Kanban Cycle Time & Throughput Coach

Kanban Cycle Time & Throughput Coach | Online Free Tool | Elysia Tools

Tool usage guide

Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Category: Data Analysis
Input types: textarea, select, text, checkbox
Output type: html
Sample coverage: 4
API ready: Yes

Overview

The Kanban Cycle Time & Throughput Coach parses issue tracking timestamps from CSV exports to generate agile flow metrics, including lead and cycle time percentiles, aging work in progress (WIP), throughput histograms, a Cumulative Flow Diagram (CFD), and Little's Law consistency validation.

When to use

Analyzing team delivery predictability and cycle time percentiles (p50, p85, p95) from Jira or issue tracker CSV exports.
Investigating bottlenecks, aging in-progress items, and flow stability during sprint retrospectives or agile coaching sessions.
Checking process stability and throughput trends using cumulative flow diagrams and Little's Law validation.

How it works

1Paste or import your work item CSV containing identifier, title, created, started (optional), and resolved (optional) timestamps.
2Configure your throughput aggregation bucket (daily, weekly, or monthly), target percentile cutoffs (such as 50, 85, 95), and an optional analysis snapshot date.
3Set fallback options like using the creation date as work start if explicit started timestamps are missing.
4Review generated metric cards, WIP aging tables, throughput breakdown charts, the visual Cumulative Flow Diagram, and Little's Law check results.

Use cases

Agile team retrospectives evaluating service level expectations (SLE) against actual p85 cycle times.
Engineering managers monitoring weekly throughput volume and identifying stalled in-progress tickets.
Delivery coaches validating flow continuity and work accumulation trends using Cumulative Flow Diagrams.

Examples

1. Jira Sprint Export Analysis

Agile Coach

Background

A software team wants to evaluate delivery predictability over the previous month using their exported Jira sprint history.

Problem

Manual cycle time calculation in spreadsheets does not provide percentile distribution, WIP aging, or CFD diagrams.

How to use

Paste the sprint CSV into the text area, set the throughput bucket to 'weekly', specify percentiles as '50,85,95', and set the analysis clock to the end of the sprint period.

Throughput bucket: weekly, Percentiles: 50,85,95, Analysis clock: 2026-07-20, Treat Created as work start: checked

Outcome

Generates cycle time p50/p85/p95 metrics, a WIP aging breakdown for open items, weekly throughput bars, and an interactive CFD.

2. Lightweight Issue Tracker Export with Missing Start Dates

Engineering Lead

Background

A team using a simple bug tracker only captures issue creation and resolution timestamps.

Problem

The team needs daily throughput statistics and lead time percentiles without an explicit in-progress start timestamp.

How to use

FAQ

What CSV columns are recognized by the tool?

The parser accepts standard headers for item identifier, summary or title, created date, started date, and resolved date, including Jira-style CSV exports.

What happens if my CSV does not contain a Started date column?

Enabling the 'Treat Created as work start' option will calculate cycle time and WIP metrics using the creation timestamp as an approximation.

Why would I set a specific Analysis Clock date?

Pinning the 'asOf' date ensures reproducible WIP age calculations for historical reporting instead of calculating age against the current date.

How are cycle time and lead time percentiles calculated?

The tool computes duration across completed work items and calculates distribution percentiles based on your configured percentile thresholds (e.g., 50th, 85th, and 95th percentiles).

What does the Little's Law check evaluate?

It tests the mathematical consistency between average WIP, average throughput, and average cycle time across your dataset to highlight delivery flow equilibrium.

Throughput bucket: daily, Percentiles: 50,85, Treat Created as work start: true

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Continue with connected tools and hubs

Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Overview

When to use

How it works

Use cases

Examples

1. Jira Sprint Export Analysis

2. Lightweight Issue Tracker Export with Missing Start Dates

FAQ

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