It’s official: demand-side measures are faster and cheaper to deploy than new generation.
Utility programs deliver energy savings at a median cost of roughly $20 per megawatt-hour1, and virtual power plants can be operationalized in a matter of months rather than years. As load growth accelerates, these characteristics make demand flexibility especially attractive to utilities facing near-term system constraints.
Yet utilities continue to undervalue the impact of demand response and behind-the-meter technologies into their plans and regulatory filings. Why does confidence in these resources remain lower than those on the supply-side?
In this guide, our goal is to define demand flexibility, discuss why and where it can fall short of its potential, and offer a practical framework for getting more from your demand-side programs, regardless of intervention type.
First: Demand Flexibility, Defined
Instead of focusing only on reducing load during system peaks, many utilities and load-serving entities rely on a range of programs, pricing structures, and customer-facing technologies to shape when electricity is used. This includes shifting consumption to different times, reducing it when the grid is strained, or increasing it when there’s excess supply.
Consider a time-of-use rate designed to shift consumption to non-peak hours, a demand response (DR) program that incentivizes reduced load during system events, or a managed charging program that aligns electric vehicle charging with grid conditions. (In practice, these programs are often managed by independent partners and vendors, even though they may affect the same customers and the same peak hours.)
When utilities use these demand-side resources to adjust electricity consumption in response to grid needs, the industry refers to this as demand flexibility. Similar to generation or storage, this flexibility is treated as a grid asset that helps balance supply and demand while improving system reliability.
Where Demand Flexibility Breaks Down
While 93% of utilities consider demand flexibility a medium-to-high priority and most are actively implementing programs2, many still lack a consistent way to measure and use performance across their portfolios.
Demand-side programs are often represented through assumptions and portfolio estimates that update slowly and are difficult to test against real-world results.
In the decade-plus of our work alongside utility teams, some consistent patterns have emerged that illustrate this measurement and verification gap:
- Program managers launch DR portfolios with strong expectations, then wait months for performance data. In some cases, a utility may not see validated results until well after the final summer event, leaving no opportunity to adjust targeting, customer mix, or expectations during the season itself.
- Planning teams face similar barriers: energy efficiency savings rely on long-standing assumptions; DER impacts are difficult to isolate; DR forecasts frequently diverge from dispatch outcomes. A forecast built on prior-year assumptions may remain unchanged even as participation shifts or customer behavior evolves, leading planners to apply conservative adjustments rather than incorporate actual performance.
- Regulatory teams preparing filings often face inconsistent data from multiple vendors and systems. DR is measured one way, energy efficiency another, and DERs are sometimes left out entirely. Without a shared measurement approach, the same season can yield different savings estimates depending on the program or vendor, making it harder to produce clear, defensible filings that regulators can trust.
If utilities aren’t able to validate results quickly enough, get insights in time to act, or see performance across their full portfolio, even the most well-designed programs risk under-delivering.
Making Demand Flexibility Work: A Practical Framework
Based on work with dozens of utilities and the analysis of over 55 million meters of utility data, we believe these three principles determine whether demand flexibility delivers sustained value.
1. Performance grounded in real-world measurement
Demand-side resources ultimately affect load at the service point, yet programs are often evaluated independently using assumptions that do not reflect how multiple interventions interact at the same location.
Measuring performance at the meter provides a consistent foundation for understanding how electricity use shifts at each premise over time. This service-point view makes intervention stacking visible, revealing the net effect when a single location participates in demand response, installs a heat pump, or enrolls in managed EV charging. Evaluating programs separately risks double counting or missed interactions, while measuring at the meter supports consistent attribution, giving planners a clearer view of true delivered impact.
Example: Using interval meter data across its full customer base, a utility evaluates the load impacts of electrification-related programs, including heat pump incentives, managed electric vehicle charging, and traditional demand response. While enrollment levels appear similar on paper, measured usage shows that these programs affect peak load in very different ways depending on time of day and season.
2. Insights for rapid, continuous improvement
Performance insights are most valuable when they arrive while programs are active and still evolving. When results come back months later, opportunities to refine targeting or adjust strategies have already passed. Faster feedback loops allow utilities to improve programs as they run rather than just evaluate them after the fact, turning measurement into a practical tool for continuous improvement.
Example: For a planning or regulatory filing, a utility brings together measured impacts from a residential energy efficiency program, a commercial demand response portfolio, and a managed electric vehicle charging initiative using the same meter-based methodology. Instead of reconciling separate vendor reports, planners present a single view of how electrification-related load growth and demand-side mitigation interact under peak conditions.
3. Portfolio-wide visibility into demand-side performance
Utilities are responsible for the combined performance of demand response, DERs, and energy efficiency across programs, vendors, and customer segments. That responsibility requires more than individual program reports; it requires a comprehensive, shared view of demand-side results using consistent methods.
When performance is visible at the portfolio level, utilities can better coordinate programs and understand tradeoffs. They can use demand-side resources more effectively in planning and operations.
Example: As a utility prepares its plan for the following year, it compares the impacts of a residential energy efficiency program, a commercial battery incentive, and a corporate electric vehicle charging initiative using different assumptions. Without a shared measurement approach, the team struggles to determine which investments should be expanded or scaled back in the next planning cycle.
Applying the Framework
Demand-side resources behave differently, which makes a consistent approach to understanding performance essential for aggregating results across programs. How might these principles boost outcomes across three key program types?
- With demand response, timely impact validation supports better forecasts and stronger confidence. Event performance can be understood within days, allowing insights to refine expectations by region or customer segment while the season is still underway.
- With distributed energy resources, visibility is essential. Meter-based analysis shows whether behind-the-meter technologies are delivering meaningful load impacts and specifically where they occur. Portfolio performance can be tracked over time and incorporated into strategic planning with greater confidence.
- With energy efficiency, measured data complements existing assumptions by showing how programs perform in practice. Outcomes can be compared by measure, implementer, and customer group while programs are still active, supporting real-time improvement rather than after-the-fact evaluation.
The Takeaway
The real opportunity for utilities is not to create more or newer demand-side programs, but to get value from the ones already in place. When demand-side performance can be measured consistently and understood quickly, these resources become more effective and reliable. They inform and shape system reliability in a way that static assumptions simply cannot.
As load growth accelerates and timelines tighten, the ability to rely on demand flexibility becomes a practical advantage. Utilities that understand how to make demand flexibility work will be better-positioned to meet growing system needs, at lower cost.
In this series, we’ll explore how utility teams are putting this framework into practice across intervention types using the data they already have. Each article focuses on a specific challenge and provides practical guidance utility teams can use to increase the impact of demand-side programs.
Next Up: Fixing Demand Response: When Performance Insight Arrives Too Late. How can utility teams better measure demand response performance and improve forecasts that planners can rely on?
Want to learn more? Connect with our team on how our FLEX platform can support your team’s demand-side goals.