12 Months Post-Covid: How Manufacturing Has Changed

Since the beginning of the pandemic, companies were forced to rethink ways to build resilient business operations. From increasing supply chain visibility to investing in advanced technologies, businesses, of all types, had to innovate. In the following article from Forbes, the author reflects on three trends that are speeding up innovation in the manufacturing industries. 

A little over a year ago I posted an optimistic position that the COVID-19 pandemic would dramatically accelerate innovation in manufacturing – a field notoriously slow to adopt new ways of thinking and working. I shared that we would see five years of acceleration in the next eighteen months. We’re two-thirds of the way there, so it’s time for a check-in.

My predictions focused on three trends:

  • That the remote work and remote oversight paradigm would finally unblock the longstanding reluctance to put manufacturing data in the cloud.
  • Automation in short-lifecycle, manual-assembly electronics would become more attractive as personnel risk outweighed the cost of capital-intensive automation projects.
  • Necessity would drive the adoption of targeted technology solutions that address specific pains related to remote work and oversight challenges, and further innovation would come later.

So, how did my predictions for the industry do? At Instrumental we dug deep with over 500 electronics manufacturers in the past 12 months. The conversations we have today are a quantum leap forward from where they were in March of 2020: engineering and operations leaders have a greater understanding of modern software offerings and are ready to act as change agents within their organizations.

Here’s how far we came in 12 months, and 1 new prediction for the next 6 months.

Unlocking the Cloud has unlocked the supply chain

Manufacturing has been notoriously slow to adopt cloud technologies – in part due to outdated concerns about the comparative security of cloud storage vs on-prem. No computer system is completely secure: modern cloud infrastructure is often more secure than on-prem solutions, which often aren’t updated as often against known exploits.

The pandemic accelerated supply chain volatility as many electronics teams executed re-shoring, near-shoring, line moves, and other methods of supply chain diversification to improve agility and avoid total production stall-out. This, in turn, accelerated the adoption of cloud-based tools for line and supply chain management and remote collaboration.

It turns out, if the need is great enough, innovators will overcome hurdles like IT and security assessment, and they did so in force in 2020. This is a particularly exciting trend because it unlocks an age where manufacturing software moves from expensive, bespoke on-prem solutions into agile cloud software that is continuously improving.

Now that many CMs and OEMs have successfully gotten their data into the cloud via services like AWS or Snowflake, they face a new challenge: what to do with all that data. Engineering and operations leaders know their data is valuable, but few have a fully developed strategic plan to get from a massive data lake to use-case-specific data streams that actually power and automate workflows. This will be the next evolution.

Automation has taken more forms than just robotics

Last March I talked about the rise of automation with the focus on rapid-lifecycle consumer electronics programs. Traditionally these rely on highly manual assembly processes because the short product lifecycle makes broad automation impractical. With the increased health risk, robotic processes would become more attractive, and perhaps enable lower headcount density on factory floors.

What I didn’t see coming was how quickly the industry would start looking beyond robotics for other forms of workflow automation, with a focus on processes that used to be dependent on co-location or access to physical systems.

At Instrumental, we responded to this need with a massive effort to apply our Discover AI to further automate the most time-consuming and inaccessible parts of the product engineering and quality functions at scale. How will product design engineers find issues without being on the line? How will they narrow down root cause without in-person tear downs and experiments, or without access to data sets to make correlations? We solved these challenges in 2020 enabling our customers to actually deliver their new product introduction programs faster and more efficiently than they had pre-COVID – in fact while 53% of programs were delayed or canceled in 2020, 100% of Instrumental customers shipped.

With this expanded view of automation, electronics innovators have redefined the problem space beyond assembly robotics to encompass any workflows where machines and AI can operate more quickly and effectively than humans. This extends to correlative analysis, which our platform automates, failure analysis, and multi-stage inspection on the line.

Necessity drove a hunger for solutions instead of technology

Part of what makes our industry slow to change is the amount of snake oil that has historically been sold in the name of buzz words like ‘digital transformation’ or ‘smart manufacturing.’ Too often, hardware folks like us are sold ‘technology’ – a broad technical achievement that could solve any number of problems. This sounds great in a slide deck, but we’ve become wise to the months of integration and implementation required to get little or no real value.

The pandemic forced manufacturing leaders to educate themselves as buyers, which in turn enables them to articulate clear, urgent problems that need solutions. Educated buyers forced manufacturing technology vendors to shift toward producing and selling solutions – that is, focused software products that solve for a specific need. Instead of dazzling with slideshows, vendors are leaning into educating these leaders so they are better equipped to evaluate potential solutions, such as the right artificial intelligence for defect detection.

The shift from technology to solutions indicates a key milestone in manufacturing software evolution, driven by more informed customers who have now looked outside of hardware manufacturing and realized many possibilities for workflow and process enhancement already exist. With more informed leadership, leaders are pushing forward urgent directives armed with new tools that work.

What’s next? Cultural shift towards building hardware like software.

With so much acceleration in the last year, what can we expect in the next six? Speaking with hundreds of companies in the last year, and watching as different players in the market have responded (or failed to respond) to COVID-related challenges, I’m seeing a new trend.

For decades, consumer electronics has been dominated by established players with a deep focus on supply chain management, manufacturing execution, and command-and-control organizations. While software companies with small hardware groups existed long before the pandemic, in 2020, these upstarts exploded into hardware juggernauts, including really innovative lines of new products from Google, Facebook, Amazon, and others.

Of the companies we spoke to this year, those with leaders who had internalized agile software development methods – measure performance, decentralize decision making, and collaborate in real-time – seemed to handle the twists and turns of 2020 better than their hardware-DNA counterparts. I didn’t make the connection until we had executives from both types of companies sitting at a “zoom table” discussing what they had learned from the year: it was stark. Executives with an agile development mindset focused on operationalizing agility, keeping the schedule moving today and tomorrow, versus hyper-optimizing for metrics in development that wouldn’t matter until production months later.

This shift creates a totally different product development philosophy: iterate quickly, understand data, and respond quickly. Hardware leadership is starting to expect the same digital-first data engine that software leadership has enjoyed for decades – so they can confidently assess in real-time and make quick decisions. Is this just a passing phase that will dim when engineers are back in the office or once again on planes to the factory? Unlikely. These leaders have already seen that measuring what matters has accelerated their schedules and enabled them to ship high quality products with better financial metrics. 

These Agile Hardware Development leaders are investing for the long-term, and in the next six months those who aren’t operating this way will start to feel pressure to do the same.


This article was written by Anna-Katrina Shedletsky from Forbes and was legally licensed through the Industry Dive publisher network. Please direct all licensing questions to legal@industrydive.com.