters of IoT today.
Early adopters most often initiate pilots to drive revenue and gain operational efficiencies faster than anticipated.
32% of enterprises are investing in IoT, and 48% are planning to in 2019.
IoT early adopters lead their industries in advanced and predictive analytics adoption.
These and many other fascinating insights are from Dresner Advisory Services’ latest report, 2018 IoT Intelligence® Market Study, in its 4th year of publication. The study concentrates on end-user interest in and demand for business intelligence in IoT. The study also examines key related technologies such as location intelligence, end-user data preparation, cloud computing, advanced and predictive analytics, and big data analytics. “While the market is still in an early stage, we believe that IoT Intelligence, the means to understand and leverage IoT data, will continue to expand as organizations mature in their collection and leverage of sensor level data,” said Howard Dresner, founder, and chief research officer at Dresner Advisory Services. 70% of respondents work at North American organizations (including the United States, Canada, and Puerto Rico). EMEA accounts for about 20%, and the remainder is distributed across Asia-Pacific and Latin America. Please see pages 11, 15 through 18 of the study for specifics regarding the methodology and respondent demographics.
Key insights gained from the study include the following:
Sales, Marketing and Operations are most active early adopters of IoT today. Looking to capitalize on IoT’s potential to gain real-time customer feedback on products’ and services’ performance, Sales and Marketing lead all departments in their prioritizing IoT’s value in the enterprises. 12% of Operations leaders say that IoT is critical to attaining their goals. Executive Management and Finance have yet to see the value that Sales, Marketing and Operations do.
Manufacturers see IoT as the most critical to achieving their product quality, production scheduling and supply chain orchestration goals. Insurance industry leaders also view IoT as critical to operations as their business models are now concentrating on automating inventory and safety management. Insurance firms also track vehicles in shipping and logistics fleets to gain greater visibility into how route operations can be optimized at the lowest possible risk of accidents. Financial Services and Healthcare are the next most interested in IoT with Higher Education and Business Services assign the lowest levels of importance by industry.
Investment in IoT analytics, application development and defining accurate, reliable metrics to guide development is the most critical aspect of IoT adoption today. Investments in the data supply chain including data capture, movement, data prep, and management is the second-most critical area followed by investments in IoT infrastructure. Analytics, application development, and accurate, reliable metrics guiding DevOps are consistent with the study’s finding that early adopters have an excellent track record adopting and applying advanced and predictive analytics to challenging logistical, operations, sales, and marketing problems.
IoT early adopters or advocates prioritize dashboards, reporting, IoT use cases that provide data streams integral to analytics, advanced visualization, and data mining. IoT early adopters and the broader respondent base differ most in the prioritization of IT analytics, location intelligence, integration with operational processes, in-memory analysis, open source software, and edge computing. The data reflects how IoT early adopters quickly become more conversant in emerging technologies with the goal of achieving exponential scale across analytics and IoT platforms.
The criticality of advanced and predictive analytics to all leaders surveyed is at an all-time high. Attaining a (weighted-mean) importance score of 3.6 on a 5.0 scale, advanced and predictive analytics is today considered “critical” or “very important” to a majority of respondents. Despite a mild decline in 2017, importance sentiment (the perceived criticality of advanced and predictive analytics) is on an uptrend across the five years of our study. Mastery of advanced and predictive analytics is a leading indicator of IoT adoption, indicating the potential for more analytics pilots and in-production IoT projects next year.
The most valuable features for advanced and predictive analytics apps include support for a range of regression models, hierarchical clustering, descriptive statistics, and recommendation engine support. Model management is important to more than 90% of respondents, further indicating IoT analytics scale is a goal many are pursuing. Geospatial analysis (highly associated with mapping, populations, demographics, and other web-generated data), Bayesian methods, and automatic feature selection is the next most required series of features.
Access to advanced analytics for predictive and temporal analysis is the most important usability benefit to IoT adopters today. Second is support for easy iteration, and third is a simple process for continuous modification of models. The study evaluated a detailed set of nine usability benefits that support advanced and predictive activities and processes. All nine benefits are important to respondents, with the last one of a specialist not being required important to a majority of them at 70%.
