Data Transformation is the process of converting data from one type or format (e.g. a database record, PDF, XML document, or Excel sheet) to another. The main reason there is a need for this conversion is to ensure that data from one application or database is capable of being understood by other applications and databases. Generally, businesses want to transform data to make it compatible with other data or move it to another system.
The best method to determine ideal business tasks for automation is to look at those repetitive, manual steps that are done by employees on a regular basis. For example, managing invoices can be a time heavy repetitive task requiring a number of personnel. Errors in both managing invoices and paying invoices can subsequently lead to further issues including payment penalties. So a common RPA task for buyers is to extract data from an invoice that has been approved and then input it electronically into the buyer’s back-office or ERP system. That extracted data is then available in a format that is understandable before Accounts Payable can further process it.
And in the case of suppliers, a very common task for the Accounts Receivable process is to take the business invoice data (from billing system) and automatically transform it into a standardised e-invoicing format that can be transmitted to a customer. So both for buyers and suppliers, automation becomes that critical enabler in improving the quality of data transformation, data transmission and in reducing costs.