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title: “DORA - Lead Time for Changes” description: > DORA - Lead Time for Changes sidebar_position: 27

What is this metric?

The median amount of time for a code change to be deployed into production.

Why is it important?

This metric measures the time it takes to a code change to the production environment and reflects the speed of software delivery. A lower average change preparation time means that your team is efficient at coding and deploying your project.

Which dashboard(s) does it exist in

DORA dashboard. See live demo.

How is it calculated?

This metric is quite similar to PR Cycle Time. The difference is that ‘Lead Time for Changes’ uses a different method to filter PRs.

1. Find the PRs' associated deployments whose finished_date falls into the time range that users select
2. Calculate the PRs' median cycle time. This will be the Median Lead Time for Changes.

PR cycle time is pre-calculated by the dora plugin during every data collection. You can find it in pr_cycle_time in table.project_pr_metrics of DevLake's database.

Below are the benchmarks for different development teams from Google‘s report. However, it’s difficult to tell which group a team falls into when the team's median lead time for changes is between one week and one month. Therefore, DevLake provides its own benchmarks to address this problem:

Groups	Benchmarks	DevLake Benchmarks
Elite performers	Less than one hour	Less than one hour
High performers	Between one day and one week	Less than one week
Medium performers	Between one month and six months	Between one week and six months
Low performers	More than six months	More than six months

Data Sources Required

This metric relies on deployments collected in multiple ways:

• Open APIs of Jenkins, GitLab, GitHub, etc.
• Webhook for general CI tools.
• Releases and PR/MRs from GitHub, GitLab APIs, etc.

Transformation Rules Required

This metric relies on the deployment configuration in Jenkins, GitLab or GitHub transformation rules to let DevLake know what CI builds/jobs can be regarded as deployments.

SQL Queries

If you want to measure the monthly trend of median lead time for changes as the picture shown below, run the following SQL in Grafana.

-- Metric 2: median change lead time per month
with _pr_stats as (
-- get the cycle time of PRs deployed by the deployments finished each month
	SELECT
		distinct pr.id,
		date_format(cdc.finished_date,'%y/%m') as month,
		ppm.pr_cycle_time
	FROM
		pull_requests pr
		join project_pr_metrics ppm on ppm.id = pr.id
		join project_mapping pm on pr.base_repo_id = pm.row_id and pm.`table` = 'repos'
		join cicd_deployment_commits cdc on ppm.deployment_commit_id = cdc.id
	WHERE
		pm.project_name in ($project)
		and pr.merged_date is not null
		and ppm.pr_cycle_time is not null
		and $__timeFilter(cdc.finished_date)
),

_find_median_clt_each_month_ranks as(
	SELECT *, percent_rank() over(PARTITION BY month order by pr_cycle_time) as ranks
	FROM _pr_stats
),

_clt as(
	SELECT month, max(pr_cycle_time) as median_change_lead_time
	FROM _find_median_clt_each_month_ranks
	WHERE ranks <= 0.5
	group by month
)

SELECT
	cm.month,
	case
		when _clt.median_change_lead_time is null then 0
		else _clt.median_change_lead_time/60 end as median_change_lead_time_in_hour
FROM
	calendar_months cm
	LEFT JOIN _clt on cm.month = _clt.month
  WHERE $__timeFilter(cm.month_timestamp)

If you want to measure in which category your team falls as in the picture shown below, run the following SQL in Grafana.

with _pr_stats as (
-- get the cycle time of PRs deployed by the deployments finished in the selected period
	SELECT
		distinct pr.id,
		ppm.pr_cycle_time
	FROM
		pull_requests pr
		join project_pr_metrics ppm on ppm.id = pr.id
		join project_mapping pm on pr.base_repo_id = pm.row_id
		join cicd_deployment_commits cdc on ppm.deployment_commit_id = cdc.id
	WHERE
	  pm.project_name in ($project)
		and pr.merged_date is not null
		and ppm.pr_cycle_time is not null
		and $__timeFilter(cdc.finished_date)
),

_median_change_lead_time_ranks as(
	SELECT *, percent_rank() over(order by pr_cycle_time) as ranks
	FROM _pr_stats
),

_median_change_lead_time as(
-- use median PR cycle time as the median change lead time
	SELECT max(pr_cycle_time) as median_change_lead_time
	FROM _median_change_lead_time_ranks
	WHERE ranks <= 0.5
)

SELECT
  CASE
    WHEN median_change_lead_time < 60 then "Less than one hour"
    WHEN median_change_lead_time < 7 * 24 * 60 then "Less than one week"
    WHEN median_change_lead_time < 180 * 24 * 60 then "Between one week and six months"
    WHEN median_change_lead_time >= 180 * 24 * 60 then "More than six months"
    ELSE "N/A.Please check if you have collected deployments/incidents."
    END as median_change_lead_time
FROM _median_change_lead_time

How to improve?

• Break requirements into smaller, more manageable deliverables
• Optimize the code review process
• “Shift left”, start QA early and introduce more automated tests
• Integrate CI/CD tools to automate the deployment process