How to enable multi Legal Entity QTC business models with process mining and AI

The evolution of cloud CRM systems into cloud platforms has opened doors to develop complex business applications like the quote to cash (QTC) systems. QTC systems will extend the CRM functionality beyond the sales process to create quotes, contracts, orders, invoices, payments, and revenue agreements. These transactions are closely tied to a legal entity, which is typically an incorporated company in a country or an independent business unit under a parent company where financial reports are generated for legal reporting.

Legal entity should be a foundational building block for any QTC system. This is the critical functionality that will help transactions to flow into the downstream ERP. A legal entity will have the company data (address, name, etc.), currency, accounting calendar, chart of accounts, tax data (VAT, sales tax etc.) and the transaction data. The transaction data is generated in CRM (leads, opportunities), QTC (quotes, contracts, orders, invoices, payments, revenue agreements), and ERP(sub-ledgers and GL transactions).

When a legal entity is created in an ERP, the master data should be synchronized to upstream CRM and QTC systems in near real-time so that these applications can use the data to create transactions. When there are updates made to legal entity data, the updates should be interfaced to other systems. A process mining platform can mine the legal entity process and recommend the optimized process to interface the master and transaction data across front office(CRM), middle office(QTC), and back office(ERP) to give seamless one office experience to business users. This will ensure that the transactions are tied to the correct legal entity, and the legal reporting will have accurate numbers.

The platform can optimize other QTC processes like CPQ, CLM, and revenue management (order management, billing, revenue recognition, and payments) that will align with the legal entity process to reduce manual effort, increase efficiency, and deliver better performance to drive the organization towards the autonomous enterprise. Process mining will help to accelerate new legal entity implementation and expand the business to new locations. It can reconcile transactions from multiple data sources to respective legal entities.

Process mining can streamline accounting and period close processes for a legal entity in the ERP, once the invoicing and revenue recognition is completed for the period in the QTC system. Any organization implementing a QTC solution with multiple legal entities should consider a process mining platform that will build the foundation for the intelligent enterprise which can process structured and unstructured data, and handle transactions with an optimized business process. This will enable accurate legal reporting and compliance.

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