State of DevOps 2019 Says "Excel or Die"

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Aug 29, 2019

Last Thursday, DORA released their 6th annual State of DevOps report, identifying this year’s trends within engineering departments across industries.

The good news: a much higher percentage of software organizations are adopting practices that yield safer and faster software delivery. 25% of the industry is performing at the “elite” level, deploying every day, keeping their time to restore service under one hour, and achieving under 15% change failure rate.

The bad: the disparity between high performers and low performers is still vast. High performers are shipping 106x faster, 208x more frequently, recovering 2,604x faster, and achieving a change failure rate that’s 7x lower.

Accelerate: State of DevOps 2019

This is the first of the State of DevOps reports to mention the performance of a specific industry. Engineering organizations that worked within retail consistently ranked among the elite performers.

The analysis attributes this pattern to the death of brick-and-mortar and the steep competition the retail industry faced online. Most importantly, the authors believe that this discovery forecasts an ominous future for low performers, as their respective industries grow more saturated. They warned engineering organizations to “Excel or Die.”

There are No Trade-Offs

Most engineering leaders still believe that a team has to compromise quality if they optimize for pace, and vice versa– but the DevOps data suggests the inverse. The authors assert that “for six years in a row, [their] research has consistently shown that speed and stability are outcomes that enable each other.”

This is in line with Continuous Delivery principles, which prescribe both technical and cultural practices that set in motion a virtuous circle of software delivery. Practices like keeping batch size small, automating repetitive tasks, investing in quick issue detection, all perpetuate both speed and quality while instilling a culture of continuous improvement on the team.

Thus for most engineering organizations, transitioning to some form of Continuous Delivery practices shouldn’t be a question of if or even when. Rather, it should be a question of where to start.

The Path Forward: Optimize for DORA’s Four Key Metrics

The DORA analysts revealed that rapid tempo and high stability are strongly linked. They identified that high-performing teams achieve both by tracking and improving on the following four key metrics.

Software Engineering Intelligence (SEI) solutions provide out-of-the-box visibility into key metrics like Deploy Frequency and Lead Time. The analytics tool also reveals underlying drivers, so engineering leaders understand what actions to take to drive these metrics down.

Why a Strategy Matters

At the heart of every successful software engineering team is a drive for three things:

1. A culture of continuous improvement
2. The ability to move from idea to impact quickly, frequently, and with confidence
3. A software organization delivering meaningful value

These goals sound simple enough, but in reality, achieving them requires more than just wishing for better performance. It takes data, action, and, most importantly, a cultural shift. And here's the catch: those three things don't come together by accident.

In my experience, whenever a large-scale change fails, there's one common denominator: a lack of a cohesive strategy. Every time I’ve witnessed a failed attempt at implementing new technology or making a big shift, the missing piece was always that strategic foundation. Without a clear, aligned strategy, you're not just wasting resources—you’re creating frustration across the entire organization.

Step 1: Define Your Purpose

The first step in any successful engineering insights strategy is defining why you're doing this in the first place. If you're rolling out developer productivity metrics or an insights platform, you need to make sure there’s alignment on the purpose across the board.
Too often, organizations dive into this journey without answering the crucial question: Why do we need this data? If you ask five different leaders in your organization, are you going to get five answers, or will they all point to the same objective? If you can’t answer this clearly, you risk chasing a vague, unhelpful path.

One way I recommend approaching this is through the "Five Whys" technique. Ask why you're doing this, and then keep asking "why" until you get to the core of the problem. For example, if your initial answer is, “We need engineering metrics,” ask why. The next answer might be, “Because we're missing deliverables.” Keep going until you identify the true purpose behind the initiative. Understanding that purpose helps avoid unnecessary distractions and lets you focus on solving the real issue.

Step 2: Understand Your People

Once the purpose is clear, the next step is to think about who will be involved in this journey. You have to consider the following:

1. Who will be using the developer productivity tool/insights platform?
2. Are these hands-on developers or executives looking for high-level insights?
3. Who else in the organization might need access to the data, like finance or operations teams?

It’s also crucial to account for organizational changes. Reorgs are common in the enterprise world, and as your organization evolves, so too must your insights platform. If the people responsible for the platform’s maintenance change, who will ensure the data remains relevant to the new structure? Too often, teams stop using insights platforms because the data no longer reflects the current state of the organization. You need to have the right people in place to ensure continuous alignment and relevance.

Step 3: Define Your Process

The next key component is process—a step that many organizations overlook. It's easy to say, "We have the data now," but then what happens? What do you expect people to do with the data once it’s available? And how do you track if those actions are leading to improvement?

A common mistake I see is organizations focusing on metrics without a clear action plan. Instead of just looking at a metric like PR cycle times, the goal should be to first identify the problem you're trying to solve. If the problem is poor code quality, then improving the review cycle times might help, but only because it’s part of a larger process of improving quality, not just for the sake of improving the metric.

Step 4: Program and Rollout Strategy

The next piece of the puzzle is your program and rollout strategy. It’s easy to roll out an engineering insights platform and expect people to just log in and start using it, but that’s not enough. You need to think about how you'll introduce this new tool to the various stakeholders across different teams and business units.

The key here is to design a value loop within a smaller team or department first. Get a team to go through the full cycle of seeing the insights, taking action, and then quantifying the impact of that action. Once you've done this on a smaller scale, you can share success stories and roll it out more broadly across the organization. It’s not about whether people are logging into the platform—it’s about whether they’re driving meaningful change based on the insights.

Step 5: Choose Your Platform Wisely

And finally, we come to the platform itself. It’s the shiny object that many organizations focus on first, but as I’ve said before, it’s the last piece of the puzzle, not the first. Engineering insights platforms like Code Climate are powerful tools, but they can’t solve the problem of a poorly defined strategy.

This small yet system-wide adjustment significantly improved delivery consistency and alignment—something that wouldn’t have been possible without examining the entire end-to-end process.

Looking Ahead

To build a successful engineering insights strategy, you need to go beyond just installing a tool. An insights platform can only work if it’s supported by a clear purpose, the right people, a well-defined process, and a program that rolls it out effectively. The combination of these elements will ensure that your insights platform isn’t just a dashboard—it becomes a powerful driver of change and improvement in your organization.

Remember, a successful software engineering insights strategy isn’t just about the tool. It’s about building a culture of data-driven decision-making, fostering continuous improvement, and aligning all your teams toward achieving business outcomes. When you get that right, the value of engineering insights becomes clear.