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

# ROI Fundamentals

> Use simple, defensible formulas for capacity, cost, revenue and payback without overstating certainty.

Keep ROI models understandable. A simple model with visible assumptions is more useful than a complex model nobody trusts.

## Labour capacity

**Annual hours released = annual volume × minutes saved per item ÷ 60**

**Capacity value = annual hours released × loaded hourly cost**

Then ask how the capacity will actually be used. If no headcount is removed, frame this as capacity rather than guaranteed cash saving.

## Avoided hiring

**Avoided hiring value = FTE requirement avoided × loaded annual FTE cost**

Use only where the organisation genuinely expects to add capacity absent the change.

## Error reduction

**Annual benefit = current error volume × cost per error × expected reduction**

Include downstream rework, credits, complaints or operational cost only where supported.

## Revenue opportunity

**Expected revenue benefit = relevant volume × conversion uplift × average contribution per conversion**

Contribution is often more useful than headline revenue when costs scale with sales.

## Payback

**Payback period = implementation investment ÷ monthly net benefit**

## Simple ROI

**ROI = (annual benefit − annualised cost) ÷ annualised cost**

## Sensitivity analysis

Change the two or three assumptions that drive the model most. Typical sensitivity variables include adoption, minutes saved, transaction volume and implementation cost.

<Warning>
  Do not present Iris-generated or consultant-estimated ROI as realised benefit. The diagnostic establishes an expected case; realised value must be measured after implementation.
</Warning>

## Minimum assumptions table

For each input include: source, owner, current value, scenario value, confidence and review date.