Case Study: Accenture achieves 57K+ controller hours saved and centralized AI pre-close variance commentary with SAP HANA

Accenture - Customer Case Study

Accenture, a global professional services firm with 700,000+ people, faced an inefficient, decentralized pre-close variance review: controllers relied on manual downloads, spreadsheets and emails to explain P&L and balance sheet variances across many countries, which was time-consuming and error-prone as data volumes grew. The challenge was to create an AI-driven, centralized pre-close commentary tool that lets controllers focus on value-add tasks while automating the routine analysis.

Accenture Global IT built a hybrid AI solution—using SAP HANA Enterprise DataMart, SAP BTP, Python/ML and a custom AWS commentary app—to generate data-driven natural language commentaries, provide line-item drilldowns and enable real-time collaboration across 93 countries. In the first 12 months the tool saved 57K+ controller hours, streamlined 737 company codes for internal control sign-off, produced 23,610 automated commentaries monthly with ~80% approved as-is, and helped shorten the close from five days to four, improving speed, accuracy and decision-making.

Accenture

Ronald Stevens

Managing Director – Finance Operations Controllership