Joseph Tsidulko | Content Strategist | August 21, 2023
In the aftermath of the COVID-19 pandemic, manufacturers are still in a world of hurt. They’re struggling to return to full staffing while dealing with continued supply chain disruptions. They also face persistent inflation, more regulations, customer expectations to act more sustainably, and geopolitical unrest in countries where they make their goods and source supplies.
Manufacturers must grapple with these challenges while investing in cutting-edge technologies—including the Internet of Things (IoT), AI, and blockchain—that will improve their efficiency, product quality, and speed to market. But getting these digital transformation projects over the finish line is a major pain point itself. Then there’s the escalating threat posed by hackers to digital infrastructure, including ransomware attacks.
While the challenges facing manufacturers can be overwhelming, solutions are within reach. Some involve significant investments to retool production floors, retrofit assembly lines, retrain employees, and restructure large workforces. Others are simple and relatively inexpensive, such as applying best practices to ensure factory processes are efficient and limit risk. Manufacturers are also alleviating their pain points with the help of interconnected software systems.
Here are the industry’s top 10 pain points and some high- and low-tech solutions.
COVID-19 shutdowns stalled manufacturing production worldwide as well as the operations of supply chain partners in warehousing, shipping, transportation, and other areas. Even with factory closures behind us, product shortages due to supply chain bottlenecks persist for other reasons, among them preexisting shortcomings exposed by the pandemic. External factors affecting supply chains include extreme weather events, labor shortages and strikes, trade embargos, and wars. Internal factors include inefficient supply chain management (SCM) processes.
Solutions: There’s not much manufacturers can do to eliminate external risks, but they can reduce their exposure to them by distributing production, sourcing, and shipping operations across geographic areas. Supply chain planning systems that include scenario modeling help manufacturers plan for potential disruptions. For example, if the pandemic resurges and a future shutdown looks likely, manufacturers can model scenarios in which they source raw materials from multiple nations or components from more than one supplier and predict how those shifts will affect costs and profit. The ability to quickly change direction when disruption happens is crucial to mitigating risk.
Cutting-edge SCM systems give manufacturers end-to-end visibility into the workflows, schedules, and capacities of suppliers, fleets, distribution warehouses, and end customers. The real-time status updates provided by these systems make it possible to quickly detect, identify, and resolve bottlenecks that stress supply chains in almost every industry. SCM systems also alleviate supply chain pain points by employing machine learning to make better forecasts of demand, letting manufacturers plan more effectively. At the same time, they help coordinate orders, deliveries, and payments to ensure smooth business transactions.
Customers, investors, employees, and government regulators insist that manufacturers report on their ESG (environmental, social, and governance) progress. They don’t want clever sustainability slogans. They want to see hard evidence that manufacturers are lowering the carbon footprint of their factories, reducing waste, protecting natural resources, paying a fair wage at their plants worldwide (as are their suppliers), employing a diverse labor force, and operating safe facilities. Studies show that a growing number of consumers—especially millennials and Generation Z—care deeply about such environmental and social issues and are willing to pay more for products manufactured according to such criteria. One study found that two-thirds of Americans, and 80% of those ages 18 to 34, are willing to pay more for a product confirmed to be sourced and produced with sustainable methods.
Solutions: There are no pat solutions, but incremental changes to various production processes can yield big results. For starters, manufacturers can retool their production lines to support closed-loop processes in which materials are reused and recycled to generate less waste. They can then implement or upgrade waste management systems to dispose of what waste remains in a more environmentally sound manner. Manufacturers can also source materials from suppliers that abide by ESG best practices. Verifying those practices requires all parties to collect and transparently report considerable amounts of data, but new systems available can collect, harmonize, and report on all this information.
