This article originally appeared in the July/August 2013 issue of Food Manufacturing.

The Food Manufacturing Brainstorm features industry experts sharing their perspectives on issues critical to the overall food industry marketplace. In this issue, we ask: What steps can food manufacturers take to reduce energy costs?

Think of energy as a variable cost of goods sold rather than a fixed expense: your goal must be to reduce the energy cost of a unit of production. You can achieve this by reducing your per-unit energy demand, finding a cheaper supply of energy (e.g. CHP, fuel cells, solar), or by changing the price you pay for utility energy. With this economic framework in mind, you can use “Predictive Analytics” to develop a fitting energy savings program.

Step 1: Measure energy intensity per unit output. Measure what you wish to manage by monitoring key load points throughout your production process.

Step 2: Design Scenarios. Using energy analytics software, you can run scenarios which vary your production volume/timing, utility tariffs and supply sources to find an optimal mix that minimizes your energy cost per unit. This form of “Predictive Analytics” allows you to determine which energy projects are most economically beneficial to your facility before implementation.

Step 3: Implement. Most companies will want to start small by identifying and implementing demand-side management and pricing changes; these often deliver high return rates on little investment. Firms seeking larger dollar savings will pursue alternative energy supply solutions. Either way, predictive analytics allows you to define the optimal energy program before you invest.

Step 4: Manage. Web-based reports allow you to manage and communicate energy costs in real time, enabling continuous improvement and facilitating training and behavioral change among staff.