Value streams represent a project management style that prioritizes delivering value for customers and working in the most efficient way possible. Applying the value streams framework to software development integrates with Lean Thinking and DevOps principles. The main goal of organizing workpieces in multiple value streams that can easily coexist is to provide better and faster output that you can keep track of at any given time.
To do so, you need specific metrics that can assess the status of your workflows and the efficiency and velocity of your engineering teams’ deliveries. Waydev is an engineering management analytics platform that measures development value stream metrics. This will help tech organizations to frame and optimize these streams in a clearer way and increase their DevOps teams’ performance using specific data. With its intuitive interface, real-time reporting, and customizable dashboards, Waydev makes it easy for organizations to track and improve their metrics. It integrates with leading tools like GitHub, GitLab, and Jira, making it a complete solution for measuring and improving your development value stream.
In this article, we will define the main value stream metrics and show you how using them can improve your capabilities of delivering value to gain customer satisfaction and scale your business.
Value streams are a concept derived from Lean thinking that entails organizing project management around adding value for customers. A value stream reunites the people, resources, and tools necessary for transforming a business idea into a finished product while increasing employee happiness.
In software development, this process generally starts with a business idea or a customer request, and it continues with the information flow – meaning to create a value stream map that traces:
Once you’ve mapped the development value streams and set them in motion, you also need specific metrics to keep track of your progress and identify where the process is stagnant. But looking at these metrics in an isolated way means nothing unless you place them in context. This entails having an overview of all the collected data provided by these metrics at hand and being able to make sense of their significance. For this to happen, you need data that is automatically fed into comprehensive dashboards such as the ones Waydev provides, giving you an overview of the workflow progress. This is where value stream management comes into play because it provides you, as a tech executive, a clear path to successfully planning the necessary steps for software product release.
Applying value stream management in a successful way means understanding that these streams are not a rigid pattern that needs to stay the way it was first designed, but rather it’s a dynamic framework that should be adjusted and improved as you. This is why you should use metrics to assess the status of your value streams – they give you an idea of what you can improve to add value for customers, which is the ultimate goal. For example, reducing the wait time between handoffs from one team to another, identifying bottlenecks in the deployment process, or lowering the time it takes for customers to find value in using new features can all contribute immensely to the overall success of your endeavors.
The entire value stream in software development is typically measured using a range of metrics that track the flow distribution of value through the development process. These may include lead time, cycle time, and time-to-market, as well as quality measures such as defect rates and customer satisfaction. Other important metrics can include productivity, throughput, and resource utilization.
The goal of measuring value streams is to identify bottlenecks, optimize workflows, and increase the speed and efficiency of software delivery. By tracking these metrics over time, software development teams can make continual improvements in their processes and make data-driven decisions that impact the entire organization.
There are a number of metrics that help you track the status of your applied value streams. These can be both flow metrics that show the velocity and efficiency of your value stream and mapping metrics that define the flow of work through the DVS. Each type has specific metrics that can offer specific data to better understand how value streams can scale your business.
By using value stream flow metrics, you can document each step of the process and find ways to improve workflow where this need arises.
Lead Time is a fundamental value stream metric as it measures the velocity of your entire deployment process. Lead Time tells how long it takes for the engineering team to take a request from submission to delivery, going through stages such as planning, coding, and testing all the way up to releasing the new feature.
A lower Lead Time is a good indicator that your teams are effective and can deliver results in a fast-paced environment. DevOps teams that integrate lean-agile practices easily achieve a lower value of this metric because they organize their work in smaller batches. This entails work pieces going through the process quicker, from request to delivery, so Lead Time will be lower.
Cycle Time is a metric that tells you how long it takes to deliver value to customers since the work begins. It is a subsidiary of the previously mentioned Lead Time, but it doesn’t include the beginning stages of the value stream, such as planning. This metric helps you see the amount of time needed from the first commit to releasing, and it’s an indication of agile teams’ efficiency. It is also useful to identify bottlenecks in the flow and what could be causing delays in the value stream.
Deployment Frequency is one of the four fundamental DORA Metrics, a concept that is derived from Lean manufacturing principles, and it’s used to measure performance. DF tells you how often DevOps teams release quality code into production within the value stream.
High-level teams will release value to customers multiple times a day, while lower-performing ones only once per month or less. This depends on the batch sizes, but DevOps practices encourage smaller batches, so frequent releases are very doable. You can also increase Deployment Frequency by implementing CI/CD pipelines and keeping value streams flowing.
