A large industrial manufacturer faced rising energy costs, unpredictable demand charges, and limited visibility into real-time power markets. With operations running 24/7, they couldn’t simply cut energy usage, but they needed a smarter way to manage costs without disrupting production.
By leveraging real-time market intelligence, predictive analytics, and automated load optimization, they transformed their energy strategy. They began proactively shifting non-essential loads, optimizing procurement timing, and participating in demand flexibility programs, significantly reducing costs while maintaining full operational efficiency.
As a result, the company saved millions annually by lowering procurement costs, reducing demand charges, and strategically adjusting energy consumption based on market conditions. This case study demonstrates how real-time energy data and AI-driven forecasting can give C&I businesses greater financial control over energy costs.
A large industrial manufacturer was struggling with the unpredictable nature of power markets. Electricity costs were eating into margins, demand charges were unpredictable, and procurement decisions were made without a clear view of market fluctuations. Their operations ran 24/7, meaning they couldn’t simply shut down equipment when prices spiked. Instead, they were left reacting to market changes, often locking in power purchases at the wrong time or running operations through peak pricing periods without alternatives.
The company had no real-time access to wholesale market prices, making it impossible to optimize procurement or hedge against price volatility. Additionally, they weren’t participating in demand flexibility programs, which could have reduced their exposure to high energy prices without affecting operations. Every month, their energy bill arrived with the same frustration—high costs, limited control, and no clear path to improvement.
Working with Arcus Power, the company gained real-time access to power market data, predictive analytics, and automated demand flexibility insights. For the first time, they could see market conditions as they changed, giving their procurement team the ability to make informed decisions instead of reacting to past price trends. By integrating hourly and day-ahead price forecasts, they identified windows where power was significantly cheaper and shifted non-critical energy purchases accordingly.
Beyond procurement, their operations team started using automated price signals to adjust energy usage. Non-essential loads—such as auxiliary systems, HVAC, and batch processing—were scheduled based on market pricing instead of rigid operational schedules. Instead of running these systems at peak hours, they were shifted to low-cost periods, reducing exposure to demand charges while maintaining production efficiency.
By layering AI-driven predictive analytics on top of market data, the company could anticipate price spikes before they happened. This allowed them to develop a proactive cost-minimization strategy, adjusting load distribution based on expected price fluctuations. What had previously been an unpredictable cost center was now an actively managed part of their business strategy.
The impact was immediate. Energy procurement costs dropped as the company leveraged real-time pricing to lock in lower-cost energy at the right moments. Demand charges, which had previously been an unpredictable and uncontrollable expense, were reduced by nearly 20% as peak-hour loads were intelligently shifted. The company also began participating in demand response programs, generating additional revenue by adjusting non-essential loads during grid stress events.
Unlike before, when the manufacturer had no insight into energy price trends, they now had full transparency into market movements, allowing them to plan with confidence. They weren’t just avoiding high prices—they were strategically using price fluctuations to their advantage. What had once been an unavoidable and painful part of their operations was now a controllable, optimized process.
Most commercial and industrial facilities treat energy as a fixed cost. In reality, it’s one of the most flexible areas of financial optimization, but only if companies have the right data and tools. Without real-time market intelligence and predictive analytics, businesses are stuck overpaying for power, running operations through peak price periods, and missing out on demand flexibility incentives. But with the right insights, C&I customers can turn energy markets into a competitive advantage, reducing costs without compromising operations.
If your business is still making energy decisions without real-time data, market forecasts, or automated load optimization, you’re leaving money on the table. It’s time to take a proactive approach. Let’s fix that.