Manufacturers can take advantage of blockchain technology to trace the environmental and labor practices of suppliers and partners. Modern enterprise performance management (EPM) systems include ESG planning, consolidation, and analytics that present decision makers with granular reporting on their progress and setbacks in meeting sustainability goals. Manufacturers can also take advantage of artificial intelligence to optimize shipping routes, reducing the number of miles logged and the amount of fuel consumed. And rather than operate their own data centers, which consume an increasing share of electricity, manufacturers can reduce their carbon footprints by relying on cloud vendors whose data centers are more efficient and powered by green energy sources.
Labor shortages are particularly acute in the manufacturing sector. As of May 2023, there were 604,000 manufacturing jobs open in the US, according to the Bureau of Labor Statistics. That number was down considerably from the 837,000 openings in May 2022, but the industry could have as many as 2.1 million unfilled jobs by 2030, according to a 2022 study by Deloitte and The Manufacturing Institute.
US manufacturers have particular trouble filling open positions for skilled factory workers, such as machinists, welders, and metalworkers. This pain point is expected to worsen in the coming years as workers retire faster than they can be replaced or seek more stable employment in other industries less likely to offshore jobs.
Solutions: Manufacturers are confronting the skills shortage in many ways. In a June 2023 survey by the National Association of Manufacturers (NAM), 57% of respondents said they expected wage growth of 3% or higher over the next year—a slight slowdown from 2022 and even larger increases in 2021.
National manufacturing organizations are instituting programs to attract more people to the profession, such as the Women MAKE America Initiative that aims to add 500,000 women to the workforce by 2030 through mentorship and educational programs, and the Creators Wanted program that’s connecting people with training and job openings.
Individual companies can follow these leads by creating or supporting mentorship programs and partnering with educational institutions, such as historically Black colleges and universities, to attract more workers to the profession while building a more diverse workforce. They can also invest in training programs, some of them using augmented or virtual reality, to bring current employees and entry-level workers up to speed on the latest manufacturing technologies and processes.
Sophisticated human capital management (HCM) application suites also help manufacturers mitigate labor shortages by predicting hiring needs, supporting talent acquisition and retention, identifying skills gaps, and offering more flexible scheduling options for current workers. Meanwhile, AI, robotics, and other advanced technologies automate some manufacturing jobs to reduce the dependence on human labor.
Meeting a heavy regulatory load strains the ability of manufacturers to operate at optimal efficiency, slowing their production output and eating into profits. While maintaining compliance with what can be thousands of state, federal, and international laws and other regulatory requirements is a common pain point, falling out of compliance can be much more damaging and costly to businesses. Lapses can lead to financial penalties and other sanctions as well as damage brand image and result in costly lawsuits.
Some manufacturers struggle to comply with regulations governing taxes, financial oversight, distribution, sourcing methods, and more. New data regulations are also emerging that govern how these companies store sensitive customer information in their on-premises and cloud-based IT systems.
Of course, many regulations are a matter of common sense. The public expects companies employing processes that use hazardous chemicals to meet rigorous environmental, health, and safety standards. Likewise, manufacturers of healthcare systems and devices must meet stringent quality and safety controls, while manufacturers of military systems are subject to strict export controls.
But regulations can come at a high cost that redounds to customers. Almost 94% of manufacturers that responded to the National Association of Manufacturers (NAM) 2022 Outlook Survey indicated that increasing regulations would weaken their ability to invest in their workers, equipment, and facilities.
Solutions: While regulations can add financial, operational, and administrative burdens, they can also spur manufacturers to modernize their operations in a way that ultimately increases productivity and profitability.
New federal and state requirements governing quality control, waste disposal, employee safety, emissions, foreign trade, and data governance are often satisfied by upgrading production lines, factory processes, and financial management and reporting systems. Such investments often reduce wasteful practices and boost profits.
