As many finance organizations know first-hand, period end closing is a lengthy, error-prone and complex process to go through. According to SAP’s Elizabeth Milne “corporate shared service centers spend an inordinate amount of time chasing down local entity invoices, POs, pricing contract, details to support reconciliations, intercompany eliminations, or accounting variances.”
According to this research by Ventana, “55% of companies take more than six business days to close their quarterly books compared to the generally accepted benchmark of one business week.”
Accelerating the close gives executives and managers, financial and managerial information sooner, enabling them to seize opportunities and address issues more quickly. Closing sooner also provides more time for analysis and crafting of narratives for external financial reports.
New technologies like Machine Learning become key enablers to automate resource intensive and manual closing processes, saving costs and letting accounting teams focus on more strategic tasks.
Take the Goods Receipt / Invoice Receipt account reconciliation process for example. To ensure good corporate governance and comply with the Sarbanes-Oxley requirements, every purchase order item with differences between goods receipt and invoice receipts needs to be properly cleared.
Clearing off the differences for each problematic Purchase Order requires many coordination cycles between Accounting, Buying Center, Logistics and Suppliers, burning a lot of time and resources.
It involves highly manual efforts including the creation of ad-hoc reports, gathering of relevant information, root cause investigation to solve the issue, communication and alignment between all the departments. The result is a delayed period end closing, with potential errors and inaccuracies.
As a result of this inefficient process, many accounts need to be written off, not only impacting P&L results but also reducing the accuracy of cost and inventory valuation in the financial statement.
To help accounting teams simplify and accelerate this process in SAP S/4HANA Cloud, a new intelligent Goods Receipt/Invoice Receipt (GR/IR) monitor is soon to be released (SAP S/4HANA Cloud 1805 release). It provides real-time insights into all GR/IR information, like open FI items, GR surplus of purchase order items, IR surplus, and more. It comes with embedded collaboration capabilities, so all the teams are working off of the same facts and figures.
Screenshot of GR/IR Monitor
The teams benefit from a central way of tracking the account reconciliation information so they can easily analyze and optimize the process and streamline the collaboration, directly resulting in a net gain over the period end closing time.
But that’s not all. To facilitate the clearing process the GR/IR monitor is using machine learning technology to automatically provide intelligent purchase order status recommendations that inform users on the best next steps to take when a problematic purchase order is detected. The application learns from historical GR/IR accounts clearing data in the system, to propose the most accurate status for a purchase order, allowing the end user to take faster and better decisions.
GR/IR recommendation service process
With the GR/IR monitor and the embedded automation, your teams spend significantly less time on reconciliation activities, become more efficient, and can re-purpose their efforts towards projects that drive the business forward.
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