Engineering Leadership Summit: Dr. Aneika Simmons, PhD, and Anjuan Simmons, Technology Translator
As part of this year’s Engineering Leadership Summit: Virtual Edition, we spoke to Dr. Aneika Simmons, PhD, and Anjuan Simmons, Engineering Coach at Help Scout. They discussed strategies for preventing and addressing burnout on engineering teams. Below is an excerpt from the fireside chat portion of their session, edited for length and clarity.
Hillary Nussbaum, Content Marketing Manager, Code Climate: Welcome. We’re with Anjuan and Aneika Simmons. Anjuan is a Technology Translator, and Engineering Coach at Help Scout. Aneika is a Full Professor of Management at Sam Houston State University. Please, introduce yourselves, and tell us a little bit about what you do and how you got to where you are now.
Dr. Aneika Simmons, PhD: I’m a Professor of Management at Sam Houston State University. I am a Texan, so I was born and raised in Texas. And then I went ahead and became a Longhorn at the University of Texas at Austin. From there, I was recruited to Accenture, where I worked as an Information Technology Consultant. And then from there I was recruited at Cap Gemini Ernst & Young. I did work at Enron for two years, but not on their finances, only on SAP, let me be clear.
I worked for about eight years, and I really wanted to do something that better utilized my gifts and my talents and my personality. So I decided to apply for a PhD program, and eventually I was accepted into the Mays program at Texas A&M University. After that, I went to Sam Houston and I’ve loved it. It’s been great for me, for my career, for my family. And it’s something I really enjoy.
Anjuan Simmons, Engineering Coach at Help Scout: Hello, everyone. Again, I’m Anjuan, and I am an Engineering Coach at Help Scout, where we support people who love their customers. I started my career at Accenture as well, working on large enterprise software projects and making sure that they got implemented. I also worked at Deloitte, and then I did a few stints at startups.
One thing I really love about Help Scout is the opportunity to take a lot of the rigor and discipline that I learned at those huge companies, but also to add the personal touch and care that I learned from startups. And so that’s really how I go about my job at Help Scout.
Great, thanks. Now let’s jump right in. We’re talking about burnout today. What do you mean when you say burnout, and why does burnout matter to us as individuals and as leaders?
Aneika: Over a year ago, Anjuan and I — we’ve been married for 18 years, and we have three, basically teenagers (I say basically, because one is 12) — discussed the fact that we were dealing with burnout. So we started doing research on it. We determined that burnout, as defined by World Psychiatry, is a psychological syndrome emerging as a prolonged response to chronic interpersonal stressors on the job. Stressors are the things that cause stress. Stress is what I feel.
There are three dimensions to this. One of them is an overwhelming sense of exhaustion. The second is a feeling of cynicism and detachment, and the third is a sense of ineffectiveness and a lack of accomplishment.
And why should we care about it? At the individual level, it can impact you emotionally, mentally, and physically with all kinds of horrible things like high blood pressure, not being able to sleep at night, or a racing mind. And then from a leader’s perspective, you should care because, number one, I hope we all care about the people that work for us, but number two, it impacts the corporate costs. People are not able to show up or give their best selves. So, this is something with a big impact, and it’s really important.
And how is burnout different for an individual and for a team? How does it impact team dynamics when it’s just one person versus everyone?
Aneika: As an individual, of course it impacts you. A lot of people think that if I’m an individual and I’m engaged, then I’m not going to be burned out. But the research actually says that you can be both engaged and burned out. Meaning that you can be fully involved and burned out at the same time. It’s not just the people who are out the door.
And so how is it different at a team level? Well, for teams there’s emotional contagion, where your emotions can trigger the same emotions in other people. Stress and burnout are not the same thing, but stress is a precursor to burnout. And that can become part of a team dynamic via emotional contagion, and that’s what we need to look out for.
And then one of the big aspects of burnout is depersonalization. If you’re working in a team and you’re depersonalizing your team members, obviously that’s not a good thing. People start depersonalizing because they have nothing left to giv, and they’re just trying to focus in on the minimal aspects of what’s happening. But that’s not healthy, and that is an aspect of burnout.
What strategies can a manager take to try to prevent burnout before it happens?
Aneika: One thing that we need to do is, we need to build our well before we need it. A manager should know their people. They should know the people who work for them, and have an understanding of their baseline. If someone was always a really patient person, and then their patience with people starts waning, that could be a signal.