Throughput measures the total number of items that are completed within a value stream over a certain period of time. This metric speaks about how effective your teams are in delivering finished products to customers. It measures the output that engineering teams are capable of delivering, and it’s an important overview of teams’ performance.
Work in Progress Limits refers to the fact that teams and organizations set in order to limit the number of workpieces that are open in a certain time interval. By using this concept that derives from Lean thinking, you can focus on a certain amount of work at a time, avoiding exceeding the teams’ capacity and energy to deliver quality and speedy code. This can improve the flow of work in value streams and help you see the bigger picture of the entire process.
Defect Density is a metric that tells you how many defects or failures there are in a given amount of work. This number is generally calculated per module or, more often, per thousand lines of code (KLOC). This number speaks to the efficiency of your team, and it can increase proportionally with the amount of work or when you deal with lower-skilled DevOps teams.
Deployment Success Rate measures what percentage of your teams’ released code is successful. Depending on how effective engineering teams are in delivering quality code in a timely manner, this metric should indicate a pretty high number, often over 90%.
Mean Time to Recovery is one of the four DORA Metrics that represents a staple in measuring DevOps team performance. This particular metric speaks to downtime and how long it takes for your teams to solve issues, and how responsive and effective they are in restoring the system. Elite performers will fix issues in less than one hour, thus reducing downtime and customer frustration to a minimum.
Time to First Value is the amount of time measured between the moment your customers make a purchase of your product or a new feature and when they get value. Think of it this way: it’s not enough to just give your customers products but also that they get actual value from using the said item. You should consider that customers generally have a limited amount of patience when it comes to getting satisfaction with what they paid for. The lower Time to First Value metric is, the happier your clients are.
Value Stream Mapping refers to a technique derived from Lean manufacturing concepts. Mapping means setting a clear path for getting a product released from start to finish. Doing this provides a way to analyze and document each stage of the value stream, starting from the preliminary ones all the way through delivery. VS mapping metrics give you a measurement of how this process is going and where there are issues.
Code review time is a metric that tells you how much time is spent on code reviews. The latter can detect issues and sources for delays in the workflow and can ensure the quality of code. Ideally, the time spent on code reviews should range between 60 to 90 minutes.
Waydev can help you identify possible sources of delaying your deployment process, such as the code review feedback time. This data could help you make the PR workflow smoother and improve your overall value stream.
Waydev can provide data to understand how long it takes to go from code review feedback to code commit. If this stage is very slow, it could affect your delivery process and have an impact on how well your value stream is put in motion.
Waydev can help you identify the bottlenecks in your development process that is slowing down your code commit to building time. It provides detailed insights into your team’s coding activities, including commit frequency, code churn, and code review feedback. You can use this information to identify areas of improvement and optimize your development process to reduce build time.
Analyze your codebase: Waydev can help you identify the size and complexity of your codebase and pinpoint areas that may be contributing to long build times. For example, you can use Waydev to identify large or complex files that are slow to compile and focus on optimizing those files.
Identify slow tests: Slow-running or problematic tests can significantly increase build times. Waydev can help you identify which tests are the slowest or most problematic, so you can focus on optimizing them.
Waydev can help you identify the factors that are slowing down your build time to deploy time. It provides insights into your team’s deployment activities, including deployment frequency, deployment success rate, and deployment time. You can use this information to optimize your deployment process and reduce the time it takes to get your code into production.
Waydev can help you track the impact of your code changes on customer feedback. It provides insights into how often your code changes result in customer-facing features and how quickly those features are adopted by customers. You can use this information to prioritize your development efforts and make sure you’re delivering value to your customers as quickly as possible.
Applying development value stream metrics to your workflows brings many benefits to the table in terms of delivering quality code faster and turning it into value for customers as soon as possible. Effective value stream management can help executives streamline the continuous delivery of new features and add more value where adjustments must be made.
In conclusion, measuring the metrics of the development value stream is crucial to improving software development and delivering better products. The value stream flow metrics and value stream mapping metrics provide key insights into the effectiveness of the development process. Engineering management analytics platforms like Waydev make it easy to measure and improve these metrics. By using the right tools and making adjustments accordingly, organizations can optimize their development value stream, deliver better products, and improve overall customer satisfaction.
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