Analysis of Security Risks Brought by Digital Transformation and How to Address Them

Analysis of Security Risks Brought by Digital Transformation and How to Address Them

by Industrial IoT

Digital transformation is now reaching every area of industry. Manufacturing companies are connecting their machines, systems, and departments to increase efficiency, reduce costs, and gain better control over production. However, every new connection also introduces new security risks. And if these risks are underestimated, a single incident can be enough to cause a data breach, disrupt production, and cost the company tens of thousands of euros — along with the trust of its customers.

Why Is Security So Important in Digital Transformation?

The shift from paper-based processes to digital ones means that a company begins to generate and store exponentially more data. At the same time, this data starts flowing between different systems — and every such connection becomes a potential point of attack. Since digital transformation connects the world of IT (information technology) with the world of OT (operational technology), it creates a complex environment where the failure of a single component can impact the entire production process.

What Threatens Companies That Neglect Security?

  • ⚠️ Leakage or loss of sensitive data (customer information, production know-how)
  • ⚠️ Virus or ransomware attacks leading to operational paralysis
  • ⚠️ Production shutdowns and financial losses
  • ⚠️ Damage to reputation and loss of trust from business partners
  • ⚠️ In extreme cases, even emergency situations impacting human safety

What Are the Most Common Security Risks in Digital Transformation?

❌ Connecting outdated systems to the network

Digitalization often begins by connecting old devices to the network to collect data. However, legacy PLCs, computers running Windows XP, or unsupported applications pose a major risk. They lack security updates, don’t support modern encryption, and often operate on outdated communication protocols.

In practice, this means that even a single such element can serve as an open gateway to the entire network. Therefore, every connection of an older system should undergo a security assessment by the IT department, or the entire system should be migrated or modernized to meet current standards.

❌ Direct connection of machines to the internet

It is common practice for machine manufacturers to enable remote diagnostics so that their technicians can quickly resolve malfunctions or update the system’s software. The problem arises when such connections are established without the knowledge of the IT department. This creates so-called “backdoors” through which anyone—whether accidentally or intentionally—can access the system.

If remote access is necessary, it should always be time-limited, encrypted, monitored, and performed only with IT’s approval.

❌ Unsecured Data Transfer to the Cloud

As part of digitalization, cloud services are increasingly used for data collection and visualization. However, the customer (in this case, the manufacturing company) does not always know where their data is being sent or how it is protected. If communication is not encrypted, or if a shared account with a simple password is used, the data may become publicly accessible.

It is equally risky when a supplier operates the cloud outside the EU without informing the customer. Every cloud solution should therefore include encrypted communication (HTTPS, VPN), individual user access, and clearly defined data ownership and server location. Without these measures, the company risks losing control over information that may be strategically sensitive.

❌ Outdated Firmware and Software

Many companies postpone updates with the argument that “the system works fine, so there’s no need to touch it.” However, outdated software and firmware are among the most common entry points for cyberattacks. Older versions often contain known vulnerabilities that are publicly available online. Attackers actively search for and exploit these weaknesses without needing physical access to the system.

The solution? Implement a regular update management process, ideally within a test environment to verify compatibility before deployment. Modern platforms such as Ignition allow fast, seamless updates without downtime — often completed within just a few minutes.

❌ Weak Access Management

Shared accounts, simple passwords, and the lack of login records are still common in many organizations. When an incident occurs, it’s often impossible to determine who made a specific change and when. In addition to the risk of unauthorized access, this also makes post-incident analysis and remediation much more difficult.

Modern systems should therefore use centralized identity management (e.g., Active Directory, SAML, OAuth, OIDC), two-factor authentication, and detailed logging of all user actions. The fundamental principle should be “least privilege” — every user has access only to what they truly need to perform their role.

❌ Insufficient Collaboration Between IT and OT

IT and OT are two very different worlds. The IT department protects the company’s network, servers, and data — their top priority is data confidentiality. OT (operational technology), on the other hand, ensures the smooth running of production, where the main priority is system availability. Without proper communication between the two, a gap emerges — one that attackers are quick to exploit.

IT teams often lack understanding of industrial protocols and production logic, while OT teams are not always familiar with cybersecurity principles. The key is to establish a shared framework of security policies, ensuring that IT and OT collaborate already at the design stage of digital solutions, not only when incidents occur.

❌ Human Factor

No firewall or antivirus can prevent human negligence. Clicking on a phishing email, sharing login credentials, or being inattentive while working with a system — these are among the most common causes of cybersecurity incidents. Attackers today use sophisticated social engineering techniques and often target maintenance staff or system administrators directly.

That’s why regular training and awareness programs are just as important as technical safeguards. Every employee should know how to recognize suspicious communication, handle passwords securely, and report unusual or potentially harmful activity to the right person.

How to Prevent Security Risks?

✅ Security as Part of Every Project

Cybersecurity should never be treated as a separate chapter that comes only after a project is completed. On the contrary, every digital project should include a security analysis from the very beginning. Customers should require their supplier to provide a system interconnection diagram detailing interfaces and communication protocols. This allows the IT department to evaluate the security of the solution before deployment, not after an incident occurs.

✅ Regular Updates and Continuous Monitoring

Every system should be continuously monitored and regularly updated. It’s important to track not only server status, but also the availability of connected devices, firmware versions, and communication changes. For example, Ignition allows a quick update to the latest version without downtime — the system can be updated and secured within minutes.

✅ Access Rights Management

No generic usernames, passwords, or shared accounts. Each user should have their own account with clearly defined permissions, following the “least privilege” principle — access only to what is absolutely necessary. Ideally, identity management should be centralized (e.g., Active Directory, LDAP) to ensure full traceability of who accessed the system and when.

✅ Training and Awareness

Security is not only about technology — it’s mainly about people. Employees should understand the basics of cyber hygiene and know what to do in case of an incident. Equally important is to train IT teams in the field of OT, so they understand the specifics of industrial technologies and can respond appropriately to differing priorities (AIC vs. CIA model). All types of software, interfaces, and communication protocols should be evaluated and approved before being deployed.

Case Study: The Cyberattack That Halted Production at Jaguar Land Rover

At the end of August 2025, automotive manufacturer Jaguar Land Rover faced a massive cyberattack that disrupted its production facilities worldwide — including the plant in Nitra, Slovakia. For safety reasons, the company had to immediately shut down several internal IT systems, including those directly controlling production.

The result was a complete production stoppage and subsequent delays in vehicle deliveries across the entire supply chain. In addition to the production downtime, a data breach was also reported, turning the incident into a complex crisis — technical, logistical, and reputational.

Although the exact causes of the attack were not publicly disclosed, the case clearly demonstrated how fragile interconnected digital infrastructures can be. A single unprotected interface, missing update, or weak access point can have global consequences.

This event serves as a warning for every industrial enterprise undergoing digital transformation. Cybersecurity is not an add-on to digital transformation — it is an essential part of it. For digitalization to truly deliver value, it must be secure. Companies that address security from the very beginning not only minimize the risk of incidents but also strengthen trust among their customers and partners.

Comprehensive Tailor-Made Solution from IoT Industries

If you are planning to digitalize your production, think about security from the very first step. At IoT Industries, we help you not only with implementation but also with security analysis, infrastructure design, team training, and long-term system monitoring — ensuring your digital transformation is both efficient and resilient.

Why Choose IoT/IIoT Implementation with IoT Industries?

Traditional companies typically specialize in OT (operational technologies, such as production lines and devices) or classic enterprise IT systems. However, we are able to connect both of these worlds. Our unique expertise in integrating OT and IT allows us to deliver innovative solutions in digital transformation, enhancing efficiency, reliability, and competitiveness for manufacturing companies.

