When Good Plans Stop Fitting Together

Individually reasonable plans can depend on assumptions that no longer fit together. The executive challenge is recognizing when that changes the decision—while management still has choices.

A utility has a large new customer asking for power.

The demand looks credible. The customer is advancing its project. Commercial commitments are strengthening. The case for investment is becoming easier to make.

At some point, expectation has to become a capital decision.

But when?

When is the evidence strong enough to commit long-lived infrastructure to a load that may develop over a very different time horizon?

Now turn the decision around.

The customer may be preparing to commit billions of dollars to a site, equipment and an operating schedule based on when the utility expects to deliver power.

When is that expectation strong enough to support a durable capital decision?

The utility needs confidence in the customer. The customer needs confidence in the utility.

And both decisions may depend on generation, transmission, equipment, regulators, fuel suppliers, permitting authorities and other organizations that neither party completely controls.

Everyone involved can be making a rational decision.

Their plans can appear aligned even while the assumptions connecting them begin to lose compatibility.

That is where the executive problem begins.

The System Is Responding

There is a temptation to frame the current energy environment primarily as a shortage story.

I don't think that is where the evidence leads.

The U.S. Energy Information Administration reported 86 GW of utility-scale generating capacity planned to come online in 2026, if realized, following 53 GW added in 2025.

Transmission investment is advancing. Storage is being deployed. Pipeline infrastructure is expanding. Regulators are changing rules. Utilities, large customers and developers are creating new commercial structures to address emerging risks.

The response is real.

So is the development activity.

Berkeley Lab's Queued Up: 2026 Edition identified roughly 8,200 active projects seeking interconnection at the end of 2025, representing 1,312 GW of generation and approximately 749 GW of storage. It also identified 549 GW with draft or executed interconnection agreements that had not yet reached commercial operation. For projects built in 2025 where the necessary data were available, the median time from interconnection request to commercial operation exceeded five years.

Those figures do not establish that the projects will fail.

They establish something more useful.

Activity is not the same thing as readiness.

A queue is evidence of development activity. An interconnection agreement can provide stronger evidence of project maturity and interconnection progress. Neither, by itself, is an operating megawatt.

The same discipline applies to transmission.

DOE's 2026 Draft National Transmission Needs Study identifies pressing additional transmission need. It also explicitly does not identify the specific transmission solutions that will satisfy those needs.

The distinction is not between progress and failure.

It is between system-level response and decision-specific readiness.

For an executive making a consequential decision, the question is not simply whether the system is responding. It is whether the particular conditions that decision requires are becoming sufficiently credible.

Start With the Decision

In a system this interconnected, almost everything can look relevant.

Most of it is not equally relevant to the decision in front of you.

So I would start somewhere narrower:

What consequential decision are we actually making?

Then:

What must remain true for that decision to work?

A consequential decision usually rests on a relatively small number of assumptions capable of materially changing its economics, timing, feasibility, capability, risk allocation or strategic value.

Those are the assumptions worth elevating.

Some will be controlled internally. Others will be influenced—but not controlled—by the company. And some will depend substantially on decisions being made somewhere else.

A generator may depend on a pipeline company. A generation project may depend on transmission. A utility may depend on a customer. A customer may depend on a utility. A developer may depend on an equipment supplier. A utility may depend on a regulator.

The important question is not whether every organization involved has a plan.

It is:

Which parts of our decision depend on another organization continuing to make the decision we currently expect it to make?

Then comes the harder question:

What evidence gives us confidence that the assumption remains valid?

When Two Plans Validate Each Other

Return to the utility and the large customer.

The utility sees the customer continuing to acquire equipment, advance construction and commit capital. Confidence in the load increases.

The customer sees the utility advancing infrastructure, completing studies and making investments. Confidence in the expected service date increases.

That may be exactly what good coordination should look like.

But suppose both decisions depend on an energization date that requires additional generation, transmission, transformers, permits or construction milestones to arrive on schedule.

The customer's investment does not prove those conditions will be satisfied. The utility's investment does not prove the customer's eventual load will materialize exactly as assumed.

Their plans can validate each other without independently validating the assumption they share.

That is the distinction between plan-to-plan alignment and plan-to-evidence alignment.

Coordination matters. But coordination is not independent confirmation.

Their plans may validate each other. The evidence still has to validate the assumption they share.

The Large-Load Question Runs Both Ways

Much of the current large-load debate has focused, appropriately, on protecting existing customers if expected demand does not materialize.

Institutions are responding.

On June 18, FERC opened Section 206 show-cause proceedings involving all six regional grid operators under its jurisdiction, directing them to justify or reform rules governing how large loads connect to the grid. Those proceedings are part of an evolving regulatory response—not a completed uniform national tariff regime.