30% of tech leaders globally predict blockchain will disrupt their businesses by 2021.
IoT, Artificial Intelligence (AI) and Robotics have the greatest potential to digitally transform businesses, making them more customer-centered and efficient.
26% of global tech leaders say e-Commerce apps and platforms will be the most disruptive new business model in their countries by 2021.
IDC predicts worldwide IoT spending will reach $1.1T by 2021.
These and many other insights are from KPMG’s recent research study Tech Disruptors Outpace The Competition. The study can be downloaded here (PDF, 42 pp., no opt-in.). The methodology is based on interviews with 750 global technology industry leaders, 85% of whom are C-level executives. For additional details on the methodology, please see pages 32 and 33 of the study. The study found that the three main benefits of adopting IoT, AI, and robotics include improved management of personal information, increased personal productivity, and improved customer experience through personalized real-time information. Key insights gained from the study include the following:
IoT, Artificial Intelligence (AI) and Robotics have the greatest potential to digitally transform businesses, making them more customer-centered and efficient. Tech leaders also see these three core technologies enabling the next indispensable consumer technology and driving the greatest benefit to life, society, and the environment. KPMG’s research team found that tech companies are integrating these three technologies to create growth platforms for new business ventures while digitally transforming existing business processes. Tech leaders in the U.K. (21%), Japan (20%) and the U.S. (16%) lead all other nations in their plans for IoT digitally transforming their businesses by 2021. Please click on the graphic below to expand for easier reading.
30% of tech leaders globally predict blockchain will disrupt their businesses by 2021. 50% of Japanese tech leaders predict that blockchain will digitally transform their industries and companies by 2021, leading all nations included in the survey. IoT processes and the rich, real-time data stream sensors and systems are capable of delivering is predicted by tech leaders to be the primary catalyst that will enable blockchain to digitally transform their businesses. 27% of tech leaders globally expect IoT data and applications combined with blockchain to redefine their companies, supply chains and industries. Identity authentication (24%), automated trading (22%) and contracts (14%) are the 2nd through fourth-most disruptive aspects of blockchain by 2021 according to tech leaders. Please click on the graphic below to expand for easier reading.
26% of global tech leaders say e-Commerce apps and platforms will be the most disruptive new business model in their countries by 2021. 19% see social media platforms creating the majority of new business models, followed autonomous vehicle platforms (14%) and entertainment platforms (11%). KPMG’s analysis includes a ranking of top business models by country, with e-Commerce dominating four of the five regions included in the survey.
50% of tech leaders expect media, transportation, healthcare, and transportation to experience the greatest digital transformation in the next three years. Respondents most mentioned Amazon, Netflix, Alibaba, Uber, Google, and Facebook as examples of companies who will digitally transform their industries by 2021. The following table provides insights into which industries by country will see the greatest digital transformations in the next three years. Entertainment platforms are predicted by tech leaders to have the greatest potential to digitally transform the media industry in the U.S. by 2021.
Tech leaders predict IoT’s greatest potential for adoption by 2021 is in consumer products, education, services, industrial manufacturing, and telecom. AI’s greatest potential to digitally transform business models is in healthcare and industrial manufacturing (both 11%), consumer products, financial, and services (10% each). As would be expected, Robotics’ adoption and contribution to digitally transforming businesses will be most dominant in industrial manufacturing (15%), followed by healthcare (11%) and consumer, financial and services (10%). Please click on the graphic to expand for easier reading.
According to IDC, worldwide spending on the IoT is forecast to reach $772.5B in 2018. That represents an increase of 15% over the $674B that was spent on IoT in 2017.
The global IoT market will grow from $157B in 2016 to $457B by 2020, attaining a Compound Annual Growth Rate (CAGR) of 28.5%.
Discrete Manufacturing, Transportation and Logistics, and Utilities will lead all industries in IoT spending by 2020, averaging $40B each.
Bain predicts B2B IoT segments will generate more than $300B annually by 2020, including about $85B in the industrial sector.
Internet Of Things Market To Reach $267B By 2020 according to Boston Consulting Group.
