Improved Profitability

Cost-effectiveness of each program can be improved through predictive analytics with the net effect of the actionable insights: of who to target with what incentive.

Utilities can re-purpose their existing data and leverage external data to improve business results across multiple dimensions. A recent research report suggests that predictive analytics can yield a return on investment of nearly 11x.

Res-Intel can reduce Demand Side Management Program (DSM) costs and increase energy efficiency savings through the modification of consumer demand for energy through various methods such as financial incentives and education.

Cost Effectiveness of Different Energy Programs
Cost Effectiveness of Different Energy Programs

Furthermore, Res-Intel moves utilities away from project-level analytics, a major barrier to better utility information use. “One-off” project-level analytics are also more expensive.

Res-Intel provides economies of scale by offering predictive analytics and business intelligence that can be used across the enterprise and re-used over time.

Res-Intel offers DSM program planners and staff two critical data points for each household in a service territory: who to target, and what program to target them with.

These are the most valuable actionable insights to increase the cost-effectiveness of DSM programs.

Note that under “Business as Usual (BAU)” conditions 5 programs didn’t meet the total resource cost-effectiveness test, yet with Res-Intel’s analytics these programs are able to show increased value and meet the critical 1.0 hurdle for cost-effectiveness.