Data-Driven Work Cultures: Jimmy McGill of Code Climate On How To Effectively Leverage Data To Take Your Company To The Next Level

An Interview With Pierre Brunelle

Use data to ensure that speed doesn’t come at the expense of quality. Optimizing and improving your organization allows your business to get the highest possible return on your investments. Use the data to identify opportunities for individual improvement, as well as to uncover necessary process changes and assess their effectiveness.

As part of our series about “How To Effectively Leverage Data To Take Your Company To The Next Level”, I had the pleasure of interviewing Jimmy McGill.

James (Jimmy) McGill is a technology leader, coach, team builder, and maker who was raised in Australia and is currently based in NYC. He brings over 10 years of experience building software tools to Code Climate. In his role as VP of Engineering, Jimmy is dedicated to helping engineering teams achieve their highest potential.

Thank you so much for joining us in this interview series. Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?

Even as a young child, it was very clear that I was meant to be an engineer. I was interested in how things work and how they came together. Computer programming was a natural fit for me and I began tinkering around on the family BBC Micro, an ancient machine by many standards, which really expanded my interest. I fell in love with it.

After I graduated from college, I was very fortunate to get a job working for Google in Australia. While Google was a large and successful company, at that point the office in Australia was fairly small — only about 20 people. We were working on a brand new product: Google Maps. Throughout my years at Google I realized that the ideas that I wanted to see brought to life were bigger than a team of just myself.

I went through the typical evolution for a technology company, which is to grow from a small team, to managing a team, and then a manager of managers and so on and so forth. The organization became larger and larger and I got further and further away from what people were doing during the day-to-day. It was extremely difficult to make good, quality decisions that would benefit my team and the business. I had an incomplete, or patchy, understanding of what was happening on the ground. At a certain size, it’s simply impossible to get first-hand information from everybody on the team. Unfortunately I went through a transition where as my team grew my ability to successfully manage them suffered. It was only when I began to bring data into my decision-making process that I was able to increase my visibility. Data improved the quality of my decisions.

I joined Code Climate years later because I was a user of the tool and really believe in the value it can bring to engineering teams.

Fun Fact: At Google I implemented a very basic version of the metrics that are in Code Climate’s Velocity tool. If I could rewind, I would love to have had access to that visibility into my team. That would have been a real game changer.

Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lessons or ‘take aways’ you learned from that?

An absence of data tends to lead to bad results rather than funny results. However, in hindsight I do have a situation that was a little funny. An engineer on my team and I were experiencing mutual frustration with each other. I was frustrated because I didn’t see any work getting done (unusual for this team member). The engineer was frustrated they weren’t receiving any recognition for their completed work. For multiple weeks, we were quietly grumpy at each other. As with many situations, the problem actually came down to a big difference in communication style. The work they were doing never came up in conversation — even though we spent a fair amount of time talking. It was a classic case of miscommunication.

Eventually we did realize what was happening. He and I still get together regularly to share a beer, and laugh whenever this story makes its way into the conversation — but at the time it was stressful!

Is there a particular book, podcast, or film that made a significant impact on you? Can you share a story or explain why it resonated with you so much?

I am a huge fan of the podcast 99% Invisible, about all the thought that goes into the things we don’t think about that shape our world. The episode on Froebel’s Gifts, a series of presents given to children to encourage them to look at the world in different ways, was particularly impactful for me. The theory heavily influenced the approaches I take to problem solving, and situational management.

Are you working on any new, exciting projects now? How do you think that might help people?

We know that being a great engineer is not just about writing great code. Based on our decade’s worth of expertise, we’re building the most comprehensive and intelligent understanding of where and how engineering teams are spending their time. Our engineering management platform provides data-driven visibility into engineering teams’ investment of time and resources, operational efficiency, and deliverable progress, enabling engineering leaders to make better business decisions and deliver results.

We have some exciting news coming up before the end of the year, but I’m keeping it under wraps for now!

Thank you for all that. Let’s now turn to the main focus of our discussion about empowering organizations to be more “data-driven.” My work centers on the value of data visualization and data collaboration at all levels of an organization, so I’m particularly passionate about this topic. For the benefit of our readers, can you help explain what exactly it means to be data-driven? On a practical level, what does it look like to use data to make decisions?

Being data-driven is not just pulling up a graph or spreadsheet and having it tell you what to do. Being data-driven is about checking your biases, checking your assumptions, and validating your hypotheses based on what you’re hearing from your team and using data that can be tied to on-the-ground facts.

Data should inspire you to ask a question that you otherwise would not have considered. By asking that question, pulling on that thread, you can arrive at either a meaningful decision or a meaningful insight about your company. When you do this effectively, you’re able to take action faster; you’re making higher confidence decisions because they are backed by data. More importantly, you’re able to take stronger, more impactful action knowing that it’s the right action based on both your own observations and facts about what is really happening on the ground.

Which companies can most benefit from tools that empower data collaboration?

Every company can benefit from data. Any company or industry that believes they won’t will be looking back in five years, saying “Huh, well we’ve been left behind.”

Over the last ten years, we’ve seen a huge digital transformation. Technology is now the basis of nearly every company, so they need to be data-driven to succeed. There are very few sectors where software research and development isn’t a significant part of what they do. Fifteen years ago Nike just made shoes and now they have hundreds of software engineers. Everything is data and increasingly data needs an engineering management platform to customize the type of data you’re looking at and the questions you’re looking to answer.

We’d love to hear about your experiences using data to drive decisions. In your experience, how has data analytics and data collaboration helped improve operations, processes, and customer experiences? We’d love to hear some stories if possible.

I specialize in supporting fast growing organizations. One of the most common struggles with a quickly growing organization is that processes are changing quickly too.

