It’s time to take a closer look at labor productivity in the manufacturing industry. For such a long time, productivity in manufacturing remained stagnant—but are the tides beginning to turn? Is AI (artificial intelligence), the IoT (Internet of Things), and other emerging technologies boosting productivity enough to the point where we are seeing some gains? The numbers tell an interesting story.
In the decade leading up to the COVID-19 pandemic, U.S. manufacturing’s total factor productivity decreased by an average of 0.3 percent per year, and McKinsey & Co., suggests this is due to a number of factors including the aging workforce.
When we put the industry under a microscope the numbers are very telling. In fact, since the pandemic, progress in the days following the pandemic looks less than stellar. The U.S. Bureau of Labor Statistics reported in August 2025 that total factor productivity—defined as output per unit of combined inputs—fell in 66 of the 86 4-digit NAICS manufacturing industries in 2022. Looking to 2023, overall total factor productivity was down 3.2%. Are we finally turning a corner? Perhaps! Let’s not get too excited just yet. It seems some slow, yet steady, progress is being made. In the second quarter of 2025, labor productivity was up slightly—2.5% in the manufacturing sector.
The question after reviewing all these numbers is, of course, why? Why is labor productivity often so low in industries like manufacturing? Certainly, the answer is myriad, but I would like to dig into one area for today’s blog: downtime.
The Hidden Causes of Downtime
My interest was piqued further by this topic when a research report crossed my desk: Beyond Breakdown: The Real Impact of Manufacturing Downtime, which surveyed 607 total respondents across 46 states, a wide variety of manufacturing sectors, and with job titles ranging from operations manager to plant manager and many others.
Here’s what the report found. Roughly six out of 10 leaders say downtime costs their business more than $250,000 per year, with facilities experiencing an average of 30 hours of downtime per month, or 360 hours annually. Some of this is planned downtime, but some of this is not. Let’s be honest here. If we do some basic math here, we can surmise every minute of lost production costs roughly $12. Or a 10-minute stoppage may cost $120. Two hours of downtime? Well, that is more than $1,400. I don’t know about you, but I could use that money. How about you?
What is causing all this downtime? Some of it is cleaning machinery, inspections, changeovers, and preventative maintenance. In most cases, these are planned downtimes. But unplanned downtimes occur too when machines break down, minor lines stop, materials are out of stock, or there is excessive wear on a machine. But in other cases, where’s the business?
Going back to the report, one of the most interesting takeaways from this study is this: 67% of respondents said their companies take a reactive approach to maintenance. Further, 55% said downtime feels more like a “when” than an “if” and it impacts nearly every area of manufacturing.
I find this baffling and surprising in an era where technology like AI and the IoT can provide much-needed information in advance. Or so we are told about all the mighty things AI can do these days. Or are we putting the cart before the horse again? I do believe AI can do wonders, But, of course, as we all know, and as we report here at Connected World, technology implementation is easier said than done. Many of the challenges that still exist include slow implementation, limited features, limited integrations, lack of visibility, and hard to use systems. Can you say silos? If you read it once I am sure you have read it a hundred times associated with manufacturing technology.
This report suggests a few strategies for how to move forward and address the challenge of manufacturing downtime including:
- A unified system that visualizes the root causes of downtime, allowing employees to act
- Communication tools to improve knowledge sharing
- Training and knowledge management strategies
- Realtime data and insights around machine performance
I would add we need to consider an organizational shift. Leadership must step up and align people, process, and technology if we want to address the challenges, we still face with manufacturing downtime. Downtime is costly in dollars, in lost opportunities, and in lost time. The cost is just simply too high, hindering cooperation and communication. So, I ask, when will we truly take that next step forward?
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