If you’ve ever championed new manufacturing technology, you know it’s a bold and necessary move. But without a direct link to the people who keep your lines running, even the best tools remain a theoretical win. Many executive leaders may find a gap between digital transformation strategies for industrial companies and the physical reality of their plant floors. Are technicians actually using the tech you sought out for, or is it just adding an administrative burden on them?
In this guide, we cover what successful digital transformation in manufacturing looks like, the technologies that make it possible, and how to bridge the gap between strategy and the shop floor.
Key highlights:
- Digital transformation in industry is the process of connecting your people, systems, and equipment under a shared technology layer, replacing reactive, fragmented workflows with an operation that learns, adapts, and improves continuously.
- The solutions driving the most impact for digital transformation of manufacturing include AI, IIoT, cloud computing, and big data analytics.
- Digital technologies work best when you deploy them around a specific, measurable business problem. Companies like PepsiCo and Hill’s Pet Nutrition prove that starting with a specific focus is how you can move past pilots toward enterprise-wide transformation.
- Digital transformation is as much an organizational challenge as a technological one. Governance, change management, and workforce enablement can determine whether your program is successful or not.
What is digital transformation in manufacturing?
Digital transformation in manufacturing is the integration of technology across your operation to redefine how you work, collaborate, and deliver value to customers. This process aims to replace manual, siloed workflows with a unified ecosystem where your people, virtual tools, and equipment work in sync.
Industries need digital transformation for these four reasons:
- Compressed competitive cycles: The market moves fast, and the window to stay ahead keeps shrinking. Facilities that predict and prevent machine failures, for example, outpace those that can’t. With industrial manufacturers losing an estimated $50 billion annually to unplanned downtime, that edge adds up quickly.
- The loss of tribal knowledge: Your most experienced technicians carry decades of critical expertise, and many are approaching retirement. Research by Deloitte and the Manufacturing Institute estimates that 2.8 million manufacturing workers will retire by 2033. Digital systems that capture this knowledge now protect your operation’s institutional memory before your senior talent walks out.
- A shifting workforce: The newer generation of workers expects modern, intuitive tools that help them succeed from day one. You need platforms that help recent employees ramp faster while allowing your senior staff to focus on higher-value, proactive work.
- Rising demand for precision and sustainability: Evolving customer expectations for faster delivery and sustainable practices are pushing factories to minimize waste from inefficient processes.
What are the benefits of digital transformation in manufacturing?
Digital transformation in industry leads to lower costs, improved equipment uptime, stronger safety, and faster decisions. Once actionable data reaches the right people, information gaps close, and plant leaders gain more control over daily performance.
Key benefits of digital transformation in manufacturing include:
Less emergency repairs, more predictable maintenance costs
The right technology can enable fewer emergency interventions, less unbudgeted spend, and smarter resource allocation. In maintenance alone, predictive tools help you schedule repairs in advance rather than absorbing the full cost of an unplanned breakdown.
Increased production runtime and agility
Connected digital systems give you a real-time view of performance across lines, sites, and functions, so your industry can respond to demand shifts or operational bottlenecks while minimizing throughput loss.
Recent solutions for condition-based maintenance show how you can leverage this benefit: with 24/7 asset monitoring and real-time alerts, you can plan equipment downtime on your own terms instead of reacting to breakdowns, streamlining operations.
Faster, more confident decisions at every level
When your ERP, production, and maintenance systems share a common data layer, information reaches stakeholders at the right time, without manual reporting or gut calls. This visibility helps manufacturing leaders justify capital investments, optimize capacity planning, and prioritize improvement initiatives based on real evidence.
Fewer workers exposed to high-risk situations
Digital tools reduce workers’ exposure to high-risk environments through remote monitoring, automated alerts, and smarter scheduling of hazardous tasks, allowing for safer manufacturing operations.
Improved employee retention and upskilling
New, intuitive platforms make your operation a place people want to stay and grow. In fact, Industry Week’s The State of Production Health shows that 99% of manufacturing leaders believe that adopting advanced technology will positively impact their upskilling efforts. According to the report, “this near-unanimous consensus underscores that those who lead the future of manufacturing will be the ones who invest in AI and their people in equal measure.”
What are the key technologies enabling digital transformation for manufacturing?
Modernizing your operations starts with a strategic decision on the solutions to prioritize. A Deloitte survey found that 80% of manufacturing executives plan to invest 20% or more of their improvement budgets in smart manufacturing initiatives, including automation hardware, data analytics, sensors, and cloud computing.
Let’s dive deeper into the key technologies enabling digital transformation for manufacturing:
1. Cloud computing
Cloud computing gives you a shared environment for data, analytics, and collaboration across plants, regions, and functions. This tech brings operational data out of silos and into a format that leaders can use quickly.
For multi-site programs, the cloud makes deployment easier because you can scale software and analytics without building separate infrastructure for each plant. IT department workers can standardize dashboards, connect sites to the same data model, and give corporate leaders a portfolio view while local leaders keep the context they need. That combination makes your digital transformation program less dependent on one facility’s internal setup.