According to IDC FutureScape: Worldwide IoT 2018 Predictions, By the end of 2020, close to 50% of new IoT applications built by enterprises will leverage an IoT platform that offers outcome-focused functionality based on comprehensive analytics capabilities.
The last twelve months of Internet of Things (IoT) forecasts and market estimates reflect enterprises’ higher expectations for scale, scope and Return on Investment (ROI) from their IoT initiatives. Business benefits and outcomes are what drives the majority of organizations to experiment with IoT and invest in large-scale initiatives. That expectation is driving a new research agenda across the many research firms mentioned in this roundup. The majority of enterprises adopting IoT today are using metrics and key performance indicators (KPIs) that reflect operational improvements, customer experience, logistics, and supply chain gains. Key takeaways from the collection of IoT forecasts and market estimates include the following:
The global IoT market will grow from $157B in 2016 to $457B by 2020, attaining a Compound Annual Growth Rate (CAGR) of 28.5%. According to GrowthEnabler & MarketsandMarkets analysis, the global IoT market share will be dominated by three sub-sectors; Smart Cities (26%), Industrial IoT (24%) and Connected Health (20%). Followed by Smart Homes (14%), Connected Cars (7%), Smart Utilities (4%) and Wearables (3%). Source: GrowthEnabler, Market Pulse Report, Internet of Things (IoT), 19 pp., PDF, free, no opt-in.
Bain predicts B2B IoT segments will generate more than $300B annually by 2020, including about $85B in the industrial sector. Advisory firm Bain predicts the most competitive areas of IoT will be in the enterprise and industrial segments. Bain predicts consumer applications will generate $150B by 2020, with B2B applications being worth more than $300B. Globally, enthusiasm for the Internet of Things has fueled more than $80B in merger and acquisition (M&A) investments by major vendors and more than $30B in venture capital, according to Bain’s estimates. Source: Bain Insights: Choosing The Right Platform For The Internet Of Things
The global IoT market is growing at a 23% CAGR of 23% between 2014-2019, enabling smart solutions in major industries including agriculture, automotive and infrastructure. ― Key challenges to growth are the security and scalability of all-new connected devices and the adherence to open standards to facilitate large-scale monitoring of different systems. Source: Export opportunities of the Dutch ICT sector to Germany (25-04-17), PDF, 95 pp., no opt-in
According to Variant Market Research, the Global Internet of Things (IoT) market is estimated to reach $1,599T by 2024, from $346.1B in 2016, attaining a CAGR of 21.1% from 2016 to 2024. Asia-Pacific is predicted to grow at the fastest CAGR over the forecast period 2016 to 2024. The growth is attributed to increasing adoption of IoT in emerging countries such as India and China, high rate of mobile and internet usage, and development of next-generation technologies. Source: Global Internet of Things (IoT) Market: Rising Adoption of Cloud Platform Noticed by Variant Market Research.
Discrete Manufacturing, Transportation and Logistics, and Utilities will lead all industries in IoT spending by 2020, averaging $40B each. Improving the accuracy, speed, and scale of supply chains is an area many organizations are concentrating on with IoT. IoT has the potential to redefine quality management, compliance, traceability and Manufacturing Intelligence. Business-to-Consumer (B2C) companies are projected to spend $25B on IoT in 2020, up from $5B in 2015. The following graphic compares global spending by vertical between 2015 and 2020. Source: Statista, Spending on the Internet of Things worldwide by vertical in 2015 and 2020 (in billion U.S. dollars).
By 2020, 50% of IoT spending will be driven by discrete manufacturing, transportation, and logistics, and utilities BCG predicts that IoT will have the most transformative effect on industries that aren’t technology-based today. The most critical success factor all these use cases depend on secure, scalable and reliable end-to-end integration solutions that encompass on-premise, legacy and cloud systems, and platforms.Source: Internet Of Things Market To Reach $267B By 2020.
