The Covid pandemic drove many manufacturers to invest more in technology than in the past. This has been as an attempt to overcome the labor restrictions, supply chain challenges and safety challenges.  Looking forward to 2022 there are a number of ongoing challenges. These include critical supply chain shortages and labor unavailability. They are driving manufacturers to invest even more in technology such as AI, robotics and additive manufacturing (3D printing).  Driven by vendor and media hype manufacturers are being led to believe that these investments will let them rise above the turmoil.  The reality is that the vast majority of these investments will only keep the businesses afloat.  They will do little to actually give them a sustainable competitive edge.  The bottom line for 2022 is that technology is manufacturing’s life preserver, but technology alone won’t rescue most companies.

Enterprises have been bombarded with the Digital Transformation message and manufacturing is no exception.  After decades of living by the mantra “if it isn’t broke don’t fix it” the corona virus pandemic forced many manufacturers to face the reality that their historically low investment in technology, often 1/3 to ¼ (as a percentage of revenue) the spend of other industries, needed to change.  The media, consulting companies, and technology vendors all rushed to promote technology as the answer to Covid driven challenges.

Some examples:

  • Labor Shortage? Invest in robots! For years manufacturers have used robots to perform tasks that are extremely repetitive, hazardous, or require precision humans can’t reliably deliver.  However, the lights-out, fully automated plant is incredibly rare. Going into 2022 the labor shortage dominating the news in late 2021 looks to continue.  So, firms are looking to robots to solve the problem.
  • Supply Issues? Use 3d Printing! The last quarter of 2021 has made “supply chain issues” a ubiquitous term that everyone knows, not just manufacturers. Enter 3d Printing or additive manufacturing (AM).  Whether for repair parts or raw materials/components the idea is with AM you can produce needed materials as needed, not relying on a long supply chain.
  • Talent Shortages? Adopt artificial intelligence and machine learning! As IIoT devices have moved to the factory floor more information than ever is available.  How to best use that information to optimize performance, whether it is improving equipment reliability, product quality or overall operational excellence, AI and ML offer a way to leverage the wealth of data to achieve your objectives.

The result is that businesses are investing in these and other technologies to help them move forward at a rate that few predicted prior to Covid.

The problem is that technology is only like a life preserver.

If you are drowning the life preserver can keep you afloat but it won’t actually save you.  Looking forward to 2022 there are two reasons that technology may fail to deliver the results manufacturers hope for:

  • Trading One Problem for Another: Many manufacturers are looking to technology to solve labor or talent shortages. Take robots as one example. The problem with robotics is that while a robot can replace someone, they are like any other piece of machinery and need maintenance. And guess what; there is a shortage of skilled robot technicians.  Amazon, well known for its aggressive adoption of robots to solve performance issues now has had to sponsor a robotics maintenance education program and offer a 40% premium to robotics techs over generalized maintenance techs.  It has been reported that at some places the service issue has led to having to replace robots that fail with spares and then waiting for traveling repair techs to fix the collection of broken units. That might work for Amazon, but many manufactures will not have the luxury of keeping entire spare robots at the ready for failed units.  Also, there is a critical shortage of robotics programmers as there are for data scientists to program AI and ML applications.
  • Automating a Bad Process: The rush to automation, from the front office using robotic process automation (RPA) to the shop floor using the technologies described above and others carries a significant risk.  Automation has proven to allow for consistency, faster execution, and often greater throughput.  However, if you automate a bad process in essence what you are doing is “doing bad bigger and faster”.  Overall only about 20% of major technology projects deliver their full expected benefits.  Most often it is because organizations fail to implement the process and people changes needed to actually get benefit from the investments.  Technology usually doesn’t fail, projects do.

This is not to say technology has no value in 2022 or beyond.  Quite the opposite.  Just like a life preserver, technology can keep your firm afloat while you figure out how to really rescue yourself.

To make the most of technology in 2020 manufactures need to:

First and Foremost:  Align technology plans with your business strategy which should have agility as an important element.  The next pandemic, climate related upset or other some other unforeseen challenge will put even more pressure on your business.  Don’t invest in technology to solve today’s problem only.  Don’t ruxh into to deploying a new technology if you aren’t willing to make the process and organizaitonal changes needed to actually derive benefit from the new tech.

Second: Make sure the technology you deploy can be supported.  A manufacturer in a remote location already struggling to keep a technically capable workforce should think twice before going all-in on technologies like robots or additive manufacturing.  If you can’t get skilled people to run traditional machinery supporting even more sophisticated tech will be even more of a challenge.

Finally

Look for technology that delivers results, not toolkits that expect you to do the work.  I can buy a smart thermostat for my home that can easily be programmed to save energy, remind me change my filters and schedule periodic maintenance. A factory owner should not need to buy sensors, communication hardware, data acquisition software and an AI platform and hire a data scientist to do a similar task.  There is technology that is plug-and-play.  Look to it first.