RFQ Management Platform Design and Deployment for a Regional Energy Services Company

When quoting happens across email threads, shared drives, and spreadsheets, no one person has the full picture. A regional energy services company was running a fragmented quoting process across multiple business divisions with no shared system of record, no standardized workflow, and no visibility into where any request stood at any given moment. The consequence was not just inefficiency. It was a structural limitation on how much work the organization could bid and win. The problem was not that teams were working too slowly. It was that they were working without infrastructure. They called BabyBots.

Strategic Impact

Our Approach

Discovery and Requirements Definition

Requirements were captured at the process level, not the screen level. Multi-division stakeholder workshops mapped current RFQ workflows, pain points, and regional variations before any system design decisions were made.

Data Model and Security Design

The data model was built to support multi-division access without data bleed between business units. Dataverse was configured with entity schemas, relationship definitions, and role-based security aligned to the client's actual organizational structure.

Model-Driven Application Build

The application was designed to enforce process discipline, not just record information. Intake forms, department-specific views, lifecycle stage gating, and status-driven interfaces ensured the system governed how work moved, not just where it was stored.

Automation, Workflow, and ERP Integration

Quoting and pricing data surfaced inside the workflow rather than requiring system switches. Power Automate flows handled routing, notifications, Service Line Transfers, and audit logging, while ERP integration made product and pricing data accessible without leaving the application.

UAT, Deployment, and Reporting

Leadership gained real-time visibility into the full RFQ pipeline from day one. UAT with departmental leads resolved all outstanding issues before production deployment, and a Power BI reporting layer delivered quote volume, status distribution, and divisional activity dashboards at go-live.

BabyBots Impact Assessment

The Impact

The organization replaced a fragmented, email-and-spreadsheet quoting process with a single governed platform giving every stakeholder, from estimators to executive leadership, real-time visibility into the full RFQ lifecycle. Divisions that had operated in silos now work from a shared system with defined handoffs, automated routing, and a complete audit trail behind every quote.

The engagement opened with structured multi-division discovery workshops covering current-state workflow mapping, pain point documentation, and requirements sign-off — ensuring every build decision was validated by the stakeholders who would use the system daily.

Centralized model-driven RFQ Management Application (Phase 1.0)
Governed Dataverse data model with full entity schema and role-based security
Unified RFQ intake interface with department-aware logic and lifecycle stage gating
Power Automate flows for routing, notifications, Service Line Transfers, and document management
ERP reference data integration with fit matrix, field mapping, and integration runbook
Standardized proposal generation capability using governed templates
Power BI dashboard suite covering pipeline, turnaround, win/loss, and workload metrics
Solution architecture, data model, and configuration documentation

Project Journey

Project Timeline

Phase 1

RFQ Management Platform — Discovery & Requirements Definition

Conducted stakeholder workshops across all participating business divisions to map current RFQ workflows, pain points, and regional variations. Produced requirements specification, solution architecture diagram, and formal sign-off before build activities commenced.

Phase 2

RFQ Management Platform — Data Model Configuration & Security Setup

Configured the Dataverse environment including all entity schemas, relationship definitions, and role-based security model. Established business rules, validation logic, and standardized field naming conventions across all RFQ entities.

Phase 3

RFQ Management Platform — Model-Driven App Development

Built the core RFQ model-driven application including intake forms, lifecycle stage gating, department-specific views, status logic, and role-based access controls. Iterative stakeholder reviews guided layout and usability refinement throughout the build.

Phase 4

RFQ Management Platform — Automation, Workflow & ERP Integration

Developed Power Automate flows for RFQ routing, notifications, Service Line Transfer logic, and document management. Executed ERP reference data integration, BAPI fit validation, field mapping, and gap analysis with integration runbook delivery.

Phase 5

RFQ Management Platform — UAT, Deployment & Reporting

Conducted user acceptance testing with departmental leads, resolved outstanding issues, deployed the application to production, published Power BI dashboards, and completed go-live sign-off and post-implementation review.

Energy Services / Field Services

A quoting process built on spreadsheets is not a process. It is a workaround.

Leadership gained real-time visibility into the full RFQ pipeline from day one. UAT with departmental leads resolved all outstanding issues before production deployment, and a Power BI reporting layer delivered quote volume, status distribution, and divisional activity dashboards at go-live.