Normative Financial Model
Climate/Energy Startup Financials (Free Excel Download)
Carbon accounting SaaS platform that calculates full Scope 1/2/3 emissions and provides net-zero action intelligence for corporate clients.
professionals from Deloitte
Used by professionals from
About this model
Normative is carbon-accounting software that converts transaction and activity data into Scope 1, 2, and 3 emissions, supplier insights, reporting, and a net-zero action plan. Its engine combines spend- and activity-based methods with a database spanning 200 million data points and 100 million company records.
The company sells subscriptions to mid-sized and large corporates, including financial services, real estate, retail, and manufacturing customers. CSRD-driven disclosure demand and the difficulty of measuring value-chain emissions are the commercial tailwinds; the deck shows 12 customer logos but no disclosed ARR or pricing.
The model should forecast monthly logo cohorts, ACV, onboarding, churn, and expansion into additional modules or advisory services. Link that ARR build to data and product gross margin, sales hiring, engineering spend, and cash runway, while making regulatory timing a scenario variable rather than assuming demand materialises immediately.
A turnkey financial model
Live formulas, no hardcoded values
Outputs are driven by live formulas, so the workbook updates from its assumptions instead of relying on hardcoded results.
All assumptions in one tab
Inputs are clearly marked in the Assumptions tab and separated from calculations, making it clear what to change and what to leave intact.
Statements always balancing
For integrated-statement models, the balance sheet, cash flow, and supporting schedules tie through properly.
Distinct schedules for clarity
Debt, working capital, taxes, and cash flow can get messy quickly. We group calculations in clear schedules, not across disconnected tabs.
No hidden macros or external links
There are no unexplained external workbook links or macros to undermine auditability or portability.
Changes flow through the model
Update a key driver and see the impact carry through the forecast, financing, and return outputs. We never use hardcoded numbers in formulas.
About Normative
normative.io
How to build a detailed financial model for Normative
A complete walkthrough of the business, drivers, and assumptions behind the downloadable Normative model - distilled from its pitch deck and publicly available information.
Product & value proposition
- SaaS platform that ingests financial transaction data and maps it to GHG emissions using a hybrid spend-based + activity-based model aligned to the GHG Protocol.
- Core workflow: upload financial data → carbon accounting engine calculates Scope 1/2/3 footprint → platform surfaces emission hotspots, supplier-level data, and net-zero action plan.
- Carbon accounting engine formula: Σ Business Activity(i) × Emission Factor(i).
- Engine inputs: internal activity/transaction data + external emission factor databases + corporate registers.
- Database: 200M data points, 100M company records. Time-to-value: 2–3 weeks for full Scope 3.
- Output modules: emission overview dashboard (Scope 1/2/3 KPIs), analysis, accounting, reporting.
- "Upgrade now" prompt visible in product screenshot - implies freemium or trial-to-paid gating.
Market
- €100 trillion globally needs to be redirected into low-carbon companies and activities, requiring carbon accounting and disclosures.
- ~50,000 companies required to report on ESG issues under the EU Corporate Sustainability Reporting Directive (CSRD).
- <5% of companies currently accurately account for their full carbon footprint.
- >90% of carbon emissions located in the value chain (Scope 3) and not currently accounted for.
- 76% of large investment managers have signed UN Principles of Responsible Investment.
- 77% of consumers say brand sustainability is at least moderately important.
- No explicit TAM/SAM/SOM figures stated in deck. The €100T figure is a capital-reallocation market context, not a software TAM.
Revenue model
- B2B SaaS subscription - implied by the "Upgrade now" CTA in the product dashboard.
- Target customers: mid-to-large corporates (client list includes BNP Paribas, SEB, Elekta, Castellum, Bonava, Flying Tiger Copenhagen, Happy Socks, Assemblin, Vitamin Well, Scapa, Sortera, MiO - mix of financial services, real estate, retail, healthcare, manufacturing).
