Publishing: May 2021 | Report Code: IM10791 | Available Format: PDF
The manufacturing analytics market is increasing rapidly attributed to the transformation from the traditional business intelligence (BI) techniques to advanced analytics techniques and growth of structured and unstructured manufacturing data. Some of the factors driving the demand for global manufacturing analytics market are the increasing need for process optimization, self-service access to centrally managed data, increased business agility and scalability, adoption of advanced data-management strategies across varied manufacturing applications, and emergence of industrial internet of things (IIOT).
Organizations are increasingly deploying manufacturing analytics solution on cloud technology to improve product design and development. The demand for on-demand or cloud-based manufacturing analytics solutions is increasing due to time efficient and cost effective features. The manufacturing analytics market growth is expected to be high in business enterprises where low cost solutions are required. However, the factors restraining the growth of the market are complex system structure, problem in integration with legacy system and lower return on investment.
Manufacturing analytics are used for gathering data from local or geographically distributed sources and from differing data streams. The data collected by manufacturing analytics can be organized and structured to enable a meaningful analysis. The results displayed enable both understanding and meaningful analysis. The use of application program interface (APIs) makes modeled data available to the end users for additional analysis. Manufacturing analytics helps in utilizing the existing production data by integrating and visualizing the data to further analyze it by using suitable data mining methods.
Many organizations across various sectors, such as healthcare, automotive, aerospace and mining, have been using big data analytics to enhance the real time and strategic decision making. There are two aspects witnessed in the manufacturing industry, which makes the use of analytics and big data suitable. Firstly, the growing market pressures, such as global industry rivalry, high profit margins, and efficient design cycle, that compels manufacturers to have the capacity to take quick data-driven decisions. Secondly, with the growing adoption of digitalization, more data is being generated with the use of systems, automation, and equipment that requires thorough analysis and precision.
The major applications of manufacturing analytics include inventory management, predictive maintenance & asset management, procurement & supply chain planning, emergency management, energy management and sales & customer management. Energy management is expected to witness fastest growth during the forecast period. Manufacturing analytics are widely used by various manufacturing verticals such as aerospace and automotive manufacturing, food & beverages manufacturing, automotive and aerospace manufacturing, chemicals and materials manufacturing, electronics equipment manufacturing, pharma and life sciences, and paper, pulp, plastic & rubber manufacturing. Amongst all the verticals, food and beverages manufacturing is expected to witness the fastest growth during the forecast period.
Geographically, North America is expected to be the largest manufacturing analytics market during the forecast period, followed by Europe. The growth of manufacturing analytics market in this region is owing to the high focus on innovations through research and development and technology upgrading such as big data and cloud services across various manufacturing industries. The market is expected to witness the fastest growth in Asia-Pacific during the forecast period.
Some of the key players of global manufacturing analytics market are Tableau Software Inc., Tibco Software Inc., Oracle Corp., IBM Corp., SAP SE, Zensar Technologies Ltd., 1010 Data Inc., Alteryx Inc., and StatSoft Inc.
Global Manufacturing Analytics Market Segmentation
By Deployment Model
By Industry Vertical
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