Grainger Innovation, Technology & Agility

What practices does your team employ to foster innovation?

One of Grainger’s company principles is to embrace curiosity. This value is encouraged at the companywide level and put in practice by teams across the organization. On the machine learning side, we’re encouraged at a company level to attend conferences to expand our knowledge base, share insights when applicable and network with others in the industry.

At a team level, we host all-hands meetings, journal clubs to discuss research papers about emerging technologies and biweekly demos both on applicable solutions and new technology functionality.

Finally, within my team, as an effort to promote personal development while also aligning to team goals, we build in time during our working hours to learn. Personal development learning could include diving deeper into research papers, exploring new solutions, learning about new technology, etc.

With such a cross-collaborative team that takes the time to learn with and from one another, I feel we are better able to gain new perspectives that help us find the best solutions to meet our customer needs. People — customers or team members — are at the center of our work, and brainstorming, networking and conversing with peers often paves the way to the best solution we can find to solve our problem.

How has a focus on innovation increased the quality of your team’s work? 

I’ve been in a manager role for about two years, and I feel that the knowledge we share with one another allows us to be creative in identifying a solution, while also remaining focused on our business objectives. 

A key Grainger principle is to win as one team, and the cross-collaborative elements of our team do exactly that. Presentations, journal sharing, demos, etc., stimulate us to design multiple innovative solutions that may solve the problem, all while building confidence in our team members to feel comfortable sharing their ideas. Creating a psychologically safe environment where team members feel they can have influence, even if it’s not directly the solution, allows us to get a full scope of a problem, and identify pros and cons to a solution. It’s often in these brainstorming sessions where we can best understand the pain-points of a customer and help discover the root of a problem.

One example of how we do this is by hosting an annual Grainger hack-a-thons where teams participate in creating innovative prototypes to solve a business case. Learning in this way makes us stronger engineers and encourages out-of-the-box thinking. Sometimes we come up with applications that may solve another problem entirely.

How has a focus on innovation bolstered your team’s culture? Do these different practices give team members greater chances to bond and have fun?

A focus on innovation has allowed our teams to bond more. We take the time to listen to unique perspectives on a solution and try to see through other eyes how a team member’s background or industry knowledge may make them approach a solution differently. Having this understanding of how others think allows us to make better decisions. Cyclically, when we’re able to understand each other better and spend time getting comfortable ideating, we feel encouraged and comfortable to share more. This mentality is already enmeshed in our culture, as we’re encouraged to in as one team, through the Grainger Edge principles, driving us to share ideas, cross-collaborate and feel like we can rely on one another.

What is the unique story that you feel your company has with AI? 

Grainger is nearly 100 years old and serves a very large customer base. What makes us stand out is our ability to balance established industry leadership with continually innovating technology solutions that aid our core business processes. My team maintains a fast-paced work environment while striving to meet business objectives that help drive the solutions we’re looking for. One of our core principles at Grainger is “start with the customer,” which, for our team, means understanding the root of the problem and finding a quality solution while working fast and completing projects at scale. AI also helps us deliver on Grainger’s purpose to keep the world working by making our processes more accurate and leaving space to continuously make improvements that allow us to solve customer needs.

What was a monumental moment for your team when it comes to your work with AI?

Every day has the potential to be monumental; some interesting moments come out of places we least expect them. One of Grainger’s principles is to “embrace curiosity,” so finding how to best apply new technology to solve business cases is exciting and our values directly encourage exploring new solutions. Simultaneously, we are intentional about remaining customer centered, finding the root of a problem and learning how to solve it. I believe that any company that wants to outlive their competitors needs to be customer-focused. Grainger’s principle of “start with the customer” enables us to understand the root of a problem so we can find the best solution.  

I am leading a team of exceptionally talented people who can work laterally across various applications of AI, yet they also have their own specializations. Being able to cross collaborate, make practical connections between customers, the problem and technology, and then adapt the tech quickly keeps me engaged. Our team expects new things to happen and stays agile to shift direction when a new solution comes along. Staying closely connected to our product team also allows us to adopt best-in-class AI technology.

What challenges did your team overcome in AI adoption? 

Proving or disproving a case is easy but getting it to work at the scale of Grainger’s business is challenging and requires a lot of data. My team has developed exceptional capabilities in simulating real-world data on which to train our models. We started with no actual data for training models and have since built models that allow us to deliver successful projects. With AI as a continual emerging technology, there’s still a challenge to pave the way in a lot of AI applications which can be a valuable learning experience. We understand that success comes from taking intentional steps and making positive contributions while learning new things. 

As for continuous learning, Grainger’s culture encourages team members to be curious and eager to learn. We’re urged to take time to develop or learn new skills, participate in weekly cross-team learning sessions, work on journal collaborations, attend conferences and share knowledge as much as possible. This culture of learning allows us to be both students and teachers, experiment with tools to discover outcomes — and, ultimately, feel like we have unlimited solutions to tap into.