Survey: Firms see ‘smart’ manufacturing investments paying off in productivity, capacity gains

“Smart” manufacturing’s value is very much being realized, according to the newly released results of a late summer/early fall 2024 Deloitte survey, with respondents reporting up to 20% improvement in production output, a 20% gain in employee productivity, and 15% more in unlocked capacity.

The respondents—600 executives from U.S.-based or operated companies with annual revenue of $500 million or more and with over 1,000 employees—also reported that they had prioritized investment over the next two years in data, with 40% investing in data analytics, 29% in cloud computing, 29% in AI and 27% in IIoT, according to the Deloitte smart manufacturing and operations study, titled “Navigating Challenges to Implementation.”

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While the study showed the C-suite is realizing value from the past several years of smart manufacturing investments, many are still facing significant challenges in managing complex digital transformations as they contend with operational risks, talent shortfalls and cybersecurity preparedness, according to Deloitte.

“The smart manufacturing journey is still emerging, but its value is undeniable. Our survey shows that most responding manufacturers agree with the need to invest in smart manufacturing but require help navigating operational complexities to see meaningful results,” Tim Gaus, Deloitte’s smart manufacturing business leader and principal, said in a Deloitte release.

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“Smart manufacturing prepares enterprises to be ready for increased demands and, in an era where increased capacity can set companies apart, organizations that have already invested in smart manufacturing solutions will likely have an advantage—those who haven’t, may not be able to defer much longer.”

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The companies represented in the survey include consumer products, industrial products and construction, energy and chemicals, mining and metals, automotive, transportation, aviation, life sciences, and technology, Deloitte said. The study was conducted last August and September.

Some other notable findings from the survey:

Generally, leaders are focusing on establishing the smart manufacturing technology and data foundations needed to enable AI and advanced capabilities.
92% of those surveyed said they believe smart manufacturing will be the main driver for competitiveness over the next three years.
Workforce and talent gaps, cybersecurity and operational risks are top concerns for manufacturers.
The survey respondents are focusing on automation. Close to half (48%) report moderate to significant challenges filling production and operations management roles, and 46% in the survey reported the same for planning and scheduling roles.
46% of respondents ranked process automation as the first or second priority investment in the next two years, 37% ranked physical automation first or second and 24% ranked factory synchronization first or second.
While nearly half (48%) of respondents reported having a smart manufacturing training and adoption standard in place, human capital was at the lowest maturity level of all smart manufacturing categories surveyed.
As the nature of work changes and people are working alongside AI, more than a third (35%) of those surveyed are concerned about upskilling their employees to work with advanced technology.
The report found 78% of surveyed leaders are allocating more than 20% of their improvement budgets toward smart manufacturing initiatives, including clean data analytics, sensors, cloud, AI, and the like.
In terms of systems prioritized for investment, the first or second highest investment priorities are advanced production scheduling (35%), execution systems (33%) and quality management (28%).

Despite the allure of cutting-edge technologies such as robotics, virtual programmable logic controllers (vPLCs) and digital twins, survey respondents reported they feel their organizations’ maturity in technology, data and automation only meets industry standards, showing room for improvement, according to Deloitte.

Regarding AI adoption, according to the group’s survey, 29% are using AI/machine learning (ML) at the facility or network level, and 24% have deployed generative AI at the same scale. Moderate investments also are being made in experiments and proofs of concept. The Deloitte survey shows 23% of respondents are piloting AI/ML and 38% are piloting Gen-AI.