The process of deploying your application to the market is a vital one. Good software delivery follows certain best practices, such as sticking to business goals, adopting early testing, and timing your release. However, there are some software development metrics, along with delivery KPIs, that can help optimize your delivery and maintainability.
Here are 7 key metrics to help measure software delivery performance:
- Time to Value
- Defect Density
- Deployment Frequency
- Lead Time
- Mean Time to Restore
- Change fail rate
Time to Value
Time to Value is a measure of the amount of time it takes for new customers to get value from the software. This metric can track how early you deliver value to customers, which is measured from the start of the development process to the deployment stage. When it comes to SaaS, many customers will have a low tolerance for delays, so a short TTV will allow customers to receive their return on investment much faster and be more satisfied.
The defect density is fairly self-explanatory – it’s the measure of how high quality your software delivery is. This is where defects will make themselves present, and this can be tracked over time to see if your delivery and machinability improves. If there are many defects, not only can this be a red flag, but it will also mean the “mean time to restore” metric below is all the more important.
Deployment frequency helps get a grasp on batch size; albeit in a roundabout way. The higher the deployment frequency, the smaller your batch size. Of course, small batch sizes reduce risk, overhead, and cycle times. With tangible products, it’s much easier to measure batch size instead, but this is difficult in software. Think of deployment as software deployment to an app store, production, and so on. This could take into consideration versions control commits.
Lead time is the time it takes from where a customer makes a request to when the request is satisfied. A shorter lead time (in the context of software delivery) can mean getting faster feedback, making it easier to course correct early on, and can also identify defects faster.
Mean Time to Restore
There are always going to be defects and failures with software – this is a given. But the meantime to restore can help measure how quickly it takes for a service to be restored. For example, in the event of an unplanned outage, how quickly are things back up and running. This is a good measure of reliability and reflects the overall stability of the product.
Throughput can help measure the total number of changes that can be finished and produced in a given time interval. Thus, increasing the efficiency of delivery would likely reflect better throughput. This can become your key measure of how much value you are delivering.
Change fail rate
It’s important to measure how many of your changes to a system or software results in production failure. This is a quality metric in which you can see how many changes you make actually degrade the end product, which can help identify lackluster delivery quality.