The hottest application areas for IoT in manufacturing include Industrial Asset Management, Inventory and Warehouse Management and Supply Chain Management. In high tech manufacturing, Smart Products, and Industrial Asset Management are the hottest application areas. The following Forrester heat Map for 2017 shows the fastest growing areas of IoT adoption by industry. Source: IoT Opportunities, Trends, and Momentum Robert E Stroud CGEIT CRISC.
B2B spending on IoT technologies, apps and solutions will reach €250B ($296.8B) by 2020 according to a recent study by Boston Consulting Group (BCG). IoT Analytics spending is predicted to generate €20B ($23.7B) by 2020. Between 2015 to 2020, BCG predicts revenue from all layers of the IoT technology stack will have attained at least a 20% Compound Annual Growth Rate (CAGR). B2B customers are the most focused on services, IoT analytics, and applications, making these two areas of the technology stack the fastest growing. By 2020, these two layers will have captured 60% of the growth from IoT. Source: Internet Of Things Market To Reach $267B By 2020.
Manufacturers most relied on the Industrial Internet of Things (IIoT) in 2017 to help better understand machine health (32%) on the shop floor, leading to more accurate Overall Equipment Effectiveness (OEE) measurements. Changing how plant maintenance personnel will work and interact with all levels of operation (29.5%) and helping to better prevent and predict shutdowns (27.1%) are the top three use cases of IIoT according to Plant Engineering and Statista.
Improving customer experiences (70%) and safety (56%) are the two areas enterprises are using data generated from IoT solutions most often today. Gaining cost efficiencies, improving organizational capabilities, and gaining supply chain visibility (all 53%) is the third most popular uses of data generated from IoT solutions today. 53% of enterprises expect data from IoT solutions to increase revenues in the next year. 53% expect data generated from their IoT solutions will assist in increasing revenues in the next year. 51% expect data from IoT solutions will open up new markets in the next year. 42% of enterprises are spending an average of $3.1M annually on IoT. Source: 70% Of Enterprises Invest In IoT To Improve Customer Experiences.
McKinsey Global Institute estimates IoT could have an annual economic impact of $3.9T to $11.1T by 2025. Their forecast scenario includes diverse settings and use cases including factories, cities, retail environments, and the human body. Factories alone could contribute between $1.2T to $3.7T in IoT-driven value. Source: McKinsey & Company, What’s New With The Internet of Things?
Business Intelligence Competency Centers (BICC), R&D, Marketing & Sales and Strategic Planning are most likely to see the importance of IoT. Finance is considered among the least likely departments to see the importance of IoT. The study also found that sales analytics apps are increasingly relying on IoT technologies as foundational components of their core application platforms.These and many other insights are from Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series study. The study defines IoT as the network of physical objects, or “things,” embedded with electronics, software, sensors, and connectivity to enable objects to collect and exchange data. The study examines key related technologies such as location intelligence, end-user data preparation, cloud computing, advanced and predictive analytics, and big data analytics. Please see page 11 of the study for details regarding the methodology.
Manufacturing, Consulting, Business Services and Distribution/Logistics are IoT industry adoption leaders. Conversely, Federal Government, State & Local Government are least likely to prioritize IoT initiatives as very important or critical. IoT early adopters are most often defining goals with clear revenue and competitive advantages to drive initiatives. Manufacturing, Consulting, Business Services and Distribution/Logistics are challenging, competitive industries where revenue growth is often tough to achieve. IoT initiatives that deliver revenue and competitive strength quickly are the most likely to get funding and support. Source: Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series study.
IoT advocates or early adopters say location intelligence, streaming data analysis, and cognitive BI to deliver the greatest business benefit. Conversely, IoT early adopters aren’t expecting to see as significant of benefits from data warehousing as they are from other technologies. Consistent with previous studies, both the broader respondent base and IoT early adopters place a high priority on reporting and dashboards. IoT early adopters also see the greater importance of visualization and end-user self-service. Source: Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series study.
Business Intelligence Competency Centers (BICC), Manufacturing and Supply Chain are among the most powerful catalysts of BI and IoT adoption in the enterprise. The greater the level of BI adoption across the 12 functional drivers of BI adoption defined in the graphic below, the greater the potential for IoT to deliver differentiated value based on unique needs by area. Marketing, Sales and Strategic Planning are also strong driver areas among IoT advocates or early adopters. Source: Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series study.
