“Global Big Data Analytics in Smart Manufacturing Market to reach a market value of USD 356.9 Billion by 2031 growing at a CAGR of 19.7%”
The Global Big Data Analytics in Smart Manufacturing Market size is expected to reach $356.9 billion by 2031, rising at a market growth of 19.7% CAGR during the forecast period.
Cloud computing enables manufacturers to store and analyze vast amounts of data without extensive on-premises infrastructure. By utilizing cloud-based solutions, manufacturers can reduce costs, improve data accessibility, and enhance their ability to innovate, further driving the growth of cloud computing within the smart manufacturing landscape. Therefore, the cloud computing segment held 14% revenue share in the market in 2023. This flexibility and scalability make it easier for organizations to leverage advanced analytics tools and collaborate across geographically dispersed teams.
The major strategies followed by the market participants are Partnerships as the key developmental strategy to keep pace with the changing demands of end users. For instance, In June, 2024, IBM Corporation teamed up with Telefónica Tech, an IT service management company to enhance AI, analytics, and data management solutions. This collaboration will deploy SHARK.X, a multi-cloud platform, and establish a use case office for client pilots. Additionally, In August, 2024, GE Vernova and Systems With Intelligence (SWI) signed an agreement at the CIGRE event in Paris to develop advanced substation monitoring solutions. This aims to integrate technologies like gas sensing and infrared thermography, aiming to enhance grid asset management and improve reliability for utilities and Transmission System Operators.
Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation is the forerunner in the Big Data Analytics in Smart Manufacturing Market. In June, 2022, Microsoft Corporation teamed up with Procter & Gamble (P&G) to enhance P&G's digital manufacturing using Microsoft Cloud. Companies such as IBM Corporation, Siemens AG, and General Electric Company are some of the key innovators in Big Data Analytics in Smart Manufacturing Market.
Reactive or scheduled upkeep is frequently employed in conventional maintenance strategies, which can be costly and inefficient. Reactive maintenance addresses issues only after a failure occurs, leading to unexpected downtime and potential damage to equipment. Scheduled maintenance, while better, can still be inefficient as it does not account for the actual condition of the equipment. On the other hand, predictive maintenance uses big data analytics to continuously monitor the condition of machinery and predict failures before they happen. This capability reduces unplanned downtime, enhances operational efficiency, and drives the adoption of predictive maintenance solutions in the smart manufacturing. Hence, an enhanced focus on predictive maintenance to reduce operational downtime propels the market's growth.
Industry 4.0 emphasizes the digitization and automation of manufacturing processes, leading to the generation of vast amounts of data from various sources such as sensors, machines, and production lines. Big data analytics tools are essential for processing and analyzing this data to uncover insights, optimize workflows, and enhance automation, ultimately improving productivity and reducing operational costs. This competitive advantage is fuelling the growth of the big data analytics in smart manufacturing market as manufacturers seek to leverage these insights to enhance their offerings. Thus, the increasing adoption of Industry 4.0 technologies in manufacturing drives the market's growth.
Implementing smart manufacturing technologies typically requires substantial investment in advanced hardware and infrastructure. This includes installing IoT devices, sensors, robotics, advanced machinery, and other smart equipment. These components are often costly, and the expenses can quickly increase, especially for large-scale manufacturing operations. The need for robust and high-performance infrastructure to support the integration of these technologies further escalates the initial investment requirements, posing a financial challenge for many manufacturers. Even though the long-term advantages are evident, the initial expenses may be beyond their financial capacity, which limits their capacity to implement these sophisticated technologies and impedes the overall market expansion. Thus, high initial investment costs are hampering the growth of the market.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships, Collaborations & Agreements.
Based on component, the market is divided into software and services. The services segment procured 39% revenue share in the market in 2023. This segment plays a crucial role in enhancing the overall effectiveness of big data analytics by providing manufacturers with the necessary expertise and support to leverage these technologies effectively. As organizations increasingly adopt big data analytics solutions, the demand for related services continues to rise, highlighting the importance of a well-rounded data management and analysis approach.
On the basis of deployment mode, the market is segmented into on-premises and cloud-based. The cloud-based segment recorded 57% revenue share in the big data analytics in smart manufacturing market in 2023. This shift toward cloud-based analytics highlights the growing preference among manufacturers for solutions that offer flexibility, scalability, and cost efficiency. As companies increasingly adopt digital transformation strategies, the ability to access and analyze vast amounts of data in real-time from anywhere has become essential, driving the demand for cloud-based analytics in the smart manufacturing sector.
