From the 1920s until the Second World War, industrial output in the major economies of the Americas fluctuated greatly. Using manufacturing output in 1938 as a benchmark, the U.S. had fairly consistent output throughout the 1920s, before there was a significant drop after the Wall Street Crash in 1929 - by 1932, output fell to around two thirds of its 1929 level, and it would take another five years to recover thereafter. After the Recession of 1937-38, manufacturing output then doubled by the early-1940s, as the U.S. ramped up armament before it joined the Second World War. Output in 1943 was almost three times higher than it had been in 1938.

Canada's industrial output followed a similar trend to that of the U.S., whereas Mexico saw comparatively little change across the given period. Similar to Mexico, Brazil's manufacturing output was not drastically affected by the Great Depression, although Brazil saw the largest relative growth over the given period, with output in 1944 over five times higher than it had been in the mid-1920s - it should be noted, however, that both Latin American countries' manufacturing industries were at a much lower stage of development than the North American industries during this time.

United States US: GDP: % of GDP: Gross Value Added: Industry: Manufacturing data was reported at 11.601 % in 2016. This records a decrease from the previous number of 11.919 % for 2015. United States US: GDP: % of GDP: Gross Value Added: Industry: Manufacturing data is updated yearly, averaging 12.807 % from Dec 1997 (Median) to 2016, with 20 observations. The data reached an all-time high of 16.022 % in 1997 and a record low of 11.601 % in 2016. United States US: GDP: % of GDP: Gross Value Added: Industry: Manufacturing data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Share of GDP. Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Note: For VAB countries, gross value added at factor cost is used as the denominator.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted average; Note: Data for OECD countries are based on ISIC, revision 4.

United States US: GDP: % of Manufacturing: Other Manufacturing data was reported at 38.796 % in 2011. This records an increase from the previous number of 37.666 % for 2010. United States US: GDP: % of Manufacturing: Other Manufacturing data is updated yearly, averaging 48.171 % from Dec 1963 (Median) to 2011, with 47 observations. The data reached an all-time high of 49.983 % in 1979 and a record low of 37.666 % in 2010. United States US: GDP: % of Manufacturing: Other Manufacturing data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Share of GDP. Value added in manufacturing is the sum of gross output less the value of intermediate inputs used in production for industries classified in ISIC major division D. Other manufacturing, a residual, covers wood and related products (ISIC division 20), paper and related products (ISIC divisions 21 and 22), petroleum and related products (ISIC division 23), basic metals and mineral products (ISIC division27), fabricated metal products and professional goods (ISIC division 28), and other industries (ISIC divisions 25, 26, 31, 33, 36, and 37). Includes unallocated data. When data for textiles, machinery, or chemicals are shown as not available, they are included in other manufacturing.; ; United Nations Industrial Development Organization, International Yearbook of Industrial Statistics.; ;

In 2024, the United States accounted for 14.88 percent of global gross domestic product (GDP) after adjusting for purchasing power parity (PPP). This share was expected to decrease to 13.98 percent by 2030, which is roughly a seventh of the global total. What is PPP? The easiest way to understand purchasing power parity is the Big Mac Index, a measure developed by The Economist. The index tracks the price of the McDonald’s Big Mac burger, sold at each of its thousands of restaurants worldwide. Countries where the Big Mac is most expensive have higher purchasing power, meaning one can buy more for each unit of that currency. To calculate PPP, economists use a group of goods to calculate the ratio of the price of this group in each country. This ratio is then used to convert all countries into a standardized price level, on parity with each other. Why use PPP? A U.S. dollar in the United States does not have the same purchasing power as a dollar in China, even after considering the exchange rate. For this reason, adjusting for PPP gives an idea of what the rest of the world could buy in the United States, if prices were the same as in their home country. However, some economists argue that using PPP for comparisons between countries is inaccurate because it changes the price level differently for each country. Still, because it accounts not only for country-specific effects but also inflation and exchange rate fluctuations, PPP is a very popular metric.