As a leader, you need to know whether the changes you’ve made have had the intended impact. We’re all human, so undoubtedly some percentage of those changes will be the wrong one. Data-driven visibility has enabled me, as a leader, to roll out process changes faster so that I can be responsive to the change in my organization. I’m able to quickly identify changes that have made processes worse and quickly check in with my team to verify. Typically, the data has pointed me in the right direction and when things aren’t trending the way they should, team members are frustrated. Then I’ve achieved two very important things: 1) I can get ahead of the problem before it bubbles over and 2) I’m able to adapt the process and we can see if the changes land in the way we expected.

I always find myself coming back to the data again and again in situations like these. Even earlier this year, Code Climate rolled out a process change outside of our engineering department and it didn’t go the way we expected. In that department, there is no equivalent to our Velocity tool so we have no means to measure whether it’s working or not. The visibility that a tool like Velocity provides would have easily provided insight to help the team assess the change and act accordingly.

Has the shift towards becoming more data-driven been challenging for some teams or organizations from your vantage point? What are the challenges? How can organizations solve these challenges?

The biggest challenge people anticipate is that the data will be used for “evil.” Almost universally when we talk to organizations about rolling it out, that is the one thing that they’re concerned about. Either the engineers are worried or the managers are worried that the engineers might be worried. From my experience, what actually happens is that when a company thoughtfully rolls out their engineering management platform, nobody uses the data for the wrong reasons, and across the board the team realizes that it’s a helpful tool.

There’s no shortage of people who, over the course of their career, have had bad managers. However, when we ask ‘Who in your organization would use the data in that way,’ the answer is always: no one. If the data was used to treat team members like machines, then it would go badly but at that point the problem is not engineering data; the problem is a bad work culture.

A positive work culture is the best way to set your team up for success in so many ways. When we can overcome this initial worry, becoming data-driven isn’t that much of a challenge.

Ok. Thank you. Here is the primary question of our discussion. Based on your experience and success, what are “Five Ways a Company Can Effectively Leverage Data to Take It To The Next Level”? Please share a story or an example for each.

I think it’s important to do a few things well and so I propose that there are three ways that, if given the appropriate attention, will be the most effective.

1. Align — Use data to align your work with your business objectives. This is the foundation for success. The key to alignment is using the data to know where your time and resources are going. I find that managers are often surprised to see what their engineers are spending their time working on. They are usually working very hard, but not always towards the goals that leadership views as most strategic. Misalignment between organizational leadership and engineering leads to wasted effort and sours workplace culture.
2. Deliver — Use data to make sure your projects are delivered on time. Data can be used to eliminate unpleasant surprises from the production cycle and find risks for delay before they happen. If leaders can see where resources are being spent, they can reallocate those resources to where they’ll have the most impact.
3. Improve — Use data to ensure that speed doesn’t come at the expense of quality. Optimizing and improving your organization allows your business to get the highest possible return on your investments. Use the data to identify opportunities for individual improvement, as well as to uncover necessary process changes and assess their effectiveness.

The name of this series is “Data-Driven Work Cultures”. Changing a culture is hard. What would you suggest is needed to change a work culture to become more Data Driven?

The most impactful way to change a work culture to become more data driven is to have someone to champion that change. This person can articulate the benefits of that change and build trust in using the tool. It’s natural for people to resist change or criticize efforts to change. They also want to know ‘what’s in it for me.’ A change champion can answer questions and communicate the positives. They take ownership of implementing the new processes but also understand that change, like using a new tool, doesn’t happen overnight.

This person can ensure that the data is being used for a purpose. You need to have an idea of what you want to do with that data. Without a plan, it can’t be used to its full potential.

It also doesn’t hurt to have an off-the-shelf tool. Implementing a tool from scratch can be a significant time investment. So if there’s a tool that can provide good, trustworthy, accurate data — you’ll be able to more immediately start making decisions based on it. Being able to trust the data is huge.

The future of work has recently become very fluid. Based on your experience, how do you think the needs for data will evolve and change over the next five years?

Over the next five years, I am extremely confident that data will be an integral part of every industry. Even less than five years ago people were talking about how data would transform business and change the world.

I’ve seen it over my lifetime as well — in college robotics we drafted with a ruler and pencil on a piece of paper. Not eight years later we were using computer-based tools, but the data was stored locally on your computer. Now? Robotics CADD is entirely in the cloud and you can collaborate in real-time.

As more and more work moves to the cloud, this trend will continue to push forward. However, it will also create opportunities to collect more data around the way people are using technology. We will see machine learning and artificial intelligence (AI) come into play, helping to identify the most interesting parts of that data. Technology will increasingly help guide you to solve problems you might not have thought to explore. Ultimately the decisions on how to use that data will remain very human.

Does your organization have any exciting goals for the near future? What challenges will you need to tackle to reach them? How do you think data analytics can best help you to achieve these goals?

Our goal is to bring this level of data insight to every engineering organization in the world and to help them see the benefits that we’ve seen. Using our own product is a huge part of how we’re making sure we take every advantage that comes in front of us to accomplish that mission.

How can our readers further follow your work?

Readers can check out the Code Climate resource page for a wealth of information, including blogs and webinars. They can also follow Code Climate on Twitter or LinkedIn.

Thank you so much for sharing these important insights. We wish you continued success and good health!

About The Interviewer: Pierre Brunelle is co-CEO and Chief Product Officer (CPO) of Noteable, the collaborative notebook platform that enables teams to use and visualize data, together. Prior to Noteable, Brunelle led Amazon’s internal and SageMaker notebook initiatives. Pierre holds an MS in Building Engineering and an MRes in Decision Sciences and Risk Management.