Inside Sales Change Request Automation at a Global Communications Services Provider — 67% AHT Improvement, 98% On-Time Closure
DocuMage + Workflow Automator + Workflow Planner intelligent-OCR-and-RPA combination handling 200+ CRs per month per agent with 7-application orchestration and soft-quote generation.
MindMap OS · installed inside the customer's perimeter by forward deployed engineers · Managed Cloud · billed on the result
The challenge
The client — a global IT-and-communications services provider operating the world's largest communications network reaching 220 countries-and-territories with operations in more than 100 countries-and-territories and a staff strength of more than 25,000 people globally — was responsible for setting up complex network-infrastructure sites for its customers. Owing to the inherent complexity in the nature of such services, multiple change-requests (CRs) were being raised by the customers, with each CR representing added potential revenue.
The mechanical workflow had structural concerns. A long and time-consuming lifecycle from the point of raising a new CR to booking an order in the ERP-system; very high manual efforts in querying multiple systems to check specifics of network-hardware-devices and inputting it back into the core ERP-system; missed-revenue-opportunities due to the delayed response-cycle; and high quantum of errors and iterative-communication with customers leading to poor customer-experience.
Quantifying the problem statement made the scope clear: 200+ CRs received in a month per inside-sales agent managing a small subset of customers; high AHT for each transaction at approximately 1 hour; extremely manual process consuming more than 1,500 hours of work per resource annually; high processing cost per CR processing (USD 75 per CR); approximately 40% of CRs not closed on time due to high volume of manual work; out of the above estimated approximately 25% of CRs or new requests lost due to untimely closure.
The approach
MindMap deployed an intelligent RPA solution composed of Workflow Automator (Wa) for the cross-system automation, DocuMage (Dm) for the AI-based Intelligent OCR with computer-vision for some applications, Workflow Planner (Wp) for the workflow-based human-input handling, and Multi-Agent Orchestrator (Mo) for the cross-system workflow coordination.
Phase one was the inside-sales mailbox-and-ticket-intake workflow. The bot maintains real-time access to the inside-sales mailbox to read new CR tickets from ServiceNow and other internal client-applications. The intake workflow handles the per-channel inbound CRs with the appropriate normalisation.
Phase two was the CR-classification-and-data-extraction workflow. DocuMage performs the automated extraction of data from the raised request to identify and classify the nature of the change-request or new-request from the customer (1 out of 4 possible categories). The extraction involves ICR capabilities in some request-types and computer-vision for the specific request-types that require it.
Phase three was the multi-system data-aggregation workflow. The bot queries up to 7 different applications to pull out the necessary information around the change-request based on the nature of the change-request. The data-aggregation handles the per-application authentication-and-data-access pattern with the appropriate per-CR information-completeness validation.
Phase four was the soft-quote-generation-and-approval-routing workflow. The bot updates the CR master-tracker and generates and sends a pre-compiled soft-quote for the new-service or change-request to the inside-sales agent. The inside-sales-team manually reviews-appends-and-approves the soft-quote, and the bot then finally queues the CR closure for final approval by the business-team.
Phase five was the sales-order-filing-and-ERP-posting workflow. Post final-approval, the bot moves on to filing the sales-order in client internal-applications and enters the order-details in the customer ERP. The end-to-end workflow handles the per-CR lifecycle from the intake through the ERP-posting.
The pre-built building blocks
Rather than commission a ground-up build, the engagement leaned on MindMap's pre-built accelerator library — production-tested components that compress what would otherwise be a six-to-nine-month build into weeks.
Workflow Automator →
Cross-system unattended-RPA per-CR execution
DocuMage →
AI-based Intelligent OCR with computer-vision for CR classification
Workflow Planner →
Workflow-based human-input handling for review-and-approval
Multi-Agent Orchestrator →
Cross-system workflow coordination with parallel data-aggregation
The architecture
The platform runs on the provider's managed cloud environment with appropriate per-customer data-residency. The integration spans the inside-sales mailbox-and-ServiceNow, the 7-plus client internal-applications for the data-aggregation, the CR-master-tracker, the soft-quote-generation system, and the customer ERP for the sales-order-posting.
Workflow Automator's unattended-RPA workers handle the per-CR execution across the multiple-systems. The workers run on a continuous cadence with the per-CR transaction-level processing and the appropriate retry-and-recovery handling.
DocuMage's AI-based Intelligent OCR handles the CR-classification-and-data-extraction with the per-CR confidence-scoring. The OCR uses the per-request-type-specific model with the computer-vision integration for the specific request-types that require visual-element-recognition.
Workflow Planner's workflow-based human-input handling supports the inside-sales-agent review-and-approval workflow for the soft-quote and the business-team final-approval workflow. The human-input handling integrates with the surrounding automated workflow with the appropriate per-stage state-preservation.
Multi-Agent Orchestrator coordinates the cross-system workflow with the per-CR lifecycle tracking from the intake through the ERP-posting. The orchestrator handles the parallel-data-aggregation where the per-application queries can run in parallel.
The audit trail captures every CR-lifecycle event with the full context preserved for the operational-and-financial audit requirements.
The numbers behind the story
Financial benefits include approximately 45% reduction in per-CR processing-cost, payback period of 3 months, and revenue-leakage cases reduced by 50%.
Operational benefits include more than 1,500 hours saved annually for each inside-sales resource, 67% improvement in AHT (Average Handling Time) for each CR, and 98% on-time closure ratio for all CRs.
Strategic benefits include improved end-customer-experience, highly-scalable solution with additional-processes identified for implementation, and multiple process-improvement-and-re-engineering ideas identified as part of implementation to improve the downstream-processes.
Inside-sales-team workforce capacity has been redirected from the per-CR orchestration work to the higher-value customer-engagement-and-relationship-management work that the previous orchestration workload had been crowding out.
An unexpected outcome: the structured CR-data has surfaced customer-engagement-pattern insights that were invisible in the manually-orchestrated workflow. The provider's strategic-account-management team is now using these patterns for the customer-engagement-strategy work that the previous workflow had structurally prevented.
“Our inside-sales CR-management workflow was absorbing more than fifteen hundred hours of work per resource annually with forty per cent of CRs missed on time and twenty-five per cent of new requests lost. MindMap delivered sixty-seven per cent AHT improvement, ninety-eight per cent on-time closure ratio, and fifty per cent reduction in revenue-leakage cases — with a three-month payback period.”— Vice President, Inside Sales Operations· Global Communications Services Provider
Why MindMap was chosen
The provider had previously evaluated two specialist sales-process-automation vendors. Both had basic RPA capabilities but limited multi-system orchestration capability across the 7-plus client internal-applications, which was the structural requirement that had defeated the previous attempts at the workflow automation.
MindMap's accelerator-composition approach — bringing Workflow Automator, DocuMage's Intelligent OCR with computer-vision, Workflow Planner and Multi-Agent Orchestrator together around the existing client internal-application estate — was the structural differentiator. The composition addressed each structural complexity with the appropriate solution-pattern.
Our embedded telecom-sales-operations expertise on the delivery team (two former global-network-services sales-operations directors and a former CR-management specialist) was the third factor. The leadership valued the team's understanding of the complex-network-services CR-management reality and the cross-system orchestration patterns.
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