Work Process Fit

Infrastructure Strategy

I turn complexity into
operational clarity.

Decision frameworks, capital allocation models, and product architecture for energy infrastructure. I work with teams that manage grid-scale investments under regulatory pressure, fragmented data, and real constraints.

See how I structure decisions

Sectors Solar, BESS, grid infrastructure

Decisions supported Capital allocation, site selection, battery sizing

Outcome Board-ready verdicts from messy data

Decision Memo — Draft

Node DE-3847 · PV + BESS Evaluation

Grid connection 25 MW import / 8 MW export

Site Central DE, agricultural, single owner

Optimal config 40 MW PV + 30 MWh asymmetric BESS

Strategy Merchant · negative-price arbitrage

IRR uplift vs. solar-only +3.2 pp

Verdict: Hunt — proceed to detailed due diligence

"The grid connection decides the project. Everything else follows."

Clients bring me in when:

The spreadsheet has become the strategy Board needs a verdict, not a slide deck Capital is waiting on unclear tradeoffs Teams are misaligned on what the data says

What I do

Three ways I typically engage.

Every engagement starts with the same question: where is the decision stuck? The format depends on what unsticks it.

Capital allocation under uncertainty

Multiple sites, competing priorities, unclear which investments to accelerate. The data exists but doesn't produce ranked, defensible decisions.

Deliverable: Deterministic scoring model that ranks projects by risk-adjusted value. Board-ready investment memos with verdicts, drivers, and confidence levels.

Site selection under regulatory pressure

Grid constraints, connection queues, changing policy. Teams are hunting land when they should be mapping grid access and regulatory windows first.

Deliverable: Grid-first site evaluation framework. Spatial analysis that identifies where connection capacity, land availability, and economics actually overlap.

Decision architecture for complex programs

The project is technically viable but the organization can't move. Engineering, finance, and leadership see different numbers, different risks, different priorities.

Deliverable: Unified decision system where the same data produces engineer-level detail and board-level verdicts. One model, multiple views, auditable logic.

The process

From noise to strategy.

01

Map the constraint landscape.

Grid capacity, regulatory windows, land status, capital structure. Identify what actually limits the decision space.
02

Separate signal from noise.

Find the structural bottlenecks. Most "data problems" are framing problems. Most "alignment issues" are missing shared models.
03

Build the decision engine.

Deterministic scoring, scenario simulation, ranked outputs. The logic is auditable. The verdicts are defensible.
04

Deliver in the language of the audience.

Engineers get the model. Leadership gets the memo. The board gets the verdict. Same data, different views.

"If a strategic direction falls apart the moment it touches teams, tooling, or real constraints — it was never a direction. It was a mood board."

— Lene Klemenz

I build decision systems that survive contact with operations. The test isn't whether the logic is elegant — it's whether the team can act on it Monday morning.

How I think about the work

Operating principles.

1. Start with the constraint. Physics, regulation, or security — constraints reveal the real decision space. Everything else is optionality.
2. Treat data as evidence, not truth. Until verified against the constraint landscape, data is hypothesis material.
3. The deterministic engine decides. AI only translates. Hard rules produce the verdict. The language layer makes it legible for the audience.
4. The "how" is the work. In regulated environments, how you arrive at a decision is as important as the decision itself. Auditability is not optional.

Is this a fit

Bring me in when.

Good fit

Board pressure on capital allocation decisions
Regulatory constraints shaping the project timeline
Fragmented data across engineering, finance, and ops
High-stakes site selection with grid bottlenecks
Unclear tradeoffs between competing investments
Cross-functional teams that can't agree on the numbers

Not the right fit

Pure software development or UI/UX projects
Early-stage ventures still searching for product-market fit
Organizations not ready to act on structured recommendations
Needs that are better served by a management consultancy

Tell me where the decision is stuck.

Whether it's a capital question no one can frame, a regulatory maze with no clear path, or a team that needs a shared model to move — the best work starts with an honest conversation about the real constraint.

I typically respond within 24 hours. Initial calls are 30 minutes, no obligation.

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I turn complexity into operational clarity.