How Grainger ties learning culture to engineering outcomes

For the past few years, Grainger has focused on modernizing, and cloud, specifically containers and Kubernetes, has been the key to that transformation. 

But to achieve this goal, they needed to upskill their teams and empower them to become fast-iterating business partners.

Grainger’s Eric Chapman, Director of Engineering Effectiveness, and Patrick Egan, Engineering Manager, explain how they connect skill development directly to engineering outcomes to scale their learning culture, improve developer productivity, and build a secure, multicloud organization.

Watch the on-demand webinar.

Every transformation starts with a North Star, and for Grainger, it was their need for continuous delivery.

“Our speed of delivery was slow, and we had the same challenges that a lot of organizations our size do: large coordinated releases, code freezes, and things like that,” says Eric.

Ultimately, they wanted to create safer, more resilient applications for their customers faster. They also wanted their team members to feel supported.

“We want to improve their joy,” says Patrick. “Happy developers produce better code. They're much more engaged in the work, and they're able to retain that knowledge when they're engaged in it.”

To achieve these goals, they knew cloud transformation was the right move—but success would hinge on getting their engineers up to speed.

“We had strong Java engineers that needed to learn cloud-native delivery practices. When you talk about moving to microservices and containers, there's lots of new challenges engineers need to face,” explains Eric. “We need to continue delivering the value in running the business of Grainger, while also learning these new skills, like cloud-native delivery and observability.”

By defining their North Star and objectives upfront, Grainger ensured their learning culture and skill development initiatives aligned with their organizational goals.

Grainger establishes sensible defaults that guide how they develop products, upskill their teams, and deliver business value.

“Sensible defaults are our guide rails and standards for what good looks like, helping the engineering side of the house know what targets they're aiming for,” explains Patrick.

In the beginning, it can take time to define your organization’s sensible defaults. But once everyone’s working from the same baseline, you can actually move faster, whether you're working towards AI adoption or a cloud migration strategy.

“Being deliberate about taking the time to define your practices and principles of how software is crafted is really important, especially when you think about AI,” says Eric.

“If you haven't taken the time to define how you're going to balance speed and velocity with safety, you're going to have a hard time with AI. But if you already know what your guiding principles are and the practices you're looking for, then you can use that to measure and kind of temper your experience.”

When it comes to learning and retaining information, Grainger uses a variety of methods to help skills stick. The most effective method for long-term retention? Immersive, hands-on learning opportunities.

“We know from statistics that learning doesn't stay with us very long unless we apply it very quickly. So we model our learning with multiple modes to help bring the best of the platform learning together alongside immersive learning,” says Patrick.

“We're seeing that knowledge with that immersive learning is still there up to a year later, so it makes a big impact on helping the team members learn how to apply the work and the learning to the work itself.”

To create those immersive experiences, Grainger uses a mix of: 

• Quarterly learning events focused on specific topics with internal and external speakers 

• Annual hackathons (with prizes)

• Conferences like the Grainger Tech Conference that help nurture a culture of continuous learning

• Dojos customized to different teams and the problems they’re working on

• Workshops that help a team member or a group learn a specific topic

• Embedded engineering events that deploy engineers into teams 

• Learning platforms for near-the-job or off-the-job learning opportunities

This approach is paying off. Says Patrick, “We use different combinations of those to really help increase velocity and bandwidth. We've seen a 20 - 150% return on what [teams are] able to produce through that delivery work.”

Understanding transformation success and the true value of upskilling relies on tracking the right metrics. That’s why Eric and Patrick recommend going beyond DORA metrics.

“The industry's sort of coalescing around the DORA metrics and DORA capabilities, which is great. We use that. But also think about metrics beyond DORA. How do you measure if teams are leaning towards your sensible default?” asks Eric.

“On average, when you look at our delivery insights across the board, we're averaging one deployment to production per day per team, so it's pretty impressive, pretty remarkable, what our teams have been able to accomplish.”

It’s insights like these that help them connect upskilling to cloud transformation and engineering outcomes.

Uncover 17 metrics to track upskilling ROI.

At the end of the day, successful digital transformation relies on leaders’ and learners’ commitment to continuous learning—and Grainger knows this.

“The pace of change is only getting faster, so you have to be a lifelong learner, a continuous learner at heart, to stay relevant,” says Eric. “At Grainger, we're heavily investing in creating that space, but as an individual, you also have to focus and put the effort in as well.”

Learn more about how Grainger scales upskilling throughout their organization—watch the on-demand webinar now.