The size of the North America Industrial Manufacturing Industry market was valued at USD 58.35 Million in 2023 and is projected to reach USD 91.39 Million by 2032, with an expected CAGR of 6.62% during the forecast period. Recent developments include: June 2023: Honeywell, an American global company, and LG CNS are collaborating further to increase smart factories' production efficiency and security. Through this collaboration, the two companies will expand cooperation in building smart factories at home and abroad and strengthen OT (Operating Technology) security, which monitors the production process in real-time and remotely controls facilities., March 2023: LG Energy Solution announced an investment of around KRW 7.2 trillion (USD 5.5 billion) in building a battery manufacturing hub in Queen Creek, Arizona. This hub will include two facilities: one for making cylindrical batteries for electric vehicles (EVs) and another for producing lithium iron phosphate (LFP) pouch-type batteries for energy storage systems (ESS)., October 2022: Emerson announced the evolution of Plantweb, a digital ecosystem incorporating the AspenTech portfolio of asset optimization software powered by industrial artificial intelligence, creating the industry's most comprehensive digital transformation portfolio. Moreover, its Plantweb digital ecosystem, optimized by AspenTech, enables industrial manufacturers across all sectors to "See, Decide, Act, and Optimize" their operations.. Key drivers for this market are: Increasing Demand for Automation to Achieve Efficiency and Quality, Need for Compliance and Government Support for Digitization; Proliferation of Internet of Things. Potential restraints include: Concerns Regarding Data Security, High Initial Installation Costs and Lack of Skilled Workforce Preventing Enterprises from Full-scale Adoption. Notable trends are: Robotics is Expected to Witness Significant Growth.

Industrial Production in the United States increased 0.90 percent in August of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Industrial Production - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Graph and download economic data for All Employees, Manufacturing (MANEMP) from Jan 1939 to Sep 2025 about headline figure, establishment survey, manufacturing, employment, and USA.

Graph and download economic data for Value Added by Industry: Manufacturing as a Percentage of GDP (VAPGDPMA) from Q1 2005 to Q2 2025 about value added, private industries, percent, private, manufacturing, industry, GDP, and USA.

The average for 2023 based on 19 countries was 15.3 percent. The highest value was in Puerto Rico: 43.6 percent and the lowest value was in Panama: 4.98 percent. The indicator is available from 1960 to 2024. Below is a chart for all countries where data are available.

United States US: GDP: % of Manufacturing: Machinery and Transport Equipment data was reported at 28.318 % in 2011. This records a decrease from the previous number of 28.967 % for 2010. United States US: GDP: % of Manufacturing: Machinery and Transport Equipment data is updated yearly, averaging 23.767 % from Dec 1963 (Median) to 2011, with 47 observations. The data reached an all-time high of 30.671 % in 1999 and a record low of 21.273 % in 1963. United States US: GDP: % of Manufacturing: Machinery and Transport Equipment data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Share of GDP. Value added in manufacturing is the sum of gross output less the value of intermediate inputs used in production for industries classified in ISIC major division D. Machinery and transport equipment correspond to ISIC divisions 29, 30, 32, 34, and 35.; ; United Nations Industrial Development Organization, International Yearbook of Industrial Statistics.; ;

The graph shows China's share in global gross domestic product adjusted for purchasing-power-parity until 2024, with a forecast until 2030. In 2024, China's share was about 19.3 percent. China's global GDP share Due to the introduction of capitalist market principles in 1978, China's economic market began to show immense change and growth. China's real GDP growth ranged at 5.0 percent in 2024. China's per capita GDP is also expected to continue to grow, reaching 13,300 U.S. dollars in 2024. Comparatively, Luxembourg and Switzerland have some of the world’s largest GDP per capita with 141,100 U.S. dollars and 111,700 U.S. dollars, respectively, expected for 2025.China is the largest exporter and second largest importer of goods in the world and is also among the largest manufacturing economies. The country also ranges among the world's largest agricultural producers and consumers. It relies heavily on intensive agricultural practices and is the world's largest producer of pigs, chickens, and eggs. Livestock production has been heavily emphasized since the mid-1970s. China’s chemical industry has also seen growth with a heavy focus on fertilizers, plastics, and synthetic fibers. China's use of chemical fertilizers amounted to approximately 50.2 million metric tons in 2023. GDP composition in China Industry and construction account for less than 40 percent of China's GDP. Some of the major industries include mining and ore processing, food processing, coal, machinery, textiles and apparel, and consumer products. Almost half of China's output is dedicated to investment purposes. However, as the country tends to support gross output, innovation, technological advancement, and even quality are often lacking.

The valued added by the manufacturing sector to GDP varies significantly across different countries worldwide. In 2023, the manufacturing sector in China added nearly *** trillion U.S. dollars to the country's GDP, while this value in the United States amounted to *** trillion U.S. dollars in the same year.

The United States is the largest crude oil producer in the world. In 2022, it held a global share of 14.73 percent. Although its production share initially declined in the early 2000s, previously inaccessible reserves were made available in the 2010s thanks to technological advances. From 2018 onward, the U.S. surpassed Saudi Arabia and Russia to become the world's largest oil producing country.

