What is chaos engineering? It is the practice of managing the “chaos” in your production to build a stronger, more resilient system.
Metrics Engineering 101: How to Gear Up for Present and Future Success
In a world where data is a new oil, the ability to analyze and measure it is a privilege. Data empowers businesses to gain a competitive edge by tapping insights into their operations, measuring success, and making data-driven decisions.
In software development, metrics play the same role by providing evidence-based insights into the team’s performance and productivity as well as the project’s progress. Even though engineering metrics are essential to project management and product development, they unfortunately seem not to be the first priority. Without the right metrics, there will be no objective way to assess the stages of an SDLC or to identify where improvement is needed.
That’s why, in this piece, we are not only going to explain to you what metrics engineering actually means, what metric matters the most to one project, and guide you on how to get started with metrics engineering in a practical way. So, buckle up and get ready for all the essentials to navigate the complex terrain of engineering metrics and metrics engineering.
Software Engineering Metrics & Metrics Engineering: What Exactly Are They?
It is not by any mistake to have these two terms together. They seemingly sound confusing and are often mistaken by outsiders as a falsehood. However, they are completely different things that we are about to clear up right now.
What Are Metrics for Software Engineering Teams or Projects?
Let’s start with what insiders call software engineering metrics. Sometimes, the term can be project metrics, process metrics, performance metrics, development team metrics, or others alike.
In the simplest terms, these metrics are the standard benchmarks or key performance indicators (KPIs) often used in the software development process to gauge actionable insights into the team performance, the software development process, and the product quality. Examples of metrics could be the number of user stories completed, the current progress rate, or the amount of time taken to finish a software feature.
Why need metrics in the software engineering process? The right metrics provide an objective view for all stakeholders involved.
In finer detail, the robust engineering metrics signify to the project managers the team’s productivity and the progress of the development process, thereby enabling them to grasp the current situation and forehandedly make data-driven decisions. For development teams, metrics enable them to identify bottlenecks in the engineering workflows and measure how much effort it takes to deliver a feature that works.
Specific organizational objectives determine each key performance indicator (Engineering KPI), and all will correlate with the purpose of measurement in various engineering disciplines (could be software development, system engineering, software maintenance, and more).
Then, What Is Metrics Engineering?
When you reverse the term engineering metrics, we have a term that is all about mapping out proper rules and measurements settled upon the engineering processes and implementing them. In other ways, metrics engineering is the standard and method to discipline all areas of development cycles with the final goal of tracking the progress, monitoring the team’s performance (both team leader and team member), and guaranteeing software quality.
At the end of the day, what makes them distinct? In the easiest way to understand, engineering metrics are what you use to measure the progress of your team, while metrics engineering is what you use to define them. You got it accurate, right?
What Are the Fundamental Metrics to Measure from a Software Engineering Team?
An engineering metric can be graded as either qualitative or quantitative. Qualitative metrics are the data that cannot be measured in numbers (e.g., customer experience, customer satisfaction). Quantitative metrics, on the other hand, are the actual values or counts of a given process or action taken by the team (e.g., how many user stories are completed per sprint).
One requisite condition you must meet before getting your hands on mapping out metric measures is to know what value means the most to your software development project and add it to your prioritized list. An important engineering metric can be either almost identical for many projects or unique to each one of them. Basically, it is up to you to determine the right engineering metrics that are the most relevant and meaningful to your team. So, let’s outline the common metrics that we think are valuable to measure for all projects alike.
In the software development context, lead time is a parameter to measure the total amount of time taken to deliver a single feature in real time, starting from the first line of code written until the team releases code. The shorter the length of time to complete one request, the faster your response to customer feedback and your software delivery process are.
The metric is defined as the time elapsed for one cycle of an operation or process to be completed. Cycle time is usually divided into two parts - the average of all tasks and the median task or unit of work. The cycle time enables engineering teams to track how much effort it takes to finish one cycle of a workflow, and it helps to identify which parts of the process may need more resources or optimization.
Technically, throughput indicates the amount of engineering work that can be completed within a certain time frame. In software engineering, throughput is the number of features or tasks that the developers complete in a given period or sprint. Thus, the metric highlights the software development team’s productivity and efficiency.