IoT early adopters are relying on growing revenue and increasing competitive advantage as the two main goals to drive IoT initiatives’ success. The most successful IoT advocates or early adopters evangelize the many benefits of IoT initiatives from a revenue growth position first. IoT early adopters are more likely to see and promote the value of better decision-making, improved operational efficiencies, increased competitive advantage, growth in revenues, and enhanced customer service when BI adoption excels, setting the foundation for IoT initiatives to succeed. Source: Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series study.
The most popular feature requirements for advanced and predictive analytics applications include regression models, textbook statistical functions, and hierarchical clustering. More than 90% of respondents replied that these three leading features are “somewhat important” to their daily use of analytics. Geospatial analysis (highly associated with mapping, populations, demographics, and other Web-generated data), recommendation engines, Bayesian methods, and automatic feature selection is the next most required series of features. Source: Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series study.
74% of IoT advocates or early adopters say location intelligence is critical or very important. Conversely, only 26% of the overall sample ranks location intelligence at the same level of importance. One of the most promising use cases for IoT-based location intelligence is its potential to streamline traceability and supply chain compliance workflows in highly regulated manufacturing industries. In 2018, expect to see ERP and Supply Chain Management (SCM) software vendors launch new applications that capitalize on IoT location intelligence to streamline traceability and supply chain compliance on a global scale. Source: Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series study.
According to IDC FutureScape: Worldwide IoT 2018 Predictions, by the end of 2020, close to 50% of new IoT applications built by enterprises will leverage an IoT platform that offers outcome-focused functionality based on comprehensive analytics capabilities. By 2021, 75% of enterprises with a positive IoT ROI will use tactical analytics applications to reduce operating costs, but the 25% that successfully invest strategically in a decision architecture will increase their revenue share. Source: IDC FutureScape: Worldwide IoT 2018 Predictions.
The global IoT market is projected to grow to $661.74B by 2021. The Industrial IoT market is expected to grow to $123.8B by 2021, and the IoT Cloud Market is estimated to grow to $7.15B by Source: IoT Growth: A Forecast.
WiFi and Bluetooth low energy (BLE) are top contenders as preferred IoT connectivity mechanisms. However, long-range, wide-area networks (LoRaWAN) and narrowband IoT (NB-IoT) are equally poised to give a tough fight to WiFi and BLE vendors. Data analytics, correlation, and pattern recognition capabilities at point-of-data creation prove to be a key decision factor in vendor evaluation. Source: IDC Survey Reveals Significant Impact of Internet of Things Initiatives on IT Infrastructure.
According to IDC, worldwide spending on the Internet of Things (IoT) is forecast to reach $772.5B in 2018, an increase of 14.6% over the $674B that will be spent in 2017. IoT hardware will be the largest technology category in 2018 with $239B going largely toward modules and sensors along with some spending on infrastructure and security. Services will be the second largest technology category, followed by software and connectivity. Source: IDC Forecasts Worldwide Spending on the Internet of Things to Reach $772 Billion in 2018.
Manufacturing-based IoT connections grew 84% between 2016 and 2017, followed by energy & utilities (41%).
73% of executives are either researching or currently launching IoT projects.
The IoT platform market is expected to grow 35% per year to $1.16B by 2020.
B2B uses can generate nearly 70% of the potential value enabled by IoT.
These and many other fascinating findings are from Verizon’s State of the Market: Internet of Things 2017, Making way for the enterprise (16 pp., PDF, free, opt-in). The Verizon study found that the Internet of Things (IoT) gained significant momentum in 2016, with 2017 IoT investments accelerating. The majority of investments today are in IoT projects that are still in the concept or pilot phase, concentrating on tracking data and sending alerts. While easier to initiate and manage, the majority of pilots aren’t providing the depth of analytics data and insights IoT has the potential to deliver.
