The State of Digital Transformation in 2024

ReadStats & TrendsInfographicIndustry Insights

Jun 19

Change before you have to: the Imperative for Digital Transformation in 2024

The term "digital transformation" has evolved beyond digitalization - it's a strategic imperative that distinguishes industry leaders from laggards.

Digital Transformation in 2024

According to TEKsystems’ 2024 State of Digital Transformation Report , digital transformation is kicking into high gear, and manufacturing is feeling the heat (in a good way). 65% of organizations are ramping up their tech investments, and manufacturers are right in the thick of it. They're focusing on automation, cloud computing, and—no surprise here—upgrading their legacy systems. For manufacturers, this means embracing innovations like smart factories and Industrial IoT (IIoT) to keep their production lines running smoothly and efficiently. After all, if you’re not automating, are you even manufacturing?

Interestingly, the gap between digital leaders and laggards is growing faster than a production line in overdrive. Manufacturers at the forefront are pouring resources into automation and cloud platforms to optimize their operations. Meanwhile, those lagging behind are still wrestling with clunky legacy systems, which is kind of like trying to run a marathon in flip-flops. On the talent front, the struggle to find workers with skills in AI, automation, and big data continues to be a big deal, and it’s not going away anytime soon.

Key Differences between 2023 and 2024

Looking back at TEKsystems’ 2023 report, manufacturers were mostly playing it safe, focusing on short-term, tactical projects—a sort of “let’s just keep the lights on” approach. With inflation and talent shortages looming, companies were cautious, putting their money into modernizing what they already had. Think small upgrades, not major overhauls. Most of the effort was geared toward improving operational efficiency and managing rising costs, which makes sense when you’re staring down economic uncertainty and supply chain headaches.

Fast forward to 2024, and manufacturers are shifting their focus to long-term innovation. They’re no longer just upgrading systems; they’re diving headfirst into AI-driven technologies, robotic automation, and even predictive maintenance tools. In other words, they’ve gone from tinkering with the engine to building a whole new machine. And while talent shortages were a big concern in 2023, the urgency has cranked up in 2024, especially as manufacturers adopt more advanced technologies like AI and smart robotics. The future is here, and manufacturers are finally getting serious about training their workforce to use these new tools—or risk falling behind.

Trends

In 2024, automation is the name of the game. A whopping 40% of organizations are focusing on automation, and it’s transforming how manufacturers operate. But it’s not just about throwing robots on the production line. Automation in manufacturing means streamlining every process, from supply chain management to production planning, and making operations more agile—so they can pivot on a dime when the market changes. AI is also making waves, especially in predictive maintenance, where systems can predict equipment failures before they happen. Less downtime? Yes, please.

Cloud technologies are another big deal this year, with 35% of companies doubling down on cloud computing. For manufacturers, the cloud is where the magic happens—it enables real-time data analytics, better inventory management, and more efficient production. By adopting cloud-based systems, manufacturers can keep tabs on their entire operation from anywhere, which is a game-changer when it comes to scalability and flexibility. Plus, cloud systems allow for quick adjustments to production schedules, helping manufacturers stay nimble in a fast-changing market.

However, not everything is sunshine and rainbows. Legacy systems continue to be a massive roadblock for many manufacturers. These old-school systems are slowing down progress, especially when it comes to integrating IIoT and big data analytics. The truth is, you can’t unlock the full potential of these newer technologies without first letting go of the clunky systems of yesteryear. But with complexity and cost involved, it’s no wonder some manufacturers are dragging their feet.

Finally, let’s talk about the skills gap. Finding workers with expertise in automation, AI, and data science is still a tall order in 2024. Manufacturers need these skills to fully embrace the technologies driving the future of production. And while companies know they need to reskill and upskill their existing workforce, many are struggling to do so at the pace technology is advancing. The clock is ticking, and the race to fill these talent gaps is heating up.

Actionable Advice for Manufacturing in 2024

Develop a “Smart Pilot” Program for Legacy System Overhaul

Instead of attempting a massive, disruptive overhaul of your legacy systems, consider implementing a smart pilot program that targets key areas where digital integration can have an immediate impact. For manufacturers, this could involve focusing on specific lines of production that could benefit most from AI-driven predictive maintenance or automated quality control. By starting small, you can gather insights, reduce the risk of widespread disruption, and create a clear roadmap for scaling digital transformation efforts. This phased approach also allows teams to gain confidence with new technology before committing to full-scale adoption, making it easier to manage costs and mitigate risks.

Create a Cross-Functional “Digital Integration Task Force”

Digital transformation isn’t just an IT project; it requires buy-in from multiple parts of the organization. Set up a cross-functional task force that brings together team members from IT, operations, HR, and business strategy to identify areas where digital tools can make the biggest impact. For manufacturers, this task force could focus on integrating IIoT solutions with cloud platforms to improve real-time data collection across production lines. The goal should be to identify bottlenecks and inefficiencies that can be solved through digital solutions, then develop a shared roadmap for implementation. This approach ensures that all parts of the organization are aligned and can move forward together, avoiding silos that slow down progress.

Leverage Micro-Learning to Close the Skills Gap

The skills gap is one of the biggest barriers to successful digital transformation, especially in industries like manufacturing where automation and AI are reshaping operations. To address this, implement a micro-learning platform that delivers short, focused training modules directly to workers on the factory floor. Instead of pulling workers off-site for long, disruptive training sessions, micro-learning allows employees to quickly gain new skills while staying on the job. Modules could focus on specific technologies like automation systems, AI-driven analytics, or even advanced robotics. This approach keeps the workforce agile and ensures that learning is continuous and adaptable to new technologies as they’re introduced.

Partner with External Experts for AI and Cloud Adoption

Adopting AI and cloud technologies can be daunting, especially if your internal teams lack experience in these areas. Consider partnering with external experts who specialize in deploying these solutions for your industry. In manufacturing, for example, a partnership with a cloud service provider that has experience integrating IIoT or AI-driven production tools can save time and prevent costly mistakes. These experts can provide tailored solutions based on your specific operational needs, helping you to implement new technologies faster and more effectively. This also allows your internal teams to learn from experienced professionals, helping you build long-term digital capabilities in-house.

Implement Digital Twins for Better Decision-Making

One of the most powerful tools for manufacturers embracing digital transformation is the digital twin—a virtual model of your production process or entire operation. By using a digital twin, manufacturers can simulate changes, test new workflows, and predict outcomes before implementing them on the factory floor. This reduces the risk of downtime or costly errors and allows for data-driven decision-making. Digital twins can be particularly useful when combined with cloud-based analytics and AI tools, as they can provide real-time insights into production efficiency, potential bottlenecks, or equipment performance. Investing in digital twin technology now will give manufacturers a cutting-edge advantage as they continue to innovate.