And then how do you prevent it? Focus on human relationships. Let’s look at one another in the eye, let’s have these meetings, let’s get to know one another. Let’s talk through what we feel. We do a thing where we talk about the importance of eye contact, just engaging in people, understanding the people that you work with. And then we have a cliche that, if you want to go fast, go alone. But if you want to go far, well, let’s go together. If we’re doing things together, we think that that can help mitigate burnout.
You just mentioned it’s easiest to spot signs of burnout if you’re familiar with how a person works. So, what strategies can one use to get that baseline assessment?
Anjuan: One of my main tools as an Engineering Manager responsible for the health and wellbeing of software developers is the one-on-one. A one-on-one is a regular meeting, hopefully weekly, but it can be biweekly, where you meet with someone and talk about what’s going on with them. I really try to make my one-on-ones different from a status update. I have many other ways to get status updates.
They’re a way for me to meet on a regular basis with the people who report to me and really get to know them outside of the work, but to also get that sense of what is their profile, how are they normally presenting themselves? One-on-ones are a crucial way for me to not only be connected to my team, but to get their profile. One other thing that I do is, in meetings, I do a lot of reading facial expressions and body language. And so over time, I just get a mental model for how this person performs. Sometimes they use lots of hand gestures, or present themselves a certain way in meetings. And so that’s a key thing as well, to know how to read a person’s body language, to know that usually they’re really open, but recently they’re closed. And then you can begin to see that they’re outside of their normal profile, and you can begin to interrogate that data.
At Help Scout, we also do self-assessments every six months, and that’s really a way for everyone to look back and reflect. We ask questions like, what has been motivating you over the past six months, or what’s changed, or what’s been draining? And when you get that information, you’ll begin to read that and you begin to see, “Okay, this person, when we had a lot of change happening at the beginning of January, it really impacted them.” And so having that information is really a great way to get the data to understand where individuals are, and then move forward from there.
You mentioned looking at body language and reading those subtle signals. Given that a lot of teams are remote now, how do those strategies differ? Do you find that you need to establish a new baseline before making an assessment?
Anjuan: Help Scout was built from the beginning to be fully remote. Going on more than eight years, the company was built to be global and to work remotely. If your company was built from the ground up to be remote, or you’ve been that way for a long time, then it’s really about continuing those practices. Regular one-on-ones, self-assessments, things like that.
In a remote culture that’s new to a company, if you are maybe thrown into working remotely due to current conditions like the global pandemic, then you have to understand that one, this is not normal. I’m a big fan of working remotely, but I know that a lot of people are not getting a really good first taste of it. Often you’re working remotely with a spouse who’s also been thrown into working remotely. You may have to share a space with that person. There may be children you now need to help with their work. And so I think that being aware, especially now, that this is not normal, and not expecting the team to be normal, is okay.You have to give the team time to figure out their new normal.
One tool that we use at Help Scout that I really like is called Fika. And Fika, loosely translated, is from a Swedish word that means to take a break, get something sweet, like a pastry, and then get a nice beverage, usually coffee or tea. And then we just, we typically use Zoom, hop on a video conference, and we just chat — not about work, but about each other and what’s going on. And so that’s a way that we are able to, even though we’re remote, to connect with each other. There’s also a tool called Donut, which is a Slack app that will randomly pair people for Fikas. And that way, not only with the Engineering Department that I sit in, but with Marketing, Sales, et cetera, I’m able to build those relationships even though we are a remote company.
We are not able to do this for the foreseeable future, but having a retreat is also crucial for a remote company. At Help Scout, we typically have them twice a year.
Are there any other special considerations when it comes to remote teams? We’ve been hearing a lot about Zoom fatigue. Are there other things that maybe you wouldn’t have to think about when you’re all in the same place, but that come up in a remote situation?
Anjuan: Yeah, for sure. Two quick things. I’m very lucky to work at Help Scout where we got a stipend for our home office, because they don’t assume that everyone has the stuff they need at home. If companies can provide that support to help everyone working remotely, especially if they were just thrown into it, that is super helpful. The other thing I would say is that often when you’re working remotely, you don’t have a commute. And most people don’t realize that’s often a really good getting ready time. You may listen to podcasts or to music or do different things, catch up on the news from the radio. And then when you’re leaving work, you have that time to decompress.
But when you’re working remotely, you don’t have that commute. That nice bookend to your work day. So, I would say have some kind of ritual — don’t just spring out of bed and hop on Zoom and start working. Maybe take a walk around the block, or make a nice cup of coffee before you start working, because it’s really easy to work a lot more than you’re used to because you don’t have those natural breaks in your day.
