CHALLENGE:
Technical debt resulted in customer dissatisfaction and revenue delays
The company faced persistent challenges with product registration and order fulfillment. The root cause was a heavily customized quoting product that had accumulated significant technical debt. The sales team had started relying on partial and non-optimized technology deployments, which made their systems more complex and less accurate. This information gap also affected finance, as they relied on data from sales and sales operations to make business decisions.
These internal quick fixes had started to disrupt integrations, causing duplicate data entry and re-entry across platforms. As a result, the team generated inaccurate data logs and incurred higher storage costs. Even worse, because the duplicate data made it impossible to capture revenue at item level, they saw a chain reaction of billing errors, customer dissatisfaction, and financial losses. Gaps in product identification led to orders being assigned to generic asset records, making it difficult to trace issues back to specific product lines.
These internal issues soon surfaced on the customer-facing side. Because of bad integrations, their CRM and ERP systems could not communicate with each other. Teams instead had to manually intervene to complete a purchase order, which required cross-referencing from the CRM system and relaying it back to the sales team. Despite having the technology, they risked errors and faced revenue delays.
The company needed a permanent solution to reduce manual workloads, improve system integration, and help rebuild strong, reliable customer relationships. It was time to move away from reactive fixes and into a more strategic, scalable approach.
SOLUTION:
Establishing a reliable system with end-to-end capabilities
To address operational inefficiencies and restore customer confidence, we implemented solutions focused on system integration, process modernization, and data accuracy.
We automated the extraction, classification, and processing of purchase orders from documents by implementing intelligent document processing (IDP), an AI-powered technology. Previously, after receiving the purchase order by email, the team had to manually create the order in Salesforce and then again in NetSuite. Now, it takes only two clicks to process purchase orders. This foundational fix enabled more accurate revenue tracking and simplified downstream processes like billing.
Recognizing the need for better coordination, we established a robust Sales-to-Finance handoff process. Now, orders are processed consistently and accurately regardless of how they entered the system, improving financial reporting and customer billing.
For their quote-to-cash process, they relied on a legacy tool heavily dependent on custom code, with little flexibility. They had to use Apex code to add new products, manage pricing, approvals, and generate documents. To address this, we implemented Salesforce Revenue Cloud (RCA), which replaced complex Apex code and allowed admins to configure products and pricing without developer support. We also streamlined their Salesforce setup by linking accounts, opportunities, quotes, and orders for a smoother end-to-end sales process. Additionally, we cleaned up their product catalog across NetSuite, Salesforce, and their internal Cloud portal, ensuring consistent data across systems. Through RCA, we enabled an out-of-the-box renewal and amendment functionality, allowing the company to track service contracts and automate renewals with minimal effort.
RESULTS:
Automation saves 3-4 hours per day on purchase orders
Following the transformation, the medical device company’s service and support teams experienced significant improvements in efficiency, accuracy, and customer responsiveness. By implementing IDP and automation, they eliminated repetitive manual tasks, saving an average of 10 minutes per purchase order. With each user handling up to 20 cases per day, this translates into 3-4 hours saved per user daily, drastically reducing overtime and freeing up budget previously allocated to manual data entry.
The automation also enabled automatic account-level discounts in CPQ, applying contracted pricing and customer-specific product discounts without manual intervention. This not only improved pricing accuracy but also accelerated quote-to-order cycles. They also laid the groundwork for next-generation AI enablement by improving data quality and system integration. With better knowledge capture and cleaner data flows, support teams could respond faster and more accurately, enhancing the overall customer experience.
Additionally, the improved Sales-to-Finance handoff and streamlined product catalog made managing orders from multiple channels easier, reducing friction between departments and ensuring consistent, reliable fulfillment.
Together, these changes moved the company from reactive operations to a proactive, data-driven model—automating processes, saving time, and reducing costs.
