Carhartt’s signature workwear is nearly ubiquitous, and its continued presence in factories and skateparks is fueled in part by an ongoing digital transformation that’s advancing the 133-year-old Midwestern company’s operations to make the most of advanced digital technologies, including cloud, data analytics and AI.
The company, which operates four factories in Kentucky and Tennessee and designs all of its products at its headquarters in Dearborn, Michigan, began its digital transformation about four years ago. Today, more than 90% of its applications run in the cloud, with most of its data hosted and analyzed in an in-house developed enterprise data warehouse.
Katrina Agusti, a 19-year veteran of the business who was named CIO six months ago, played a pivotal role in revamping the workwear retailer for the modern age under former CIO John Hill .
Today, Agusti, who began his tenure at Carhartt as a senior programmer analyst, is responsible for leading the company’s transformation into its next phase, a phase that is accelerating daily with the barrage of complex technologies changing global supply chain and business practices, says Agusti.
As part of this transformation, Agusti plans to integrate a data lake into the company’s data architecture and expects two AI proofs of concept (POCs) to be ready to go into production at course of the quarter. Like all manufacturers in the information age, Carhartt is also increasingly relying on automation and robotics in its service and distribution centers as it faces challenges finding industry talent. side of technology and manpower to meet growing demand.
And demand is certainly on the rise for the workwear maker, which is currently seeing double-digit growth across all three of its lines of business – direct-to-consumer, direct-to-business and wholesale.
Optimize a transformation to get the most out of data
Carhartt launched its Cloud Express initiative as part of a fundamental transformation to move the company’s 220 applications to Microsoft Azure. Two legacy applications, its warehouse management solution and its payroll and benefits solutions, still work on-premises, but those applications may soon be replaced by cloud-native solutions, Agusti says.
Moving to the cloud – even in the midst of the pandemic – was a major win for Carhartt. Besides the obvious speed-to-market and scalability gains, the vast improvements in stability, performance, availability, maintainability, failover monitoring, and alerting have automated many costly IT tasks and time-consuming, freeing up the IT team to tackle advanced issues. data analysis and experimenting with other new technologies.
Agusti says Carhartt will likely adopt a multicloud architecture in the long term, but for now she and her team are building their cloud expertise in part through conversations with other CIOs about best practices.
“We’re always learning and building the muscle internally to operate properly in the cloud and how to manage in the cloud, and not just managing the systems, but how to scale them,” she says, adding that she’s also focused on the cloud. data architecture and retention strategies. “It’s a different beast to manage workloads in the cloud versus on-premises workloads. We are still on this journey.
Like many CIOs, Carhartt’s digital leader understands that data is key to making advanced technologies work. Carhartt chose to build its own enterprise data warehouse even as it built a data lake with Microsoft and Databricks to ensure its handful of data scientists have the two engines with which to manipulate structured datasets. and unstructured.
“Today, we are backscanning our data lake through our data warehouse. Architecturally, what we’d like to do is bring data into the data lake first, whether it’s structured or unstructured, and then feed it into our data warehouse,” says Agusti, adding that they continue to design a data architecture that is ideal for different data sets.
It currently has no plans to retire the internally developed data warehouse in favor of the data lake, as the team has customized many types of certified datasets for it.
“The data lake will serve more for our data science team and the consumer-facing teams who are building journeys using unstructured data to inform these personalizations,” says Agusti, noting that the six data scientists from Carhartt have built several machine learning models that are currently in test mode.
Two of these projects are nearing production, the first of which supports Carhartt’s inventory replication for its five distribution centers and three different businesses.
“We’re trying to use it for decision support and planning all of this inventory across different distribution centers based on service levels,” she says, noting that the model can optimize Carhartt’s distribution network by taking into account capacities as well as supply and level of demand and stocks.
The second POC aims to help data scientists collect consumer data that can be leveraged to “personalize the consumer journey,” including demographic information and consumer survey data, Agusti says.
The power of technology
Like many CIOs, Agusti’s biggest challenge is managing change, especially when it comes to persuading employees that the company’s AI models really work.
“Teams are skeptical that technology can deliver the decision support and automation they offer today,” the CIO says. “We have many use cases and we run them in POC mode because we need to prove to our end users and our business community that these models can make those decisions for you.”
Agusti expects many companies to be in this transition mode. “There are different functions along the maturity curve,” she says of ongoing AI efforts, “but I think there are so many potential applications that can take advantage of the technology, in particular in data analysis spaces”.
To pique its resolve on the power of technology, all the CIO has to do is think about how, without investments in technology and talent, the pandemic could have derailed business operations.
Early on, during the pandemic, many essential workers needed to be outfitted with Carhartt work gear for extra protection. As a result, the company’s revenue stream grew by double digits, even as some business segments were reduced due to widespread work stoppages.
Once work stoppages began to set in, Carhartt gained rare insight into its supply chain, allowing its data analysts to visualize supply chain stages in exquisite detail, like individual frames of a film.
“What the pandemic has done is create the need for that visibility and proactive exception management,” says Agusti. “Each step of this journey becomes important when you encounter disruption. This has allowed us to achieve more granular visibility and exception management at every stage of the supply chain. »
With this visibility — and the push from IT to keep Carhartt’s business running — the company is in a better position with its supply chain. It’s still not at the “predictable” level it was before the pandemic, Agusti says, but “we’re starting to see logistics times stabilizing and improvements in cargo creation times improving.”