Aneika: I know for myself, I wasn’t really on Zoom that much until everything happened with COVID-19. And so if you could have blocks in your day where you say, “Well, no, I’m not having any Zoom meetings at that point,” that helps. Because Zoom fatigue is real, the stress of making eye contact. When you’re on the phone, you can walk around and do things, but in Zoom meetings, some people may feel a little bit held captive.
That makes a lot of sense. We’ve been talking a little bit about preventing burnout and causes of burnout, but obviously it’s not always preventable. What steps would you recommend that a manager take to address burnout when they become aware of it?
Anjuan: As a manager, it’s really important to understand a person’s baseline profile. And ideally what you’ll be able to do is to say, “Okay, this person reports to me, and they’re beginning to diverge from their baseline profile. They’re acting in a way that is an anomaly from everything that I’ve seen before.” And then the key thing is that don’t diagnose that person. Don’t say, “You have burnout, here’s what we’re going to do.” That is something that a professional should do, and that person may not respond well to you trying to diagnose them.
What you do instead is you share observations. You say, “Hey, I’ve seen you typically log on if you’re remote at nine o’clock in your local time, you’re getting on at around closer to noon.” Or, “You typically don’t introduce a lot of bugs into the system, but I’m seeing more bugs that are introduced by your code.” Or, “You typically are more thoughtful and intentional when you comment on pull requests, and now you’re just writing one sentence.” And so by doing that, you can say, “This is what I’m observing. What do you think is going on?” And often it’s in that conversation that you’ll begin to glean what’s happening. And then as a manager you can do things like, “Okay, let’s look at your workload, and you know what? Out of these five things, only these two are really valuable. Let’s just focus on that.”
And in our framework, we talk about having the need to burn down distractions. And so by doing that, you can focus on what’s really valuable. I find that if I can narrow down what my team has to worry about to just one or two things in a given sprint, that goes a long way toward releasing the stress that builds up when we try to keep a lot in our minds. I really try to make sure that my team only has one or two things that they have to think about, because in a world where there is a global pandemic and there’s a lot of civil unrest and a lot of disruptions to the economy, the last thing I want my people to worry about is work. And so I try to make work as simple as possible.
What would you recommend that people do if they’re feeling burned out? Or if they notice a team member is burned out, but they’re not that person’s manager, so they don’t necessarily have the ability to say, “Let’s focus and take things off your plate?”
Aneika: The first step is acknowledgement. So, for you to acknowledge that you’re burned out. You would ask yourself, are you feeling exhausted? The things that used to really light your fire and make you passionate about work, are they still there? How healthy are your relationships at work? Are you engaged with people? Those types of things are important. One of the main things that we do to mitigate stress is, we go for walks every day. We go for walks in the evening and just kind of decompress and talk. So, the first step is acknowledgement and accepting that there’s nothing wrong with you. We’re human beings. And that we get to a point sometimes where we feel that, “My plate is full, I have nothing else to give, and I have to address this.”
Anjuan: To the latter part of the question, which is, I’m not this person’s manager, but I see that they’re burned out — if you have the right relationship with that person, you can share your observation. Again, don’t try to diagnose them as being burned out, but say, “Hey, I’ve been noticing this.” Like my wife said, “You used to be really energized by working in our CI/CD pipelines, but now you seem to have slowed down there.” Share those observations. And then what you can do is say, “Here are some things that have worked for me when I’ve gone through that.
The ideal is that you’ve already built up what we call burnout resistance in your own life, and you’re able to model that to the other person. If you don’t feel that you have the relationship to be able to share those observations, it’s really important to find someone in the organization who does, and candidly share those observations with that person
Aneika: And I’ll just say real quick that all of these types of things that we’re talking about requires a certain level of psychological safety at your job. So you have to have an organization where you feel that you can be vulnerable. And if you can’t be vulnerable, then maybe you really won’t know what your employees, or the people who work for you, or work with you, are going through. The organization has to have a culture where people feel like they actually can be vulnerable and say how they truly feel.
I’m curious about what you just said, that it is important to be vulnerable as a manager, as a leader. Do you have some tips or strategies for people who aren’t necessarily as comfortable or as practiced with that?
Aneika: Well, there are different types of personalities, like my husband is an introvert, and I’m an extrovert. Of course not all introverts and extroverts are the same, some personality types might be more comfortable sharing things that are close to your heart. So, you would need to keep that in mind. But one of the things that I would say is just make sure you develop a healthy relationship with at least one or two people on your team. I know that as teams get larger, you can’t be close to everyone, but you do want to try to have that interconnectedness. That is really important so that when things do come up, you feel comfortable sharing.
