Deloitte Insights

2018 Skills gap in manufacturing study

Future of manufacturing: The jobs are here, but where are the people?

The Fourth Industrial Revolution is transforming the world of work through artificial intelligence, advanced robotics, automation, analytics, and the Internet of Things. Despite common fears, these technologies are likely to create more jobs than they replace—as illustrated by the tight labor conditions in the US and global manufacturing industry.

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Managing the shortfall of manufacturing workers

For more than two centuries, the manufacturing industry has adopted new technologies and provided new jobs for workers. Today, the industry is experiencing exciting and exponential change, as technologies such as artificial intelligence (AI), robotics, and Internet of Things (IoT) are rapidly changing the workplace. While some predicted that these new technologies would eliminate jobs, we have found the reverse—more jobs are actually being created.

In fact, job openings have been growing at double-digit rates since mid-2017, and are nearing the historical peak recorded in 2001.1 In this dynamic manufacturing environment, Deloitte and The Manufacturing Institute launched their fourth skills gap study to reevaluate their prior projections and move the conversation forward on today’s hiring environment and the future of manufacturing work. The results appear to highlight a widening gap between the jobs that need to be filled and the skilled talent pool capable of filling them.

The study reveals that the skills gap may leave an estimated 2.4 million positions unfilled between 2018 and 2028, with a potential economic impact of 2.5 trillion. Further, the study shows that the positions relating to digital talent, skilled production, and operational managers may be three times as difficult to fill in the next three years.

How can the manufacturing industry get ready for the future of work and prepare workers to work with robots and advanced technologies? What are the skills that will become must-haves in the workplace? What are the pathways for training and education to enable these skills? Finding potential solutions to close the manufacturing skills gap begins by exploring what’s possible for future jobs.

Skills gap in US manufacturing infographic

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Reimagining manufacturing jobs

To help manufacturing leaders visualize the future of work, we’ve developed a series of personas that describe what jobs could look like in 2028. These jobs are described from the standpoint of the workers themselves, exploring how their work has changed, what skills and career pathways they have, the digital tools that assist them in their work, and what a normal day on the job looks like.

Bringing these jobs to life can help business leaders, workers, educators, and policymakers shape their vision and spark conversations around what may need to change.

These future personas represent our research on the manufacturing skills gap and reflect several important themes:

  • Putting humans in the loop
  • Expanding digital and “soft” skills
  • Leveraging the digital toolbox

Future personas

Summary

Digital twin engineers create a virtual representation of both the physical elements and the dynamics of how an IoT-connected product operates and interacts within its environment, throughout its entire life cycle. Ranging from a jet engine or aircraft to a shop floor, an assembly line, or even an entire factory building, digital twin engineers make it possible to virtually see inside any physical asset, system, or structure that could be located anywhere, thereby helping to optimize its design, monitor its performance, predict its maintenance, and improve the overall experience. View the complete persona of the Digital Twin Engineer.

Employee profile

The digital twin engineer plays a crucial role in building the relationships and communication lines across silos to create a network that marries the physical and digital worlds throughout the manufacturing value chain.

Digital twin engineers must be proficient in creating virtual replicas of major industrial products and helping companies predict and respond to customer problems using real-time data analysis and advanced technologies.

Skills include:

  • Simulations
  • Analytics
  • Sensors
  • Software development
  • Systems engineering
  • Research and development
  • Algorithms
  • Image processing
  • Cross-functional team leadership
  • Program management

Toolbox

The toolbox supports the worker in achieving external outcomes such as productivity as well as internally focused ones such as decision making and learning. View complete toolbox of the Digital Twin Engineer.

Productivity

  • Venus–Artificial intelligence (AI)-powered, voice-enabled digital assistant provides a conversational interface for all productivity-related tasks
  • WeAR–Augmented reality (AR) wearable device that connects digital twin engineers to IoT devices and receives work instructions and training
  • InstaCap–Captures data automatically using digital technologies such as radio frequency identification (RFID) and speech recognition

Decision-making

  • Smart Dash–Visual display that presents data, live information, and analysis from multiple sources to facilitate informed decision-making
  • Envision–uses machine learning to identify potential problems as well as opportunities to devise solutions that make a positive impact
  • RealConnect–Enables an engineer to seamlessly interact with suppliers, partners, customers, and the broader ecosystem

Learning

  • SkillsPro–Smart learning assistant that helps digital twin engineers refresh existing skills as well as learn new emerging skills
  • SmartLab–Facilities classroom learning using virtual reality headsets and simulation

Summary

Predictive supply network analysts of the future are a connected and integrated part of the broader digital supply network (DSN) at their organization. Skilled in data sciences and big data modelling techniques, they use digital tools to move materials and finished goods through the DSN for just-in-time deliveries. With a portfolio of digital tools, these analysts rely on machine learning and cognitive computing instead of “gut feel” and static reports to identify opportunities for calibrating demand and supply to maximize performance based on metrics, including customer satisfaction, productivity, and margin. View the complete persona of the Predictive Supply Network Analyst.

Employee profile

An analytics professional with expertise in multiple analytics platform, predictive technologies, machine learning tools and connected inventory management. Help companies achieve optimal inventory and network health management per ongoing and anticipated supply demand scenarios.

Skills include:

  • ERP
  • Demand analytics
  • Inventory optimization
  • Network planning and optimization
  • Replenishment analytics
  • Logistics and warehouse management
  • Analytics
  • General tech fluency
  • Visualization

Toolbox

The toolbox supports the worker in achieving external outcomes such as productivity as well as internally focused ones such as decision making and learning. View complete toolbox of the Predictive Supply Network Analyst.

Productivity

  • Rosetta–An AI based real-time language translator listens to speech, converts it into text, and then translates that into the destination language
  • ShareSmart–AI-bot encompasses enterprise social and mobile technologies to collaborate across operations, both inter and intra companies
  • DSN Tower–Surfaces relevant information from all the connected supply chain applications across the enterprise and provides a customized interface by role and experience

Decision-making

  • Smart Dash–AI dashboard that presents live data and information from multiple sources along with recommendations to enable informed decisions
  • PRO-phet–Uses machine learning to identify potential problems that can be addressed before they cause an impact and can also discover new opportunities to influence business decisions that drive financial or other key results
  • The Hive–Enables a worker to seamlessly interact with suppliers, partners, customers, and the broader ecosystem

Learning

  • Career Coach–This personal bot performs strengths assessments, and understands the broader talent picture at the company. It can use AI to suggest different career pathways and coordinate with SkillsPro training course to create a program for the user to accomplish their pathway. It also links real-time to the talent management system at the company to alert the user of job openings and opportunities for advancement.

Future of work in manufacturing

With digital technologies poised to transform work, explore what the future of manufacturing jobs will look like in this digital era. 

Blending digital skills and uniquely human skills

As digital transformation and the Fourth Industrial Revolution redefine manufacturing jobs, leaders and workers alike need to embrace a new work environment. Here, advanced technology and digital skills must blend with uniquely human skills to yield the highest level of productivity. Understanding how work might change can help the industry as a whole prepare for a future that promises to be transformative.

Endnotes

1 BLS, “Job openings and labor turnover survey,” August 7, 2018.
 

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