Key takeaways from the study include the following:
Manufacturing-based IoT connections grew 84% between 2016 and 2017, followed by energy & utilities (41%). Transportation and distribution (40%), smart cities and communities (19%) and healthcare and pharma (11%) are the remaining three industries tracked in the study who had positive growth in the number of IoT connections. The following graphic compares year-over-year growth by industry for the 2016 to 2017 timeframe.
Manufacturing is predicted to lead IoT spending in 2017 with $183B invested this year. Verizon’s study predicts that transportation and utilities will have the second and third-largest capital expenses in IoT this year. Insurance, consumer and cross-industry IoT investments including connected vehicles and smart buildings will see the fastest overall growth in 2017.
Improving the customer experience and excel at customer service by gaining greater insights using IoT leaders enterprises’ investment priorities. 33% of enterprises interviewed prioritize using IoT technologies and the insights it’s capable of providing to excel at customer service. 26% intend to use IoT technologies to improve asset management and increase Return on Assets (ROA) and Return on Invested Capital (ROIC). Consistent with how dominant manufacturing’s investment plans are for IoT this year, production and delivery capabilities are the top deployment priority for 25% of all businesses interviewed.
IoT has the potential to revolutionize pharmaceutical supply chains by drastically reducing drug counterfeiting globally. It’s estimated that counterfeit drugs cost the industry between $75B to $200B annually. The human costs of treating those who have been sold counterfeit drugs back to health are incalculable. IoT platforms and systems have the potential to drastically reduce the costs of counterfeiting, both on a personal impact and market standpoint. Drug manufacturers operating in the United States have until November 2017 to mark packages with a product identifier, serial number, lot number and expiration date, plus electronically store and transfer all transaction histories, including shipment information, across their distribution supply chains. Pharmaceutical manufacturers have a high level of urgency to make this happen and stay in compliance with the US Drug Supply Chain Security Act. IoT solutions are flourishing in this industry as a result.
According to the Cisco Visual Networking Index, M2M connections will represent 46% of connected devices by 2020.
95% of execs surveyed plan to launch an IoT business within three years.
These and many other insights are from the recently published Cisco Internet of Things (IoT) study, The Journey to IoT Value: Challenges, Breakthroughs, and Best Practices published on SlideShare last month. The study is based on a survey of 1,845 IT and business decision-makers in the United States, UK, and India. Industries included in the analysis include manufacturing, local government, retail/hospitality/sports, energy (utilities/oil & gas/mining), transportation, and health care. All respondents worked for organizations that are implementing or have completed IoT initiatives. 56% of all respondents are from enterprises.
Key takeaways from the study include the following:
73% Are Using Internet Of Things Data To Improve Their Business. The data and insights gained from IoT are most often used for improving product quality or performance (47%), improving decision-making (46%) and lowering operational costs (45%). Improving or creating new customer relationships (44%) and reducing maintenance or downtime (42%) are also strategic areas where IoT is making a contribution today according to the Cisco study.
IT executives often see IoT initiatives as more successful (35%) than their line-of-business counterparts (15%). With IT concentrating on technologies and line-of-business users focused on strategy and business cases, the potential exists for differences of opinion regarding IoT initiatives’ value. The following graphic provides an overview of how stark these differences are.
Engaging with the IoT partner ecosystem in every phase of a project or initiative improves the probability of success. The most valuable phases to engage with ecosystem partners include strategic planning (60%), implementation and deployment (58%) and technical consulting or support (58%). The following graphic provides an overview of most and less successful organizations by their level of involvement in the IoT partner ecosystem.
Only 26% of all companies are successful with their IoT initiatives. The three best practices that lead to a successful IoT implementations include collaboration between IT and business, the availability of internal and external partnerships to gain IoT expertise; and a strong technology-focused culture.
60% of companies believe IoT projects look good on paper but prove more complex that expected. This finding underscores how critical it is for IT and line-of-business executives to have the same goals and objectives going into an IoT project. Being selective about which integration, technology, and professional services partners are chosen needs to be a shared priority between both IT and line-of-business executives.
Enabling real-time integration across on-premise and cloud platforms often involves integrating SAP, Salesforce, third-party and legacy systems. 2017 will be a break-out year for real-time integration between SAP, Salesforce, and third party systems in support of Internet of Things and Industrial Analytics.