Anjuan: Yeah. And at Help Scout, we use a tool called Know Your Team, which is a website that asks a question every week and then people respond to it. It seems kind of trite, but by just sharing those answers, just sharing more about what you think outside of work…you’ll begin to make the first steps toward having that relationship. And then building that culture where people do feel a sense of a psychological safety. Aneika and I have often said that healthy teams build healthy code, and people can be healthy obviously by taking care of their physical body, by exercising and eating properly, and by having relationships that are strong and meaningful. But I also think if people can bring their authentic self to work, then you’ll get their best work.
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Navigating the world of software engineering or developer productivity insights can feel like trying to solve a complex puzzle, especially for large-scale organizations. It's one of those areas where having a cohesive strategy can make all the difference between success and frustration. Over the years, as I’ve worked with enterprise-level organizations, I’ve seen countless instances where a lack of strategy caused initiatives to fail or fizzle out.
In my latest webinar, I breakdown the key components engineering leaders need to consider when building an insights strategy.
Why a Strategy Matters
At the heart of every successful software engineering team is a drive for three things:
- A culture of continuous improvement
- The ability to move from idea to impact quickly, frequently, and with confidence
- 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.
Sign up for a free, expert-led insights strategy workshop for your enterprise org.
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:
- Who will be using the developer productivity tool/insights platform?
- Are these hands-on developers or executives looking for high-level insights?
- 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.
It’s also essential to approach this with an experimentation mindset. For example, start by identifying an area for improvement, make a hypothesis about how to improve it, then test it and use engineering insights data to see if your hypothesis is correct. Starting with a metric and trying to manipulate it is a quick way to lose sight of your larger purpose.
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.
I’ve seen organizations spend months evaluating these platforms, only to realize they didn't even know what they needed. One company in the telecom industry realized that no available platform suited their needs, so they chose to build their own. The key takeaway here is that your platform should align with your strategy—not the other way around. You should understand your purpose, people, and process before you even begin evaluating platforms.
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.
Want to build a tailored engineering insights strategy for your enterprise organization? Get expert recommendations at our free insights strategy workshop. Register here.
Andrew Gassen has guided Fortune 500 companies and large government agencies through complex digital transformations. He specializes in embedding data-driven, experiment-led approaches within enterprise environments, helping organizations build a culture of continuous improvement and thrive in a rapidly evolving world.
Most organizations are great at communicating product releases—but rarely do the same for process improvements that enable those releases. This is a missed opportunity for any leader wanting to expand “growth mindset,” as curiosity and innovation is as critical for process improvement as it is product development.
Curiosity and innovation aren’t limited to product development. They’re just as essential in how your teams deliver that product. When engineering and delivery leaders share what they’re doing to find efficiencies and unclog bottlenecks, they not only improve Time to Value — they help their peers level up too.
Create Buzz Around Process Wins
Below is a template leaders can use via email or communication app (Slack, Microsoft Teams) to share process changes with their team. I’ve personally seen updates like this generate the same level of energy as product announcements—complete with clap emojis👏 and follow-up pings like “Tell me more!” Even better, they’re useful for performance reviews and make great resume material for the leads who author them (excluding any sensitive or proprietary content, of course).
Subject: [Experiment update]
[Date]
Experiment Lead: [Name]
Goal: [Enter the longer term goal your experiment was in service of]
Opportunity: [Describe a bottleneck or opportunity you identified for some focused improvement]
Problem: [Describe the specific problem you aimed to solve]
Solution: [Describe the very specific solution you tested]
Metric(s): [What was the one metric you determined would help you know if your solution solved the problem? Were there any additional metrics you kept track of, to understand how they changed as well?]
Action: [Describe, in brief, what you did to get the result]
Result: [What was the result of the experiment, in terms of the above metrics?]
Next Step: [What will you do now? Will you run another experiment like this, design a new one, or will you rollout the solution more broadly?]
Key Learnings: [What did you learn during this experiment that is going to make your next action stronger?]
Please reach out to [experiment lead’s name] for more detail.
Sample Use Case
Subject: PR Descriptions Boost Review Speed by 30%
March 31, 2025
Experiment Lead: Mary O’Clary
Goal: We must pull a major capability from Q4 2024 into Q2 2025 to increase our revenue. We believe we can do this by improving productivity by 30%.
Opportunity: We found lack of clear descriptions were a primary cause of churn & delay during the review cycle. How might we improve PR descriptions, with information reviewers need?
Problem: Help PR Reviewers more regularly understand the scope of PRs, so they don’t need to ask developers a bunch of questions.
