efficiencies saved annually
seconds needed to return queries
Late insights delay resolution
Before Incorta, it wasn’t easy — or fast — for the Sales Comp, Finance and IT teams at a leading Fortune 100 technology company to accumulate, synthesize and understand the data needed to support specific queries and other manual processes relating to sales commissions. These data-intensive activities were always time-consuming and prone to error. Various systems — including SFDC, Oracle, Snowflake and Kafka — were the data sources. A dependency on IT resources and a few core developers caused weeks of delays when preparing and summarizing data. It took minutes — even hours — to run important reports due to manual data refreshes and unwieldy SQL Server data schemas.
Low replication with the company’s Snowflake data warehouse often resulted in unreliable data. In 2020, a change in the company’s commission data created an explosion of transactions, making a bad situation even worse. The amount of time required to transform data to insights increased to 4-6 weeks, while the average amount of time needed to resolve approximately 3,000 commission disputes ballooned to 40 days. Traditional approaches like increasing staffing were not the right solutions anymore. There was a need for fundamental transformation.
Fast sales commission insights via real-time analytics
Within three short months of implementing Incorta, the Fortune 100 technology leader’s Sales Comp and Finance teams can see instant results for the new — and modified — sales compensation use cases and reports they build while resting assured of the data’s continued security and governance. Incorta can quickly ingest large data volumes and enable complex data transformations at large data loads via Apache Spark.
Team members can access data directly from any application in seconds. By pairing a machine-learning model with Oracle Territory Management (OTM), transactions are automatically credited to sellers, eliminating manual intervention and weeks of delays when preparing and summarizing data.
OCTOBER 13, 2022
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