McKinsey Global Institute predicts that the Internet of Things (IoT) will generate up to $11T in value to the global economy by 2025.
Predictive and prescriptive maintenance of machines (79%), customer/marketing related analytics (77%) and analysis of product usage in the field (76%) are the top three applications of Industrial Analytics in the next 1 to 3 years.
Real-Time Integration Is the Cornerstone Of Industrial Analytics
Industrial Analytics (IA) describes the collection, analysis and usage of data generated in industrial operations and throughout the entire product lifecycle, applicable to any company that is manufacturing and selling physical products. It involves traditional methods of data capture and statistical modeling. Enabling legacy, third-party and Salesforce, SAP integration is one of the most foundational technologies that Industrial Analytics relies on today and will in the future. Real-time integration is essential for enabling connectivity between Internet of Things (IoT) devices, in addition to enabling improved methods for analyzing and interpreting data. One of the most innovative companies in this area is enosiX, a leading global provider of Salesforce and SAP integration applications and solutions. They’re an interesting startup to watch and have successfully deployed their integration solutions at Bunn, Techtronic Industries, YETI Coolers and other leading companies globally.
A study has recently been published that highlights just how foundational integration will be to Industrial Analytics and IoT. You can download the Industrial Analytics Report 2016/17 report here (58 pp., PDF, free, opt-in). This study was initiated and governed by the Digital Analytics Association e.V. Germany (DAAG), which runs a professional working group on the topic of Industrial Analytics. Research firm IoT Analytics GmbH was selected to conduct the study. Interviews with 151 analytics professionals and decision-makers in industrial companies were completed as part of the study. Hewlett-Packard Enterprise, data science service companies Comma Soft and Kiana Systems sponsored the research. All research and analysis related steps required for the study including interviewing respondents, data gathering, data analysis and interpretation, were conducted by IoT Analytics GmbH. Please see page 52 of the study for the methodology.
With real-time integration, organizations will be able to Increase revenue (33.1%), increase customer satisfaction (22.1%) and increase product quality (11%) using Industrial Analytics. The majority of industrial organizations see Industrial Analytics as a catalyst for future revenue growth, not primarily as a means of cost reduction. Upgrading existing products, changing the business model of existing products, and creating new business models are three typical approaches companies are taking to generate revenue from Industrial Analytics. Integration is the fuel that will drive Industrial Analytics in 2017 and beyond.
For many manufacturers, the more pervasive their real-time SAP integration is, the more effective their IoT and Industrial Analytics strategies will be. Manufacturers adopting this approach to integration and enabling Industrial Analytics through their operations will be able to attain predictive and prescriptive maintenance of their product machines (79%). This area of preventative maintenance is the most important application of Industrial Analytics in the next 1 – 3 years. Customer/marketing-related analytics (77%) and analysis of product usage in the field (76%) are the second- and third-most important. The following graphic provides an overview of the 13 most important applications of Industrial Analytics.
68% of decision-makers have a company-wide data analytics strategy, 46% have a dedicated organizational unit and only 30% have completed actual projects, further underscoring the enabling role of integration in their analytics and IoT strategies. The study found that out of the remaining 70% of industrial organizations, the majority of firms have ongoing projects in the prototyping phase.
Business Intelligence (BI) tools, Predictive Analytics tools and Advanced Analytics Platforms will be pivotal to enabling industrial data analysis in the next five years. Business Intelligence Tools such as SAP Business Objects will increase in importance to industrial manufacturing leaders from 39% to 77% in the next five years. Predictive Analytics tools such as HPE Haven Predictive Analytics will increase from 32% to 69%. The role of spreadsheets used for industrial data analytics is expected to decline (i.e., 27% think it is important in 5 years vs. 54% today).
The Industrial Analytics technology stack is designed to scale based on the integration of legacy systems, industrial automation apps and systems, MES and SCADA systems integration combined with sensor-based data. IoT Analytics GmbH defines the technology stack based on four components inclouding data sources, necessary infrastructure, analytics tools, and applications. The following graphic illustrates the technology stack and underscores how essential integration is to the vision of Industrial Analytics being realized.