Priemyselný internet vecí (IIoT) ako kľúč k digitálnej transformácii výroby | Industrial Internet of Things (IIoT) as the key to the digital transformation of manufacturing

Industrial Internet of Things (IIoT) — The Key to Digital Transformation in Manufacturing

by Industrial IoT

The manufacturing industry is undergoing a revolution — one that is undeniably driven by the Industrial Internet of Things (IIoT). Its role is to connect sensors, devices, applications, and network components into a single intelligent ecosystem. The result is a production environment that is not only more efficient and flexible, but also safer and more competitive.

Priemyselný internet vecí (IIoT) ako kľúč k digitálnej transformácii výroby | Industrial Internet of Things (IIoT) as the key to the digital transformation of manufacturing

What Is the Industrial Internet of Things (IIoT)?

The Industrial Internet of Things (IIoT) builds upon the concept of the Internet of Things (IoT), familiar from everyday life — such as smart homes or wearable devices. However, in an industrial setting, it operates on a much larger scale, with significantly higher demands. The key differences lie in the volume of data, as well as its accuracy, processing speed, and security.

IIoT represents an ecosystem of sensors, devices, applications, and network components that continuously communicate with one another. Data from these elements is collected, transmitted, analyzed, and evaluated in real time, providing immediate, actionable insights for managing production, maintenance, logistics, and energy. This gives companies complete control over every aspect of their operations.

The goal of such a system is not merely to “see more data.” Its true value lies in enabling businesses to monitor critical parts of production, prevent unplanned breakdowns and downtime, and optimize the use of materials, workforce, and equipment. All of this leads to higher productivity and lower costs.

The IIoT Cycle in Practice — 4 Steps to Success

The essence of IIoT can be summarized in a cyclical four-step process. The first three steps form the foundation, but the true value emerges in the fourth, when data is transformed into concrete actions. This process continuously repeats itself — and it’s precisely this ongoing cycle that makes the Industrial Internet of Things not just a technological solution, but also a powerful tool for continuous optimization and innovation.

1. Selection and Deployment of IIoT Sensors

The Industrial Internet of Things (IIoT) begins at the production floor level. Modern sensors today can monitor a wide range of parameters, such as:

  • Vibration and temperature (bearing, motor, and gearbox conditions)
  • Energy consumption (electricity, gas, water, compressed air)
  • Environmental factors (humidity, dust, CO₂ levels)
  • Quality output (optical sensors, camera systems)
  • Process parameters (pressure, flow rate, speed, torque)
  • Movement and position (pallets, products, AGVs, or robots)
  • Safety and maintenance (oil levels, cycle counts, gas leaks, fire risks)

Choosing the right sensors is the cornerstone of a successful IIoT implementation. It determines the quality of collected data—and therefore the accuracy of analysis and effectiveness of all subsequent actions.

2. Connectivity and Data Collection

Sensors must be able to communicate securely with one another. The Industrial Internet of Things (IIoT) relies on protocols such as OPC UA, MQTT, and Modbus to ensure that data flows reliably to higher-level systems. At this stage, security plays a crucial role — encrypted communication, network segmentation, and access control help protect sensitive production data from leaks or misuse.

The result is a unified and reliable data stream across the entire production environment — replacing isolated, inconsistent, and fragmented information silos.

3. Monitoring, Analysis, and Data Evaluation

Collecting data alone is not enough — it must be processed and interpreted to turn raw numbers into actionable insights. In this phase, several key functions come into play:

  • Visualization (clear dashboards in SCADA, MES, or BI systems)
  • Trend analysis (identifying deviations and long-term patterns)
  • Automated alerts (notifications for anomalies or unexpected changes)
  • Prediction and modeling (forecasting future developments)
  • Reporting (tailored outputs for operators, management, and auditors)

Through these steps, data is transformed from complex figures into practical tools that help manage production faster, more accurately, and more efficiently.

4. Action and Implementation

The fourth and most important step is transforming data into concrete actions that have a direct impact on production operations and the company’s overall performance. The outcomes can include:

  • ✅ Higher productivity (automated production control, more efficient use of resources, and minimized downtime)
  • ✅ Lower costs (optimized use of materials, labor, equipment efficiency, maintenance, and energy consumption)
  • ✅ Better decision-making (real-time, accurate data that reduces the risk of poor decisions)
  • ✅ Continuous IIoT development (adding new sensors, expanding reports, analyses, and notifications based on company needs)

However, the IIoT cycle doesn’t end here — quite the opposite. It loops back to the first step, enabling continuous improvement and innovation in production processes.

Integrating IIoT with Other Systems

As you can see, the Industrial Internet of Things (IIoT) is not just about passive data monitoring — it enables active, real-time improvement of production and creates the foundation for long-term optimization. While IIoT can function as an independent ecosystem, it becomes even more powerful when integrated with other — even existing — systems such as:

  • MES for digitalizing production processes
  • SCADA for monitoring and controlling production equipment
  • OEE for measuring equipment efficiency
  • CMMS for predictive maintenance management
  • EMS/BMS for tracking energy consumption and managing building operations
  • BI for advanced data processing and reporting

In this way, an integrated Industry 4.0 ecosystem can emerge — one that connects technologies, people, and processes into a single, intelligent environment.

The Industrial Internet of Things is not merely a technological trend — it is the essential foundation of modern manufacturing. Companies that implement IIoT gain not only higher efficiency but also the ability to respond faster to market demands, minimize losses, and maintain long-term competitiveness.

Comprehensive Tailor-Made Solution from IoT Industries

At IoT Industries, we’ll support you through the complete implementation of IIoT — from system architecture design, integration with SCADA, MES, OEE, CMMS, and EMS/BMS, all the way to creating custom BI dashboards tailored to your operations. Contact us to discover how the Industrial Internet of Things can transform your business and drive your digital future.

Why Choose IoT/IIoT Implementation with IoT Industries?

Traditional companies typically specialize in OT (operational technologies, such as production lines and devices) or classic enterprise IT systems. However, we are able to connect both of these worlds. Our unique expertise in integrating OT and IT allows us to deliver innovative solutions in digital transformation, enhancing efficiency, reliability, and competitiveness for manufacturing companies.

Electrical Management System (EMS) | Ako získať kontrolu nad spotrebou elektriny vo vašej firme | How to Gain Control Over Electricity Consumption in Your Company

Electrical Management System | How to Gain Control Over Electricity Consumption in Your Company

by Industrial IoT

Today, most companies are aware that electricity costs increasingly impact their profitability and competitiveness. Yet many still operate without systems that would allow them to monitor, analyze, and optimize electricity consumption in real time. The solution may be an EMS – Electrical Management System, which brings companies transparency, automation, and measurable savings.

Electrical Management System (EMS) | Ako získať kontrolu nad spotrebou elektriny vo vašej firme | How to Gain Control Over Electricity Consumption in Your Company

What is EMS (Electrical Management System)?

EMS – Electrical Management System is a system designed for detailed monitoring, analysis, and control of electricity consumption in production halls or office buildings. It collects data from electricity meters, transformers, switchboards, or directly from devices, providing an accurate picture of when, where, and why energy is being lost—and how it can be used more efficiently.

Electrical Management System vs. Energy Management System

When discussing energy efficiency and automation, it’s important to distinguish what EMS actually refers to, as the acronym can mean two different levels:

  • Electrical Management System focuses specifically on monitoring and managing electricity consumption. It tracks voltage, current, outages, demand peaks, and enables optimization of electrical equipment and switchboard operation.
  • Energy Management System is a broader concept that monitors and evaluates the consumption of all energy media—including electricity, gas, water, heat, compressed air, and steam.

This article focuses primarily on the Electrical Management System, since in production and technology operations, electricity is often the most significant cost and the most critical part of the infrastructure.

What Problems Do Companies Face Without EMS?

❌ Without a modern EMS, companies often rely on outdated data that only arrives on the end-of-month bill, making it impossible to respond in time to sudden consumption changes or unexpected cost increases.

❌ Energy monitoring is mostly manual—entering meter values into spreadsheets or taking photos. This method is time-consuming, error-prone, and does not allow for ongoing evaluation.