The quality of any piece of code is determined by how well the code performs and how secure it is. It is fundamental for engineering teams to track and monitor these metrics, which measure quality assurance indicators such as test coverage, number of bugs encountered within a sprint, or defect density rate. The higher the code quality score, the better your team can deliver high-quality software with fewer errors and issues. In contrast, high code churn can indicate instability in the development process and result in code being rewritten or discarded.
Work In Progress (WIP)
The number of tasks or user stories that are currently being worked on. The metric is often used to determine the amount of work your team can effectively handle without overloading them. Additionally, this is a balance metric that forms the foundation for engineering leaders to evenly distribute the team’s workload and guarantee that no critical or urgent duties are overlooked.
The development cost is always a crucial metric for any project. It represents the total amount of money spent per month, quarter, or year on the development activities. Costs partially yet accurately reflect a project’s or team’s progress by measuring performance and consumption of resources. Thus, the cost metric is one of the engineering KPIs for financial planning and alignment of budgeting with the overall strategy and the final deliverable.
Shortly known as CI, continuous improvement is more of a qualitative metric that is utilized to monitor and assess the non-numerical progress of a project, a team, or a development cycle.
Such a team’s metrics showcase the degree to which a whole team, as well as all the team members, including team leaders, are committed to learning from mistakes, adapting to new challenges, and working on improvement. From there, engineering teams can identify any potential areas of improvement that can help boost team productivity, thereby making informed decisions on innovation.
The number of times engineers deploy code to production is one of the key components of the development cycle as well. This metric is used to track how often your team releases features (e.g., once a day, twice a week).
Deployment frequency provides engineering teams with an insight into the performance and pace of work, as well as highlights any issues that could be slowing down the completion time for each feature or task. On top of that, tracking the number of deployments helps increase transparency and predictability in terms of delivery for stakeholders.
Depending on the engineering organizations’ and project leaders’ wills, metrics are modifiable and can be reshaped to fit the project’s exact needs, and these are just a few typical ones. To define the right metrics and apply them effectively, managers and leaders can use some help, which is the tips outlined right after this section.
Tips for Setting Up & Tracking Engineering Metrics
Software development requires well-established steps to succeed, and so do metrics engineering and engineering metrics. Use some of the following tips, and you will be able to come up with measurable yet realistic metrics that accurately reflect your project’s everything.
Tip #1: Metrics Must Be Realistic & Understandable
Any parameter or statistic that proves valuable must be derived from real insights. Insightful metrics should be easy to comprehend by both technical and non-technical teams. You can link the metrics to your business priorities. But do not set your metrics at the same level as your ideal expectations because it is surreal and will not bring real value and improvements to your product.
Tip #2: Do Not Use Metrics to Punish
Metrics are created in the first place to be guidance and consultancy, not as a punishment. So, do not get it wrong. It helps to keep each and every team member posted on the current progress, what needs to be done, and what is not, with the common goal to get the best result. Therefore, you intentionally or unintentionally need to avoid using the engineering metrics as a means of penalizing your team or any other way around. Keep this in mind even when you are brainstorming the metrics. Instead, create and use the metrics as goals and motivation for your engineering team.
Tip #3: Regularly Evaluate Metrics
You know what? Your project direction may change over time due to various factors - it could be subjective or objective, and so should your metrics. It means you need to review the efficacy of your metrics every now and then. Be sure that you are measuring the right things at the right time and that your engineering KPI dashboard is making sense to everyone involved in the project.
Tip #4: Balance Quality & Quantity
It is a common mistake to rely more on quantitative metrics versus qualitative metrics. For software development, you need to balance between these two things and measure both of them as much as possible. That way, you can get a clear insight into your team’s performance in terms of quality or quantity and then use that insight to make informed decisions.
Tip #5: Do Not Rely on Only Metrics to Judge Performance
Metrics are a great tool to track progress and help engineering teams work efficiently. Still, you should remember that these metrics should not be solely used to judge an engineer’s performance on the job. They can only be used as guidance or indicators of progress and performance. Therefore, they must not be treated as an absolute measure of individual performance, which should be evaluated with other factors.
Tip #6: Ask for Expert Help
Metrics engineering is not everyone’s cup of tea, and if you feel intimidated or unable to come up with the right metrics for your project, never hesitate to consult industry experts like Orient Software. Obviously, no one can understand your project better than you, and with an expert point of view from our experts, you can set the metrics right and help your team reach the performance goals. For further details, let’s talk.
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