50 Industrial IoT Statistics and Trends for 2018

We’ve collected the latest case studies, surveys, and research papers, giving you one spot to learn more about the growing field of Industrial IoT. To make things easier, click the subject below that you want to learn more about:

The Industrial IoT field is expanding every single day. Make sure you’re up to date with the latest statistics and trends to ensure your operation is ready for the digital revolution.


The German wing of PwC published findings of what they expect of IoT and Industry 4.0 adoption in the German manufacturing industry in the future.

  • 91% of respondents are investing in digital factories, but only 6% consider their factories to be fully digitized.
  • 75% of respondents invested in digital factories in order to better serve customer preferences.
  • Nearly 50% of respondents expect an ROI on their digitization efforts in 5 years
  • Companies expect a total of 12% efficiency gains over five years thanks to Industrial IoT technology

Research by Accenture outlines both the benefits and obstacles corporations see when implementing IoT solutions.

  • 44% sight poor information and communications infrastructure, and poor access to required capital
  • 42% said lack of government support is preventing them from adoption
  • 18% felt there is insufficient science, technology, engineering, and mathematics skills in the workforce
  • 46% expect IoT to increase employee productivity
  • 46% expect improvements in asset optimization thanks to IoT
  • 44% expect IoT to cut costs

In their IoT Platforms: Market Report 2015-2021, IoT Analytics shared exciting insights about the growth of the IoT platforms market.

  • In 2015, the worldwide IoT platforms market reached a value of $295 million
  • The IoT platform market is growing at a CAGR of 33%
  • The market is expected to reach a value of $1.6 billion by 2021
  • Manufacturing is slated to be the largest market for IoT platforms with an expected value of $438 million by 2021

In TechJini’s roundup of expert opinions on the future of IoT, several contributors anticipate more robust technology integration and increased data processing nearer to the original data source.

  • Ian Moyse of Natterbox anticipates more blended solutions that include mobile, Big Data, cloud, and IoT technology
  • Digital influencer Dion Hinchcliffe believes the growth of edge computing systems will enable organizations to scale IoT systems of greater complexity
  • Joe Klein of Disrupt6 expects to see analytics and machine learning functioning closer to the edge (i.e. closer to the point of data collection)

The Future of Industrial IoT Adoption

As a whole, it appears European manufacturers are ahead of the curve when it comes to IoT implementation and application. Manufacturers in the EU, particularly in Germany, are eager to implement advanced IoT systems in their domestic operations. Such systems will uncover revenue opportunities, reduce operating costs, and increase employee productivity.

While some challenges lie ahead, including poor infrastructure and lack of government support, the worldwide growth in Industry 4.0 applications points to a significant paradigm shift in the next 5 years. We expect the emergence of industry-wide standards in system implementation, asset tracking, and data analysis.


A press release from the International Federation of Robotics (IFR) outlined the present and expected future market for industrial robotics.

  • 2.6 million industrial robots are expected to deployed worldwide by 2019
  • By 2019, China will account for 40% of sales of industrial robots
  • The world average for robot density is 69 units per 10,000 employees
  • Asia leads the pack in robot density, with Korea being the most robot dense country in the world at 531 units per 10,000 employees
  • In Germany, employment and robotics in manufacturing are growing at parallel rates (2.5% and 3%)
  • Between 2017 and 2019, the robotics market is expected to grow by 13% annually

In a European study between 1999 and 2010, researchers found that fear of job loss due to automation are likely exaggerated.

  • The study found that automation resulted in the equivalent labor loss of 9.6 million jobs in the EU
  • Price reductions due to automation increased product demand, and as a result labor demand by 8.7 million jobs
  • The resulting multiplier effect of increased spending in the economy would further increase labor demand by up to 12.4 million jobs
  • The net total effect of increased automation would labor demand by 11.6 jobs  

The Future of Industrial Robotics

Global demand for industrial robotics and automation is expecting tremendous growth in the next few years, particularly in key emerging markets such as China. Many fear that increased automation will result in dramatic job loss, but research says otherwise. The increase in product demand thanks to cost savings is expected to generate an increase in labor demand to offset the expected loss of certain jobs.