2. Artificial intelligence (AI)
Artificial intelligence (AI) is one of the most powerful levers for digital transformation in the manufacturing industry. You can apply it to quality control, inventory management, predictive safety alerts, and many more use cases. By deploying AI in maintenance, for example, you can detect equipment faults weeks before they disrupt production.
According to McKinsey, generative AI has the potential to create $2.6 trillion to $4.4 trillion in value across industries, including advanced manufacturing. In a plant context, that means faster diagnosis, quicker response to issues, and streamlined access to operational knowledge and insights.
Agentic AI in manufacturing goes even further by using digital systems that don’t just surface insights, but act on them, working as active co-pilots in your operations.
Learn how digital transformation and artificial intelligence are reshaping the manufacturing industry in this episode of our Manufacturing Meet Up podcast:
3. Industrial Internet of Things (IIoT)
The Industrial Internet of Things (IIoT) connects machines and virtual software into a unified network of intelligent assets. Where traditional monitoring once told you what already happened, IIoT now gives you a real-time living picture of your operation, from individual equipment sensors to smart energy grids that automatically balance load across your production lines.
IoT-driven predictive maintenance, for example, gives your engineers real-time visibility into vibration, temperature, pressure, and other signals that indicate how equipment behaves under load. This capability helps you detect small issues before they compound into larger machine faults. If your technicians can hear a problem on the floor, it may already be too late to fix it.
Digital transformation for manufacturers requires systems that surface those signals early on. In this sense, IoT devices are the connective tissue of a modern plant, feeding the cloud analytics and integrated platforms that keep your enterprise running.
Discover the best predictive maintenance technologies.
4. Big data analytics
Your machines, sensors, and systems on the plant floor generate signals around the clock. The question isn’t whether you have enough of these indicators, but what you do with them. Big data analytics gives enterprises the infrastructure to collect, process, and act on real-time information at scale.
When you gain insights from patterns across thousands of data points, including production rates, energy consumption, and equipment cycles, those findings compound across every line, shift, and facility you run.
Pair big data analytics with the IIoT sensors and AI models, and you’ve got an operation that adapts quickly and gives you the visibility to lead with confidence rather than catch up after the fact.
Common challenges for the digital transformation of manufacturing
Digital transformation in manufacturing can be as much an organizational challenge as a technological one. The right tools matter, but so does the system around them: how you make decisions, communicate, and manage change across a complex operation. Understanding where these programs typically hit friction is the first step to building one that doesn’t.
| Challenges for digital transformation in manufacturing | What this challenge means for your operations | How to mitigate this challenge |
| Organizational resistance to change | Resistance can be a response to rollouts where the “why” isn’t clear or the shop floor team wasn’t part of the conversation from the start. When technicians and plant managers don’t see themselves in the solution, adoption stalls regardless of how good the technology is. | Bring operational teams in early, before implementation, not after. Then, define what success looks like at the floor level, not just in the boardroom. When people understand how the technology makes their specific job easier, resistance gives way to ownership. |
| Fragmented data and technical silos | When your systems don’t communicate, you end up with different versions of the truth and no clear picture of what’s actually happening across your production lines. Decisions slow down, and the value of your digital investments stays locked inside individual tools. | Prioritize interoperability when evaluating technology. Cloud-based platforms that connect data from across your operation, including IoT sensors, analytics tools, and existing systems, give your teams a single source of operational truth to work from. |
| Workforce skills gaps | Digital transformation asks your workforce to work in new ways, often with tools they haven’t encountered before. Without structured enablement, even the best platforms go underused, and the productivity gains you invested in can never fully materialize. | Pair every technology rollout with targeted upskilling. Treat capability building as part of the program, not a nice-to-have. Budget time for training before go-live, and make sure industrial workers feel confident using the tools from day one. |
| Scaling beyond pilots | Without clear KPIs, documented learnings, and executive alignment, promising proofs of concept stay isolated wins rather than becoming the foundation for enterprise-wide change. This gap is where most digital transformation efforts stall. | Define your scale criteria before the pilot ends. Know which metrics you need to hit, which stakeholders need to sign off, and how the solution will adapt across different facility sizes and contexts before committing to a broader rollout. |
| Data security concerns | Connecting operational technology (OT) to cloud systems and external platforms can expand your attack surface. In a manufacturing environment, even a small breach can mean compromised production, safety, or customer commitments. | Work with vendors who treat security as a core part of their product, not an afterthought. Establish data governance, define what information leaves your environment and where it goes, and involve your security team from the first conversation, not the last. |
6 digital transformation strategies for industrial companies
Scaling digital transformation across a manufacturing enterprise takes more than a technology roadmap. The manufacturers who get it right build the conditions for value to compound: clear use cases, the right internal champions, and a rollout approach that turns one successful site into a repeatable global program.