❌ Equipment often runs during weekends, holidays, or shutdowns. Without automation, systems remain active even when unused—leading to major energy losses simply because the system can’t respond to changes in operational status.

❌ There’s no integration between systems, so managers must log into multiple apps to piece together the big picture. This delays decision-making and increases the risk of mistakes.

❌ Companies without EMS cannot effectively evaluate their carbon footprint or track ESG (Environmental, Social, Governance) performance—both increasingly important for reputation and business relations.

❌ Accurate allocation of energy costs between departments, lines, or tenants fails. This leads to internal confusion and unnecessary conflicts that hinder planning and responsible resource management.

How Does EMS Work in Practice?

A modern EMS acts as the brain of energy management. It collects data from sensors, meters, switchboards, and PLC units. All data is then visualized in clear dashboards (e.g., using the Ignition platform), enabling analysis by object, department, production line, or time period.

But EMS is not just a passive monitoring tool. It can alert you in real time to limit breaches, faults, or unusual fluctuations, and it can actively control equipment operations based on predefined rules or live data—such as automatically switching off lights during inactivity or lowering heating on weekends.

Thanks to automated cost allocation across operations, EMS saves time, increases accuracy, and simplifies planning. The collected data is immediately usable for decision-making. Management can respond in real time, identify the root causes of issues, and take action that truly impacts cost and performance.

Importantly, this is not a one-time process. EMS should function as a system of continuous improvement. Through repeated data evaluation, rule adjustments, and automation fine-tuning, its efficiency can be gradually increased. This approach enables companies to optimize consumption, reduce waste, and achieve higher sustainability and economic efficiency.

Why Is EMS Implementation Worth It?

✅ EMS allows companies to immediately reduce costs—not only by identifying unnecessary usage, but also by optimizing demand peaks and inefficient equipment operation.

✅ Managers no longer rely on estimates or outdated reports—they make decisions based on accurate, real-time data. With EMS integrated with all key systems, all data is centralized, accelerating decisions.

✅ EMS can autonomously control device operations based on set schedules or real-time conditions. This reduces manual intervention and lowers costs without compromising operations.

✅ From a sustainability and ESG perspective, EMS is an invaluable tool. It provides accurate, trustworthy data for reporting on carbon footprint, environmental goals, and legal compliance.

✅ EMS offers detailed consumption monitoring down to individual devices, lines, departments, or rented spaces, significantly simplifying internal billing and financial planning.

✅ EMS significantly enhances operational safety. It can detect faults or grid overloads early, helping to prevent breakdowns, serious damage, and unnecessary expenses.

✅ Finally, a modern EMS system is essential for meeting ISO 50001 requirements. This certification confirms that the company actively manages its energy efficiency and reduces environmental impact.

A Comprehensive Tailored Solution from IoT Industries

Want to gain control over electricity consumption in your company?

Contact us. Together, we’ll design a modern, tailored EMS solution that gives you a clear view of where your energy is being wasted—and concrete steps to turn those losses into savings.

Why Choose IoT/IIoT Implementation with IoT Industries?

Traditional companies typically specialize in OT (operational technologies, such as production lines and devices) or classic enterprise IT systems. However, we are able to connect both of these worlds. Our unique expertise in integrating OT and IT allows us to deliver innovative solutions in digital transformation, enhancing efficiency, reliability, and competitiveness for manufacturing companies.

Výpočet produktivity práce | Ako merať to, čo reálne ovplyvňuje výkon vašej výroby? | Calculating Labor Productivity | How to Measure What Truly Impacts Your Production Performance?

Calculating Labor Productivity | How to Measure What Really Impacts the Performance of Your Production?

by Industrial IoT

In our previous article, we showed why many companies live under the impression that their production is running at full capacity. Machines are running, people are working, orders are being fulfilled. But underneath, there are often downtimes, underused capacities, and small inefficiencies that add up to reduce both efficiency and profitability. Without accurately measuring performance, it’s impossible to identify or eliminate these losses. And that’s exactly where calculating labor productivity comes in—not as a formal obligation, but as a tool that helps you make better, data-driven decisions.

Výpočet produktivity práce | Ako merať to, čo reálne ovplyvňuje výkon vašej výroby? | Calculating Labor Productivity | How to Measure What Truly Impacts Your Production Performance?

Why Do You Need to Calculate Labor Productivity?

Labor productivity is one of the key indicators that reveals the ratio between inputs and outputs—that is, between what a company puts into production and what it gets out. Calculating labor productivity enables you to compare the actual performance of individual workers, machines, production lines, work shifts, or entire departments. Without this overview, it’s impossible to identify weak points, set realistic goals, or evaluate the effectiveness of implemented changes.

What Does Labor Productivity Calculation Look Like?

Labor productivity can be measured in various ways, depending on the measurement goal, production type, and level of detail desired. The formula for calculating labor productivity must always be based on what you consider a relevant output (e.g., number of units produced / value added / machine performance) and which inputs you want to track (time / labor / technologies). Only then will the result provide relevant and comparable information with real value.

1️⃣ Labor Productivity per Worker or per Hour Worked

The simplest way to calculate labor productivity is to compare output with input. In practice, this might mean dividing the number of units produced by the number of workers or hours worked.

Example:

If five workers produce 2,000 units in an eight-hour shift:

Productivity per worker = Units produced / Number of workers

= 2,000 units / 5 workers = 400 units per worker

You can also calculate productivity per hour:

Productivity per hour = Units produced / Total hours worked

= 2,000 units / (5 workers × 8 hours) = 2,000 / 40 person-hours = 50 units per hour


This type of productivity calculation is more suitable for basic comparisons, especially in labor-intensive production where the human factor dominates. A drawback is that it doesn’t take into account technological factors, quality losses, or the efficiency of the machines themselves.

2️⃣ GDP per Employee or per Hour Worked

At the macro level, two indicators are commonly used: GDP per employee and GDP per hour worked. Both express the economic value created by one worker, but each takes a slightly different angle.

GDP per employee shows how much value, on average, one employee creates over a given period. It’s a widely recognized metric used for comparing countries, sectors, or regions, but can also be applied within a company.

Example:

If a company creates added value of €3,000,000 per year and employs 60 people:

GDP per employee = Gross Domestic Product / Number of employees

= €3,000,000 / 60 employees = €50,000 per employee annually

For a more precise view, GDP per hour worked is better. It accounts for part-time contracts, vacation, and inefficiently used time, providing a more accurate reflection of actual work performance.

Example:

If employees worked a total of 96,000 hours in the same company:

GDP per hour worked = Gross Domestic Product / Total hours worked

= €3,000,000 / 96,000 hours = €31.25 per hour

3️⃣ Machine Utilization Efficiency – OEE

In industrial production, it’s not enough to track only what people produce. It’s equally important to know how well machine capacities are utilized. That’s what OEE (Overall Equipment Effectiveness) is for.

OEE is calculated as the product of three factors: availability, performance, and quality. Each one represents a potential source of losses.

  • Availability shows how much of the planned time the machine actually ran.
  • Performance compares the real operating speed of the machine with its ideal cycle time.
  • Quality expresses the proportion of defect-free units to total output.

Each factor is expressed as a percentage, and multiplying them gives a percentage indicating how much of the machine’s full potential is being used.

Example:

A machine should run for 8 hours per day (480 minutes). During the day, it was down for 30 minutes.

Availability = Actual run time / Planned production time

= (480 min. – 30 min. downtime) / 480 min. = 93.75%

 

If the machine produced 900 units in 450 minutes, with an ideal capacity of 2 units per minute (i.e., 900 units in 450 minutes = ideal), then:

Performance = Actual units produced / Ideal units

= 900 pieces / (450 min. / 0.5 min. (ideal cycle time)) = 900 / 900 = 100%

 

If 870 out of those 900 units were defect-free:

Quality = Good units / Total units

= 870 good pieces / 900 total pieces = 96.67%

 

OEE = Availability × Performance × Quality

= 93.75% × 100% × 96.67% = 90.6%

This means the machine is using 90.6% of its maximum potential. In industrial practice, OEE above 85% is considered excellent. A lower value is a clear signal that there are losses—whether due to downtime, reduced speed, or quality issues.

