> ## Documentation Index
> Fetch the complete documentation index at: https://docs.salvidia.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Lesson 3: Get a rough number fast

> Connect your spend to produce a complete but approximate footprint in an afternoon. Its job is not to be accurate. Its job is to tell you where to aim.

**What you will do:** produce a footprint with nothing missing from it, most of which is estimated, and resist the urge to fix it.

This is the step that feels wrong. You are about to generate a number you do not trust, on purpose. Do it anyway, because until you have one you cannot tell which categories deserve the next four weeks of your effort.

## Why approximate first

Most people are wrong about where their emissions are. Waste feels significant and is usually small. Professional services feel trivial and are frequently the largest single line. Business travel is either dominant or negligible with very little in between.

You cannot reason your way to the answer. A rough pass tells you in an afternoon what guessing would get wrong for a month.

## Connect your spend

Your accounting platform reaches every category you buy from at once. Salvidia reads the ledger for your period and applies industry-average factors per dollar. Finance can usually authorise the connection in minutes.

If you would rather not connect it directly, export the general ledger for your period and import that instead. The result is the same. See [working with data](/platform/working-with-data).

## What you now have

A complete footprint. Every category you spend money on is present, sorted into Scope 1, 2, and 3, and none of it is missing.

It is also mostly estimated. Spend-based factors cannot tell a renewable-powered supplier from a coal-powered one, because both charged you dollars. That limitation is fine for now and is the reason lesson 4 exists.

## Read it for shape, not for size

Open the category breakdown and ignore the total. You are looking for three things:

* **Which categories are largest.** Usually a handful account for most of it.
* **Whether anything is missing.** A category at zero that you know you spend on means a mapping gap, not an absence of emissions.
* **Whether anything looks implausible.** A number that surprises you is worth checking now rather than after you have built on it.

If Scope 3 dominates, that is normal and not an error. For most service businesses it is the large majority. See [understanding your results](/platform/understanding-dashboard-and-charts).

<Note>
  Do not show this number to anyone yet. It is a working artefact, not a result, and a figure shared before lesson 4 tends to become the figure everyone remembers.
</Note>

## Write down your top three

Before you close the tab, note the three largest categories. That list is the entire agenda for the next lesson, and it is the reason this rough pass was worth doing.

## You are done when

* You have a footprint with every category present, however estimated
* You have written down your three largest categories
* You have resisted fixing anything

## Next

[Lesson 4: Upgrade what actually matters](/learn/lesson-4-upgrade-what-matters)