Solution: Issue simple guidelines for what we are looking for PR descriptions
Metric(s): PR Review Speed. We also monitored overall PR Cycle Time, assuming it would also improve for PRs closed within our experiment timeframe.
Action: We ran this experiment over one 2 week sprint, with no substantial changes in complexity of work or composition of the team. We kept the timeframe tight to help eliminate additional variables.
Result: We saw PR Review Speed increase by 30%
Next Step: Because of such a great result and low perceived risk, we will roll this out across Engineering and continue to monitor both PR Review Speed & PR Cycle Time.
Key Learnings: Clear, consistent PR descriptions reduce reviewer friction without adding developer overhead, giving us confidence to expand this practice org-wide to help accelerate key Q2 2025 delivery.
Please reach out to Mary for more detail.
How Make This Process Stick
My recommendation is to appoint one “editor in chief” to issue these updates each week. They should CC the experiment lead on the communication to provide visibility. In the first 4-6 weeks, this editor may need to actively solicit reports and coach people on what to share. This is normal—you’re building a new behavior. During that time, it's critical that managers respond to these updates with kudos and support, and they may need to be prompted to do so in the first couple of weeks.
If these updates become a regular ritual, within ~3 months, you’ll likely have more contributions than you can keep up with. That’s when the real cultural shift happens: people start sharing without prompting, and process improvement becomes part of how your org operates.
I’ve seen this work in large-scale organizations, from manufacturing to healthcare. Whether your continuous improvement culture is just getting started or already mature, this small practice can help you sustain momentum and deepen your culture of learning.
Give it a shot, and don’t forget to celebrate the wins along the way.
Jen Handler is the Head of Professional Services at Code Climate. She’s an experienced technology leader with 20 years of building teams that deliver outcome-driven products for Fortune 50 companies across industries including healthcare, hospitality, retail, and finance. Her specialties include goal development, lean experimentation, and behavior change.
Output is not the same as impact. Flow is not the same as effectiveness. Most of us would agree with these statements—so why does the software industry default to output and flow metrics when measuring success? It’s a complex issue with multiple factors, but the elephant in the room is this: mapping engineering insights to meaningful business impact is far more challenging than measuring developer output or workflow efficiency.
Ideally, data should inform decisions. The problem arises when the wrong data is used to diagnose a problem that isn’t the real issue. Using misaligned metrics leads to misguided decisions, and unfortunately, we see this happen across engineering organizations of all sizes. While many companies have adopted Software Engineering Intelligence (SEI) platforms—whether through homegrown solutions or by partnering with company that specializes in SEI like Code Climate—a clear divide has emerged. Successful and mature organizations leverage engineering insights to drive real improvements, while others collect data without extracting real value—or worse, make decisions aimed solely at improving a metric rather than solving a real business challenge.
From our experience partnering with large enterprises with complex structures and over 1,000 engineers, we’ve identified three key factors that set high-performing engineering organizations apart.
1. Treating Software Engineering Insights as a Product
When platform engineering first emerged, early innovators adopted the mantra of “platform as a product” to emphasize the key principles that drive successful platform teams. The same mindset applies to Software Engineering Intelligence (SEI). Enterprise organizations succeed when they treat engineering insights as a product rather than just a reporting tool.
Data shouldn’t be collected for the sake of having it—it should serve a clear purpose: helping specific users achieve specific outcomes. Whether for engineering leadership, product teams, or executive stakeholders, high-performing organizations ensure that engineering insights are:
- Relevant – Focused on what each audience actually needs to know.
- Actionable – Providing clear next steps, not just numbers.
- Timely – Delivered at the right moment to drive decisions.
Rather than relying on pre-built dashboards with generic engineering metrics, mature organizations customize reporting to align with team priorities and business objectives.
For example, one of our healthcare customers is evaluating how AI coding tools like GitHub Copilot and Cursor might impact their hiring plans for the year. They have specific questions to answer and are running highly tailored experiments, making a custom dashboard essential for generating meaningful, relevant insights. With many SEI solutions, they would have to externalize data into another system or piece together information from multiple pages, increasing overhead and slowing down decision-making.
High-performing enterprise organizations don’t treat their SEI solution as static. Team structures evolve, business priorities shift, and engineering workflows change. Instead of relying on one-size-fits-all reporting, they continuously refine their insights to keep them aligned with business and engineering goals. Frequent iteration isn’t a flaw—it’s a necessary feature, and the best organizations design their SEI operations with this in mind.
2. The Value of Code is Not the Code
Many software engineering organizations focus primarily on code-related metrics, but writing code is just one small piece of the larger business value stream—and rarely the area with the greatest opportunities for improvement. Optimizing code creation can create a false sense of progress at best and, at worst, introduce unintended bottlenecks that negatively impact the broader system.
