> ## 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.

# Activity-based vs spend-based

> When to use activity data, when to use spend-based estimates, and how Salvidia works with both.

There are two main ways to measure emissions:

* **Activity-based data** – based on what physically happened
* **Spend-based data** – based on how much money you spent

Both are valid. The key is knowing **when to use which**, and how they show up in your Salvidia assessments.

***

## The basic difference

> **Activity-based**\
> Uses real-world quantities (kWh, litres, km, tonnes, etc.)

> **Spend-based**\
> Uses money spent (e.g. AUD, NZD, USD) as a proxy for emissions

Examples:

* Activity-based:
  * 12,500 kWh of electricity
  * 3,200 litres of diesel
  * 4.2 tonnes of mixed landfill waste

* Spend-based:
  * \$120,000 on marketing services
  * \$45,000 on IT and software
  * \$9,500 on catering

In both cases, Salvidia uses **emission factors** to convert the input into **CO₂e**, but activity-based data is generally **closer to reality**.

***

## At a glance

<Columns>
  <Column>
    <Card title="Activity-based">
      <ul>
        <li>Higher accuracy (when data is good)</li>
        <li>Direct link to physical activity</li>
        <li>Best for energy, fuels, travel, waste, materials</li>
      </ul>
    </Card>
  </Column>

  <Column>
    <Card title="Spend-based">
      <ul>
        <li>Fast to implement using finance data</li>
        <li>Good for broad categories or long tails</li>
        <li>Less precise, depends on price and inflation</li>
      </ul>
    </Card>
  </Column>
</Columns>

***

## Activity-based data

Activity-based data uses **physical quantities** directly linked to emissions.

Common examples:

* kWh of electricity
* Litres of petrol, diesel, gas
* Kilometres travelled by mode and vehicle type
* Tonnes of waste by stream (landfill, recycling, organics)
* Tonnes or kg of materials and products

Why it’s preferred:

* Less influenced by price changes, inflation, or exchange rates
* Easier to compare across time and locations
* More useful for **designing reduction projects** (“use less fuel / different materials”, not just “spend less”)

In Salvidia, most **Energy**, **Travel**, **Waste**, and **Product** tables are designed for activity-based inputs.

***

## Spend-based data

Spend-based methods use **money spent** as a proxy for emissions.

Example:

* \$10,000 spent on IT services
* × emission factor per dollar (kg CO₂e / \$)
* \= emissions estimate for that spend

Spend-based data is useful when:

* You don’t have detailed activity data
* You’re dealing with **lots of small purchases**
* You want a first-pass footprint using **finance exports**

It’s most common for:

* Professional services
* Marketing and advertising
* Office supplies
* Software and subscriptions
* “Long tail” vendors where activity data isn’t realistic to collect

In Salvidia, spend-based methods are usually used in **Purchases and services** tables, where categories and factors can be mapped to your spend.

***

## Pros and cons

<Columns>
  <Column>
    <Card title="Activity-based – Pros">
      <ul>
        <li>More accurate and stable over time</li>
        <li>Directly tied to physical activities</li>
        <li>Great for tracking progress and designing reductions</li>
      </ul>
    </Card>
  </Column>

  <Column>
    <Card title="Activity-based – Cons">
      <ul>
        <li>Requires better data and systems</li>
        <li>Can be harder to collect for some categories</li>
        <li>More up-front setup for data pipelines</li>
      </ul>
    </Card>
  </Column>
</Columns>

<Columns>
  <Column>
    <Card title="Spend-based – Pros">
      <ul>
        <li>Fast to implement using existing finance data</li>
        <li>Good coverage of “everything else”</li>
        <li>Useful for early baselines and screening</li>
      </ul>
    </Card>
  </Column>

  <Column>
    <Card title="Spend-based – Cons">
      <ul>
        <li>Emissions estimates move with price, not just activity</li>
        <li>Less granular for reduction planning</li>
        <li>Can be sensitive to inflation and exchange rates</li>
      </ul>
    </Card>
  </Column>
</Columns>

***

## When to use which

A simple rule of thumb:

* **Use activity-based** when:
  * You have metered or measurable data (kWh, litres, tonnes, km, etc.)
  * The category is **material** (big part of your footprint)
  * You’re planning **reduction actions** in that area

* **Use spend-based** when:
  * Activity data is unavailable or extremely hard to get
  * You want to cover many small, diverse purchases
  * You’re doing an initial **screening** or rough baseline

<Note>
  You don’t have to choose one or the other for your whole footprint. Most strong inventories use a <b>mix</b>: activity-based for big categories, spend-based for the long tail.
</Note>

***

## Examples

### Electricity (office or event venue)

* **Best**: kWh from meter readings or bills (activity-based)
* Avoid: spend-based factors for electricity if you can easily get kWh

In Salvidia:\
Add to **Energy and utilities** with kWh, not just \$.

