Defining success in software development is a complex and multifaceted task. Inevitably, each software project will measure success in different ways.
In a sector known for high performance and workplace productivity, clearly defined metrics have been key to the success of projects large and small. An insightful metric lets developers know what’s expected of them and allows you to judge the quality of a software product.
There are countless technical metrics for performance, reliability, and security that developers can use to determine the success or failure of a piece of software and compare this to the competition.
As well as technical metrics, which lend themselves to automation and require the most input from coding teams, there are also business process-oriented and more customer-centric metrics that assess the user experience of a piece of software.
When initiating measurement procedures, just be sure to avoid using metrics to set targets arbitrarily. Instead, use them as a measurement of the health of processes and their results to seek improvement in discussion with the relevant teams.
This article covers three key metrics that can be measured to assess the success of a software development process from a whole-project perspective.
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Arguably the ultimate measure of success in software development is how satisfied and engaged end-users are with the final product. This includes responses to the initial release of a piece of software, but you should also keep track of how customers experience updates and patches. For Software as a Service, or on-demand software products, you will need to measure customer satisfaction with the performance of your technology continuously.
Customer satisfaction can be understood through the completion of surveys. A widely employed and respected metric for customer satisfaction is the Net Promoter Score (NPS), a customer loyalty and satisfaction measurement taken by asking customers how likely they are to recommend your product or service to others on a scale of 0-10. NPS is calculated as a value ranging from -100, indicating no customers would recommend a product to others, to +100, meaning all customers would be likely to recommend.
Of course, NPS alone is of relatively little use as a pointer for further improvement. To get the most out of customer surveys, the results need to be contextualized.
For example, if you’re attempting to measure the success of a voip solutions for small business, additional information such as whether the customer is using the best VoIP router or not is also needed.
For this reason, consumer surveys rarely only ever collect an NPS but will also ask other questions. The best surveys provide space for recommendations that can’t be communicated quantitatively. Continuing with the VoIP example, if customers were happy with general software performance, but most also wanted call recording functionality, metrics alone wouldn’t pick up on this.
Test coverage is a sort of meta-metric that determines how well an application is tested against its technical requirements.
Although related, test coverage differs from code coverage, in which the idea is to measure the percentage of lines and execution paths in the code covered by at least one test case. While code coverage is the responsibility almost exclusively of developers, test coverage is a more holistic metric that belongs to any comprehensive quality assurance program.
The collation of both test coverage and code coverage data is amenable to different types of testing technology that uses scripted sequences to examine the software and then reports on what’s been found.
Software engineers will frequently refer to test coverage when they really mean unit test coverage. Unit tests assess very small parts of an application in complete isolation, comparing their actual behavior with their expected behavior. This means that, when unit testing, you don’t typically connect your application with external dependencies such as databases, the filesystem, or HTTP services.
On the other hand, true test coverage tells you how much of your codebase is covered by all types of tests—unit, integration, UI automation, manual tests, and end-to-end acceptance tests. It’s a useful way to reveal quality gaps, and low test coverage is an indicator of areas where your testing framework needs to be improved.
Software quality assurance is a process that checks that all software engineering processes, methods, activities, and work items are monitored and comply with the defined standards. Deploying a quality assurance plan for your software product requires open communication across multiple teams.
Many software developers will use a cloud communications platform like a voicemail service for business to facilitate remote collaboration. But with remote work more widespread, the quality of software quality control mustn’t lapse. Engineers should adapt and make their quality control procedures more stringent and metric-based.
Ultimately, buggy or defective software is bad software. Measuring the number of bugs discovered after release is a good way to keep track of your quality assurance program. A high or increasing number of escaped defects can be an indicator that you’re not testing enough or that you need to implement some extra performance review prior to releases and updates.
Depending on whether your company is a start-up or a well-established software developer, you will have different quality assurance mechanisms and defect detection checks in place. Just be sure not to cut corners with this vital aspect of software development. If faulty or glitchy products go to market, the damage it does to your reputation can take years to overcome.
Remember that these three metrics are intended to be helpful for allowing you an overview of your entire development cycle. As part of an overarching business strategy, they will need to be aligned with the processes of individual teams who will each have their own standards by which they measure success. The only way to do this is to have the best project management procedures in place and great team communication. These should allow your entire software development process to knit seamlessly together.
Author: Grace Lau - Director of Growth Content, Dialpad
Grace Lau is the Director of Growth Content at Dialpad, an AI-powered cloud communication platform that enables streamlined whiteboard app and contact center outsourcing. She has over 10 years of experience in content writing and strategy. Currently, she is responsible for leading branded and editorial content strategies, and partnering with SEO and Ops teams to build and nurture content. Here is her LinkedIn.