High-performing engineering organizations recognize this risk and instead measure the effectiveness of the entire system when evaluating the impact of changes and decisions. Instead of focusing solely on PR cycle time or commit activity, top-performing teams assess the entire journey:
- Idea generation – How long does it take to move from concept to development?
- Development process – Are teams working efficiently? Are bottlenecks slowing down releases?
- Deployment & adoption – Once shipped, how quickly is the feature adopted by users?
- Business outcomes – Did the feature drive revenue, retention, or efficiency improvements?
For example, reducing code review time by a few hours may seem like an efficiency win, but if completed code sits for six weeks before deployment, that improvement has little real impact. While this may sound intuitive, in practice, it’s far more complicated—especially in matrixed or hierarchical organizations, where different teams own different parts of the system. In these environments, it’s often difficult, though not impossible, for one group to influence or improve a process owned by another.
One of our customers, a major media brand, had excellent coding metrics yet still struggled to meet sprint goals. While they were delivering work at the expected rate and prioritizing the right items, the perception of “failed sprints” persisted, creating tension for engineering leadership. After further analysis, we uncovered a critical misalignment: work was being added to team backlogs after sprints had already started, without removing any of the previously committed tasks. This shift in scope wasn’t due to engineering inefficiency—it stemmed from the business analysts' prioritization sessions occurring after sprint commitments were made. A simple rescheduling of prioritization ceremonies—ensuring that business decisions were finalized before engineering teams committed to sprint goals. 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.
3. Shifting from Tactical Metrics to Strategy
There are many frameworks, methodologies, and metrics often referenced as critical to the engineering insights conversation. While these can be useful, they are not inherently valuable on their own. Why? Because it all comes down to strategy. Focusing on managing a specific engineering metric or framework (i.e. DORA or SPACE) is missing the forest for the trees. Our most successful customers have a clear, defined, and well-communicated strategy for their software engineering insights program—one that doesn’t focus on metrics by name. Why? Because unless a metric is mapped to something meaningful to the business, it lacks the context to be impactful.
Strategic engineering leaders at large organizations focus on business-driven questions, such as:
- Is this engineering investment improving customer experience?
- Are we accelerating revenue growth?
- Is this new approach or tool improving cross-functional collaboration?
Tracking software engineering metrics like cycle time, PR size, or deployment frequency can be useful indicators, but they are output metrics—not impact metrics. Mature organizations go beyond reporting engineering speed and instead ask: "Did this speed up product releases in a way that drove revenue?"
While challenging to measure, this is where true business value lies. A 10% improvement in cycle time may indicate progress, but if sales remain flat, did it actually move the needle? Instead of optimizing isolated metrics, engineering leaders should align their focus with overarching business strategy. If an engineering metric doesn’t directly map to a key strategic imperative, it’s worth reevaluating whether it’s the right thing to measure.
One of our retail customers accelerated the release of a new digital capability, allowing them to capture additional revenue a full quarter earlier than anticipated. Not only did this directly increase revenue, but the extended timeline of revenue generation created a long-term financial impact—a result that finance teams, investors, and the board highly valued. The team was able to trace their decisions back to insights derived from their engineering data, proving the direct connection between software delivery and business success.
Understanding the broader business strategy isn’t optional for high-performing engineering organizations—it’s a fundamental requirement. Through our developer experience surveys, we’ve observed a significant difference between the highest-performing organizations and the rest as it relates to how well developers understand the business impact they are responsible for delivering. Organizations that treat engineers as task-takers, isolated from business impact, consistently underperform—even if their coding efficiency is exceptional. The engineering leaders at top-performing organizations prioritize alignment with strategy and avoid the distraction of tactical metrics that fail to connect to meaningful business outcomes.
Learn how to shift from micro engineering adjustments to strategic business impact. Request a Code Climate Diagnostic.
