The rising trend of Industry 4.0 will drive the market in the forecast period. An increasing number of IoT and IIoT installations are the primary enablers of industrial analytics in the global market. The growing availability of data from multiple sources across the production line, such as sensors, machine vision systems, PLCs, etc., is moving industries from data metrics models to data analytics models.

- Industrial analytics includes the collection, analysis, and use of data generated in industrial operations. It covers a wide range of data captured from all kinds of devices and sources, whether an asset or a production process. Anything with the sensor creates data, and industrial analytics examines all this data.

- Industrial analytics differs from Big Data analytics systems in that they are designed to meet the exacting standards of the industry in which they work. It includes processing vast quantities of time series data from numerous sources and turning it into actionable insights. Industrial analytics is relevant to any company that manufactures and/or sells physical products.

- The typical and traditional approach to industrial analytics involves data scientists building an analytics model. Data scientists are required to understand the use case scenario and then gather, transform, optimize, and load the data in the developed data model, which needs to be validated, optimized, and trained. The completed data model delivers answers to the initial questions.

- However, this approach leaves organizations dependent on their data scientists and results in a solution that subject matter experts (SME’s) (engineers and operators) might not fully understand. Moreover, In the past few years, the market has witnessed a growing trend toward self-service applications. This next generation of software uses advanced search algorithms, machine learning (ML), and pattern recognition technologies to make querying industrial data as easy as using Google.

- An industrial analytics solution that focuses on self-service results in benefits to day-to-day plant operation. This includes enhanced root cause analysis, objective performance prediction, automated monitoring, and knowledge retention. By sharing analytics insights with users, they can take immediate action when a trend appears and directly contribute to improving overall plant performance at all levels of production.

- The COVID-19 outbreak forced companies worldwide to adjust their strategies to survive in the “new normal.” Customers have changed their priorities, too. Many are shopping online or have found that the stores they frequented in person not so long ago now only provide deliveries. Businesses witnessed surges in demand for some products, while entire industries virtually ceased operations due to COVID-19 shutdowns impacting the market adversely.

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Key Market Trends

Manufacturing Sector to Dominate the Market Over the Forecast Period

- Industry 4.0 is transforming the manufacturing industry by leaps and bounds by enabling them to make a global shift toward the futuristic manufacturing sector. With the advent of industry 4.0 in the manufacturing industry, various plants adopt digital technologies, such as IIoT, AI, ML, Robotics, and many more, to enhance, automate, and modernize the whole process.

- The integration of different technologies is significantly becoming prevalent, as it provides exceptional benefits. Leveraging the above-mentioned technologies into a new way of doing business is a key factor in Industry 4.0 for companies to gain a competitive edge and be more profitable and scalable.

- Technologies like Industrial IoT are expected to connect millions of things to ensure that automation can be achieved across the entire value chain. Implementing analytics in the manufacturing industry is expected to boost customization and automation by collecting the huge amount of data generated by these technologies in real-time, providing actionable insights to the manufacturers, reducing machine downtime, and enhancing productivity.

- The application of industrial analytics is expected to gradually improve production processes' productivity and efficiencies throughout the supply chain. For instance, the manufacturing processes would be capable of administering itself, using intelligent machines and devices that can take corrective action, to avoid machine breakdowns. Individual parts would be automatically replenished, based on real-time data.

- Data-driven companies in the manufacturing sector are already using IoT-generated data by feeding them into their existing analytical pipeline and improving operational management and efficiencies by reducing the variable costs.

North America to Account for Significant Market Share

- The use of advanced technologies, such as cloud computing, AI, big data and analytics, mobility/social media, cybersecurity, IoT, among others, has led to innovation and transformation, thereby stimulating growth in the business ecosystem of North America. These technologies have transformed the legacy approach to business into a modern approach. Also, the region is becoming a new hotspot in the digital transformation market due to rising investments in the process of digitalization across potential economies. Such trends are expected to boost the adoption of industrial analytics across the industries in the region.

- The United States, for instance, is expected to dominate the Industry 4.0 market globally, as the companies in the country are rapidly adopting the concept of smart manufacturing. Industry 4.0 technologies provide improved operational efficiency, enhanced productivity, optimization of costs, and reduction in downtime. Most of the factories in the country are already equipped with modern machines and smart factory technology, which is using industrial analytics, enabling them to gather actionable insights by deploying technologies across their industries.

- Further, the growth in deployment of advanced communication technologies across the industries is expected to create significant opportunities for the adoption of industrial analytics in the region. According to GSMA, in 2021, 5G connections are forecast to account for 14% of all mobile connections in North America, and by 2025, it is expected to reach 46% of the total connectivity. Since fast and secure 5G connectivity is expected to enable agile operations and flexible production, the technology is expected to facilitate automated warehouses, automated assembly, connected logistics, packing and product handling, and the use of autonomous carts.

- For example, according to GSMA, IoTprofessional services revenue and IoT connectivity revenue in North America amounted to USD 25 billion and 8 billion in 2018 and is forecasted to reach USD 101 billion and 16 billion in 2025. SMEs are becoming increasingly flexible in incorporating new technologies with their existing systems, whereas large manufacturers have heavy budgets for digitization, thus giving momentum to industrial analytics in the region.

Competitive Landscape

The major players include Intel, Cisco Systems, IBM, General Electric, Amazon.com, Oracle Corporation, Hewlett-Packard, Microsoft Corporation, Genpact, amongst others. The market is fragmented since there is high competition among major players due to the adoption of industry 4.0 and the companies spending heavy amounts in the R&D for better operational activities. Therefore, the market concentration will be low.

- April 2019 - Aruba, a Hewlett Packard Enterprise company, announced two new offerings to help enterprise customers simplify the adoption of IoT. ArubaClearPass Device Insight delivers a single pane of glass for device visibility employing automated device discovery, machine learning (ML) based fingerprinting, and identification.

- June 2020 - IBM Corporation announced many changes and additions to IBM Watson Discovery. Inside the Watson Discovery Premium plan, users can experience a new user interface, a guided experience to help users quickly start using Watson Discovery for their specific use case, and many other new features including content mining.

- September 2020 - HCL Technologies (HCL) launched MINTVIZOR, an easy-to-use manufacturing analytics solution for plant managers and factory personnel. The solution provides real-time machine monitoring and analytics of shop-floor data to drive decision making for higher throughput, reduced downtime, and improved product quality.

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