> For the complete documentation index, see [llms.txt](https://help.modelreef.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.modelreef.io/how-tos/core-modelling/build-a-bottom-up-forecast.md).

# Build a Bottom Up Forecast

This guide shows you how to build a forecast by starting from operational inputs instead of top line financial percentages.

***

## Before you start

Identify:

* The operational levers that drive revenue and costs (for example units, customers, projects, hours).
* Capacity limits and utilisation assumptions.
* Staffing requirements per unit of output.

***

## What you will build

* Operational drivers for units, customers, projects or hours.
* Revenue, COGS, opex and staff variables driven by these inputs.
* Capacity aware forecasts that reflect physical or operational constraints.

***

## Steps

{% stepper %}
{% step %}

### List operational drivers

For your business, examples might include:

* Number of active customers.
* Number of projects delivered.
* Number of store visits.
* Production volume in units or tonnes.
* Billable hours.

Decide which metrics best reflect actual activity.
{% endstep %}

{% step %}

### Create operational drivers in the Data Library

* Open the Data Library.
* For each operational metric create a Driver entry, for example:
  * `Units - Product A`
  * `Projects - Consulting`
  * `Billable Hours - Team A`
* Enter:
  * Current levels.
  * Growth assumptions.
  * Seasonality if relevant.

These drivers will underpin revenue and cost variables.
{% endstep %}

{% step %}

### Build revenue from operational drivers

For each product or service line:

* Create a **Revenue variable**.
* Use formulas such as:
  * `Revenue = Units × Price_per_unit`
  * `Revenue = Billable_hours × Rate_per_hour`
* Where needed, link to:
  * `Rate` or `Price` drivers in the Data Library.
  * Capacity or utilisation modifiers.
    {% endstep %}

{% step %}

### Build costs from operational drivers

Costs often scale with the same units:

* Create **COGS variables** that use:
  * `COGS = Units × Cost_per_unit`
* For **Staff**:
  * Use headcount drivers or hours based staffing ratios.
  * For example:
    * `Headcount_t = Units_t ÷ units_per_FTE`
  * `Staff_cost = Headcount × salary_per_FTE`
* For **Opex**:
  * Model where costs scale by operational intensity (for example logistics or customer care).
    {% endstep %}

{% step %}

### Introduce capacity and utilisation constraints

Avoid unrealistic growth by modelling capacity:

* Create **capacity drivers**, for example:
  * Maximum units per plant.
  * Maximum hours per team.
* Apply simple logic, for example:
  * `Units_t = min(desired_units_t, capacity_t)`
  * `Utilisation = units_t ÷ capacity_t`
* Monitor utilisation using charts.

Even simple capacity logic can prevent obviously impossible forecasts.
{% endstep %}

{% step %}

### Verify outputs and refine drivers

Use P\&L and Cash Waterfall to:

* Confirm revenue and cost patterns match operational expectations.
* Check margins, staff ratios and unit economics.
* Adjust drivers where assumptions are unrealistic.
  {% endstep %}
  {% endstepper %}

***

## Check your work

* Every major financial line is traceable back to an operational driver.
* Headcount and staff costs are linked to actual workload.
* Unit volumes do not exceed realistic capacity.
* Capacity changes (for example new plant or hires) are explicitly modelled.

***

## Troubleshooting

<details>

<summary><strong>Revenue looks fine but capacity is unrealistic</strong></summary>

Check that you have not omitted capacity constraints.

</details>

<details>

<summary><strong>Costs are not scaling with units</strong></summary>

Confirm variables use unit based formulas rather than fixed amounts.

</details>

<details>

<summary><strong>Difficulty managing many drivers</strong></summary>

Group drivers in the Data Library with clear naming and tags.

</details>

***

## Related guides

* [New Product Launch Forecast](/use-cases/consumer-goods-fmcg-and-cpg-manufacturers/new-product-launch-forecast.md)
* [Financing Cashflow](/help/financial-outputs-and-valuation/financing-cashflow.md)
* [Fixing Merged Cells](/help/importing-and-data-inputs/fixing-merged-cells.md)
* [KPI Cards](/syntax/chart-and-table-syntax/kpi-cards.md)