Code Climate has supported thousands of engineering teams of all sizes over the past decade, enhancing team health, advancing DevOps practices, and providing visibility into engineering processes. According to Gartner®, the Software Engineering Intelligence (SEI) platform market is expanding as engineering leaders increasingly leverage these platforms to enhance productivity and drive business value. As pioneers in the SEI space, the Code Climate team has identified three key takeaways from partnerships with our Fortune 100 customers:
- Engineering Metrics Are Not Enough
- Engineering leaders that adopt a Software Engineering Intelligence (SEI) platform without a proper SEI strategy fail to extract value from the data
- Engineering leaders that adopt quantitative metrics without qualitative measures are missing the full picture
- Engineering leaders that adopt a Software Engineering Intelligence (SEI) platform without a proper SEI strategy fail to extract value from the data
- Hands-Off Approach Falls Short
- Approaching an SEI platform as a traditional turnkey SaaS product does not ensure team success
- Organizations that lack collaboration with an SEI solutions provider often struggle to drive adoption and understanding of engineering insights
- Approaching an SEI platform as a traditional turnkey SaaS product does not ensure team success
- Insights Alone Do Not Drive Outcomes
- Engineering leaders often struggle to translate insights from an SEI platform into actionable steps
- Engineering leaders often struggle to align engineering performance to meaningful business outcomes
- Engineering leaders often struggle to translate insights from an SEI platform into actionable steps
Empowering Engineering Leaders at Enterprise Organizations
The above takeaways have prompted a strategic shift in Code Climate’s roadmap, now centered on enterprise organizations with complex engineering team structure and workflows. As part of this transition, our flagship Software Engineering Intelligence (SEI) platform, Velocity, is now replaced by an enhanced SEI platform, custom-designed for each leader and their organization. With enterprise-level scalability, Code Climate provides senior engineering leaders complete autonomy over their SEI platform, seamlessly integrating into their workflows while delivering the customization, flexibility, and reliability needed to tackle business challenges.
Moreover, we understand that quantitative metrics from a data platform alone cannot transform an organization, which is why Code Climate is now a Software Engineering Intelligence Solutions Partner—offering five key characteristics that define our approach
- Tailored Solutions: We provide engineering solutions via quantitative insights and qualitative workshops that are specifically designed to meet the unique needs of enterprise engineering teams—moving beyond standard, black-box solutions.
- Strategic Collaboration: We enable our enterprise customers to build an SEI strategy, engaging with key stakeholders to align Code Climate’s solution and services with their broader business goals.
- Long-Term Partnership: Our strategic partnership with our enterprise customers is typically ongoing, focusing on long-term value rather than offering a standard insights platform. As an enterprise-level SEI solutions partner, we are invested in the sustained success of our customers.
- Expert Guidance: We offer expert guidance and actionable recommendations to help our enterprise customers navigate challenges, optimize performance, and achieve business goals.
- End-to-End Support: We provide comprehensive services, from advisory support and implementation to ongoing support and optimization.
A Message from the New CEO of Code Climate
"During my time at Pivotal Software, Inc., I met with hundreds of engineering executives who consistently asked, “How do I improve my software engineering organization?” These conversations revealed a universal challenge: aligning engineering efforts with business goals. I joined Code Climate because I'm passionate about helping enterprise organizations address these critical questions with actionable insights and data-driven strategies that empower engineering executives to drive meaningful change." - Josh Knowles, CEO of Code Climate
Ready to make data-driven engineering decisions to maximize business impact? Request a consultation.
Today, we’re excited to share that Code Climate Quality has been spun out into a new company: Qlty Software. Code Climate is now focused entirely on its next phase of Velocity, our Software Engineering Intelligence (SEI) solution for enterprise organizations
How It Started
I founded Code Climate in 2011 to help engineering teams level up with data. Our initial Quality product was a pioneer for automated code review, helping developers merge with confidence by bringing maintainability and code coverage metrics into the developer workflow.
Our second product, Velocity, was launched in 2018 as the first Software Engineering Intelligence (SEI) platform to deliver insights about the people and processes in the end-to-end software development lifecycle.
All the while, we’ve been changing the way modern software gets built. Quality is reviewing code written by tens of thousands of engineers, and Velocity is helping Fortune 500 companies drive engineering transformation as they adopt AI-enabled workflows.
Today, Quality and Velocity serve different types of software engineering organizations, and we are investing heavily in each product for their respective customers.
Where We're Going
To serve both groups better, we’re branching out into two companies. We’re thrilled to introduce Qlty Software, and to focus Code Climate on software engineering intelligence.
Over the past year, we’ve made more significant upgrades to Quality and our SEI platform, Velocity, than ever before. Much of that is limited early access, and we’ll have a lot to share publicly soon. As separate companies, each can double down on their products.
Qlty Software is dedicated to taking the toil out of code maintenance. The new company name represents our commitment to code quality. We’ve launched a new domain, with a brand new, enhanced edition of the Quality product.
I’m excited to be personally moving into the CEO role of Qlty Software to lead this effort. Josh Knowles, Code Climate’s General Manager, will take on the role of CEO of Code Climate, guiding the next chapter as an SEI solutions partner for technology leaders at large, complex organizations.