For example, manufacturers getting in line with a proposed federal requirement to report greenhouse gas emissions have used the data they’re collecting to figure out where they’re overspending on energy. Likewise, new product safety regulations might complicate a quality assurance process, but when satisfied they let manufacturers promote the high standards of their products to inspire customer loyalty. And to meet emerging regulations around financial reporting, taxation, and foreign trade, manufacturers might be motivated to adopt cloud-based software that granularly tracks business expenditures and performs routine audits—and has the added benefit of identifying wasteful spending.
Advanced automation technologies, including IoT, AI, robotics, 3D printing, and cloud-based monitoring and control systems, have the potential to make factory operations more efficient and reliable by reducing or eliminating manual processes. But implementing those technologies often creates headaches for manufacturers.
While the industry is evaluating smart automation methods to improve plant operations, it hasn’t yet standardized on general processes, tools, protocols, and devices. For that reason, automating the factory floor often becomes a challenge of integrating multiple, distinct systems rather than upgrading individual ones.
Another challenge is that factories typically need to maintain their full-scale operations while introducing these new technologies, which may interact with multiple production systems. Managers may hope to modernize an assembly line by introducing advanced data-gathering sensors, but they may struggle to find a way to do so while that line is churning out an important component.
Solutions: Automation-enabling devices and applications installed along assembly lines—such as IoT sensors, cameras feeding computer vision systems, and robots—need to be networked to effectively stream data to cloud-based applications that perform monitoring, control, and data analytics.
Based on their specific needs and constraints, manufacturers start by selecting either wired or wireless (increasingly 5G) networking infrastructure. This decision is often guided by the layout of the factory floor, accessibility of equipment, and data volumes. Whether it runs network cables or implements wireless technologies, the equipment must provide the bandwidth, network resilience, and security to support modern automation systems.
Capable data networks, however, will take manufacturers only so far. Given the hodgepodge of communications protocols used in manufacturing, typically more integration work is required to get automation projects over the finish line.
Manufacturers have high expectations for AI, especially for use cases such as smart manufacturing, preventive maintenance, online support, field service, and faster QA testing with digital twins (virtual representations of systems). Generative AI, in particular, is so new that many manufacturers don't yet understand the potential applications or how to implement the technology. The most advanced supply chain and manufacturing applications reduce such concerns by incorporating AI into the applications. With built-in AI and machine learning, manufacturers can predict machine failures to get ahead of maintenance, adjust production schedules, and avoid costly downtimes. They can also run root cause, impact, and containment analyses on industrial equipment delivered to customers, continuously monitoring the performance of the final product to provide the highest levels of customer satisfaction.
Manufacturing teams often need to work together across sites, some of them geographically distant. For example, they may assemble the same product in plants in different cities (or countries) and need to coordinate production methods and goals to ensure consistent functionality and quality. Or they may make different components for the same product in different factories and need to align production schedules to avoid delays in final assembly.
Creating a unified product or different product lines is hampered by using different assembly methods, documentation procedures, tracking processes, and reporting requirements, even among facilities within the same organization. Manufacturers also need to coordinate their schedules and logistics with those of partners and suppliers whose systems are likely incompatible and disconnected.
Solutions: Efficient collaboration is often a result of effective communication. Within a company, that can be as simple as establishing communication channels between managers and employees, including internal messaging groups, regular team briefings, and Q&A sessions. These low-tech approaches can go far in making sure all coworkers are on the same page. Managers should prioritize keeping all employees informed of business developments. They can even offer training on effective communication methods.
Some of these approaches can be extended to suppliers and other partners. Regular meetings and open lines of dialogue across companies, connecting employees at different levels of leadership, go a long way in smoothing collaboration snags.
Technology can also play a big role. Cloud-based collaboration and project management platforms make it easier for large, geographically dispersed workforces to manage manufacturing processes across sites and organizations by tracking resources, tasks, and budgets; standardizing operations on a common reporting framework; and controlling who gets access to various aspects of the production workflow based on their relevant duties.
Manufacturers are looking to compensate for labor shortages, inflationary pressures, and supply chain disruptions by boosting employee productivity, commonly defined as the volume of output relative to the inputs (such as labor hours and capital) needed to produce it.