Commissioner David Rosner, for example, discussed Cost Recovery Agreements designed so large loads bear appropriate infrastructure costs even if the expected load does not come online as planned.

That matters.

Financial commitments can help distinguish serious demand from speculative demand. They can allocate economic exposure more deliberately. They can reduce the risk that other customers are left paying for infrastructure built around a load that never arrives as expected.

But a financial commitment does not manufacture a transformer.

It does not complete a transmission project.

It does not build generation.

It does not secure fuel.

It does not turn an expected service date into physical capability.

That gives the large customer the mirror-image problem.

If I am committing a campus, equipment, financing and an operating schedule because I expect power on a particular date, what evidence supports the physical delivery path behind that date?

The utility is asking:

Is the load sufficiently credible to support durable investment?

The customer should be asking:

Is the delivery path sufficiently credible to support durable investment?

Neither question invalidates the other. Together, they expose the dependency.

Commercial certainty is not delivery certainty.

And physical readiness, by itself, does not establish that the economic exposure remains prudent.

Five Questions Under the Decision

Once the critical assumptions are visible, I would interrogate them through five lenses:

Commitment | Timing | Capability | Deliverability | Economic Exposure

Is the commitment real?

Does the timing still work?

Will the required capability exist?

Can that capability actually be delivered where and when it is needed?

And then a different question:

If one of those assumptions proves wrong, who owns the economic consequence?

That last question is deliberately different.

Commitment, Timing, Capability and Deliverability principally test the credibility of conditions the decision requires.

Economic Exposure asks what happens if management is wrong—how the consequence is allocated and where it ultimately lands.

These are not five boxes to score. Different decisions will place different weight on each.

The diagnostic exists to interrogate the assumptions supporting the decision, not to replace executive judgment.

Alignment is a diagnostic. Evidence determines confidence. The decision remains the object.

Retirement and Replacement

The same discipline applies beyond large loads.

Consider a decision to retire an existing dispatchable resource.

The decision may depend on assumptions about replacement generation, transmission, fuel, load trajectory and the timing at which replacement capability will actually become available.

The executive question is not simply whether sufficient replacement capacity appears somewhere in a plan.

It is:

Will the required replacement capability actually be available before the capability being surrendered exits?

That makes milestone credibility important.

A proposed project and a project under construction do not deserve identical confidence. Neither do an expected commercial-operation date and demonstrated operation.

But there is no universal milestone at which a project suddenly becomes “real.”

The relevant question is whether the evidence has matured enough for the decision being made.

Berkeley Lab's queue data illustrate why that distinction matters. Enormous quantities of capacity can be in active development while individual projects remain at very different stages between request and operation.

That does not argue against retirement.

It argues against confusing planned replacement with delivered replacement.

If construction advances, required transmission is completed, equipment arrives, operating milestones hold and the necessary capability becomes increasingly credible, the evidence may strengthen the retirement decision.

Good.

The framework should say so.

Preparedness is not an argument for preserving an existing asset indefinitely. It is knowing what must remain true for the retirement decision to work—and what evidence would cause management to make that decision again.

When the Solution Changes the Dependency

Now consider a customer whose grid connection cannot be delivered on the schedule its project requires.

One possible response is onsite or behind-the-meter generation.

That may solve the immediate electrical problem.

But if the alternative depends on natural gas, the decision may now depend on sufficient fuel transportation, contractual rights and physical deliverability at the site when the generation needs to run.

The question becomes:

Did solving the electric-delivery problem make our strategy dependent on a fuel-delivery condition we have actually secured?

The answer may be yes.

Pipeline expansion, firm transportation or other arrangements may make that dependency entirely manageable.

If so, recognize it and move on.

The point is not that every solution creates another bottleneck.

It is that solving one constraint can change the dependency that matters next.

Follow that dependency only while it remains capable of materially changing the decision.

Three Questions

The underlying analysis can become complicated.

The executive discipline does not have to be. It begins with three questions.

1. What must remain true?

Identify the few material assumptions the decision actually requires.

Understand which are controlled internally, which are influenced externally and which depend substantially on organizations you do not control.

2. What would tell us it is changing?

Identify observable evidence that should increase or decrease confidence in those assumptions.

Not activity for activity's sake.

Evidence relevant to the condition the decision actually requires.

3. What decision would we make again?

Identify when confidence in a material assumption has changed enough that management should reconsider the original decision.

Not automatically reverse it.

Make it again.

Those three questions change what management monitors.

Instead of asking whether the latest development is good or bad, the organization asks whether it materially changes confidence in an assumption supporting a consequential decision.

