In the past few years, companies have weathered everything from a global pandemic to component shortages, geopolitical turmoil and an ongoing battle to attract talent.
To effectively respond to disruption in the supply chain and manufacturing ecosystems, decision-makers need to fully understand how to manipulate the various company dials in their control.
In addressing this, decision-makers need to fully understand their companies and how to manipulate different dials in the supply chain and manufacturing ecosystems to optimize the product lifecycle and respond effectively to disruptions.
These dials — and the degree to which they are turned up and down — will vary from company to company. However, organizations must take decisive steps to adopt advanced technologies, streamline processes, and secure a dependable, well-trained workforce.
Embracing Industry 4.0
In 2022, MIT Machine Intelligence for Manufacturing and Operations (MIMO) and McKinsey partnered to survey 100 high-performing companies across sectors to learn how they deploy machine intelligence (MI) and data analytics for manufacturing and operations.
The study found that ‘overall, those who extracted the biggest gains from digital technologies had strong governance, deployment, partnerships, MI-trained employees, and data availability. They also spent up to 60% more on machine learning than their competitors.’
Deploying advanced manufacturing technologies and solutions enables resiliency and competitiveness in an increasingly digital world. However, to gain the greatest advantage from these Industry 4.0 improvements, companies must fully commit to the process and invest in areas like ongoing workforce training and development.
Companies must weigh the initial cost of implementing advanced manufacturing technologies with the benefits of optimized production lines, less waste, and higher visibility into the product life cycle. Therefore, the best forward strategy looks different for each company. Manufacturers of complex, higher cost, and longer lifecycle products — such as automotive and medical devices — may choose to invest in highly specialized automation solutions to optimize their product lines.
In contrast, a manufacturer who produces a high mix of consumer lifestyle products may find that it is more cost-effective to implement ‘vanilla automation’, or automation processes that can be used in many different projects to carry out common steps like fastening screws, applying labels, and packaging products.
Streamlining and Optimizing Processes
Fully realizing the promise of Industry 4.0 goes beyond the acquisition of advanced technologies. Without a firm grasp of process know-how and the application of Six Sigma and lean manufacturing principles during implementation, companies may still be left with idle machines, underutilized software platforms, or poor-quality products. For example, a manufacturer may automate a manual inspection process while not clearly defining pass/fail criteria. This can either lead to too many rejects and a higher cost per unit, or low-quality products that damage the brand reputation.
Digital Technologies Predicting and Responding to Supply Chain Disruptions
When deployed intelligently, Industry 4.0 technologies can also provide unprecedented insight into the entire product lifecycle. Digital technologies — including AI, analytics, blockchain, and IOT — can be used to design and operate the kind of revamped ‘Just in Time’ network we’ve described. Analytics, for example, can help members of the supply chain identify common parts across product lines and design optimal buffers. Digital twins — digital models of the supply chain — can alert downstream plants about any upstream disruptions faster so they can avail themselves of the buffers more quickly.
Investing in the right technologies and solutions can provide manufacturers with better insights for planning and data-driven action in both their production lines and supply chains. In fact, the factories of the future and the manufacturing sector as a whole have potential to utilize data architecture to connect every part of the product lifecycle — from planning to production to warehousing to delivery and aftermarket.
This will empower those on the ground to make real-time decisions that help to absorb setbacks while identifying growth opportunities and ways to be more competitive.
Hiring, Retention and Securing Capacity in Manufacturing
In the global search for talent, the manufacturing industry’s long-term success depends on its talent pool.
This means ensuring that the industry continues to hire and retain purpose-driven innovators, problem-solvers, and makers who can help mold the next era of manufacturing. In day-to-day production, securing capacity must also be considered so that staff can increase to full production after a disruption. For example, in the face of component shortages, manufacturers sometimes make the mistake of reducing workforce because they currently have fewer or less optimized factory lines running.
Often, the smarter option is to retain workers until full production returns. People are important in the manufacturing process, especially today when many countries are faced with staffing challenges. Workers can be deployed to support different factory lines or support other areas of the production ecosystem temporarily when needed.
This allows manufacturers to be more agile while remaining in control when components are restocked or demand increases. Keeping workers employed even during downtime can work as a strategic resiliency play, one that considers the high cost and time commitment of rehiring and training new employees.
Resiliency Looks Different for Everyone
Ultimately, the building blocks of resiliency will look slightly different for every company, but the common thread is the need to understand the data and variables behind your own business operations while embracing innovation and change.
