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Home > Canon Business Process Services > Learn What It Takes to Be a Top Performing AP Department with Impressive Cycle Times at High Volumes
 

Learn What It Takes to Be a Top Performing AP Department with Impressive Cycle Times at High Volumes

White Paper Published By: Canon Business Process Services
Canon Business Process Services
Published:  Nov 08, 2013
Type:  White Paper
Length:  14 pages

This whitepaper sponsored by Canon Business Process Services provides finance and business leaders with the performance indicators for becoming brutally efficient in the accounts payable function.  We will examine the three drivers responsible for the efficiency and success in high performing AP departments. We also look at how the “best-in-class” AP functions differ from the average through six performance indicators.

In this AP survey report, you will learn:

  • The several underlying “operating performance metrics” that drive core efficiency and ultimately lower the total cost of processing an invoice
  • The six metrics you need to measure and benchmark to identify the improvement areas that will take you from an average performing AP department to a best-in-class performing department.
  • How one biopharmaceutical company transformed its accounts payable process by adopting several best practices examined in the report – such as centralizing invoice receipt – to decrease backlog from 3,000 to 50 invoices and a 22 percent increase in on-time payments.

Transforming an accounts payable department from a majority of paper invoices and manual processes to an automated high-performance one requires several steps that address process, labor and technology requirements.  Get the latest data and learn how.  Complete the form today to download  this important industry survey.



Tags : 
blitzmedia, ap department, cycle times, high volumes, high-performance ap, transform accounts payable, market competition, accounts payable function, canon business process service, ap organizational structure, data capture, data extraction, optical character recognition, enterprise applications