These are revolutionizing the game," he says. "They enable us to process change records without the compute expense of batch- or SQL-based transformations.
Suhas Hanumanthaiah
Precision in inventory management is no longer a back-office function, it is a frontline imperative in today's rapidly changing world of retail. With uncertain demand cycles, perishable inventory, and seasonal purchasing behavior, grocery retailers face the constant challenge of keeping store shelves full but not too full. Digital transformation has now made real-time data-driven decision-making possible, substituting gut-feel estimates with algorithm-optimized planning. This transition is rewriting the playbook on how retail chains streamline their inventory, eliminate waste, and increase revenue-largely due to next-generation data infrastructure that weaves together sales, inventory, and procurement systems with scalpel-like precision.
At the heart of such transformation initiatives in the grocery retail space is Suhas Hanumanthaiah, a Data Architect whose efforts at Grocery Outlet have been key in revamping legacy data systems to drive smart business operations. As per insiders in the industry, Suhas had a pivotal leadership function of creating near-real-time data pipes that consolidated disparate information between POS systems, SAP HANA, and custom ordering systems. "The pace of retail is not merely about complexity, it's all about timing and accuracy," he explains. "Knowing when to order milk vs. when to replenish alcohol boils down to knowing item velocity-and that information has to be accurate."
From the expert committee, his professional successes are a résumé for a data backbone for the modern retail age. He spearheaded the petabyte-scale Amazon Redshift to Google BigQuery migration, drew more than 300 data tables, and created foundational ELT frameworks on Google Data Fusion that allegedly reduced development by 50%. His work didn't simply bring infrastructure up to speed-it actually transformed the way decisions were being made on the ground. For instance, his central work on Sales Margin Reports permitted price decisions directly influencing profitability. According to the reports, this was particularly important after deployment, where his role went up to verifying and ensuring data quality on business intelligence reports within a strict 15-minute SLA window.
In addition, in the mission-critical migration to digital commerce touchpoints, Suhas created and optimized data streams from SAP HANA and SAP CAR to drive partnerships with eCommerce leaders such as Instacart, UberEats, and Doordash. He states, "This interface wasn't merely a back-end transformation. It directly allowed Grocery Outlet's mobile platforms and eCommerce strategy to become responsive to inventory in real-time."
To this, he addressed some long-standing technical problems that had remained unsolved. Significantly, running SAP's SLT Replication tool had no inherent failure notifications-preying on hidden data losses. He addressed this by creating bespoke data quality reports and alert mechanisms to identify and notify the SAP support team for replication delays. This guaranteed freshness for key sales and inventory information utilized by store managers to plan weekly purchases. "One faulty table in replication can bias an entire category's sales forecast," Suhas explains.
On the expense side, his rearchitecture of more than 250 custom APIs reduced BigQuery operational costs by 35%, and MicroStrategy report query tuning by 15% produced a performance improvement. These are not merely engineering victories-they're bottom-line results in a margin-hungry business.
Although his written work in this area is ongoing, his thoughts about the retail data architecture of the future include more utilization of messaging technology such as Kafka and Debezium for CDC. "These are revolutionizing the game," he says. "They enable us to process change records without the compute expense of batch- or SQL-based transformations."
Suhas's odyssey is a testament to the depth that technical expertise coupled with industry-specific knowhow can rewire the very spine of a retail business. His on-the-ground effort amidst a complete digital overhaul-through integration challenges, data integrity, and real-time reporting-has not only made sure shelves are full, but that each item shelved there is a bet put in after careful consideration, supported by data.
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