Skechers Runs On Better Data With Incorta

Summary: Before Incorta, delivering a new dashboard at Skechers could take six months. Today, the data and analytics team can do this in weeks. Data is refreshed daily before the business logs in, near-real-time refreshes are available for critical datasets, and a unified inventory view lets users slice billions of rows by country, distribution center, or day. For a retailer shipping 272 million pairs of shoes to 200+ countries, that speed and grain of insight is a massive competitive advantage.

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‍When Manish Ahluwalia joined Skechers as VP of Data & Analytics, his mandate was clear: modernize BI and analytics, and make the company genuinely data-driven. What he inherited was a fragmented landscape: data spread across systems, no single source of truth, and a BI team spending more time wrangling data than delivering insights.

Traditional data warehouse pipelines required seven to nine steps before any business user could access insights. By the time data moved from source systems through ETL, modeling, warehousing, and semantic layers, it was stale - and the team had burned weeks delivering it.

Skechers’ core data challenges were interconnected and compounding:

▪  No single source of truth. Business users pulled data from different systems and arrived at different numbers, eroding trust in reporting.

▪  Speed to delivery. Delivering a new dashboard or insight took three to six months - far too slow for a fast-moving global retailer.

▪  Volume and complexity at scale. With tables containing billions of rows across inventory, wholesale, and e-commerce data going back three years, most BI tools simply couldn’t keep up.

▪  BI team dependency. Analysts were bottlenecked, spending cycles on data engineering rather than insights. Business users couldn’t self-serve.

The stakes were high: without trustworthy, timely data, Skechers couldn’t make confident decisions on inventory positioning, sales performance, or global wholesale trends.

Skechers implemented Incorta as the silver and gold layer in a lakehouse architecture, with raw data residing in Databricks and Incorta handling the analytical layer that serves the BI team and business users. Incorta’s Direct Data Mapping dramatically reduced the modeling burden, enabling the BI team to move from data ingestion to dashboard delivery without the traditional engineering overhead.

Key use cases deployed include:

▪  Inventory visibility. A unified inventory dashboard lets users slice data by product status (in production, in DC, in transit), by day, month, country, and distribution center - pulling on three years of historical data to surface patterns and trends.

▪  E-commerce performance. A single digital dashboard consolidates margins, gift card usage, conversion metrics, and more - giving the digital team a complete view of what’s happening across channels.

▪  Forward-looking wholesale performance. Rolled out to 30–40 countries, this dashboard tracks bookings, popular SKUs, and forward demand signals to help commercial teams plan ahead.

Incorta’s in-memory architecture enabled the team to join and harmonize data across billions of rows - something no prior solution could handle at the required speed and granularity.

Skechers has made significant strides since deploying Incorta. Delivery timelines that once stretched to three to six months are now targeted at three to four weeks within a Scrum sprint cycle—a pace that’s improving trust and adoption across the business.

Data is refreshed daily by 8:30 a.m. so that every team starts the day with current numbers. Near-real-time refreshes are being rolled out for the most time-sensitive datasets. Role-level security ensures that country managers and regional sales reps see only the data relevant to their territory: enabling a confident, compliant global rollout.

The BI team itself has been transformed. With Incorta’s flexibility, analysts can modify materialized views and schema directly - no longer at the mercy of data engineering bottlenecks. The result: faster iteration, higher quality, and a team that can actually focus on generating insight.