Manufacturing companies have been attempting to reduce costs for decades by optimizing routes, minimizing inventory levels, or automating repetitive tasks. However, over time, manufacturing became so complex that traditional optimization stopped working so well.
They simply don’t address the growing complexity of modern operations, the hidden losses from manual work, or the inefficiencies buried in disconnected systems and outdated processes. Interested in how new tools can change your business? Keep reading this article to find out the benefits of automation!
What is Digitalization in Manufacturing?
Digitization in manufacturing means adopting modern technologies to collect, analyze, and manage various work-related processes. This process reduces manufacturing costs by using sensors, the Internet of Things, and other remotely controlled devices.
Many companies already leverage analytics and business intelligence (BI) tools to transform raw data into actionable insights. Digitalization helps businesses make decisions based on accurate data rather than assumptions. Trackers gather data about equipment status or climate, while CRM and ERP systems record that data and use it during procurement, manufacturing, warehousing, and sales.
How To Properly Digitize the Work Process?
First of all, you need to find a logic behind your manufacturing, since automating a flawed process is like putting a diesel engine on a wooden cart. Yep, it may look more modern, but it will retain its core flaws.
That’s why redesign starts with a shift in mindset when you ask yourself how you can do things differently. Digitalization doesn’t mean introducing software solely to track old steps with a modern tool. No, it doesn’t work that way! You need to redesign the entire system, making it more efficient with a higher return on investment (ROI) while keeping most of your staff at work. The goal is to remove the unnecessary while teaching your core team.
What Costs Can Be Reduced Through AI and Automation?
Let’s get one thing straight. AI and automation aren’t magic. However, manufacturing planning software is a powerful tool that can change your business when used with intention. It can help you reduce business losses, improve predictability, and increase overall efficiency across the entire production cycle.
Business manufacturing software can help you combat production losses by detecting potential failures before they even occur. Automation systems can even help you spot human resource inefficiencies, freeing staff time to focus on higher-value work such as creative problem-solving.
Another benefit of software for manufacturing processes is simplified logistics and warehousing. From overstocked shelves to empty bins, traditional stock management often relies on guesswork. Predictive algorithms can forecast demand and streamline procurement. You no longer need to overstock “just in case.”
Truth be told, AI-based business manufacturing software won’t solve everything overnight. But when implemented thoughtfully, these tools can reshape operations not just by cutting costs, but by making businesses smarter, faster, and more resilient.
Real-World AI in Action: How Companies Are Turning Algorithms Into Advantage
AI-based tools are already transforming all business processes, from supply chains to client communications. Let’s examine how smart manufacturing planning software has already helped companies around the world.
Take Mars, for example. The confectionery and pet care giant has partnered with Celonis to bring generative AI into its logistics workflows. They use AI to analyze routes, weather, and cargo types. The system consolidates shipments and reroutes deliveries, eliminating potential delays. It results in an 80% reduction in manual order processing, lowering delivery costs.
Meanwhile, Siemens is quietly running some of the most advanced AI-based industrial systems in the world. They embedded AI into its quality control and energy management layers, reducing defects by 15% and cutting energy use across key operations by 20%.
Industrial heavyweight General Electric (GE) targeted equipment wear and tear, a silent profit killer in many manufacturing sectors. Machine learning models detect patterns and early signs of wear, allowing the company to anticipate failures before they occur. The result is a more efficient, cost-effective, and reliable production process, with up to 25% savings on maintenance costs and a 50% reduction in unexpected outages.
No conversation about scale would be complete without Amazon. With over 750,000 mobile robots and thousands of robotic arms deployed across its warehouses, Amazon has already cut order processing costs by 25%. It aims to save $10 billion by 2030 by utilizing automation and manufacturing optimization software.
Launching Digital Transformation in Manufacturing: A Step-by-Step Playbook
Starting digital transformation doesn’t mean rushing to automate everything at once. It means carefully identifying the areas where digital tools can deliver real value right now. The goal isn’t to go digital for the sake of it, but to solve real business problems.
That’s why the process should always start with analysis. You need to understand your pain points, what inefficiencies cost you the most, and where automation could bring the fastest ROI. And if you want to avoid costly mistakes, it’s smart to do this with experienced partners who’ve done it before. Otherwise, digital transformation can easily turn into a budget drain instead of a business win.
Audit and Identify Your Digital Hotspots
Before diving into automation or AI, take a step back and ask: How are things really working right now? Where are your bottlenecks? What still lives in spreadsheets, copied from file to file, just because “that’s how we’ve always done it”?
You need to figure out what is holding you back, what the real price of staying the same is, and whether sticking to old solutions threatens your business. Once you have that clarity, the next step is to identify pain points and digital opportunity zones, areas where AI and automation will bring the most visible impact.
Here’s a snapshot of what that might look like:
| Zone | What’s Happening | How AI/Automation Helps |
| Production | Manual shift planning, delayed quality checks | Fewer defects, real-time analytics, and better forecasting |
| Logistics | Guesswork-based routes, overstocked warehouses | Saves fuel and storage costs, smarter routing |
| HR & Scheduling | Burnout, chaotic shift swaps, and reactive planning | Fairer distribution, improved coverage, less stress |
| Equipment Service | Repairs only after breakdowns | Predictive maintenance, fewer emergency downtimes |
Audit is a crucial part of automating, since it reveals real friction points. If you don’t know what’s broken, you can’t fix the system. A smart audit maps out which tasks drain time, where human error creeps in, and what processes can be redesigned instead of just digitized.