From Signal to Tripwire

Not every development deserves executive intervention.

A signal tells us something relevant may be changing.

A tripwire is different:

A tripwire is evidence that confidence in a material assumption has changed enough that the decision deserves reassessment.

Sometimes the underlying condition has changed.

Sometimes better evidence simply reveals that management's earlier confidence was too high—or too low.

The distinction matters.

The framework is not waiting for physical failure before management responds.

Nor does a crossed tripwire establish that the original decision was wrong.

Reassessment is required; reversal is not.

Management may delay, accelerate, modify, renegotiate, hedge, choose another path—or reaffirm the original decision with greater confidence.

A tripwire does not provide the answer.

It tells management when the previous answer deserves to be tested again.

Preserve the Options Worth Preserving

That leads to one additional question:

What option would we wish we still had if that tripwire were crossed?

It could be contractual flexibility, an alternate site or supplier, phased commitment, or the ability to defer a difficult-to-reverse step.

But options have costs.

Preserving every option can be as economically irrational as preserving none.

The question is therefore:

Which options are worth paying to preserve because failure of the underlying assumption would otherwise create disproportionate loss?

Sometimes the rational answer will be to surrender the option.

That is not a failure of preparedness. It is a decision made with the exposure understood.

“We Already Do This”

A sophisticated executive could reasonably read this and say:

We already do this.

Many companies do significant parts of it through scenario planning, enterprise risk management, capital committees, project controls, integrated resource planning, commercial contracting and contingency planning.

Those disciplines matter.

I am not proposing replacements for them, and I am not claiming to have invented dependency analysis.

The vulnerability I am interested in may not exist inside any one of those processes.

It may exist between them.

A utility planning team can be doing its job. A customer development team can be doing its job. A generator, pipeline company, transmission planner, equipment supplier and regulator can each be making rational decisions within their responsibilities.

And a consequential decision can still become less secure if the assumptions connecting those plans cease to remain sufficiently compatible.

That is the integration problem.

If an organization already identifies those cross-enterprise dependencies, tests them against independent evidence and knows when changed confidence requires reconsideration, good.

Keep doing it.

Preparedness Is Not Prediction

The U.S. energy system is responding to extraordinary change.

That response matters.

New generation can strengthen an assumption. A completed transmission project can remove one. A stronger customer commitment can reduce economic exposure. A pipeline expansion can improve fuel deliverability.

Better evidence can make a consequential decision more secure, not merely less.

That is why the objective is not to predict every disruption or search for reasons to delay.

Executives do not need to know exactly what the future will be.

They need to know what future their decision assumes.

They need to know what—and whose decisions—that future depends on.

And they need to recognize when the evidence no longer supports the confidence they placed in it.

Preparedness is recognizing when a consequential decision deserves to be made again while management still has choices.

Selected Primary Sources

• U.S. Energy Information Administration — New U.S. electric generating capacity expected to reach a record high in 2026 — February 20, 2026. EIA confirms 86 GW planned for 2026, if realized, following 53 GW added in 2025.

• Lawrence Berkeley National Laboratory — Queued Up: 2026 Edition, Characteristics of Power Plants Seeking Transmission Interconnection As of the End of 2025 — 2026. Berkeley Lab confirms approximately 8,200 active projects, 1,312 GW of generation and about 749 GW of storage, while explicitly framing queue data as an indicator rather than a forecast of completed capacity.

• U.S. Department of Energy, Office of Electricity — 2026 Draft National Transmission Needs Study — July 2026. DOE identifies pressing transmission need while explicitly stating that the study does not identify specific transmission solutions.

• Federal Energy Regulatory Commission — FERC Launches Aggressive Targeted Action to Speed Large Load Integration — June 18, 2026. FERC confirms the six Section 206 show-cause actions.

• Federal Energy Regulatory Commission, Commissioner David Rosner — Remarks on the Large Load Show Cause Orders, E-7 to E-12 — June 18, 2026. Rosner describes the Cost Recovery Agreement concept and explicitly characterizes the actions as beginning a dialogue with RTOs/ISOs.

Phoenix Intelligence provides strategic advisory products that are developed from three decades of ground-to-grid operational experience across the energy value chain and are intended to identify emerging structural risks, hidden market distortions, and second-order consequences before they become widely recognized.

Phoenix Intelligence briefings are not forensic investigations, engineering studies, regulatory findings, or investment recommendations. Readers should evaluate these briefings as industry perspectives and opinions of the author which are intended to provoke executive consideration, challenge conventional assumptions, and support strategic preparedness.

Artificial intelligence tools may be used to assist with research, source analysis, and the development of these briefings; the interpretations, judgments, and conclusions presented remain those of the author.