Picture this: you paid between $5,000 and $20,000 for a financial model. The advisory firm came recommended. They specialise in startup finance. The model they delivered looks professional: colour-coded tabs, a clean summary dashboard, charts that would look great in a pitch deck.

The problem is that the model was built from a template, and the template doesn’t reflect how your specific business actually works.

Let me be clear - this isn’t a criticism of advisors. Most are genuinely trying to deliver value. But the economics of advisory financial modelling create a structural problem: to be profitable at $5K–20K per model, firms need to work from base templates that they customise for each client. The customisation is real — they change your inputs, adjust your cost structure, tailor the presentation — but the underlying architecture remains generic.

The Template Problem

Most advisory firms maintain three to five base templates: one for SaaS, one for marketplaces, one for e-commerce, sometimes one for services and one for hardware. When a new client comes in, the advisor selects the closest template and starts swapping input cells.

On the surface, this looks like a custom model. The company name is right. The revenue numbers match what the founder provided. The headcount plan reflects the team. But the structure — how revenue flows through the model, what metrics are calculated, how costs scale — is inherited from the template.

This matters because businesses within the same category can have radically different economics. Two SaaS companies might have completely different acquisition models (product-led growth versus enterprise sales), different revenue structures (flat subscription versus usage-based), and different cost profiles (infrastructure-heavy versus services-heavy). A single SaaS template can’t capture both accurately.

Common Structural Failures

Here are specific examples of how template-driven models fail founders:

  • Marketplace models: A marketplace has two sides — supply and demand — with different acquisition costs, different churn rates, and different unit economics. A template that treats marketplace revenue as a single GMV line with a take rate misses the fundamental dynamics of whether you have a supply problem or a demand problem.

  • SaaS with usage-based pricing: If your pricing includes a base fee plus per-unit charges, a template designed for flat-rate subscriptions will model your revenue wrong. Expansion revenue from usage growth is fundamentally different from expansion revenue from seat additions.

  • Hardware plus software: Hardware models need to capture BOM costs, manufacturing lead times, inventory management, and the cash flow timing of production runs. A SaaS template with a hardware line item bolted on will get the cash flow horribly wrong.

The Black Box Problem

There’s a second issue that’s equally damaging: when someone else builds your model, you often can’t explain how the numbers were derived.

In an investor meeting, the question “How did you arrive at this churn assumption?” should have an immediate, confident answer from the founder. When the answer is “I’ll need to check with my advisor,” the investor hears: “I don’t understand my own financial model.”

This is lethal for credibility. The financial model is supposed to demonstrate that you understand the economics of your business. If you can’t walk through any assumption on any tab and explain why it’s what it is, the model is working against you rather than for you, no matter how polished it looks.

What Good Looks Like

A financial model should be built from the founder’s understanding of their business, not adapted from a generic template. That means the modelling process should start with questions, not cells.

A properly structured financial model for a marketplace should ask fundamentally different questions than one for a SaaS company. The marketplace model needs to understand supply-side and demand-side acquisition separately, model GMV and take rate dynamics, and capture liquidity metrics. The SaaS model needs to understand ARR composition, seat-based versus usage-based revenue, and cohort behaviour. Lisa and I have explored high level overviews of financial modelling for both SaaS and hardware companies on the blog previously.

When every assumption traces back to a specific question that the founder answered — with benchmark context for questions where they didn’t know the answer — you get two things: a model that genuinely reflects the business, and a founder who can explain every number in it.

Your Financial Model, Built Your Way

Radley Finance is designed to enable early-stage SaaS founders to build their own financial models. If you run a different type of business, or simply want an expert to handle the building, our team can do it for you.

Build a tailored financial model for your startup

This post is the latest installment in a series on fundraising and investment for founders. Previously, we've covered:

Next up, we will be exploring the possibilities and pitfalls of AI in financial modelling.