When applying information technology to drive better business performance, companies and the systems integrators that assist them often underestimate the importance of organizing data management around processes. For example, companies that do not execute their quote-to-cash cycle as an end-to-end process often experience a related set of issues in their sales, marketing, operations, accounting and finance functions that stem from entering the same data into multiple systems. The inability to automate passing of data from one functional group to the next forces people to spend time re-entering data and leads to fragmented and disconnected data stores. The absence of a single authoritative data source also creates conflicts about whose numbers are “right.” Even when the actual figures recorded are identical, discrepancies can crop up because of issues in synchronization and data definition. Lacking an authoritative source, organizations may need to check for and resolve errors and inconsistencies between systems to ensure, for example, that what customers purchased was what they received and were billed for. The negative impact of this lack of automation is multiplied when transactions are complex or involve contracts for recurring services.
Topics: Big Data, Mobile, ERP, Operational Performance Management (OPM), Operations, Management, close, closing, computing, end-to-end, quote-to-cash, requisition-to-pay, Analytics, Cloud, Data Management, Accounting, Business Performance Management (BPM), CRM, Data, finance, Information Applications (IA), Information Management (IM), Sales Performance Management (SPM), Supply Chain Performance Management (SCPM), FPM