Despite the exponential growth of automation, organizations the world over still rely on manual data entry for procurement. Employees are transferring data from purchase and requisition orders, invoices, and receipts into ERP systems such as SAP, NetSuite, and more. And while the financial implications of error could be disastrous for the bottom line, businesses rarely view data entry as a critical strategic operation.
And while data entry may not be considered a strategically important operation, there is no doubt procurement is, which is the reason businesses spend large amounts of time and resources implementing eProcurement and ERP systems and transferring data into them.
Manually entered data—even by the most experienced professional— is, by nature, error-prone; transposition and transcription errors, for example, are omnipresent sources of unreliable data for companies that still rely on manual data entry. Additionally, the speed of automatic transfers of data between platforms is significantly higher than even the most productive employees.
Inaccurate or incorrect data is a significant risk, and therefore data entry is of strategic importance to any business. According to The Data Warehouse Institute, upwards of $600 billion every year can be attributed to data entry errors in the supply chain, data procurement, and other vital areas, exposing organizations to compliance risks in addition to a large amount of wasted money and resources.
Even if manual data entry is 90% accurate (which is unlikely given the “acceptable” rate of errors is roughly 70%), do you want to be held accountable for the disparate data that causes thousands or even millions of dollars worth of misspent resources? What about the potential legal ramifications that occur as a result of those errors? Automating data entry results in quick, accurate records that are reliable and free of inadvertent errors and costly mistakes.
Thomas C. Redman wrote about a project In the Harvard Business Review, in which AT&T set out to reduce invoicing errors. The project found that a mind-boggling 40% of their invoicing data contained errors resulting in the telecom giant overpaying vendors by tens of millions of dollars. The majority of these errors were caused by incorrect data entry somewhere along the chain from the supplier to AT&T’s accounts payable department.
While other costs associated with manual data entry errors may not be as tangible from a cost perspective, they are no less important. An ERP platform that is ripe with errors leaves a business without a trusted source of data to inform business decisions, or, if they do rely on the inaccurate data, the resulting decisions are unlikely to produce the best outcomes for the business. Inaccurate data is a poison that infiltrates nearly every facet of your organization, including overall productivity as well as market competitiveness.
It is for these reasons that Itemize introduced our data automation solution, Retriever. It works in tandem with your ERP systems to ensure the transferred data is accurate, reliable, and parsed rapidly.
The AI-powered engine extracts data from invoices and other documents in less than 30 seconds, itemizing the contents and providing numerous fields of accurate, searchable data. Imagine a compliance department accessing a hotel folio and knowing the full extent of the mini-bar charges versus the daily room rate or a staff accountant quickly locating documents that are critical to closing your books at the end of the year.
Don’t let human error and inaccurate data wreak havoc on your operations. Learn more <link to Retriever page> about Retriever and how this solution will decrease headaches and increase efficiency simply and effectively. Better yet, try the solution for free and see for yourself. Set-up is quick and easy, and results are viewable in under 20 minutes.
