Manufacturers Are Falling Behind on Digital Transformation. How Can They Catch Up?

Digital transformation promises to help manufacturers optimize their operations and gain competitive advantage—but they need to play catch-up to realize those benefits.

Digital transformation is becoming increasingly predominant—and increasingly important—across a large cross-section of industries thanks to the growth of digital tools and technologies such as the Industrial Internet of Things (IIoT) and artificial intelligence (AI).

In the past, manufacturers have relied on methodologies such as benchmarking and Kaizen to refine and improve their processes. While useful, these methodologies—which can often be manual processes—have been unable to access, process and derive insights from the massive amounts of data that can be generated on the factory floor.

New digital technologies such as machine learning, AI and IIoT sensors can both capture and generate extensive amounts of data. Analyzing and deriving actionable insights from it requires a digital solution. That’s the problem digital transformation means to solve.

Being able to do so would be of clear benefit for manufacturers. Digital transformation can be challenging to implement, though—and many manufacturers are falling behind on the digital transformation curve. Technologies such as high-performance computing or supercomputing could be key components that enable those businesses to catch up with the competition.

What is digital transformation?

You’ve heard the buzzword, but what does it actually mean?

Digital transformation—as the term implies—is the process of using digital technologies to improve and enhance a company’s business and production processes. But it’s more than just putting sensors on a legacy machine—though that in itself is a valuable part of the process.

Rather, it’s about intentionally and strategically implementing comprehensive changes to the business to reach its goals (improving efficiency, boosting customer and shareholder value, becoming greener, etc.)—and carefully selecting and deploying digital technologies to make that change happen. The consensus among manufacturers across industries is that digital transformation is a powerful tool that will help companies improve performance, respond to market challenges, meet the demands of their customers and become more resilient and adaptable to the future.

How Digital Transformation Helps Manufacturers

Manufacturers can gain a lot of actionable insight from data and analytics, AI and digitally enabled machinery and processes—resulting in opportunities to add significant value to their companies and give them a competitive edge. Research and advisory firm McKinsey estimates that companies that successfully navigate this transformation could see forecasting accuracy increases of up to 85 per cent, machine downtime reductions of 30 to 50 per cent, throughput increases of 10 to 30 per cent and labor productivity improvements ranging from 15 to 30 per cent.

Digital transformation is “the only way to respond to sustainability, changing customer requirements, competitors who are in the process of transforming, increased operating resilience, supply chain volatility, cost control, and increasing product and packaging complexity,” said Greg Gorbach, vice president of digitalization and Internet of Things at ARC Advisory Group, a leading technology market research firm for industry and manufacturing.

This transformation can benefit manufacturers in a variety of ways:

  • Higher productivity: automated systems can accomplish repetitive processes that humans aren’t particularly suited for, reducing errors and inefficiency and freeing up employees to focus on more value-added work.
  • Reduced operating costs: automation, data analytics and IoT sensors can enable operations to be adjusted automatically to save time and money through measures such as predictive maintenance to avoid machine breakdowns and optimizing energy use to save utility costs.
  • Resolve labor challenges: automation on factory floors and in the office can help reduce manual workloads, enabling manufacturers to conduct business with smaller workforces—and helping maximize the work of skilled laborers through the use of technologies such as collaborative robots.
  • Create resilient supply chains: the transparency enabled by real-time data analytics allows manufacturers to become more flexible and responsive to supply chain challenges.
  • Enabling ongoing improvements: data generated from digital transformation can be used by businesses to recognize and address opportunities to further optimize their operations.

How Are Manufacturers Doing?

In a recent Gartner report, large operations are spending twice as much and taking twice as long to implement their digital transformation plans than they originally expected to. In addition, 53 per cent of the organizations the firm surveyed haven’t been tested by a digital challenge yet, undermining their readiness for that transformation.

According to McKinsey, there are five recurring reasons for the failure of manufacturers to see their digital transformation through.

First, implementation tends to be siloed. Companies often set up digital transformation delivery teams that are not plugged in to executive leadership, site operations or enterprise-wide IT departments. Other firms try to replicate the success of a single site transformation across the enterprise without taking into account broader network complexities.

Second, companies fail to adapt to challenges along their transformation trajectory. They pursue a one-size-fits-all solution (such as the single site experience applied to all sites in the previous point) that is not resilient or adaptable enough to take advantage of unique circumstances or respond to particular challenges in separate manufacturing sites.

Third, companies could find themselves paralyzed by overanalysis. It may not always be ideal for a company to perform a deep and exhausting analysis of its current operations, leaving it with no further stamina to implement that transformation. Instead of going all-in on a top-to-bottom review, companies could be better served with a limited, strategic analysis from which to extract actionable insights.

Fourth, companies may become enamored with implementing a particular technology rather than putting their values and vision first. A technology-first approach means solutions are implemented without sufficient focus on actual business challenges or capabilities—which can undermine the plan’s adoption by the very people tasked with implementing it.

Lastly, companies could be making “perfect” the enemy of the good. Waiting on the ideal digital architecture and complete amount of data before implementing any solutions could mean manufacturers miss the opportunities to add value that come from a pragmatic and viable architecture. This flaw is somewhat related to the third point about analysis paralysis.

Companies that have successfully implemented a robust digital transformation plan haven’t jumped headlong into acquiring and deploying particular technologies. Instead, they have invested time in properly identifying how Industry 4.0 can meet the needs of their operations first—and planning and deploying a digital transformation strategy focused on meeting those needs.

HPC and Supercomputing

As you can imagine, digital transformation can generate massive amounts of information. This presents a unique challenge to the operation that’s undergoing that transformation: how do you capture all that data and turn it into insights that you can use to grow your business?

Increasingly, the answer could be supercomputing and high-performance computing (HPC).

Supercomputing is the use of a powerful computer to perform tasks that require a lot of computational power or handle a lot of data—more than a shop floor manager’s computer can handle. In contrast, high-performance computing is a broader term that covers all the skills and tools needed to build supercomputers—and link them together into a cluster to work as one. Since most of today’s supercomputers are HPCs that operate in clusters, the two terms have become interchangeable.

Imagine if you had tens of thousands of laptops, all connected together, running one piece of software that needs all of the laptops running it at the same time, to solve one single problem. That’s what supercomputing does.

But while supercomputing offers great potential, the costs of owning a supercomputer can be prohibitive—and it requires specialized staff with thorough knowledge of advanced modeling and simulation techniques. The U.S. Department of Energy does provide American businesses with access to its HPC resources. And increasing demand could put market pressure on the sector to reduce costs.

But with or without a supercomputer, digital transformation is not only necessary, but achievable. Oracle estimates that 82 per cent of manufacturers either already have, or intend to develop, a digital transformation strategy—and that nearly a third of those operations already report having a competitive advantage. It’s a process rather than a destination—and is one that can be initiated right now.

This story is one in a series underwritten by AMD and produced independently by the editors of Subscribe here to receive informative infographics, handy fact sheets, technology recommendations and more in AMD’s data center insights newsletter.