Industrial Internet of Things (IIoT) and Industry 4.0 will rely on real-time integration to enable an era of shop-floor smart sensors that can make autonomous decisions and trade-offs regarding manufacturing execution. IoT Analytics GmbH predicts this will lead to smart processes and smart products that communicate within production environments and learn from their decisions, improving performance over time. The study suggests that Manufacturing Execution System (MES) agents will be vertically integrated into higher level enterprise planning and product change management processes so that these organizations can synchronously orchestrate the flow of data, rather than go through each layer individually.
Cisco predicts the global IoT market will be $14.4T by 2022.
IC Insights predicts revenue from Industrial Internet IoT spending will increase from $6.4B in 2012 to $12.4B in 2015.
IoT in manufacturing market size is estimated to grow from $4.11B in 2015 to $13.49B by 2020, attaining a CAGR of 26.9%.
With the potential to streamline and deliver greater time and cost savings to a broad spectrum of enterprise tasks, opportunities for Internet of Things (IoT) adoption are proliferating. It’s encouraging to see so many industry-leading manufacturers, service providers, software and systems developers getting down to the hard work of making the vision IoT investments pay off.
IC Insights predicts revenue from Industrial Internet of Things spending will increase from $6.4B in 2012 to $12.4B in 2015, attaining a 17.98% CAGR. IC Insights predicts the Industrial Internet will lead all five categories of its forecast, with Connected Cities being the second-most lucrative, attaining a 13.16% CAGR in the forecast period. The research firm segments the industry into five IoT market categories: connected homes, connected vehicles, wearable systems, industrial Internet, and connected cities. Source: IC Insights Raises Growth Forecast for IoT.
Manufacturing (27%), retail trade (11%), information services (9%), and finance and insurance (9%) are the four industries that comprise more than half the total value of the projected $14.4T market. The remaining 14 industries range between 7% percent and 1%. The following graphic based on Cisco’s analysis of the IoT market potential by industry and degree of impact. Cisco predicts Smart Factories will contribute $1.95T of the total value at stake by 2022. Source: Embracing the Internet of Everything To Capture Your Share of $14.4 Trillion, white paper published by Cisco.
Intel Capital, Qualcomm Ventures, Foundry Group, Kleiner Perkins Caufield & Byers (KPCB), Andreessen Horowitz, Khosla Ventures, True Ventures and Cisco Investments are the leading IoT investors this year. Intel Capital is investing in a broad base of IoT-related technologies, encompassing 3D body-scanning and biometric sensors, wearable sand IoT infrastructure startups. Source: The Most Active VCs In The Internet Of Things And Their Investments In One Infographic.
Vodafone’s latest Machine-to-Machine (M2M) study found that 37% of enterprises have projects targeted to go live in 2017. Vodafone defines M2M as technologies that connect machines, devices, and objects to the Internet, turning them into ‘intelligent’ assets that can communicate. M2M enables the Internet of Things. The following graphics compare M2M adoption trends from 2013 and 2015 and by industry. Source: 2015 Vodafone M2M Barometer Report (free, opt-in reqd., 36 pp.).
New connections to the Internet of Things (IoT) will grow from about 1.7B in 2015 to nearly 3.1B in 2019. IoT applications will also fuel strong sales growth in optoelectronics, sensors/actuators, and discrete semiconductors, which are projected to reach $11.6B in 2019, attaining a CAGR of 26% during the forecast period. Source: IC Insights Internet of Things Market to Nearly Double by 2019.
IDC predicts that by 2018, 40% of the top 100 discrete manufacturers will rely on connected products to provide product as a service. 55% of discrete manufacturers are researching, piloting, or in production with IoT initiatives. By 2017, 50% of manufacturers will explore the viability of micrologistics networks to enable the promise of accelerated delivery for select products and customers. 65% of companies with more than ten plants will enable workers on the factory floor to make better business decisions through investments in operational intelligence. Source: IDC Manufacturing Insights Report courtesy of Cognizant, Transforming Manufacturing with the Internet of Things May 2015