Traction & metrics
- Named customer logos displayed: Bonava, BNP Paribas, Sortera, Scapa, SEB, Castellum, Vitamin Well, MiO, Elekta, Flying Tiger Copenhagen, Happy Socks, Assemblin (12 logos).
- Testimonial from Head of Sustainability at Flying Tiger Copenhagen.
- No revenue, ARR, MRR, growth rate, or customer count numbers stated in deck.
- Product database scale: 200M+ data points, 100M company records. (These are engine specs, not revenue traction.)
Competition / moat
- Moat framed around data scale (200M data points, 100M company records) and speed (2–3 weeks vs. months for competitors).
- Methodology moat: GHG Protocol-aligned hybrid spend-based + activity-based model - regulatory-standard accuracy.
- No named competitors mentioned in deck.
Team & funding ask / use of funds
Recommended financial model
- Archetype + why: B2B SaaS ARR model. Revenue is recurring subscription fees from corporate accounts; the product is a platform with onboarding, retention, and expansion dynamics typical of enterprise SaaS. Secondary advisory/services revenue possible but not stated.
- Forecast horizon & granularity: 5 years (2021–2026), monthly for Years 1–2, quarterly for Years 3–5. Monthly needed to model ramp and churn in early stage.
- Key drivers & assumptions:
| Driver | Value |
|---|---|
| Starting named customers (logo count as proxy) | ~12 |
| New logos per month - Year 1 | 2–4 |
| New logos per month - Year 3+ | 8–15 |
| Average ACV (mid-market corporate) | €20k–€60k |
| Net revenue retention | 110–120% |
| Gross logo churn (annual) | 8–12% |
| Gross margin | 70–80% |
| S&M as % of revenue (Year 1–2) | 50–60% |
| R&D as % of revenue (Year 1–2) | 30–40% |
| G&A as % of revenue | 10–15% |
| CSRD-driven demand inflection year | 2024–2025 |
- Scenarios (Base / Bull / Bear - which variables flex):
- Bear: Slower enterprise sales cycle, CSRD enforcement delayed, ACV pressure from free tools; new logos at low end, churn at high end.
- Base: Steady Nordic then EU expansion; CSRD creates pull-demand from 2024; NRR ~115%.
- Bull: CSRD drives inbound demand surge from 2024; large enterprise ACV (€80k+); international (UK, DACH) expansion; strong NRR from upsell into advisory/action modules.
- Required sheets / outputs:
- Assumptions - all drivers in one place, clearly tagged
- Revenue - logo cohort waterfall (new/churned/expanded), ARR bridge, MRR by month
- P&L - gross margin, OpEx (S&M, R&D, G&A), EBITDA, net income
- Headcount - sales, engineering, data science, ops; drives S&M and R&D costs
- Cash flow - burn rate, cash balance, runway
- KPI summary - ARR, logo count, NRR, LTV/CAC (estimated), CAC payback, gross margin
- Dashboard - ARR waterfall chart, logo growth, burn vs. runway
Frequently asked
Is the Normative financial model free?+
Yes. The Normative model is a free Excel (.xlsx) download with live formulas. Sign up with your email and the workbook is yours to keep, review, and edit.
What's included in the model?+
A 5-year monthly forecast with P&L, cash flow and runway, valuation (exit multiple plus a DCF cross-check), MOIC/IRR returns, and unit economics, with live formulas throughout.
How was this model built?+
It was built from Normative's pitch deck and publicly available information, then structured to investment-banking standards as a fully editable Excel model.
Can I change the assumptions?+
Yes. You can change assumptions and the live formulas will recalculate in the downloadable Excel model.
Have more financial modelling questions? Contact us
Created by ex-finance professionals
Hey, I’m Alex and I created Finamodel.
Over my years in the finance industry I kept building the same models over and over again. Same structure, same assumptions, different logo. So I started building frameworks to turn them into clean, reusable templates.
Every model here is one I’d actually use for a client, and I personally vet each one before it goes up.
I’m not an expert in every industry, but I’ve built enough models to know what belongs in one. And when something is completely foreign to me, I reach out to my network for experts to work on our models with us.
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