India’s speciality retail major, Arvind Fashions Ltd (Arvind), has built a modern data platform to improve productivity and other existing business processes and systems using Google Cloud.
Arvind Fashions’ CIO, Satish Panchapakesan, said the Google BigQuery-enabled data platform supported critical business pivots like variety, variability, velocity and volume for successful retailing.
The key business principles have targeted variety to deal with seasonal fashion trends, variability for handling footfalls during festivals and weekends, velocity to respond to customer needs and volume to generate data that can bring rich insights.
Arvind has been operating for more than 90 years, forming the backbone for several brands in the retail industry.
It includes six high-conviction brands like Tommy Hilfiger, Calvin Klein, Sephora, Arrow, and US Polo Assn. and Flying Machine in its portfolio.
Using the modern data platform, the firm has now been able to bring the ingestion frequency of store-level inventory, for around 800 stores, to once a day.
“We achieved seamless scaling of additional data volumes and process with BigQuery,” Panchapakesan said.
The firm has embarked on the digital transformation journey with a focus on profitability and improving customer experience. It built its objectives to gain new insights and to form solid workflow with resilient systems.
The company implemented new processes and dashboards for reconciliation and root cause analysis.
This successfully reduced discrepancies in various reconciliation activities for the firm drastically. “We could not identify discrepancies but also identify the root cause,” he added.
Moreover, Arvind was able to improve operational efficiencies leading to better productivity and reduced turnaround times. It has enhanced some existing business processes and systems with insight from the data platform.
Challenges
Arvind’s enterprise applications comprise various applications such as SAP, Oracle POS, logistics management systems and others.
With such a wide range of applications, it faced several challenges to gain consolidated data for retail insights.
For instance, its existing sales reporting and inventory reconciliation process was enabled by both automated and semi-automated desktop applications.
“We found it difficult to scale the infrastructure to process large amounts of data at low latency,” he said.
Panchapakesan added that it was also less feasible to synchronise master data across functions without a data platform that would provide “consistent insights” for multiple stakeholders across the firm.
BigQuery
As part of its extended partnership with Google, the retailer decided to implement BigQuery, as it believed the serverless construct would allow data engineering teams to focus only on insights and analytics.
“We needed a solution with vast technical capabilities like data lake or data warehouse, which would also be simple to run ongoing operations,” he added.
With BigQuery procedures, the company processed data natively within the data warehouse using familiar SQL.
The team has achieved ease of operations in infrastructure setting and management operations, as now it focuses on building the data pipelines and models to feed into analytics, he explained.
Panchapakesan said by implementing BigQuery, the retailer decoupled storage and compute, leading to flexible pricing. “The pay-as-you-go model turned out to be an ideal solution to manage costs,” he added.
Arvind Fashions is now ready with many new initiatives in getting more apps on edge devices, warehouse analytics and in advanced customer data platforms space. It is also expecting tech launches to predict the lifecycle of designs, style codes and more.
