Sharp Logica, Inc.
AI Toolkit

Automation ROI Calculator

Estimate workflow automation ROI from process volume, manual handling time, error and rework reduction, and run cost.

This model is for process and workflow automation economics where labor and rework reduction are the main value channels.

It is best for operations teams that already know process volumes and need to estimate whether automation economics hold after platform run cost. The model captures both speed gains and quality gains.

Monthly gross savings

$32,780.00

Monthly net savings

$27,780.00

Annual net savings

$333,360.00

Payback period

2.34 months

How This Model Works

Computes labor-time savings from automated process volume and manual handling time.

Adds rework savings from baseline error rate and rework effort assumptions.

Subtracts recurring platform cost and estimates payback on implementation spend.

Field Definitions

Use these definitions to set assumptions consistently before comparing results across teams.

Process volume / month

Monthly item volume for the process targeted for automation.

Manual handling time / item (min)

Current average human handling time per item before automation.

Current error rate

Percent of items that currently require correction or rework.

Rework time per error (min)

Average time needed to correct a single error event.

Automation coverage

Percent of process volume expected to flow through automation reliably.

Loaded hourly cost

Fully loaded labor value for the team handling this workflow.

Platform run cost / month

Monthly operating spend for software, infrastructure, and support.

Implementation cost

One-time delivery cost to build and deploy the automation program.

Frequently Asked Questions

+Why include rework reduction?

Automation value often comes from quality improvement, not just speed.

+What does coverage represent?

The share of process volume realistically automated by the target workflow.

+Is this LLM-specific?

No. It applies to broader process automation, with or without LLM components.