Case Study: ARVIND FASHIONS' Data-Driven Digital Transformation with Google Cloud

The key objectives for Arvind's DX were to unlock the value of existing applications, gain new insights, and build a solid workflow with resilient systems. To help in this journey, it partnered with Google Cloud...

- Satish Panchapakesan & Mandar Chaphalkar

Arvind Ltd. has been in the apparel industry for more than 90 years, with its retail powerhouse Arvind Fashions Ltd. (Arvind) being the backbone of well-known names in the retail fashion industry in India.

Arvind has seen significant growth in its portfolio with new franchises being added every year. The six high conviction brands include Tommy Hilfiger, Calvin Klein, Sephora, Arrow, U.S. Polo Assn. and Flying Machine.

To secure a foundation for future growth, Arvind has embarked on a digital transformation (DX) journey, focusing on profitability and improving the customer experience. The key objectives for Arvind's DX were to unlock the value of existing applications, gain new insights, and build a solid workflow with resilient systems. To help in this journey, it partnered with Google Cloud Getting Google Cloud to address the challenges around insights and analytics was a natural step forward, since Arvind had already formed a relationship with Google Cloud, starting with its productivity and collaboration tools during the pandemic.

The Business Need

Arvind's enterprise applications estate is a mix of SAP, Oracle POS, logistics management systems and other applications. Having so many different applications made it challenging for the company to bring all of this data together to drive retail insights and at the same time maintain the freshness of its products.

As a case in point, the existing sales reporting and inventory reconciliation process had been enabled by a mix of automated and semi-automated desktop applications. There were challenges to scale the infrastructure to process large amounts of data at a low latency.

The synchronization of master data across functions was critical to building the data platform that provides consistent insights to multiple stakeholders across the organization.

The Approach