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HomeTechCarhartt's new CIO is using data 2022

Carhartt’s new CIO is using data 2022

19-year Carhartt veteran Katrina Agusti takes the IT management of the workwear maker to capitalize on its cloud-based journey by enhancing data processing and making the best use of AI.

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Carhartt’s new CIO is using data, USA TODAY and TOMORROW.

Carhartt’s iconic workwear is all over the place, and its constant appearance in factories as well as in skate parks as well is partly due to a constant digital revolution that is pushing the 133-year-old Midwest firm’s operations to take advantage of the latest digital technologies, such as the cloud data analytics, data analytics, and AI.

This company, which has four manufacturing facilities in Kentucky and Tennessee and develops all its products in its Dearborn, Mich., headquarters, started its digital transformation around five years ago. Today over 90% of its software is cloud-based, with the bulk of the data being stored and processed in a local corporate data warehouse.

Katrina Agusti, a 19-year veteran of the company who was appointed CIO just six months ago, has played an integral role in retooling the retailer of workwear to meet the demands of the 21st century under the previous CIO, John Hill.

Today, Agusti was hired to begin her Carhartt time as a senior program analyst and is in charge of guiding the company’s transformation to the next phase of its growth which is growing each day due to the flood of new technologies that are changing the supply chain globally and the way businesses operate, Agusti says.

As part of that change, Agusti plans to integrate a data lake in the company’s data architecture and anticipates two AI prototypes (POCs) are in production in the next quarter. As with other manufacturers in this age of information, Carhartt is also increasingly relying on robotics and automation in its fulfillment and service centers as it struggles to attract talent on the technical side as well as on the labor force to meet the increasing demands.

Demand is increasing for the manufacturer of workwear that is currently seeing an increase of double-digits in the three lines of business: direct to the consumer, Direct to Business, Direct Consumer, and wholesale.

A transformation’s tuning to make the most use of the data

Carhartt has launched its Cloud Express initiative as part of a transformational process to move its 220 applications toward Microsoft Azure. Two of its legacy applications, the warehouse management software and its payroll and benefits applications, are still on the premises. Still, they are likely to be replaced with cloud-based services, Agusti says.

Moving to the cloud, even during the spread of the pandemic, was a massive success for Carhartt. Apart from its apparent benefits in speed of the market and increased scalability as well as the vast improvements in performance, stability uptime, monitoring of failovers, maintenance, and alerting has streamlined a lot of the time-consuming, expensive IT tasks, leaving the IT department to focus on advanced data analytics as well as to play with new technologies.

Agusti claims that Carhartt will likely embrace a multi-cloud platform in the future. However, for the moment, Agusti and her staff are working to ramp up their expertise in cloud computing by having conversations with other CIOs regarding the best practices.

She adds that she is researching the data architecture and retention techniques. “We’re in the process of learning and developing the internal muscle to function in the cloud and to be able to handle cloud-based workloads not just managing systems, but also how to scale these systems,” she says. “It’s an entirely different process to manage cloud workloads as opposed to workloads that are on-premises.” “We’re in the process of figuring that out.”

As with many CIOs, Carhartt’s most senior digital executive knows that data is crucial to enabling advanced technologies to work. Carhartt chose to construct its enterprise-level data warehouse while also building a data lake using Microsoft Databricks and Microsoft Databricks to ensure its few data scientists have the suitable engines and the capability to manipulate data in unstructured and structured formats.

“Today, we are using our database to backflush our data lake.” “The way we’d prefer to do is to bring the data first to the lake, regardless of whether it’s structured or not, and then feed in our database,” Agusti says, adding that they are continuing to develop the data architecture that works for various kinds of data.

She has yet to make plans to shut down the local data warehouse to make way for the data lake since the team has customized several kinds of data sets certified for it.

“The Data Lake will become serving our Data Science team as well as teams working with consumers to build experiences using unstructured data to aid in personalizations,” Agusti says, noting that Carhartt’s data scientists have developed a variety of machine learning models, which are currently being tested.

Two of these projects are in production, with the first which will allow Carhartt to replicate inventory for five distribution centers and three distinct business units.

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According to the degree of service, she says, “We’re attempting to use it to help with decision-making and to distribute that inventory to different distribution centers.” She says, noting that the system can improve the efficiency of Carhartt’s distribution system by taking capacities into consideration in addition to demand and supply levels.

This second POC is designed to assist data scientists in gathering consumer data which can be used to “personalize the journey of a consumer,” including demographic information and information taken from consumer surveys, Agusti says.

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The power of technology

As with many CIOs, Agusti’s greatest challenge is change management, especially regarding convincing employees that AI models work.

The CIO claims that teams are wary about technology that can provide the same degree of assistance and decision support as it does now. “We have many scenarios to use and are operating them in POC mode as we have to show our business partners and end-users that the models are able to take the decisions for you.”

Agusti believes that many companies are currently in this state of transition. “There are various functions on the maturity curve,” she says about the AI projects in the pipeline, “but I think there are a lot of applications that could benefit from technology particularly in the data analysis space.”

To entice her into the potential of technology, All the CIO needs to think about is the ways that the pandemic could have disrupted the company’s operations without investment in technology and human capital.

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At the beginning of the outbreak, most workers were required to be fitted with Carhartt workwear to provide additional protection. This resulted in the company’s revenues growing by double digits even though certain business areas were slowed down due to the massive work stoppages.

Carhartt gained a rare glimpse of its supply chain when work stoppages began taking place. This allowed the data scientists to see the various steps of the supply chain in stunning detail as if they were each frame of the film.

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“What the pandemic has done was to create the need for an understanding of the situation and proactive control,” Agusti says. “Every step of the journey is crucial when there’s disruption. This was the reason that led us to be more precise in the monitoring and control of each individual step of your supply chain.”

Because of that visibility and IT’s efforts to keep Carhartt’s business running, The company is now in a better position in the supply chain. The supply chain isn’t at the “predictable” level before the pandemic, Agusti says, but “we’re seeing logistics lead times diminishing and the speed of lead time for creating goods becoming more efficient.”

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Gulsher Ali
Gulsher Ali
Journalist | Media | Blogging. These Three Words Describe Me in The Best Way. I Am a Journalist with 10 Years of Experience. I have a small team who helps us with content writing.
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