Mastering Lead Time for Changes to Improve Software Delivery

Introduction

To deliver new features and improvements quickly, it’s essential to have a clear understanding of how long it takes for changes to be deployed from development to production. This is where Lead Time for Changes (LTFC) comes in. Let’s explore how improving LTFC can help software development teams improve their performance.

What is Lead Time for Changes

Lead Time for Changes is a software development metric that measures the time it takes to implement a code change from the moment it is requested until it is deployed into production. This metric includes all the necessary steps for the change to be implemented, such as code review, testing, and deployment.

In other words, Lead Time for Changes measures the speed at which changes are delivered from idea to production. 

The metric helps teams to identify bottlenecks and optimize their development processes for faster and more efficient code releases. Additionally, it can be used to set realistic expectations and make informed decisions regarding timelines for feature delivery and project completion.

Why to aim for low Lead Time for Changes?

A low Lead Time for Changes helps to reduce waste and optimize the software delivery process. By identifying and eliminating bottlenecks, you can work more efficiently and reduce the amount of time and resources required to deliver new features.

Additionally, a low Lead Time for Changes can help you to better manage risk by enabling more frequent and smaller releases. This allows for faster feedback and testing, which in turn mitigates the risk of releasing major bugs or issues.

Software delivery performance perspective  - benefits of measuring and improving Lead Time for Changes

Measuring and improving Lead Time for Changes is a key driver for improving software delivery performance:

Faster feedback loops

Measuring Lead Time for Changes allows you to identify and address issues more quickly, leading to faster feedback loops and a more responsive development process.

Continuous improvement

You can spot areas for improvement in your development process and make data-driven decisions to optimize the workflow and achieve continuous improvement.

Reduced costs

You reduce the costs associated with development, testing, and deployment, as well as reduce the risks of delayed releases and missed deadlines.

Improved customer satisfaction

Faster Lead Time for Changes means that features and updates can be delivered to customers more quickly, improving customer satisfaction and loyalty.

Competitive advantage

Delivering high-quality features and updates faster than your competitors, gives you a significant competitive advantage in the marketplace.

Lead Time for Changes - limitations

Like any metric, Lead Time for Changes has its limitations. Here are some of them to keep in mind:

Narrow focus

While Lead Time for Changes can provide valuable insights into software delivery performance, it's important to remember that it's just one metric. You should avoid focusing too narrowly on it to the exclusion of others, as this could lead to missing important insights into their development process.

Difficulty in measuring

Measuring Lead Time for Changes accurately can be challenging, especially if you don't have consistent processes in place for tracking when work begins and ends.

Lack of context

Lead Time for Changes can tell you how long it takes to deliver a change, but it doesn't provide much context about the quality of the change or the overall impact it has on the software.

Variation between teams 

Different teams may have different development processes, tooling, and levels of expertise, which can make it difficult to compare lead times between teams.

How to derive right conclusions from measuring Lead Time for Changes?

It's important to approach this metric with the right mindset. 

Use it as a starting point

Don’t use Lead Time for Changes as the sole measure of success. Use it as a starting point for further investigation into your team's development process.

Look for trends

Rather than focusing on individual data points, look for trends in your Lead Time for Changes over time. Are your lead times getting longer or shorter? Are there certain types of changes that consistently take longer than others? These trends can help you identify areas for improvement.

Dig deeper

Lead Time for Changes can be influenced by many factors, including team size, development processes, and tooling. If you see a spike in lead time, don't just assume that it's due to a problem with your team. Take the time to investigate the root cause of the issue.

Use it in combination with other metrics

Lead Time for Changes is just one metric in a larger set of software delivery performance metrics. Use it in combination with other metrics, such as MTTR or deployment frequency, to get a more complete picture of your team's performance.

Don't forget about the human element

While Lead Time for Changes is an important metric, it's crucial to remember that software development is a complex process that involves people as well as tools and processes. Don't lose sight of the human element when interpreting your Lead Time for Changes data.

How to measure Lead Time for Changes?

Lead Time for Changes can be calculated by measuring the time from when a change is requested or identified to the time when it is delivered to production. Here are the steps to calculate Lead Time for Changes:

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1. Identify the start and end points of the change request process. This may vary depending on the organization, but it typically starts with a request for change (RFC) and ends when the change is deployed to production.
2. Record the time stamp of the start and end points for each change request.
3. Calculate the time difference between the start and end points. This is the lead time for the change.
4. Repeat this process for all change requests over a given period of time, such as a week or a month.
5. Analyze the data to identify trends and areas for improvement.

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It's important to note that Lead Time for Changes can vary depending on the complexity of the change and the processes involved in delivering it to production. Therefore, it's crucial to measure lead time consistently over time to identify trends and improvements.

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Example

1. A change request is submitted on January 1st.
2. The change is completed and deployed to production on January 15th.
3. The lead time for this change is 14 days (January 15th minus January 1st).
4. Another change request is submitted on January 5th.
5. The change is completed and deployed to production on January 10th.
6. The lead time for this change is 5 days (January 10th minus January 5th).
7. Over the course of January, there were a total of 10 change requests with lead times ranging from 3 to 15 days.

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By analyzing the data, you can identify the changes that require multiple approvals from different teams tend to have longer lead times and may need process improvements to streamline the approval process.

How to maintain low Lead Time for Changes?

Here are some strategies to maintain a low Lead Time for Changes:

Reduce handoffs

Each handoff in the change process increases the lead time. To maintain low lead times, try to minimize the number of handoffs between teams and departments.

Automate processes

Automating repetitive and time-consuming tasks such as testing, deployment, and provisioning can help you reduce lead times.

Prioritize changes

Prioritizing changes based on business value and impact ensures that high-value changes are completed quickly.

Standardize processes

Standardizing processes and using consistent tools and technologies reduces variability and increases efficiency, resulting in lower lead times.

Improve communication

Ensure clear communication between stakeholders and teams to prevent misunderstandings and delays, which can increase lead times.

Monitor and analyze data

By continuously monitoring and analyzing lead time data, you will be able to identify bottlenecks and process improvements that can further reduce lead times.

Alternatives to Lead Time for Changes

Some popular alternatives to Lead Time for Changes include cycle time, Time To Restore Service (TTRS), and Mean Time Between Failures (MTBF).

Cycle time measures the time it takes to complete a specific task or process from start to finish. TTRS, on the other hand, focuses on the time it takes to restore service after an incident or outage. Finally, MTBF measures the average time between system failures.

While each metric provides valuable insights into software delivery performance, the choice of metric depends on your specific goals and needs.

Summary

By reducing Lead Time for Changes, you can improve software delivery performance and respond more quickly to market demands. However, it is important to measure lead time accurately and avoid common pitfalls such as only focusing on optimizing lead time without considering other factors like quality and efficiency. Explore other software delivery performance metrics discussed in this handbook to get a better understanding.