OEE is considered one of the most comprehensive and practical indicators of productivity in manufacturing. Unlike macroeconomic indicators, it can be measured in real time, in a specific production segment, on a specific machine. It allows companies not only to track performance over time, but more importantly, to identify the exact causes of losses and assign precise goals for elimination.

What Next?

As you can see, calculating labor productivity isn’t about one universal formula. It’s a set of indicators a company must choose depending on what it wants to monitor and improve. For some, labor productivity per worker is key; for others, machine utilization efficiency is the priority. But the most important thing is that these calculations must be based on accurate and current data.

If you don’t have a reliable data collection system in place, you might be able to calculate productivity, but the result will be more of a guess than a fact. That’s why it’s beneficial to connect productivity calculations with tools that ensure automated data collection and real-time evaluation, such as SCADA or MES systems. This gives you not only accurate calculations, but also the ability to monitor productivity trends, identify hidden patterns, and make data-based decisions.

At the end of the day, it’s not just about knowing the formula for calculating labor productivity, but about being able to work with that data. The calculation only makes sense if you can evaluate it, compare it with your goals, and turn it into concrete measures to improve productivity.

A Comprehensive Tailored Solution from IoT Industries

Calculating labor productivity is not a goal in itself. It’s a tool that helps you uncover weak spots, assess the impact of changes, and continuously improve performance—without having to invest in expanding capacity. Instead, you learn how to fully utilize what you already have.

At IoT Industries, we’ll help you build a complete system—from automated machine data collection, through calculations of indicators like OEE, to clear real-time visualizations. Don’t hesitate to contact us. Together, we’ll identify your biggest opportunities for improvement and show you how to make the most of them.

Why Choose IoT/IIoT Implementation with IoT Industries?

Traditional companies typically specialize in OT (operational technologies, such as production lines and devices) or classic enterprise IT systems. However, we are able to connect both of these worlds. Our unique expertise in integrating OT and IT allows us to deliver innovative solutions in digital transformation, enhancing efficiency, reliability, and competitiveness for manufacturing companies.

Produktivita práce pod lupou 🔎 Odhaľte skryté straty vo vašej výrobe | Productivity Under the Microscope 🔎 Uncover Hidden Losses in Your Production

Productivity Under the Microscope 🔎 Uncover Hidden Losses in Your Production

by Industrial IoTReporting and Business IntelligenceSCADA/MES

At first glance, everything seems to be working as it should. Machines are running, people are working, orders are being fulfilled. You might feel that you’re already getting the most out of your available capacities—that this is the maximum your operation can deliver. But this is often where the greatest potential lies hidden.

Many companies today operate under the impression that they’re running at full capacity, while in reality, they may be losing tens of percent of their true potential. Losses hidden in minor downtimes, underutilized resources, or inefficient processes often go unnoticed because they aren’t visible at first glance. This is why labor productivity is crucial—not as an abstract concept, but as a concrete metric that shows where real improvements are possible.

Produktivita práce pod lupou 🔎 Odhaľte skryté straty vo vašej výrobe | Productivity Under the Microscope 🔎 Uncover Hidden Losses in Your Production

What is labor productivity and why should you start measuring it?

Labor productivity shows how much value your company can create in a given period. Whether it’s the number of units produced, completed orders, or the volume of services delivered, it always answers the same essential question: What is the output compared to the time, people, and technology required?

That’s why productivity is one of the most important indicators of efficiency. If it’s low, the company must invest more energy, time, and money to achieve the same result, which translates into higher costs, lower competitiveness, and weaker business outcomes. On the other hand, increasing productivity allows you to achieve more with what you already have—without unnecessary investment in new machines or the need to hire more people.

There are various ways to measure productivity. These include metrics such as GDP per employee, GDP per hour worked, output per worker, or machine utilization efficiency (OEE). The right metric depends on the type of production and the goals you aim to achieve.

Since proper measurement is the foundation of all improvement, we’ll cover this topic in more detail in a dedicated article, “How to Calculate Labor Productivity.”

Labor productivity in the EU and Slovakia

Looking at the numbers, Slovakia has long lagged behind the EU average in terms of labor productivity. According to Eurostat, the Slovak economy reaches only about 70 to 80% of the average labor productivity in the EU. This means the average Slovak worker produces less value per hour than their counterpart in Western Europe.

For manufacturing companies, this is not only a warning sign but also a huge opportunity. The productivity gap isn’t necessarily due to a lower quality workforce. More often, it’s the result of insufficient use of technology, a lack of automation, poor production planning, or missing reliable data for decision-making. Simply put, Slovak firms often work more, but achieve less.

Common problems in companies that don’t measure productivity

If a company doesn’t measure labor productivity or relies only on estimates, the same scenario tends to repeat itself. Production may be running, but results don’t match the effort. Everything might look fine on the surface, but beneath that, small inefficiencies accumulate into major losses.

❌ 1. Unclear Downtimes

Without precise measurement, no one knows exactly when and why machines stop, how long downtimes last, or what their real impact is. Planned, unplanned, and short downtimes are accepted as “just part of the job” instead of being systematically reduced or eliminated.

❌ 2. Rapidly Rising Costs Without Clear Cause

Unnecessary waiting, material waste, overproduction, inefficient production cycles, and reduced machine speeds all increase costs, even when no one seems to be doing anything wrong. If these losses aren’t tracked and analyzed, they can’t be identified, quantified, or strategically reduced.

❌ 3. Invisible Quality Losses

Without consistent measurement, only the biggest failures are reported, while smaller but frequent errors during startup or in-process often go unnoticed. These can add up to significant losses. If they aren’t tracked, they won’t be addressed—and remain hidden costs.

❌ 4. Lack of Transparency in Production Processes

If performance, downtimes, and other key data are recorded manually (on paper or in spreadsheets), the outputs are often inaccurate, delayed, and don’t reflect real-time conditions. There’s no clear view of what’s happening on the floor, making it hard to respond quickly. This lack of agility is a serious disadvantage today.

❌ 5. Ineffecient Reporting and Intuition-Based Decisions

Without reliable performance data, decisions are made based on estimates, experience, or gut feeling. The result is often poor planning, unbalanced workloads, unnecessary stress, and ultimately, increased losses.

These problems result in tangible long-term consequences:

  • Lower efficiency
  • Higher operating costs
  • Reduced competitiveness at home and abroad

How to increase productivity without unnecessary investments

The good news is that higher productivity doesn’t necessarily mean buying new machines, hiring more staff, or pushing people to work faster at the cost of quality. In many cases, it’s the opposite. The greatest impact often comes from better use of what you already have. The key is to know where losses arise, why they happen, and how to reduce or eliminate them.

✅ 1. Start by measuring productivity precisely

The foundation of improvement is accurate data. Without measurement, you can’t know where losses occur or how much they impact your performance. In many cases, productivity increases by 10 to 15% immediately after measurement begins—a phenomenon known as the “halo effect,” where people naturally perform better because they know their output is being tracked.

✅ 2. Automate data collection and eliminate manual errors

If you’re still recording downtimes, breakdowns, and other data manually, you’re leaving room for errors and delays. The solution is automated data collection from machines, production lines, and sensors, using IIoT systems or traditional SCADA/MES platforms. These provide real-time, accurate insights into what’s happening in production.

✅ 3. Focus on uncovering hidden losses

Wasted time, frequent interruptions, poor planning—these are common but often overlooked productivity killers. The “Six Big Losses” model helps categorize these losses into availability, performance, and quality. What makes this model powerful isn’t just naming the six main losses, but assigning clear reduction goals to each. Some can be eliminated completely, while others should be minimized.