Actual value and historical data chart for World Manufacturing Value Added Us Dollar

United States US: GDP: % of Manufacturing: Medium and High Tech Industry data was reported at 41.166 % in 2015. This stayed constant from the previous number of 41.166 % for 2014. United States US: GDP: % of Manufacturing: Medium and High Tech Industry data is updated yearly, averaging 49.199 % from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 51.786 % in 1998 and a record low of 38.398 % in 1996. United States US: GDP: % of Manufacturing: Medium and High Tech Industry data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Share of GDP. The proportion of medium and high-tech industry value added in total value added of manufacturing; ; United Nations Industrial Development Organization (UNIDO), Competitive Industrial Performance (CIP) database; ;

The US manufacturing sector has achieved revenue growth over the past five years, benefiting from widespread demand in industries such as automotive, electronics and consumer goods. Advances in production automation, including robotics and automated assembly lines, have reduced labor costs and errors, while 3D printing allows for rapid prototyping and tailored products. Lean manufacturing has minimized waste and improved quality, helping the sector maintain positive revenue even amid regulatory and commodity price pressures. Efficient global supply chains and impactful trade agreements like the USMCA have sustained this growth, alongside innovations in predictive maintenance and data-driven operational optimization. Despite rising revenue, profit margin has been challenged by increasing material and energy costs, particularly from surges in crude oil prices and tariffs on steel and aluminum. Manufacturers have countered these pressures by embracing energy-efficient technologies and substituting advanced materials, such as composites, to lower costs. Supply chain analytics are optimizing forecasting and inventory, while automation and just-in-time strategies are minimizing excess expenses and improving efficiency. Sustainability efforts, including recycling and circular economy practices, are aligning cost savings with regulatory compliance. Cloud-based ERP systems have further enhanced planning and resource allocation, supporting financial performance. Revenue has been expanding at a CAGR of 1.8% over the past five years and is expected to total $6,948.5 billion in 2025, when revenue will fall by an estimated 5.0%. Looking ahead, manufacturing revenue is expected to see moderate growth, with innovation and digital transformation driving performance. The growing adoption of artificial intelligence, IoT devices and machine learning will optimize production and quality control. Automation and robotics will increase efficiency and adapt to expanding consumer needs, while digitalization and smart factories will boost productivity using real-time data. Augmented reality tools will enhance training and maintenance. However, profit growth will be constrained by material cost volatility and compounding environmental regulations. Market agility will become essential as downstream markets and global trade continue to influence the sector’s strategic direction. Revenue is expected to inch upward at a CAGR of 0.4% to $7,083.4 billion over the five years to 2030.

United States US: GDP: % of Manufacturing: Food, Beverages and Tobacco data was reported at 15.162 % in 2011. This records a decrease from the previous number of 15.734 % for 2010. United States US: GDP: % of Manufacturing: Food, Beverages and Tobacco data is updated yearly, averaging 11.852 % from Dec 1963 (Median) to 2011, with 47 observations. The data reached an all-time high of 15.734 % in 2010 and a record low of 9.901 % in 1979. United States US: GDP: % of Manufacturing: Food, Beverages and Tobacco data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Share of GDP. Value added in manufacturing is the sum of gross output less the value of intermediate inputs used in production for industries classified in ISIC major division D. Food, beverages, and tobacco correspond to ISIC divisions 15 and 16.; ; United Nations Industrial Development Organization, International Yearbook of Industrial Statistics.; ;

Graph and download economic data for Manufacturing Sector: Labor Share (MPU9900681) from 1987 to 2023 about sector, labor, manufacturing, and USA.

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Big Data In Manufacturing Market Size 2025-2029

The big data in manufacturing market size is valued to increase by USD 21.44 billion, at a CAGR of 26.4% from 2024 to 2029. Rising adoption of industry 4.0 will drive the big data in manufacturing market.

Major Market Trends & Insights

North America dominated the market and accounted for a 50% growth during the forecast period.
By Type - Services segment was valued at USD 2.9 billion in 2023
By Deployment - On-premises segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 552.73 million
Market Future Opportunities: USD 21444.10 million
CAGR from 2024 to 2029 : 26.4%

Market Summary

The market is witnessing significant growth due to the increasing adoption of Industry 4.0 and the emergence of artificial intelligence (AI) and machine learning (ML) technologies. These advanced technologies enable manufacturers to collect, process, and analyze vast amounts of data in real-time, leading to improved operational efficiency, enhanced product quality, and optimized supply chain management. One real-world business scenario demonstrating the impact of big data in manufacturing is supply chain optimization. By analyzing historical data and real-time information, manufacturers can predict demand patterns, optimize inventory levels, and reduce lead times. For instance, a leading automotive manufacturer was able to reduce its lead time by 15% by implementing predictive analytics in its supply chain management system.
The complexity of big data analytics presents a challenge for manufacturers, as they need to invest in advanced technologies and skilled personnel to effectively process and interpret the data. However, the benefits far outweigh the costs, as manufacturers gain valuable insights that inform strategic decision-making, enhance customer satisfaction, and drive competitive advantage.

