New Relic : Empower Your Engineers With A Data-Driven Approach

What you don't know can hurt your teams-and your company's bottom line. That's why successful companies use data to empower their software engineers and to measure their impact. Ideally, this data provides powerful insights on what your software engineers should do to optimize application performance, build new features, and prevent problems that can lead to service outages, bugs, and lost customers from suboptimal experiences. Whether that's analyzing website traffic to optimize the performance of your web pages, benchmarking to ensure that your code runs efficiently, or using observability to detect anomalies, you need a continuous stream of all of your telemetry data-metrics, events, logs, and traces-to empower your engineers to plan, build, deploy, and run great software.

Data-driven engineering is the practice of using the telemetry collected from engineering tools and platforms to optimize the work of your software engineering teams, which leads to direct benefits for your teams, customers, and bottom line.

Benefits of data-driven engineering

Here are a few of those benefits:

• Using a data-driven approach means you are using clear, concrete insights from all of your telemetry to drive business decisions, not relying on incomplete information or gut feelings.
• Making the data behind your decisions visible enables all of your engineers across every stage of the software lifecycle to see, understand, and optimize performance based on data.
• Measuring customer impact with data can illuminate what your customers need and can ensure that your business decisions, products, and services solve those needs.

In fact, according to a report from Accenture, 'data-driven organizations with an enterprise strategy are actually growing at a rate of more than 30% annually.'

However, despite the clear benefits of data-driven engineering and the fact that modern organizations use data for just about everything in their businesses, the concept is often poorly defined, which makes it challenging to implement.

How to implement data-driven engineering

Ultimately, data-driven engineering asks the following questions:

• Are your teams taking on the right projects?
• Are your teams doing work that has the desired effect on end-users?
• Are your teams' resources properly allocated against business goals?

If you are using data to answer these questions about your software engineering teams, then you're already practicing data-driven engineering and likely seeing noticeable benefits as a result. However, if you aren't answering these questions through an empirical, data-driven process, you likely have blind spots that limit the full potential of your engineers and your company as a whole.

So how do you set up a process that actually answers those questions using a data-driven approach? To implement data-driven engineering across your organization, answer five critical questions.

What data should you collect to meet your goals?

You likely already have business key performance indicators (KPIs), but do you have KPIs for your software engineering teams as well? You should define concrete goals for them and then design metrics that measure those goals. They can even be similar to the goals of other teams in your organization. For instance, increasing user signups might be a KPI for your marketing and sales teams. It might not seem like an obvious goal for your software engineering teams, and yet your developers are the ones actually implementing the code for the signup page and experience.

In addition to establishing more general organizational goals, you can implement specific goals that apply only to software development. For example, you might include goals for the overall reliability and uptime of individual pages and customer engagement with specific pages. The chart below illustrates useful telemetry data that you can collect at each stage of the software lifecycle.