✅ 4. Optimize production planning

When you have real-time visibility into machine capacities, line status, and resource availability, you can align production with actual demand—avoiding overloads and downtimes. Integrating MES with ERP or BI systems lets you manage production, maintenance, logistics, and inventory as a unified, data-driven process.

✅ 5. Use visualization and clear reporting

Data is only useful when it’s accessible and understandable. Interactive dashboards in tools like Ignition or Power BI give managers and line operators instant insights into production status, performance, and the root causes of downtime. These insights must be available not just at weekly meetings, but in real time and to everyone who needs them.

✅ 6. Make productivity improvement an ongoing effort

A common mistake is to treat productivity improvements as one-time projects. Successful companies know it’s a continuous process. Regular performance reviews, KPI tracking, and strategic adjustments help maintain improvements and adapt quickly to new challenges.

Labor productivity isn’t about making people work more, but about empowering them to work smarter. To reduce downtime, prevent overloads, and make decisions based on real data—not guesses. That’s why measuring productivity isn’t just another metric. It’s a tool for better decisions, sustainable growth, and a stronger operation.

A Custom Solution from IoT Industries

At IoT Industries, we help you gain precise insights into the performance of your machines and processes, uncover hidden losses, and set measurable goals for boosting productivity. We bring experience with automated data collection, SCADA, MES, OEE implementation, and more—so you can make decisions based on facts, not assumptions. Contact us to find out where your biggest improvement opportunities lie—and how to unlock them. Let’s take your production to the next level.

Why Choose IoT/IIoT Implementation with IoT Industries?

Traditional companies typically specialize in OT (operational technologies, such as production lines and devices) or classic enterprise IT systems. However, we are able to connect both of these worlds. Our unique expertise in integrating OT and IT allows us to deliver innovative solutions in digital transformation, enhancing efficiency, reliability, and competitiveness for manufacturing companies.

OEE – Myslíte si, že vaša výroba funguje na 100 %? Možno prichádzate až o 50 % potenciálu! | OEE – Do You Think Your Production Is Running at 100%? You Might Be Losing Up to 50% of Its Potential!

OEE – Do You Think Your Production Is Running at 100%? You Might Be Losing Up to 50% of Its Potential!

by Industrial IoT

In many manufacturing companies, everything seems to be running smoothly at first glance. Machines are running, workers are working, and the production plan appears to be on track. Management believes that the business is operating at 100% simply because they’ve gotten used to calling this their maximum. But the reality can be quite different. Not because something visibly isn’t working, but because no one realizes that it could work much better. The company may have a hidden potential that remains untapped.

OEE – Myslíte si, že vaša výroba funguje na 100 %? Možno prichádzate až o 50 % potenciálu! | OEE – Do You Think Your Production Is Running at 100%? You Might Be Losing Up to 50% of Its Potential!

Today, the winner in manufacturing is not the one with more machines or a larger workforce. The winner is the one who can maximize the use of the resources already available. And that’s exactly the essence of the OEE – Overall Equipment Effectiveness indicator. It’s one of the most important tools for managing production performance, capable of uncovering where a company’s hidden potential lies. More importantly, it enables this potential to be converted into tangible results.

What Is OEE and What Does It Measure?

OEE is a quantitative indicator of a machine’s overall effectiveness. It measures how efficiently a machine actually operates compared to its full potential, by considering three critically important components: availability, performance, and quality.

  • Availability shows how much time the machine was actually producing compared to how much time it was scheduled to produce.
  • Performance indicates whether the machine produced the expected number of units in the actual production time, based on the ideal cycle time.
  • Quality measures the ratio of defect-free products to total output.

Each of these dimensions is expressed as a percentage, and the final OEE value is the product of these three percentages. In practice, this means that even if each individual component is relatively high, the combined effect may still reveal significant losses.

Example:
If a machine had 100% availability (ran for the full 8 hours) and 100% performance (produced the expected number of pieces), but only 50% of the products met quality standards, the resulting OEE would be just 50%.
Because 100% x 100% x 50% = 50%

OEE is also commonly used as a core metric in methodologies such as Downtime Management, Lean Manufacturing, Six Sigma, or Kaizen.

What Does the Final OEE Value Really Tell Us?

OEE acts like a diagnostic tool, similar to a thermometer. It won’t fix the problem by itself but helps identify it. The final OEE value is above all an indicator of where the company has room for improvement.

  • If availability is low, it’s time to analyze downtime.
  • If performance is poor, focus on optimizing production cycles.
  • If quality is lacking, investigate causes of defects.

Many companies assume they’re running at 90–100%, simply because production appears to be moving. But this subjective perception often hides a harsher reality. Real-world data often reveals that OEE is around 50–60%. In some cases, it’s as low as 45%, meaning more than half of the machine’s potential goes unused.
On the other hand, the “World Class” level of OEE is around 85%, which is already exceptional in many sectors. And the gap between these two levels represents a huge improvement opportunity.

It’s easy to “create” perfect numbers – by setting low production targets or ignoring true cycle times. When data is collected manually, it’s not unusual to see inflated values like 97–98%, which reflect a convenient plan, not actual performance.

Sometimes, with a poorly defined goal and only 50% availability, a company can “achieve” an OEE of over 130%. This is obviously methodologically incorrect.
Only if the cycle times reflect the real mechanical capabilities of the equipment and data collection is accurate, can OEE be a reliable indicator.

What Comes After Measuring OEE?

With a well-configured data collection system, the application itself can identify most of the specific reasons for reduced efficiency:

  • Why is the machine not running?
  • How many minutes per day are lost to short stoppages?
  • How often does material run out?
  • Which breakdowns occur most frequently?

All of this can be monitored in real-time and easily evaluated using clear reports. These reports reveal where the biggest losses occur – whether in terms of time or costs – and give management a solid basis for corrective actions.

Just like with IoT solutions, the goal isn’t to collect data. The goal is to act on it. That’s why we use the Six Big Losses model.

The Six Big Losses Model

This model categorizes losses into three groups, each linked to one of the three OEE components:

  1. Availability Losses
    • Unplanned Downtime: machine failures, missing materials, unexpected maintenance
    • Planned Downtime: changeovers, scheduled maintenance, cleaning
  2. Performance Losses
    • Short Stops: brief downtimes typically under one minute
    • Reduced Speed: when a machine runs slower than its optimal rate
  3. Quality Losses
    • Startup Defects: errors during machine warm-up
    • Production Defects: non-conforming products during normal operation

What makes this model powerful is not just naming the six major loss types, but also assigning a specific goal for their elimination.

  • Some losses (e.g., unplanned downtime, short stops, speed losses, process defects) can and should be eliminated entirely.
  • Others (like changeovers or startup errors) can at least be minimized.

This structure helps businesses not only define problems but also set realistic and measurable goals – resulting in a much more systematic improvement process.

six big losses

OEE as a Practical Tool, Not Just a Metric

One of the biggest strengths of OEE is its ability to challenge gut feelings with facts. It replaces assumptions with data, emotions with numbers, and “we think we’re efficient” with measurable reality. It exposes hidden machine capacity, which often remains unused simply because no one is tracking it.

With OEE, performance becomes something that can be measured, managed, and improved. It’s not just a metric – it’s a transformational tool.

✅ OEE Increases by 10–15% Right After Implementation

Simply starting to measure – without any other changes – often leads to a dramatic shift in behavior. It boosts discipline, reduces unnecessary downtime, and makes time usage more efficient. This “halo effect” typically results in an immediate OEE boost of 10 to 15%.
Not because the technology changed – but because awareness did.

✅ A Key Milestone on the Road to Digital Transformation

OEE is also an essential step toward digitalizing production.
It replaces paper forms, messy spreadsheets, and imprecise guesses with automated data collection, instantly available real-time reports, and a whole new level of management insight.