What will be the Size of the Big Data In Manufacturing Market during the forecast period?

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How is the Big Data In Manufacturing Market Segmented ?

The big data in manufacturing industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Services
  Solutions


Deployment

  On-premises
  Cloud-based
  Hybrid


Application

  Operational analytics
  Production management
  Customer analytics
  Supply chain management
  Others


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Type Insights

The services segment is estimated to witness significant growth during the forecast period.

In the dynamic and expansive realm of manufacturing, big data has emerged as a game-changer. By 2024, the services segment dominated market segmentation, with an estimated 45% market share. The manufacturing sector generates copious amounts of data from sensors, machines, production lines, and supply chains. This data deluge presents a rich opportunity for analytics and insights. Big data services empower manufacturers to optimize resource allocation, minimize operational inefficiencies, and uncover cost-saving opportunities, ultimately boosting profitability. Predictive maintenance using big data analytics minimizes downtime and reduces unplanned repairs, while real-time quality control ensures fewer defects, scrap, and rework, resulting in significant savings.

Additionally, big data analytics enable manufacturers to optimize supply chain operations through supply chain analytics, inventory management systems, and demand forecasting methods. Digital twin technology, process simulation software, and machine learning models facilitate energy efficiency monitoring, sustainable manufacturing practices, and waste reduction strategies. Cloud computing platforms and data integration pipelines streamline data access, while edge computing devices and manufacturing execution systems enable real-time data streams. Data security protocols safeguard sensitive information, and capacity planning models ensure efficient production optimization. Overall, big data analytics is revolutionizing manufacturing, driving innovation and competitiveness.

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The Services segment was valued at USD 2.9 billion in 2019 and showed a gradual increase during the forecast period.

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Regional Analysis

North America is estimated to contribute 50% to the growth of the global market during the forecast period.Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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Manufacturing Data Lakehouse Market Outlook

According to our latest research, the Global Manufacturing Data Lakehouse market size was valued at $2.1 billion in 2024 and is projected to reach $11.6 billion by 2033, expanding at a robust CAGR of 20.3% during the forecast period of 2025–2033. The primary driver fueling this impressive market growth is the increasing adoption of advanced analytics and artificial intelligence to optimize manufacturing processes, enhance supply chain visibility, and enable real-time decision-making. As manufacturers face mounting pressure to improve operational efficiency and adapt to Industry 4.0 paradigms, the integration of data lakehouse solutions—which unify the capabilities of data lakes and data warehouses—has become a critical enabler for digital transformation across the global manufacturing sector.

Regional Outlook

North America continues to hold the largest share of the global Manufacturing Data Lakehouse market, accounting for approximately 38% of the total market value in 2024. This dominance is attributed to the region’s mature manufacturing landscape, early adoption of digital technologies, and a strong ecosystem of software vendors and cloud service providers. U.S.-based manufacturers, in particular, are leveraging data lakehouse architectures to consolidate disparate data sources, streamline compliance, and facilitate predictive analytics. Additionally, favorable government policies supporting digital innovation and significant investments in smart manufacturing initiatives have further strengthened North America’s leadership position in this market. The presence of major technology players and a highly skilled workforce also contribute to the region’s sustained growth and innovation in manufacturing data management.

In contrast, the Asia Pacific region is emerging as the fastest-growing market, projected to register a remarkable CAGR of 25.7% during the forecast period. Rapid industrialization, the proliferation of smart factories, and substantial investments in digital infrastructure are key factors driving this accelerated growth. Countries such as China, Japan, and South Korea are at the forefront of integrating data lakehouse solutions to enhance manufacturing agility, reduce downtime, and improve product quality. The region’s large and diverse manufacturing base, coupled with government-led initiatives like “Made in China 2025” and “Make in India,” are fostering widespread adoption of advanced data management platforms. Furthermore, the increasing presence of multinational corporations and strategic collaborations between regional manufacturers and technology providers are propelling the Asia Pacific Manufacturing Data Lakehouse market to new heights.

Meanwhile, emerging economies in Latin America and the Middle East & Africa are gradually embracing Manufacturing Data Lakehouse solutions, albeit at a slower pace due to certain adoption barriers. These regions face challenges such as limited digital infrastructure, skill gaps, and budget constraints, which impact the rate of technology deployment. However, the growing demand for operational efficiency, improved supply chain management, and compliance with international quality standards is gradually driving interest in data lakehouse architectures. Localized demand from sectors like automotive, food and beverage, and chemicals, combined with government efforts to modernize manufacturing, are expected to create new opportunities for market expansion. As these regions continue to address infrastructure and policy challenges, the adoption of data lakehouse solutions is likely to gain momentum in the coming years.

Report Scope