Tell us about yourself and your role with Accruent.

As Vice President and General Manager of Asset Solutions at Accruent, my primary goal is to ensure our portfolio of products delivers the highest value to our customers. I work alongside my talented team of product managers and solution experts, leveraging innovative processes and strategic market insights to drive success.

My job is to identify high-impact opportunities, validate solutions with customers, and execute initiatives that strengthen product excellence and accelerate growth.

With a passion for optimizing my portfolio by driving product excellence and market expansion, I have led Accruent to target profitable growth zones, revitalized key product lines, and launched initiatives projected to deliver significant value.

What are your predictions for how food and beverage manufacturers will prioritize energy efficiency in 2026?

The food processing industry relies heavily on energy for heating, cooling, and electricity as food moves through the supply chain, consuming around 30% of the world’s available energy. And while companies claim they’ve made measurable progress on energy reduction, major inefficiencies remain. Machines can move out of tolerance, and motors draw more amps than needed. The result isn’t just higher utility bills—it’s a risk to non-perishable inventory when systems can’t adapt to fluctuating conditions.

ESG and sustainability goals will increase within the manufacturing industry, as companies look to preserve revenue, comply with regulations, and uphold brand reputation. In 2026, more companies will prioritize energy usage data with maintenance and asset performance data, so energy changes become part of their workflow, not a separate cost line.

How can manufacturers use AI and IoT to gain visibility into energy usage?

Through IoT sensors and connected devices, facility teams within manufacturing plants can quickly collect data on asset conditions, temperature changes, and energy usage.

By using these real-time analytics, teams can detect changes in energy consumption patterns, such as refrigeration failures or excess energy drawn during production. AI then adds another layer by identifying deeper patterns, predicting anomalies, and helping teams understand why these changes occur, making it easier to assess asset health, production quality, and potential downtimes, so energy spikes aren’t isolated, but rather tied to performance risks. This visibility allows teams to make more informed decisions about operations, maintenance, and potential upgrades needed.

How can asset management systems automatically balance energy savings with meeting quality goals?

In the competitive landscape of the food and beverage industry, product quality is key, influencing brand reputation, consumer safety, and compliance. Yet achieving production quality is not achieved in isolation, but instead in a system where companies can identify and mitigate potential quality issues before they can escalate.

That said, while IoT devices can detect real-time conditions and fluctuations in energy usage, asset management systems that are tightly integrated and connected to these devices can leverage that data before production quality is negatively impacted.  

For example, by embedding energy data into maintenance workflows, the system can automatically trigger corrective actions when an asset is consuming more energy than normal due to wear or misalignment—issues that may not yet affect output but could soon compromise quality if not acted on quickly enough. These insights and recommended actions ensure teams intervene before production is impacted, preventing a trade-off between energy efficiency and product quality.

What tools can teams use to reduce downtime and anticipate issues before critical failures cause spoilage or product waste?

Downtime is not an option for food and beverage production. Companies are squeezed for costs, under immense pressure to deliver on time, all while ensuring production quality is up to par.

By running preventive and predictive maintenance so that equipment issues or high-energy anomalies are caught early, IoT-driven work orders can be automatically triggered before any quality or throughput failures occur. For example, if a refrigeration system fails and temperatures begin to drop slowly inside cold rooms, perishables like dairy, seafood, or fresh produce could drift out of a safe temperature range and cause waste, spoilage, and ultimately costs. This is especially detrimental, as 40 million tons of wasted food was generated in 2019 from the food and beverage manufacturing and processing sectors - underscoring the severity of equipment failures.

Using tools like enterprise asset management systems (EAM), manufacturers can significantly reduce downtime by automating scheduled routine maintenance and anticipating issues before critical faults. This can save companies up to millions, while also helping them to comply with regulations and avoid facing backlash for recalled products.

How do you see energy optimization becoming a competitive differentiator for food and beverage manufacturers in the next year?

Energy efficiency will ultimately shift from a “nice to have” to a competitive enabler and risk mitigator in the F&B manufacturing space. Using IoT and asset management systems, manufacturers can build resilience with more predictable production strategies, fewer shutdowns from equipment failures, and lower regulatory risk.

Externally, F&B producers who can credibly claim a lower carbon footprint will build more appeal for customers and partners. Internally, energy efficiency becomes a differentiator for capital allocation: instead of simply buying new capacity, manufacturers investing in smarter asset management, IoT, predictive maintenance, will enable existing lines to run smoother and cheaper. With industry volatility, rising costs, and stricter regulations, it will be imperative for companies to stay competitive in ESG and production success.
 

The content & opinions in this article are the author’s and do not necessarily represent the views of ManufacturingTomorrow

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