A power plant can be fully built, with a multimillion-dollar investment already committed, and still generate zero revenue. The asset is ready, but the project stays stalled waiting on studies, technical validation, and the approvals needed to connect to the grid.

Meanwhile, the utility keeps buying power on the wholesale market. The delay strains debt management, disrupts the investment timeline, and constrains the expansion decisions that come next.

It’s a clear example of what defines utility planning today: a single technical variable can cascade all the way to a project’s financial outcome. For years, the key question was how much demand would grow. Today, the central question is what happens to the entire plan every time one of its variables changes.

Planning was never simple for a utility. These are capital-intensive organizations, with long-lived infrastructure and decisions subject to regulation and public scrutiny. That complexity isn’t new. What changed is how fast the environment they plan around now moves. Assets are built to run for 30 or 40 years, but the context that justified an investment can shift several times before it ever goes into operation.

For decades, historical demand trends offered a fairly reliable base for forecasting. That reference has since lost much of its value. The energy transition, transportation electrification, and above all the expansion of artificial intelligence and data centers are now disrupting variables that used to evolve gradually.

The scale of the shift shows up in the forecasts themselves. According to Grid Strategies, the aggregate five-year summer peak demand growth forecast for the United States went from 24 GW in 2022 to 38 GW in 2023 and 64 GW in 2024. The 2025 report pushed that figure to 166 GW by 2030, more than six times what was projected just three years earlier. Data centers account for roughly 55% of that projected growth.

“We started from a demand curve that was practically flat. Projects could be planned ten years out because consumption grew slowly. Then everything started to change,” says Pablo Molina, Vertical Specialist DAPLAN at Quanam.

But demand is only one variable in motion. For a small or mid-sized utility, a sudden jump in transformer prices or a longer supplier lead time can throw off a five-year investment plan. And an interconnection delay can stop a project that’s already been built.

From forecasting to simulating

Against that backdrop, building a single forecast is no longer enough. The value lies in being able to change any variable and trace how its effects ripple through the rest of the model, including the projected financial statements for the years ahead.

“Planning is no longer just about building a forecast. The biggest value is being able to ask what happens if this variable changes, and trace that impact all the way to the bottom line,” Molina notes.

In practice, that means systematically testing scenarios: what happens if demand accelerates, if a supplier changes its costs, if a connection is delayed, if interest rates rise, or if a regulatory change alters the terms of an investment.

Each shift stops being a surprise and becomes a scenario that can be anticipated, quantified, and compared.

Doing this rigorously means the data can’t stay siloed. Asset condition, maintenance schedules, supply costs, construction timelines, and demand forecasts all need to be assessed together.

When Engineering, Operations, Regulatory, and Finance work off different versions of the data, each team can build a view that’s valid from its own angle but incomplete for the organization as a whole. Simulating scenarios requires a shared foundation.

Why it weighs more on public power utilities

The cost of a bad forecast isn’t the same for every organization. It hits hardest at small and mid-sized public power utilities in the United States, which answer directly to city councils, local boards, and the communities they serve.

These organizations don’t have the same financial cushion or regulatory resources as a large investor-owned utility.

The margin for error is thin. Overbuilding capacity passes avoidable debt on to customers. Underinvesting can compromise service reliability and limit local economic growth. And every decision has to be justified to regulators and ratepayers.

Utilities still have to make decisions that will shape their operations for decades. The difference is that they now have to do it in an environment that can shift multiple times over the life of a single investment.

Historical data is still necessary, but it’s no longer enough to anticipate what’s next. If the conditions that investments are built on have changed, the way they’re planned has to change too.

In the next article, we’ll look at what it takes to build integrated planning, why a single source of truth becomes critical, and how to move from static budgets to continuous processes that can respond faster.