We believe the future of developer tools to review and improve code automatically is brighter than ever – from command line tools accelerating feedback loops to new, AI-powered workflows – and we’re excited to be on that journey with you.
-Bryan
CEO, Qlty Software
Technology is evolving very quickly but I don't believe it's evolving as quickly as expectations for it. This has become increasingly apparent to me as I've engaged in conversations with Code Climate's customers, who are senior software engineering leaders across different organizations. While the technology itself is advancing rapidly, the expectations placed on it are evolving at an even faster pace, possibly twice as quickly.
New Technology: AI, No-Code/Low-Code, and SEI Platforms
There's Generative AI, such as Copilot, the No-code/Low-code space, and the concept of Software Engineering Intelligence (SEI) platforms, as coined by Gartner®. The promises associated with these tools seem straightforward:
- Generative AI aims to accelerate, improve quality, and reduce costs.
- No-code and Low-code platforms promise faster and cheaper software development accessible to anyone.
- SEI platforms such as Code Climate enhance productivity measurement for informed decisions leading to faster, efficient, and higher-quality outcomes.
However, the reality isn’t as straightforward as the messaging may seem:
- Adopting Generative AI alone can lead to building the wrong things faster.
- No-code or Low-code tools are efficient until you hit inherent limitations, forcing cumbersome workarounds that reduce maintainability and create new challenges compared to native code development.
- As for SEI platforms, as we've observed with our customers, simply displaying data isn't effective if you lack the strategies to leverage it.
When I joined Code Climate a year ago, one recurring question from our customers was, "We see our data, but what's the actionable next step?" While the potential of these technologies is compelling, it's critical to address and understand their practical implications. Often, business or non-technical stakeholders embrace the promises while engineering leaders, responsible for implementation, grapple with the complex realities.
Navigating New Technology Expectations and Realities
Software engineering leaders now face increased pressure to achieve more with fewer resources, often under metrics that oversimplify their complex responsibilities. It's no secret that widespread layoffs have affected the technology industry in recent years. Despite this, the scope of their responsibilities and the outcomes expected from them by the business haven't diminished. In fact, with the adoption of new technologies, these expectations have only increased.
Viewing software development solely in terms of the number of features produced overlooks critical aspects such as technical debt or the routine maintenance necessary to keep operations running smoothly. Adding to that, engineering leaders are increasingly pressured to solve non-engineering challenges within their domains. This disconnect between technical solutions and non-technical issues highlights a fundamental gap that can't be bridged by engineering alone—it requires buy-in and understanding from all stakeholders involved.
This tension isn't new, but it's becoming front-and-center thanks to the promises of new technologies mentioned above. These promises create higher expectations for business leaders, which, in turn, trickle down to engineering leaders who are expected to navigate these challenges, which trickle down to the teams doing the work. Recently, I had a conversation with a Code Climate customer undergoing a significant adoption of GitHub Copilot, a powerful tool. This particular leader’s finance team told her, "We bought this new tool six months ago and you don't seem to be operating any better. What's going on?" This scenario reflects the challenges many large engineering organizations face.
Navigating New Technology Challenges and Taking Action
Here's how Code Climate is helping software engineering leaders take actionable steps to address challenges with new technology:
- Acknowledging the disconnect with non-technical stakeholders, fostering cross-functional alignment and realistic expectations. Facilitating open discussions between technology and business leaders, who may never have collaborated before, is crucial for progress.
- Clearly outlining the broader scope of engineering challenges beyond just writing code—evaluating processes like approval workflows, backlog management, and compliance mandates. This holistic view provides a foundation for informed discussions and solutions.
- Establishing a shared understanding and language for what constitutes a healthy engineering organization is essential.
In addition, we partner with our enterprise customers to experiment and assess the impact of new technologies. For instance, let's use the following experiment template to justify the adoption of Copilot:
We believe offering Copilot to _______ for [duration] will provide sufficient insights to inform our purchasing decision for a broader, organization-wide rollout.
We will know what our decision is if we see ______ increase/decrease.
Let’s fill in the blanks:
We believe offering Copilot to one portfolio of 5 teams for one quarter will provide sufficient insights to inform our purchasing decision for a broader, organization-wide rollout.
We will know what our decision is if we see:
- An increase in PR Throughput
- A decrease in Cycle Time
- No negative impact to Rework
- No negative impact to Defect Rate
Andrew Gassen leads Code Climate's enterprise customer organization, partnering with engineering leaders for organization-wide diagnostics to identify critical focus areas and provide customized solutions. Request a consultation to learn more.