Factors impeding productivity include inefficient processes, convoluted workflows, ineffective performance management, and insufficient worker training. As a result, manufacturers waste precious resources, including energy, materials, and employee time. Poor productivity also hurts employees’ job satisfaction, which makes them less engaged and enthusiastic to solve problems and more likely to look for work elsewhere.
It can be difficult to implement productivity-boosting technologies, processes, and training while maintaining consistent operations across the factory floor. Investing in new systems might make each worker and production facility more productive in the long run, but it can cause near-term snags and delays.
Solutions: Boosting productivity can be a matter of just reviewing and reworking workflows and providing better, more regular training for employees—both line managers and the workers they oversee on the production floor. Manufacturers can engage consultancies that specialize in improving plant operations by refining or overhauling processes, training, and related systems.
Cloud-based ERP systems geared to support manufacturing processes can also give an assist. These applications provide a centralized platform for all company data and processes. A capable ERP system can boost worker output by automating repetitive tasks and administrative processes. ERP systems also manage the collection, aggregation, and organization of data, paving the way for the deployment of advanced analytics and AI tools that can deliver operational insights that further ramp up productivity. To avoid implementation headaches and burdensome delays that can precede deployment, manufacturers look for comprehensive ERP and supply chain suites that come fully integrated out of the box.
Digital transformation in the manufacturing industry, sometimes known as smart manufacturing or Industry 4.0, involves the implementation of technologies to collect and analyze data and coordinate physical and digital processes within factories and across the supply chain. Goals include boosting productivity, speeding time to market, and reducing costs. Most manufacturers know they can’t put off comprehensive digital transformation projects for long, but many move forward cautiously, implementing new systems one at a time.
These complex IT implementations, integrations, and change management programs can take years to complete, but in the meantime, production lines need to keep moving. Manufacturers also know that deploying new internet-connected machines, devices, servers, and software isn’t the finish line for a digital transformation initiative—workers must be retrained and processes must be updated, creating more pain points amid the industry’s labor shortage.
Solutions: The concept of digital transformation involves a broad set of technologies; just the term itself can intimidate executives, IT specialists, facility managers, and assembly line workers. One approach to getting started is to identify a unique pain point that needs to be addressed, such as an inefficient process or outdated system.
Once that pain point has been identified, company leaders can build a use case for introducing a specific module into a current system, moving an application from legacy infrastructure to software as a service, or adopting an entirely new cloud-based system. That might include introducing a warehouse management module into a current ERP system or replacing legacy HCM applications with a cloud suite that includes new talent management, training, employee engagement, and other capabilities.
Once a manufacturer successfully eliminates (or at least alleviates) a nagging pain point and begins to see a return on that initial investment, it’s easier to justify and get C-suite approval for investing in the next step in the digital transformation agenda.
In 2022, manufacturing notched its second straight year as the industry most-targeted by cybercriminals, accounting for nearly a quarter of all attacks, according to IBM’s X-Force Threat Intelligence Index.
Many of these have been concerted attacks involving the installation of ransomware that threatens to release stolen data if a ransom isn’t paid. Manufacturers were the victims of more than 70% of ransomware attacks in 2022, according to cybersecurity firm Dragos.
Other cyberattacks have been used to steal intellectual property. Hackers are also becoming highly proficient at executing changes to software that controls industrial equipment—for example, applications that run assembly lines and control systems for energy, shipping, and manufacturing companies. Those attacks have a chilling effect on manufacturers looking to ramp up automation and connectivity because they pose a substantial financial threat to specific businesses as well as the larger, integrated economy that relies on those businesses.
Solutions: Cybersecurity experts say manufacturers often have little visibility into the systems that control their production facilities. Many also make the mistake of letting employees share credentials to computer networks that store sensitive data and control mission-critical processes.