Companies that adopt OEE gain continuous visibility into performance – at the level of specific machines, lines, and operations.

✅ Immediate Response to Any Issue

With OEE, data is no longer a historical snapshot – it becomes a daily decision-making tool.
If management sees that a machine loses an hour each shift due to lack of materials, they can act. Maybe the issue is delayed warehouse communication. By adding a simple feature – such as an automatic alert when material drops below 10% – the downtime can be reduced from 60 minutes to just 5.

Not next week. Not after a meeting. But the next day. That’s the power of real-time data.

✅ A Continuous Optimization Process

OEE isn’t just analysis – it’s action.
Everyone from operators to managers has live access to what’s really happening. They know what changed, what worked, and what needs further adjustment. This transforms improvement from a one-off project to a continuous optimization process, built not on guesses, but on data.

✅ Savings of Tens or Hundreds of Thousands of Euros, ROI Within Months

Perhaps most importantly, OEE increases output without needing new machines.
A 25% OEE improvement across 20 machines can achieve the same output gain as buying five new machines, saving tens to hundreds of thousands of euros.

Thanks to the flexible licensing of Ignition software, the return on investment in OEE is often just a few months to a year. And from that point on, the system pays for itself.

Tailor-made end-to-end solution by IoT Industries

OEE is not just a number. It’s a tool for smarter production management – one that connects data, people, and decisions into a single, efficient system. And that’s exactly what modern manufacturing is about – not just producing, but producing effectively.

At IoT Industries, we’re ready to help you with a complete OEE implementation – from data collection to visualization.
Get in touch with us today.

Why Choose IoT/IIoT Implementation with IoT Industries?

Traditional companies typically specialize in OT (operational technologies, such as production lines and devices) or classic enterprise IT systems. However, we are able to connect both of these worlds. Our unique expertise in integrating OT and IT allows us to deliver innovative solutions in digital transformation, enhancing efficiency, reliability, and competitiveness for manufacturing companies.

Optimalizácia výrobných procesov, ktorá prináša reálne výsledky | Manufacturing Process Optimization That Delivers Real Results

Manufacturing Process Optimization That Delivers Real Results

by Industrial IoTReporting and Business IntelligenceSCADA/MES

Manufacturing is changing faster than ever. A globalized market, fluctuating demand, rising costs, and increasing pressure on lead times and flexibility — all of this means that simply producing is no longer enough. You need to produce efficiently. Every unnecessary step, every underutilized resource, every inaccuracy in planning or maintenance leads to a loss of time, money, resources, reputation — and ultimately competitiveness.

Optimalizácia výrobných procesov, ktorá prináša reálne výsledky | Manufacturing Process Optimization That Delivers Real Results

What is the key to sustainable efficiency? It’s not about pushing people harder or investing in new technologies without a clear strategy. The key is optimizing your manufacturing processes. But this isn’t a one-time project — it’s a systematic approach that constantly identifies bottlenecks, uncovers hidden reserves, and transforms data into tangible improvements in real time. That’s what drives lower costs, higher productivity, and overall better performance across your operations.

Why does manufacturing process optimization often fail?

Many companies have tried to “streamline” production in the past. They’ve modernized machines, adjusted shifts, introduced KPIs… Yet problems persist. Delays continue, costs rise, competitiveness drops. Why?

Because without reliable data, it’s impossible to objectively identify where the problems arise, what causes them, or how to fix them. Optimization efforts often stop at the symptoms — not the root cause.

And that brings us to the most common reason why optimization fails: many manufacturers still work with inaccurate or incomplete data. Data is collected manually, reports arrive late, and the numbers often don’t add up. As a result, decisions are based on guesswork, gut feeling, or outdated templates — not current reality. And without real data, there can be no real optimization.

What does truly effective optimization look like?

Manufacturing process optimization isn’t just about doing things faster or cheaper. It’s a far more strategic and systematic effort. It means understanding the entire value stream — from the moment raw material enters your facility to the final shipping of finished goods. The goal is to identify and eliminate anything that doesn’t add value for the customer. In practice, this includes several key steps:

✅ Gain complete and transparent visibility of your operations in real time. Because only with accurate, up-to-date data can you identify bottlenecks and make decisions based on facts, not assumptions.

✅ Minimize all forms of waste. Whether it’s time, material, machinery, human capital, or energy — any waste represents untapped potential and unnecessary cost.

✅ Optimize planning and production management. Instead of relying on ideal models or historical templates, you need to plan based on current priorities and real capacity — including staff, machines, and materials.

✅ Shift from reactive to predictive and condition-based maintenance. That means using real-time data about the current technical state and performance of machines — not waiting until failures occur.

What role does digital transformation play in this?

Thanks to digital transformation, data is no longer collected manually — it’s gathered automatically, straight from machines, production lines, sensors, and measurement devices. These insights are immediately connected with other systems like ERP, warehouse management, maintenance, or quality control.

The result is a Single Source of Truth (SSOT) — a consistent and reliable data layer that every level of management can trust, from operators to the CEO.

But to make such complex data flows work as one cohesive ecosystem, you need the right tools. This is where modern digital solutions like SCADA, MES, or EMS come into play. These systems together create an interconnected, centralized environment where data can be collected, analyzed, and visualized across the entire production process — in real time, from one place.

With this approach, data is no longer buried in complex tables — it’s transformed into clear, interactive dashboards that instantly show material availability, equipment status, energy consumption, production progress, or deviations from the plan. No more waiting for weekly reports or gathering data from multiple departments — everything is available instantly, in one place.

When efficiency drops, equipment fails, or anomalies occur, management can respond immediately. Manufacturing optimization thus becomes a proactive management tool, not just reactive analysis. Companies can prevent issues before they escalate. And even more importantly, optimization becomes a continuous, data-driven improvement process — not a one-off initiative.

A tailored solution from IoT Industries

At IoT Industries, we believe that real manufacturing process optimization starts with accurate data and well-connected systems. We help manufacturing companies set up their entire data pipeline — from collection to visualization — so they can make smarter, faster, and more confident decisions.

If you want to identify exactly where your losses are and how to turn them into savings and performance gains, we’re here to help. Let’s talk.

Why Choose IoT/IIoT Implementation with IoT Industries?

Traditional companies typically specialize in OT (operational technologies, such as production lines and devices) or classic enterprise IT systems. However, we are able to connect both of these worlds. Our unique expertise in integrating OT and IT allows us to deliver innovative solutions in digital transformation, enhancing efficiency, reliability, and competitiveness for manufacturing companies.

10 dôvodov, prečo je implementácia systémov SCADA a MES kľúčom k úspechu vášho podniku | 10 Reasons Why Implementing SCADA and MES Systems is the Key to Your Business Success

10 Reasons Why Implementing SCADA and MES Systems is the Key to Your Business Success (Part 2)

by Industrial IoTSCADA/MES

In the first part of this article, we discussed the major challenges that manufacturing companies face. The solution to these challenges lies in implementing SCADA and MES systems. These systems enable transparent management and optimization of production processes. While SCADA focuses on monitoring and controlling production equipment, MES is dedicated to production management, planning, tracking efficiency, and ensuring smooth production operations.

10 dôvodov, prečo je implementácia systémov SCADA a MES kľúčom k úspechu vášho podniku | 10 Reasons Why Implementing SCADA and MES Systems is the Key to Your Business Success

➡️ SCADA

SCADA (Supervisory Control and Data Acquisition) serves as the eyes and hands of operators. It provides real-time oversight of manufacturing technology. It primarily communicates with PLC (Programmable Logic Controller) systems, which control individual machines. However, in the IoT environment, SCADA can also communicate directly with sensors via protocols such as MQTT and OPC UA.