Start Small: Why a Pilot Project Matters
If you want to avoid wasting budget and your team’s goodwill, start with a pilot. It will help you test the waters, so you can see what to change and how to make your team more innovation-friendly.
You don’t need to launch a full-scale service. Just launch a few crucial features. It could be a single production line, one department, or even a process like quality control. The key is to launch it not in simulation but in a real process with actual workload and staff who work with it.
Have a clear goal (e.g., reduce downtime, improve data accuracy), a cross-functional team (production, IT, management), and solid data (no pilot works without clean, structured inputs). Once launched, evaluate the pilot across five key dimensions:
- Operational efficiency (less manual work, fewer delays)
- Process quality (better traceability, fewer reporting errors)
- User adoption (do people actually use it?)
- Financial value (time/materials saved vs. cost)
- Technical reliability (smooth operation, system compatibility)
If the pilot works, you can scale it. If it doesn’t, adjust and iterate. Either way, that’s the fastest and safest option to test a manufacturing resource planning software. Always test an MVP on a small team before adding other features.
Launching a full-scale implementation
The next step is to gradually implement automation across teams. Expand with intention, adapting each solution to the specific needs of every function. Don’t let enthusiasm override logic. Choose the next areas for automation based on real impact:
- Where are the biggest time sinks, paper piles, or material losses?
- Where are employees burning out from repetitive, unclear work?
Use this to build a roadmap of optimization priorities, with business value as your compass. Keep in mind that what worked in one department may need adjustments in others. So, you’ll need to reconfigure the automation tools and manufacturing software for every team to provide the best experience for each member.
Turn people from the pilot team into internal ambassadors. Let them guide new teams, answer doubts, and demonstrate how the system works in real life. People are far more likely to trust their colleagues than a slide deck. Meanwhile, don’t forget about a salary bonus for the ambassadors. No one likes new responsibilities that are not paid for.
Work With Your Team, Not Against Them
Just as we said, you NEED to work WITH your team, showing them how new tools benefit them. If people feel like the system is being forced on them, or worse, that it’s meant to replace them, you’ll face resistance, frustration, and eventually, a turnover. So, to make your automation launch successful, it is essential to collaborate directly with your team, providing them with a solid Learning Management System (LMS).
Don’t just say, “We’re rolling out a new system.” Tell them why you do that and how it will help the team to spend less time on mundane tasks. Show them the benefit, not just the name of the platform.
Invite key team members to take part in early testing, give feedback, and make suggestions. If people feel like co-creators instead of guinea pigs, they’re much more likely to engage. Respect different learning curves. While someone learn new tech-related things fast, others may have excellent soft skills but panic when learning automation tools. Whether it takes a week or three months, that’s okay.
Key Barriers of Manufacturing Automation and How to Overcome Them
As we’ve mentioned, implementing digital solutions is a fundamental shift. Like any change, even the business manufacturing software can meet resistance. Such resistance often comes from fear, uncertainty, and a lack of understanding. People worry about job security, doubt the benefits, or simply feel overwhelmed by new tools and ways of working.
The good news is that with clear communication, proper training, and a human-centered approach, you can turn skepticism into acceptance and even enthusiasm. Digital transformation should feel like an opportunity to make work easier.
Barrier 1: Fear of Change
Let’s be honest, we’re all afraid of being replaced. Movies like Terminator and real stories like Duolingo cutting a bunch of jobs because “AI can do it” only add fuel to the fire. Employees think, “Oh great, another new system. Nobody will explain anything, people will point fingers and yell, and then they’ll say we’re inefficient. And, of course, we’ll be replaced because now ‘the robot will do everything.’ Ugh.”
The truth is, digitalization shouldn’t hit like a lightning bolt from above. People respond better when they understand why this change is happening and that this new thing actually helps them without replacement potential. Your team will also like to test the waters, so it’s better to run pilot options and an MVP, and listen carefully to all of the feedback.
When you do it right, digital transformation stops being a scary AI takeover story and starts being a genuine relief that makes work easier.
Barrier 2: Lack of Digital Skills
There’s always a part of the team that panics even before knowing what exactly will change. Everyone has their own “digital trauma”: the old-school salesperson shakes at the sight of a tablet thinking, “There’s some smart stuff in there, I never learned this, goodbye”; an experienced nurse turns away from a new app thinking, “Wait, is the app replacing people now?”
In manufacturing, it’s similar: an operator might know their machine perfectly but not understand what “enter the data into the system” means. And if the interface is more complicated than an iPhone, full panic mode kicks in.
So you need to start training far before launch, explaining to your team all the system’s peculiarities. Don’t be afraid to pay people from your team to become digital mentors, as non-savvy staff need someone they know, someone from their department, not a weird dude from the IT branch.
Nobody wants to feel stupid. When you help people transition with respect, even the most conservative employees start asking, “Wait, we don’t have to do reports manually anymore?”. After this question, you can be sure that even the biggest tech haters implement new tools into their workflow.
Wrapping up
Digital transformation isn’t just about installing new business manufacturing software or jumping on the AI trend. It’s a deep shift in how your business works. But most importantly, even the best innovations won’t replace people. It frees them up to do more meaningful work.
Corpsoft Solutions isn’t just a dev team. We’re your implementation partner, helping you to launch a manufacturing process analysis, identifying digital hotspots, running real pilot projects, and scaling what works across your entire business. All while adapting to your workflows, your people, and your pace. Digital change doesn’t have to be painful. With the right partner, it becomes clear, safe, and profitable.
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