In a study of 151 analytics professionals in industrial companies, IoT Analytics discovered numerous insights into the current state of industrial analytics, and how the industry is expected to change in the next few years.

  • 15% view industrial analytics as an important part of success in business today, while 69% believe it will be important in the next 5 years
  • 68% of professionals said they have an established analytics strategy, while 46% have a dedicated organizational unit
  • Increased revenue is seen as the primary value driver (33%), while cost savings are perceived as less valuable (3%)
  • 79% see the predictive maintenance of industrial machinery as a primary application of industrial analytics in the next 3 years
  • Spreadsheet importance is expected to decline from 54% to 27% in the next 5 years
  • The industrial analytics applications that are expected to increase in the next 5 years are Business Intelligence (39% to 77%) and advanced analytics tools (50% to 79%)
  • While 60% of respondents felt they could effectively collect IoT-related sensor data, only 32% feel they can identify good or excellent insights

A report on industrial analytics from Datawatch revealed how many organizations are using Big Data and analytics to drive revenue and reduce operating costs.

  • A medical device manufacturer reduced the cost of maintenance by 20% using insights from industrial analytics
  • A petroleum company saved millions in downtime and lost production by monitoring critical equipment remotely
  • A global component manufacturer and service provider reduced unplanned failures and downtime by tracking cold storage assets across 4500 supermarkets
  • Danfoss helped its users reduce alarms by 70% with a proprietary predictive maintenance system

The Future of Industrial Analytics

Industrial analytics is the next logical step in the digital transformation of manufacturing operations. Most manufacturers are already comfortable collecting data from IoT-enabled sensors, but only half feel they can properly identify valuable insights. This indicates an apparent need for intelligent systems that can automate data analysis and insight discovery.

Industrial analytic systems in the future will come in the form of robust business intelligence and advanced analytics tools. Manufacturers with functioning industrial analytics systems are seeing great results, ranging from increased machine availability and decreased maintenance costs.


Research by the German wing of Mckinsey & Company support the incredible potential Machine Learning and A.I. could present to manufacturers, including improved asset management and production efficiency.

  • 55% of all human activity in manufacturing has the potential to be automated
  • 90% of manufacturing work done in a predictable environment (physical activities, machine operation) has the potential to be automated
  • Firms can increase asset productivity by 20% and reduce costs by 10% through the use of AI-enabled predictive maintenance systems
  • Collaborative and context-aware robots can increase work productivity by up to 20%
  • Firms can reduce yield loss by up to 30% through the use of AI-enabled yield enhancement systems
  • Automating quality tests with AI can increase defect detection accuracy by up to 90% when compared to humans

Machine learning is improving the accuracy and insight of simulation engines. One manufacturer of off-highway equipment managed to cut costs and improve efficiency by simulating a proposed assembly line under multiple conditions:

  • 20% cost savings to customer due to outsourcing
  • Our solution reduced fork truck usage and floor space requirements
  • Eliminated non-value added work and increased productivity by 20%

The Royal Society conducted research into how the public views technological advances in machine learning and artificial intelligence. The research also explores historical advances in data processing that contribute to the growth of machine learning.

  • Researchers estimate nearly 90% of all the world’s data was produced in the last 5 years.
  • The accuracy of a machine learning imaging challenge surpassed human accuracy, increasing from 72% in 2010, to 96% in 2015
  • Processors in the 1970s could manage 92,000 instructions per second, while processors in smartphones today manage billions per second
  • Google DeepMind reduced the amount of energy needed for cooling their data centers by 40%

The Future of Machine Learning in Manufacturing

The future is bright for machine learning and artificial intelligence. As the accuracy of machine learning systems surpasses that of humans, manufacturers can expect to automate over half of the human activity on the plant floor. These systems would introduce cost savings and revenue increase in the form of reduced maintenance costs, increased product yields, and enhanced human productivity.

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