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By conducting a variance analysis on its fixed asset management processes, the company successfully identified inefficiencies and implemented targeted solutions. This initiative led to a 30% decrease in maintenance expenses and a 50% drop in administrative effort through the use of automation.
The company needed to address hidden inefficiencies and discrepancies between their budgeted and actual costs specifically related to the maintenance and repairs of their fixed assets.
Automated the ingestion of logistics invoices into a new procurement system, saving up to 70 hours per month and preventing late payment fees on $2M in delayed payments.
A transition to a new procurement system broke an existing automated integration that previously allowed seamless upload of a major logistics provider's invoices. This forced the account manager and operations team to manually download, format, and upload CSV files. The resulting bottleneck created significant payment delays of around $2M, accrued late payment fees, and caused vendor frustration.
Automated manual flux analysis processes for an accounting operations team, reducing the time of analysis to minutes instead of hours and saving 3 Full-Time Equivalents (FTEs).
The existing recurring process for preparing monthly Flux Analysis was extremely manual and time-consuming, consuming an estimated 400 hours per month across 1–2 business days. The process involved at least 100 people from the Accounting Operations team across 5 regions and relied heavily on time-consuming drill-through investigations rather than identifying clear operational metrics that drive variances.
Centralized over 250 distributed tax and regulatory payments, reducing report generation time by 75% and reconciliation time by 80% while establishing robust governance.
The company's tax and regulatory payments were heavily decentralized and distributed across various local operations. This fragmented approach lacked standardized procedures, clear accountability, and centralized governance, leading to inefficiencies and potential control risks.
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