✅ Immediate Response to Failures

One of the key advantages of SCADA is its ability to immediately respond to failures, minimizing downtime and reducing production losses. If a machine shuts down unexpectedly, experiences performance drops, or technological deviations (e.g., unacceptable temperatures or pressures), operators can quickly intervene and restore production.

✅ Remote Control of Technology

Another key feature of SCADA is remote control of technology. It allows operators to turn equipment on and off remotely, as well as adjust parameters such as speed, pressure, and temperature directly from their interface without having to be physically present at the machine.

✅ Historical Data Storage for Analysis and Optimization

SCADA also stores historical data, enabling not only retrospective analysis of problems but also long-term improvements in production processes.

❓ When is SCADA (Not) Suitable for a Business?

If a SCADA system were not implemented, operators in smaller plants might be able to manage oversight manually. However, in large-scale enterprises, this would significantly extend response times and cause losses. Additionally, without data collection, it would be impossible to generate accurate reports, further complicating strategic decision-making at the management level.

➡️ MES

While SCADA monitors technological equipment, MES (Manufacturing Execution System) manages the production process itself. It integrates machines, materials, and workers to provide a comprehensive view of the entire production process — from planning and execution to storage. While SCADA collects data at intervals of seconds, MES links them to orders, allowing managers to monitor production status in real-time and respond to deviations immediately.

✅ Digitalization and a Unified Data Source

The MES system replaces paper-based processes with electronic data collection, ensuring that all information is available in real-time and eliminating errors caused by manual data handling.

It allows both automated and manual data entry throughout the entire production process, creating a single source of truth (SSOT). All data is centrally recorded and accessible at every level of management, eliminating delays, inaccuracies, and adjustments caused by manual reporting. Decision-making is based on hard real-time data.

✅ Automated Production Planning

One of the main benefits of MES is automated production planning. The system uses data from ERP (e.g., SAP) to manage manufacturing operations based on orders and available resources, providing a complete real-time overview of production status (WIP – Work in Progress). MES also synchronizes production data with ERP systems, ensuring seamless data exchange between the company and the shop floor without the need for manual intervention.

✅ Efficient Workforce Management

The system ensures that only qualified employees are assigned to production operations. By logging into the MES system, employees verify their credentials, and the system checks whether they meet the requirements for operating a specific machine or performing a particular task. This process eliminates errors caused by unqualified workers and reduces the likelihood of workplace accidents.

✅ Optimization of Resource Utilization

MES provides detailed insights into the use of production resources, whether it be machines, materials, or personnel. It monitors equipment conditions, reports failures, and alerts to potential shortages of materials. If necessary, the system automatically notifies the warehouse to replenish materials before production is disrupted. This approach minimizes downtime and maximizes resource utilization.

✅ Production and Product Traceability

Every manufactured unit or batch is linked to all production data — from raw materials and individual operations to the final product. This system allows for full traceability in the event of a complaint, which is crucial in industries with strict regulations, such as pharmaceuticals and food production.

✅ Quality and Performance Management

MES actively monitors the quality of production processes. It detects deviations from standards and immediately signals them, minimizing the risk of production errors. Quality data can be integrated with external software for Statistical Process Control (SPC) or Laboratory Management Systems (LMS), ensuring even more precise quality management.

The system also calculates OEE (Overall Equipment Effectiveness), identifying production bottlenecks and providing tools for their optimization.

✅ Digitalization of Documentation

MES automates document management, ensuring that workers have access to all necessary information, such as work instructions, technical drawings, and safety guidelines, at the right time. Documentation is available electronically, often via QR codes placed directly on machines, reducing the need for physical documents and increasing operational efficiency.

✅ Efficient Maintenance Management

MES plays a significant role in maintenance management. The system enables preventive maintenance planning, reducing unexpected failures and minimizing costs associated with reactive maintenance. Maintenance staff can log interventions, plan tasks, and monitor equipment status directly in the system.

MES also analyzes historical equipment performance data, allowing businesses to predict potential failures before they occur. In combination with SCADA, businesses can gradually transition to predictive maintenance, leveraging advanced analytical algorithms to detect anomalies and prevent failures before they happen.

❓ When is MES (Not) Suitable for a Business?

Not every business requires all MES system functionalities. While some companies implement only selected modules to address specific issues, industries such as pharmaceuticals or food production (F&B) often require a comprehensive MES system. These sectors must ensure batch traceability, quality control, and strict regulatory compliance, as even the smallest mistake can have serious consequences for consumer health.

Companies that aim to improve efficiency, reduce costs, and increase competitiveness can no longer rely on outdated manual processes and paper-based records. SCADA and MES are not just technologies—they are strategic tools that enable businesses to transition to smart manufacturing, driven by real-time data and automated processes. Are you ready to take the next step?

10 Reasons to Implement SCADA and MES

📌 1. Increased transparency in production processes

📌 2. Faster and more accurate reporting

📌 3. Precise inventory management

📌 4. Immediate response to issues

📌 5. Reduced downtime and prevention of unplanned failures

📌 6. Improved workforce management and error reduction

📌 7. Higher product quality and elimination of production defects

📌 8. Complete traceability and tracking of production processes

📌 9. Increased efficiency, productivity, and optimization of production resources and costs

📌 10. Readiness for Industry 4.0 and future innovations

Why Choose IoT/IIoT Implementation with IoT Industries?

Traditional companies typically specialize in OT (operational technologies, such as production lines and devices) or classic enterprise IT systems. However, we are able to connect both of these worlds. Our unique expertise in integrating OT and IT allows us to deliver innovative solutions in digital transformation, enhancing efficiency, reliability, and competitiveness for manufacturing companies.

10 dôvodov, prečo je implementácia systémov SCADA a MES kľúčom k úspechu vášho podniku | 10 Reasons Why Implementing SCADA and MES Systems is the Key to Your Business Success

10 Reasons Why Implementing SCADA and MES Systems is the Key to Your Business Success (Part 1)

by Industrial IoTSCADA/MES

SCADA and MES systems are key pillars of modern manufacturing companies striving to optimize production processes, increase efficiency, and minimize costs. Despite their advantages, many businesses still rely on outdated manual processes, paper-based records, and inaccurate estimates. To enhance competitiveness and adapt to changing market demands, implementing SCADA and MES is no longer just an option. It is a necessity.

10 dôvodov, prečo je implementácia systémov SCADA a MES kľúčom k úspechu vášho podniku | 10 Reasons Why Implementing SCADA and MES Systems is the Key to Your Business Success

Challenges Faced by Companies Without SCADA and MES

❌ Lack of Transparency in Production Processes

The biggest challenge in such companies is the lack of transparency in production. Without a comprehensive system for monitoring and managing manufacturing, efficiency is often estimated based on manual records, Excel spreadsheets, or inaccurate reports.

However, these data do not reflect the real situation. When companies try to optimize costs or increase production, they lack clear data to pinpoint bottlenecks and identify where the biggest time or financial losses occur.

❌ Inefficient Reporting and Production Tracking

One of the main consequences of a lack of transparency is inefficient reporting. Many companies struggle with slow and inaccurate reporting. Obtaining the necessary data can take days or even weeks. By the time management receives reports, they are often outdated and do not reflect the current state of production. In many cases, reports are distorted or embellished because data is collected manually, making accuracy dependent on subjective reporting from employees.

This issue is particularly evident in tracking work-in-progress. At the end of the month, an ERP system like SAP might record a lower number of produced units than planned. However, the company may struggle to quickly determine whether the products have been manufactured or are still in production. This leads to delays, inefficient planning, and difficulties in meeting deadlines.

A similar issue arises in production planning. If a production plan changes, many companies still rely on printed documents. These must be physically distributed to workers on the shop floor, and changes must be explained in person. This results in unnecessary delays and the risk that some employees may miss critical updates.

❌ Material Tracking and Inventory Management Issues

Another significant challenge is material tracking and inventory management. In many cases, production teams realize they are out of materials only when workers on the production line run out. When an operator reports a material shortage, it often takes hours to resolve the issue. The material must be manually picked from storage, checked, transported to the right location, and prepared for further processing. During this time, production slows down or completely stops, causing downtime and disrupting delivery schedules.

