Adrian Stelmach is the founder and CEO of EXPLITIA.
Today, it would be difficult for any of us to get by without electricity. Electrification, the second industrial revolution, is the foundation for every modern technological revolution.
Because technology is developing so rapidly, energy demand is constantly growing. Today’s modern factories, infrastructure and data centers require enormous amounts of energy to operate reliably.
As demand and availability issues grow, so do energy prices. Businesses are now increasingly looking not only for additional energy sources but also for ways to use existing sources more efficiently.
To manage energy more effectively, business leaders must understand how they actually use it and where it may be generating costs that can be eliminated.
Technologies like energy management systems (EMSs) play an important role in understanding energy costs, but I’ve found that many companies still need guidance for implementing these systems into their workflows.
A Global Cost Crisis Fueled By Growth
Rising energy costs are a global problem. In business, they aren’t limited to the bills that manufacturers pay. Higher utility prices mean higher production costs, which in turn lead to higher prices for the end customer and fuel inflation—a force that ultimately shrinks all of our wallets.
Research conducted by Eurostat shows that the real share of electricity in the cost of manufacturing a product ranges from 3% to as high as 20%. In energy-intensive sectors, energy is a major cost driver. Rising prices weaken competitiveness, particularly against producers in countries with lower energy costs, and can erode already thin margins, limiting further growth and investment.
It is, therefore, not surprising that a 2026 PwC study found that rising energy costs were one of the most serious threats to business operations, alongside rising labor costs and geopolitical tensions.
Despite this, optimizing energy consumption rarely turns out to be an operational priority.
Where Energy Leaks In Factories
While visiting and analyzing many factories, I’ve noticed that energy often escapes in very mundane ways.
Many machines operate in “idle mode.” The equipment consumes electricity when it isn’t actually producing anything, during work breaks or when an operator forgets to turn it off.
Energy consumption is also affected by the condition of equipment and systems, as old or poorly maintained machinery typically uses more electricity.
Inefficient planning similarly prevents cost optimization. Poor organization of changeovers, repairs or downtime can generate unnecessary power consumption spikes and, consequently, increase costs.
Another problem is the failure to adjust the operation of refrigeration or air conditioning equipment to external conditions. If dynamic adjustments aren’t made, we can end up drastically inflating our bills.
EMS And AI In Energy Management
Even when you know where problems lie, how do you properly identify and eliminate them? One way to manage these challenges is with an EMS, which are now often supported by AI.
Based on my experience working with clients, I’ve found that many struggle to get the most of these systems. My company is one of many that offers an EMS, but here’s a step-by-step guide that should apply broadly to overcoming implementation hurdles:
1. Diagnosis: This allows for a comprehensive understanding of the business problem. Analyze the “as-is” situation, identify potential waste. In this way, you can realistically assess whether the investment will yield a satisfactory ROI within a reasonable timeframe.
2. Energy Flow Map: These visualizations (e.g., Sankey diagrams) show how energy actually flows throughout the facility, from the main source, through individual production halls, all the way to specific machines.
3. Prioritization: Identify the points with the highest energy consumption and the greatest potential for optimization. During the pilot phase, the most reliable results can be obtained by selecting machines “in the middle of the pack.” Those that are neither the easiest nor the hardest to meter.
4. Metering And Pilot Phase: Implement industrial energy meters and the system. Based on my evaluation of successful projects, the pilot phase should consume no more than 20% of the planned budget. This buffer will allow you to effectively verify the project assumptions.
5. Providing Production Context: Integrating the EMS with a manufacturing execution system (MES) or similar system provides production context, enabling precise calculation of the actual energy cost per unit produced.
6. Building A Knowledge Base: This step involves collecting historical data that allows you to establish appropriate KPIs and benchmarks to effectively distinguish between normal conditions and anomalies.
7. AI Implementation: AI can enable you to perform root cause analysis and detect anomalies, as well as predict future consumption based on production plans.
8. Optimization And Scaling: Based on the collected analyses, you can implement permanent organizational and process changes, as well as expand metering to other areas of the plant. In this way, you obtain a complete picture and realize the full potential of the implementation.
System Implementation In The Chemical Industry
One of my company’s clients in the chemical industry (where energy costs can account for up to 20% of product manufacturing costs) had a facility that used approximately 200 different types of equipment operating continuously.
An initial analysis indicated that, due to a lack of precise monitoring, the factory was overpaying by an average of about 12% for electricity alone.
The steps above can provide the insights to understand where the losses are coming from. In their case, they found out that many of the machines were running in dry-run mode.
Each stage of the implementation process allowed for a chance to identify bottlenecks and inefficiencies that prevented these costs from being uncovered. Having a real-time view of where energy was being used made it possible to eliminate unnecessary consumption. Inefficient consumption was reduced to zero.
Conclusion
In an era of high energy costs, optimizing energy consumption can prove to be one of the most important investments, providing not only long-term savings but also a crucial competitive advantage.
Getting started with improving these processes doesn’t need to mean a major overhaul. By taking smaller steps, you can achieve significant improvements, gather more data for analysis and effectively eliminate energy waste in factories.
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