When you can’t gauge software development productivity and outcomes, you don’t know where you stand against competitors, nor demonstrate the progress of the team to peers, management nor direct reports. Just like you cannot know how fast or slow you're driving without using a speedometer. With the businesses being very agile, engineering is expected to be agile where decision-making is vital. In such situations where you want to make decisions, gut-based decisions can prove costly in lost opportunities, time and money.
…and saves companies from making expensive, ineffective decisions.
The future of performance management is more data-driven, flexible, continuous, and development-oriented, according to McKinsey, as organizations move past the excessively subjective, confusing, and unhelpful ways of measuring employee performance based on guesswork or gut feeling.
Software quality can be differentiated internally and externally. Customers might see what makes a software product high-quality externally, but can’t differentiate between higher or lower quality internally. Not right away, anyway.
Martin Fowler makes a case for high-quality software appealingly. Cruft is the term used to name the difference between the current code and how it would be ideally. If a software code is neatly divided into modules and is clean and easy to follow, it can be revised and comprehended by succeeding developers.
Since customers care that new features are made available ASAP, internal quality makes its case. And so does having the ability to measure it objectively.
Objectivity in software development allows leaders to:
Engineering metrics are elusive, which makes quantifying software development impossible. What is the measure of an effective software development process? How do you identify an elite software engineering team?
In stark contrast to sales and marketing departments identifying KPIs, engineering teams fall short and risk failure. Also, it’s humorous to note that engineering teams that fall short of goals don’t know that they have- due to a lack of quantification. You don’t know when you’ve succeeded, and you don’t know when you’ve fallen short.
Healthy engineering metrics should establish agreed-upon standards, make quantification easy and accessible, and help optimize code production at high quality.
Research by Stripe shows that while the number of developers is increasing year on year at most companies, what’s most important is how they are being leveraged. When their skills are utilized effectively it helps companies differentiate themselves and even enter new markets or product lines. Insightly collects data from developer tools and offers actionable insights in interactive dashboards to facilitate quicker releases, better quality, and increased throughput.
What engineering leaders don’t know can hurt their teams and the company. Data can provide visibility into the working of development teams and engineering processes. It can also reveal where in the process effort is being lost and where one can find efficiency gains
Data also provides potent insights into helping engineering teams improve performance, untangle bottlenecks in the process, leading indicators into software delivery signals, team burnout, and more.
Data-driven engineering uses data from tools that engineering teams use on an everyday basis, such as version control tools like Bitbucket, GitHub, and GitLab or project management tools like Jira to help optimize the productivity of software engineers, which directly benefits the engineers, customers, and the business.
Leverage real-time engineering data for modern data-driven engineering managers with Insightly.