The absence of a digital system also affects the accuracy of material usage. There is no mechanism to ensure that workers use the correct material in the required quantity. Without automated verification, operators may use incorrect components or incorrect dosing, leading to defective products or even damage to machinery.

❌ Delayed Fault Detection and Reactive Maintenance

In large and complex manufacturing facilities, it is impossible to have everything physically monitored at all times. Production often relies on workers noticing a malfunction and contacting maintenance, leading to time losses and unplanned downtime.

Without proactive monitoring, companies cannot detect warning signs before a failure occurs. For example, an increase in oil temperature in a machine may indicate an impending issue. However, if there is no monitoring system in place, maintenance only reacts when an actual failure happens. This approach, known as reactive maintenance, means problems are only addressed after they have already caused disruptions.

Additionally, when a failure occurs, the root cause is often unclear. There are no historical records indicating which parameters were out of range, what actions preceded the failure, and what interventions operators attempted. As a result, companies simply “extinguish the fire” and hope the issue does not recur, rather than preventing it proactively.

❌ Limited Remote Control of Production

Without a SCADA system, controlling production equipment is only possible locally. Operators must be physically present at the machines to make adjustments. If an error occurs or a process is configured incorrectly, there is no way to address the issue remotely, leading to extended response times and costly consequences.

For instance, if a worker misconfigures the routing of a manufactured product, employees must manually transfer materials to the correct location. This causes delays and disrupts production planning. Moreover, many local control panels do not require operator authentication, meaning that if an error occurs, there is no way to trace who was responsible. This lack of accountability prevents targeted prevention measures such as training.

❌ Limitations in Workforce Management

Many companies aim to optimize labor costs, but without accurate data, this becomes extremely challenging. Without an MES system, it is impossible to track individual worker efficiency, evaluate performance, and analyze how much time is spent on specific operations. In most companies, productivity is measured only at the team or department level, making it difficult to identify areas for optimization.

HR records may indicate which employees are trained to operate specific machines, but production equipment itself does not use this information. This means that an unqualified worker may access and operate machinery, increasing the risk of production errors, lowering product quality, and, in the worst cases, leading to workplace accidents.

❌ Lack of Traceability in Production Information

Another critical issue is the lack of traceability in production records. If a product defect is discovered, companies often struggle to determine which other products may have the same issue. There are no detailed records of when the product was manufactured, which machine was used, what settings were applied, or what materials were used.

For example, if a production deviation occurs on a specific machine, the company cannot simply recall the affected batch of 1,500 units. Instead, they must recall all 10,000 products made during the same period as a precaution. This results in significant financial losses and unnecessary waste.

❌ Limitations in Energy Management

Companies may have ambitious plans to implement an Energy Management System (EMS) to monitor energy consumption and reduce operating costs. However, even if energy meters are installed on all machines, their effectiveness is limited without centralized data collection and visualization.

If a company cannot track and analyze this data in real time, the only option is manual regulation—employees would have to physically check and turn off machines that are not in use, which is inefficient and impractical. Energy savings are not just about data collection but also about real-time response and automated interventions, which are impossible without SCADA and MES.

❌ Inability to Implement Advanced Technologies

Without comprehensive data collection and production monitoring, adopting advanced technologies such as artificial intelligence and predictive maintenance is unrealistic.

SCADA and MES systems provide the foundation necessary for expanding production monitoring. For example, predictive maintenance relies on machine learning algorithms to analyze machine vibrations and detect anomalies early. However, this approach is ineffective if the company lacks a basic system to monitor key parameters such as temperature, pressure, and speed.

SCADA and MES as a Solution to Manufacturing Challenges

In this part of the article, we explored the biggest challenges that slow down manufacturing companies and lead to unnecessary costs. In the second part, we will look at specific solutions and show how SCADA and MES systems help optimize production management and reduce losses.

Why Choose IoT/IIoT Implementation with IoT Industries?

Traditional companies typically specialize in OT (operational technologies, such as production lines and devices) or classic enterprise IT systems. However, we are able to connect both of these worlds. Our unique expertise in integrating OT and IT allows us to deliver innovative solutions in digital transformation, enhancing efficiency, reliability, and competitiveness for manufacturing companies.

Premeňte dáta na zisk – Microsoft Power BI mení rozhodovanie vo výrobných podnikoch | Turn Data into Profit – Microsoft Power BI Transforms Decision-Making in Manufacturing Businesses

Turn Data into Profit – Microsoft Power BI Transforms Decision-Making in Manufacturing Businesses

by Industrial IoTReporting and Business Intelligence

In today’s world, managing a company based solely on intuition and experience is no longer enough. Truly successful businesses rely on accurate data that enables them to make quick and informed decisions. However, many manufacturing companies still struggle with manual data collection, delayed and inaccurate reports, and inefficient processes. This costs them money, customers, and a competitive edge. But what if you could have all the essential information visually clear, up-to-date, and accessible with just a few clicks? That’s exactly what Business Intelligence (BI) offers, along with one of the most powerful tools on the market – Microsoft Power BI.

Premeňte dáta na zisk – Microsoft Power BI mení rozhodovanie vo výrobných podnikoch | Turn Data into Profit – Microsoft Power BI Transforms Decision-Making in Manufacturing Businesses

What Are the Most Common Problems Faced by Companies Without Modern Business Intelligence Tools Like Microsoft Power BI?

In most manufacturing companies, data is still collected manually. Workers record information on paper forms, which are then transcribed into spreadsheets at the end of the shift. Reports are generated daily or weekly from these spreadsheets, meaning management receives them with significant delays. Not only can such data be inaccurate or distorted, but if production issues arise, management learns about them too late to take timely action.

Without a unified data source, different departments often have conflicting views on the actual state of production. Sales teams might sell more than production can deliver, or the production team might overproduce, leading to excess inventory that ties up capital and remains unsold. There is no Single Source of Truth (SSOT) to consolidate all data into one system and eliminate inconsistencies between departments.

How Can MS Power BI Solve These Problems?

Power BI is Microsoft’s Business Intelligence tool that transforms raw data into clear, real-time insights and visualizations.

Unlike outdated manual methods, Microsoft Power BI collects, analyzes, and visualizes data automatically. By integrating with other systems such as ERP, SCADA, and MES, company leaders can monitor production performance, order status, and financial indicators at any time without waiting for manual reports. In case of production issues, managers gain instant insight into what happened.

MS Power BI also unifies data from various departments into a single central information source (SSOT). This ensures that everyone works with the same accurate data.

Why Power BI Alone Is Not Enough

Microsoft Power BI is a powerful tool, but the quality of its outputs depends on the quality of the input data. If data is incomplete, inaccurate, or delayed, even the best BI tool cannot enable effective decision-making. That’s why having a well-structured data collection and management system is crucial. This is where systems like SCADA and MES come into play, ensuring the automatic collection of precise data directly from production lines.

Comprehensive Custom Solution from IoT Industries

For Business Intelligence to deliver the desired results, it is essential to connect the right tools with high-quality data sources. IoT Industries offers a comprehensive solution. From setting up data flows and integrating Microsoft Power BI with MES and SCADA systems to creating custom interactive dashboards. The result is a system that provides accurate and up-to-date information necessary for efficient production management.

If you want to take your business decision-making to the next level, contact us. Discover how Power BI, combined with intelligent data collection, can transform your operations!

Why Choose IoT/IIoT Implementation with IoT Industries?

Traditional companies typically specialize in OT (operational technologies, such as production lines and devices) or classic enterprise IT systems. However, we are able to connect both of these worlds. Our unique expertise in integrating OT and IT allows us to deliver innovative solutions in digital transformation, enhancing efficiency, reliability, and competitiveness for manufacturing companies.