Manufacturers should consider implementing a zero-trust security strategy, which involves continually authenticating access for all users. They should also train employees on the latest security best practices, including using strong passwords (and not sharing them), not opening links from unknown parties, using secure Wi-Fi, and regularly installing security software updates.
When manufacturers introduce a new IT system, security must be top of mind. That means investing in the full spectrum of cybersecurity software, including endpoint protection, threat detection, network monitoring, and next-generation firewalls. To ease a lot of these security pain points, manufacturers can run more of their applications with a cloud provider that implements end-to-end security by default.
Manufacturers aren’t struggling to generate data. The proliferation of industrial applications and IoT-enabled machinery on the factory floor and throughout the supply chain churns out vast amounts of raw data. The challenge for manufacturers is collecting, aggregating, and analyzing all that data to deliver meaningful insights into production and supply chain operations.
Solutions: Big data platforms and advanced analytics turn raw data into business intelligence. These systems can surface patterns buried in massive volumes of data, helping business leaders make smarter and more timely decisions. Advanced data analytics can reveal looming snags and potential vulnerabilities in supply chains, letting manufacturers get head starts on making those logistics networks more resilient to geopolitical shocks. They can also predict when machines or vehicles need maintenance or are in danger of failure, preventing unexpected downtime. Some companies use data analytics to optimize their inventory processes so they’re confident they always have needed components on hand without excessive warehousing. Others use advanced analytics to smooth transactional complexities by detecting errors in invoicing, payments, and shipments.
Business leaders also rely on analytics systems, often integrated with their cloud-based ERP, SCM, and HCM applications, to help them visualize, interpret, and report higher-quality financial, supply chain, and HR metrics.
There’s no one application, suite of applications, or even category of technology and services that broadly alleviates manufacturers’ many pain points. But Oracle offers the most comprehensive portfolio of applications, technologies, and support services to help manufacturers build a digital foundation for success. This starts with an integrated suite of cloud-based manufacturing, supply chain, financial, and workforce management applications.
Oracle Fusion Cloud Manufacturing, part of the Oracle Fusion Cloud SCM suite, can boost productivity on the factory floor by connecting shop floor data coming from IoT sensors with maintenance and planning systems. The application uses AI to predict the machine failures that cause downtime. Other productivity-boosting features include intelligent track and trace, logistics visibility and management, and procurement tools.
Oracle Fusion Cloud SCM and ERP applications let manufacturers manage financials, coordinate the activity of supply chain partners, achieve sustainability goals, and ensure regulatory compliance. And Oracle Cloud HCM helps manage all their HR processes, from recruitment, hiring, and onboarding to retirement.
Complementing Oracle’s cloud ERP, SCM, and HCM applications are its industry-leading data management and analytics capabilities. Oracle Cloud Infrastructure (OCI), Oracle’s next-generation cloud infrastructure, is empowering manufacturers to put their data to work, improving demand forecasting and order management, detecting equipment failures, and improving quality control. With the high performance computing available on OCI, manufacturers can run advanced design simulations with improved speed, at a lower cost.
What common pain points do manufacturers face?
Supply chain disruptions, labor shortages, sustainability pressures, and regulations are just several of the many pain points that manufacturers try to alleviate.
Which technologies help manufacturers cope with supply chain disruptions?
Supply chain management systems that introduce granular visibility into the activities of suppliers, transport fleets, warehouse operators, and other partners help manufacturers avoid the adverse effects of supply chain disruptions.
How can manufacturers address the industry’s ongoing labor shortage?
The industry labor shortage requires manufacturers to improve their strategies and processes for recruiting, paying, training, engaging, and managing their people as well as charting career paths for them—all assisted by the latest human capital management tools.
How are manufacturers analyzing data for competitive advantage?
Manufacturers analyze vast amounts of data to make their production processes more efficient, enhance worker productivity, gain more visibility into supply chain activity, and deliver key metrics to frontline and executive decision makers.