***

### Business travel

* Flights:
  * **Better**: distance and class per flight (activity-based)
  * **Fallback**: total spend on flights by region/route (spend-based)
* Hotels and accommodation:
  * Activity-based if you have nights by city and hotel type
  * Spend-based if you only have total \$ from finance

In Salvidia:\
Use the **Travel and transport** tables. Aim for activity-based where booking data is available.

***

### Purchased services (e.g. marketing, legal, IT)

* Often no practical activity metric
* Spend-based is usually appropriate
* You can still improve quality over time by:
  * Better categorisation
  * Supplier-specific data where available

In Salvidia:\
Use **Purchases and services**, mapped to appropriate spend-based factors.

***

### Waste

* **Best**: tonnes per stream (landfill, recycling, organics, etc.) from waste contractors
* **Fallback**: spend on waste services by stream (spend-based)

In Salvidia:\
Use **Waste and materials** with tonne-based inputs if possible.

***

## How Salvidia handles both approaches

In Salvidia:

* Some tables are **activity-first** (e.g. Energy, Travel, Waste)
* Others are **flexible** and can support activity **or** spend (e.g. Purchases and services)

Under the hood, Salvidia:

1. Detects whether a row is activity-based or spend-based.
2. Applies the appropriate emission factor type.
3. Stores both the **input** and the method used, so you can see where your numbers came from.

This means you can:

* Start with **more spend-based data** in early years.
* Gradually shift important categories towards **activity-based** as your data improves.

***

## Common patterns for a first footprint

<Tabs>
  <Tab title="Organisation">
    <ul>
      <li>Activity-based: electricity, gas, fuels, refrigerants, waste, major travel</li>
      <li>Spend-based: professional services, IT, marketing, office supplies, long-tail vendors</li>
    </ul>
  </Tab>

  <Tab title="Event">
    <ul>
      <li>Activity-based: venue energy (or estimates), generators, waste, travel (where possible), catering volumes</li>
      <li>Spend-based: some suppliers, services, and hard-to-measure logistics</li>
    </ul>
  </Tab>

  <Tab title="Product">
    <ul>
      <li>Activity-based: materials and components, manufacturing energy, transport distances, packaging</li>
      <li>Spend-based: complex or indirect services supporting the product, where appropriate</li>
    </ul>
  </Tab>
</Tabs>

***

## Practical guidance for your assessments

<Steps>
  <Step title="1. Prioritise by impact">
    Use activity-based data first for categories you expect to be large (energy, travel, materials), and worry less about perfect precision in tiny categories.
  </Step>

  <Step title="2. Use finance exports to fill gaps">
    Where you can’t easily get activity data, use spend-based factors on finance exports to avoid missing whole categories.
  </Step>

  <Step title="3. Document your choices">
    Make a note in your methodology of where you used spend-based vs activity-based data and why. This makes year-on-year comparisons much easier.
  </Step>

  <Step title="4. Improve over time">
    Each year, decide 1–3 categories you’ll upgrade from spend-based to activity-based, rather than trying to perfect everything at once.
  </Step>
</Steps>

***

## If you only remember three things

<Columns>
  <Column>
    <Card title="1. Activity-based is the gold standard">
      Use it where you can, especially for big categories like energy, travel, and major materials.
    </Card>
  </Column>

  <Column>
    <Card title="2. Spend-based is a useful bridge">
      It’s better to have a reasonable spend-based estimate than to ignore a category entirely.
    </Card>
  </Column>

  <Column>
    <Card title="3. Mix and improve">
      A strong footprint uses both methods thoughtfully and gets more activity-based over time.
    </Card>
  </Column>
</Columns>

***

## Where to go next

* Learn about **[Data quality tiers](/guides/data-quality-tiers)** (if enabled)
* See how this sits inside **[Carbon accounting in 10 minutes](/guides/carbon-accounting-in-10-minutes)**
* Or start applying it in practice in your actual data tables in Salvidia.