Need to prove the value of new technology? Consider these six digital transformation strategies for industrial companies:
1. Identify high-impact technology use cases
The most effective digital transformation programs start by pinpointing where technology can deliver the most immediate value, whether that’s reducing downtime on critical assets, closing a visibility gap, or improving quality at a specific point in production. A focused use case gives you a clear target, makes it easier to demonstrate ROI, and builds the internal confidence you’ll need to scale.
2. Avoid one-size-fits-all digital platforms
When evaluating technology for digital transformation in industrial manufacturing, look for solutions that can flex to your specific assets, workflows, and operational context. Avoid one-size-fits-all digital platforms that force your operation to conform to their architecture. Tailor your approach to what each part of your plant actually needs, and you’ll avoid over-investing in areas that don’t move the needle while under-protecting the ones that do.
3. Prioritize plant-floor level insights
Corporate dashboards are useful and important. But the real transformation happens when your maintenance technicians, operators, and plant managers have access to the information they need to act right on the factory floor. Look for solutions that integrate with your existing CMMS and EAMS systems and give every level of your organization the right view of what’s happening and what to do about it.
4. Select and empower a local digital champion
Every plant has someone the rest of the team listens to. A person who understands the floor, earns trust naturally, and knows how to cut through resistance. That’s your digital champion, and bringing them on board early can make a difference in your program. Give them the resources, authority, and visibility to drive adoption and push through obstacles.
5. Track and share your wins to build momentum
As you roll out new technology, track results against the specific goals you set at the start: downtime hours avoided, response times to alerts, adoption rates, cost savings, etc. Then make those wins visible. Share them across shifts and leadership levels to build the kind of momentum that turns a pilot into a company-wide program.
6. Build a repeatable playbook for global scaling
After a solutions pilot, document what worked: how you rolled out the technology, tracked results, and trained the staff. That documentation becomes your scaling playbook: a blueprint that lets other plants get up and running faster, with fewer missteps, adapted to local context.
Discover our tips for getting started with Machine Health.
Digital transformation: Examples in manufacturing
Real-world proof beats theory. Here’s what we can learn from top digital transformation examples in manufacturing, and why the companies leading the way share one thing in common: they started with a clear business problem definition.
PepsiCo: Scaling ROI from four plants to a global footprint
When PepsiCo’s Frito-Lay business set out to reduce unplanned downtime across its production lines, the team didn’t start with a mandate to “go digital.” They started with a specific operational target and went looking for the best technology to hit it. After running an objective, side-by-side evaluation of both large and small vendors, they chose Augury’s Machine Health Solutions to monitor and predict equipment faults.
The pilot ran across four Frito-Lay facilities. After one year, the results were clear: zero unexpected breakdowns, interruptions, or incremental costs for replacement parts, saving over one million pounds of food from preventable downtime.
What made PepsiCo’s approach a standout digital transformation example in manufacturing was the discipline. As Anna Farberov, General Manager of PepsiCo Labs, put it, the team focused on real business needs first, brought in the right internal stakeholders, and moved fast. PepsiCo Labs then helped navigate the broader organization to get decision-makers aligned and accelerate the rollout.
That foundation turned a successful pilot into a global program. Augury’s system scaled to nearly all of Frito-Lay’s US plants, adding the equivalent of four additional months of production runtime each year.
Hill’s Pet Nutrition: Optimizing operations with predictive maintenance
Hill’s Pet Nutrition, part of the Colgate-Palmolive family, had a clear priority: maximize uptime to meet growing consumer demand for its products. The team knew that calendar-based maintenance, where you service equipment on a fixed schedule regardless of its actual condition, was leaving too much to chance. They needed real-time data on how their machines were performing, not a report on how they performed last quarter.
Partnering with Augury, Hill’s piloted a predictive maintenance program across one facility. Within the first six weeks, two early equipment alerts surfaced issues that, left undetected, would have caused line shutdowns. Those interventions alone covered the entire cost of deploying the technology across that plant for the full year. Hill’s team then rolled out the solution across all six of its facilities, achieving 100% coverage.
What makes this a compelling case is the mindset shift that the new technology enabled. As one leader on Hill’s team noted, colleagues from other departments started asking about Augury’s alerts during any downtime event, because the platform had become part of how the plant operates, not a tool bolted on from the outside. That’s what genuine digital transformation looks like: technology so embedded in your operation that your people build their work around it.
Scale digital transformation in industrial manufacturing with Augury
Digital transformation strategies for industrial companies point to one consistent fact: the manufacturers pulling ahead are those starting with a clear problem, proving value fast, and building from there.
That’s exactly where Augury meets you. With a cloud-native architecture, our Machine Health Solutions are made for easy deployment. Having been implemented at hundreds of global sites, our rollout strategy ensures your business sees consistent predictive maintenance results without adding administrative overhead.
You’ve got the roadmap for digital transformation in manufacturing. We can help you run it. Get an Augury demo to see how our solutions work for your specific use cases.