The cloud-based segment is further subdivided into public cloud, private cloud, and hybrid cloud. In 2023, the public cloud segment attained 44% revenue share in the big data analytics in smart manufacturing market. Public cloud solutions enabled manufacturers to leverage vast amounts of data for real-time analytics, enhancing operational efficiency and decision-making. This trend facilitated advanced analytics capabilities, fostering innovation and competitive advantages within the industry.
On the basis of organization size, the market is segmented into large enterprises and small & medium-sized enterprises (SMEs). In 2023, the small & medium-sized enterprises (SMEs) segment attained 44% revenue share in the market. SMEs, although smaller in scale compared to large enterprises, are increasingly recognizing the value of big data analytics in enhancing their competitive edge. These enterprises are leveraging big data analytics to improve their manufacturing processes, reduce operational costs, and drive innovation.
Based on application, the market is categorized into predictive maintenance, supply chain optimization, quality management, production optimization, asset management, and others. In 2023, the predictive maintenance segment registered 25% revenue share in the market. This significant growth can be attributed to manufacturers’ increasing focus on minimizing downtime and enhancing operational efficiency. Predictive maintenance leverages data analytics to forecast equipment failures and proactively schedule maintenance, reducing costs and improving productivity.
By industry vertical, the market is divided into automotive, electronics, aerospace & defense, healthcare & pharmaceuticals, energy & utilities, food & beverages, and others. In 2023, the electronics segment registered 19% revenue share in the market. This performance can be attributed to the rapid technological advancements within the electronics industry, where manufacturers are increasingly leveraging big data analytics to enhance product quality, streamline production processes, and optimize supply chain management. Integrating smart manufacturing practices in this sector has made analytics an indispensable tool for innovation and efficiency.
Based on technology, the market is divided into artificial intelligence (AI), machine learning, internet of things (IoT), cloud computing, and others. The artificial intelligence (AI) segment attained 34% revenue share in the big data analytics in smart manufacturing market in 2023. AI is critical in processing large datasets, identifying patterns, and generating actionable insights that enhance decision-making processes. By integrating AI into their operations, manufacturers can optimize production schedules, improve quality control, and reduce operational costs, making it a pivotal component of smart manufacturing strategies.
Free Valuable Insights: Global Big Data Analytics in Smart Manufacturing Market size to reach USD 356.9 Billion by 2031
The Big Data Analytics in Smart Manufacturing Market is marked by intense competition, driven by the adoption of Industry 4.0, IoT, and automation technologies. Key players are focused on developing advanced data analytics tools that offer real-time insights, predictive maintenance, and operational optimization. The competitive landscape is shaped by the demand for AI-driven analytics, cloud computing integration, and seamless connectivity, which help manufacturers enhance efficiency and reduce costs. Additionally, companies are competing by offering customizable solutions that cater to specific industry needs and regulatory requirements. As smart factories become more prevalent, the market is expected to see further growth in innovation and strategic partnerships.
Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America region witnessed 39% revenue share in the market in 2023. This can be attributed to a robust manufacturing sector, advanced technological infrastructure, and a high level of investment in research and development. North American manufacturers are increasingly adopting big data analytics solutions to enhance operational efficiency, optimize supply chains, and improve product quality.
| Report Attribute | Details |
|---|---|
| Market size value in 2023 | USD 89.5 Billion |
| Market size forecast in 2031 | USD 356.9 Billion |
| Base Year | 2023 |
| Historical Period | 2020 to 2022 |
| Forecast Period | 2024 to 2031 |
| Revenue Growth Rate | CAGR of 19.7% from 2024 to 2031 |
| Number of Pages | 623 |
| Number of Tables | 953 |
| Report coverage | Market Trends, Revenue Estimation and Forecast, Segmentation Analysis, Regional and Country Breakdown, Competitive Landscape, Market Share Analysis, Porter’s 5 Forces Analysis, Company Profiling, Companies Strategic Developments, SWOT Analysis, Winning Imperatives |
| Segments covered | Technology, Industry Vertical, Deployment Mode, Organization Size, Component, Application, Region |
| Country scope |
|
| Companies Included | IBM Corporation, Siemens AG, General Electric Company, SAP SE, Microsoft Corporation, Honeywell International Inc., Oracle Corporation, Rockwell Automation, Inc., PTC Inc., Cisco Systems, Inc. |
By Component
By Deployment Mode
By Organization Size
By Technology
By Industry Vertical
By Application
By Geography
Our team of dedicated experts can provide you with attractive expansion opportunities for your business.
Unique Offerings 