In today’s fast-paced technological landscape, tomorrow’s products are already at risk of being “old news.” To overcome lengthy production cycles, successful software developers are focusing on efficiency and productivity. Greater efficiency leads to greater productivity, accelerated product life cycles, shorter time to market and, ultimately, an increased bottom line. Engineering team managers can use many metrics to gauge efficiency and productivity along the way. But of course, the ultimate measure of a software application’s success is whether it meets end users’ needs and improves the organization’s business results.
Tracking the metrics
Keeping track of certain metrics is an important step in making sure your company’s software engineering team is performing as efficiently and productively as possible. Here are some of the most essential metrics for developers to track:
- Lead time — Lead time is a general measurement of the amount of time that passes from product concept to final delivery. It will depend on project complexity and the number of engineers working on the project, both of which will, in turn, affect project cost. By tracking project lead times, developers can better predict time to market for current and similar future projects.
- Impact — Impact measures how much changes to the code affect the overall project. It is also a measurement of how those changes impact the engineers who make them. This is an important metric to measure as code changes can lengthen the product’s time to market, making it costlier. In addition, developers could be dedicating too much time to making certain changes, negatively affecting their productivity and adding to such delays. Therefore, large changes, such as those that involve more code or files, and changes that are more difficult to make have higher impact scores.
- Churn — Churn is the percentage of time developers spend editing, adding to, or deleting their own code. A high code churn indicates rework and may mean something is wrong in the development process.
- Efficiency — Efficiency measures the amount of each engineer’s “productive” code, or code that provides business value. An engineer creating a whole new solution or implementing sweeping code changes will likely deal with lots of trial and error with a low efficiency rate. An engineer who is making a lot of small changes with a low churn rate, however, is likely to have a higher efficiency rate.
- Cycle time — Cycle time, part of lead time, is how long it takes to make a desired change to the software and put it into production. When a team is using DevOps and employing continuous integration, continuous delivery (CI/CD) practices, they can often measure cycle time in minutes rather than months.
- Open and close rates — The open and close rate is the number of issues or problems developers report and fix or close over a period of time.
- Production — Production is a downtime analysis and includes mean time between failures (MTBF) and mean time to recover/repair (MTTR). These measure how well software performs in a production environment.
TEAL to the Rescue
What does improving software engineering efficiency and productivity look like in a real-life situation? The professionals at Parkar Digital used the TEAL test automation solution to solve a problem in the Kronos development process. Kronos is a workforce management software and services company whose leaders needed to test a large set of applications on various frameworks. With such large loads, they needed a more efficient way to test their products. The Parkar experts created a flexible, scalable test solution that was 100% automated as well as reduced defect leakage by 85% and execution time by 90%. The single test solution removes the need for other tool sets, reducing management headaches and enhancing the user experience.
But which metrics are the most important for helping you meet your goals?
Making use of metrics
With so many metrics available to track, it’s important developers don’t get carried away. Only track metrics directly tied to your business goals. Typically, you’ll want to use metrics to judge general trends to see where problems might exist, then do more in-depth research to discover more specific causes for inefficiencies or low productivity. For example, a high churn rate could mean a problem with the development process, such as lack of clarity over requirements or an issue with a specific engineer who might not have the best skills for developing a particular set of code. An engineer with a low churn rate, however, may have developed highly efficient code, or the low churn could indicate that he or she already resolved major issues.
Metrics are great to show the management team, but those who don’t know how to interpret or use them to drive improvements might as well not track them at all. If productivity is not up to expectations or efficiency is lagging, it might be time to take a hard look at the above seven metrics to decipher where problems exist. Developers can then use this information to make positive business changes. Once they understand their strengths and opportunities for improvement, software developers can take action. When they increase software development efficiency and productivity, they can increase product ROI, improve the development process, reduce costs, and better manage workloads.