​​How iceDQ Fixed Faulty Discounting with Data Reconciliation

– Case Study

Summary

Company: A $2 billion global leader in academic publishing, research, and education services.

Challenge: The organization was losing revenue through its VIAX B2B ecommerce platform by applying for expired or incorrect discounts on customer orders. The root cause was discount data falling out of sync between VIAX and the SAP ECC system of record.

Solution: iceDQ enabled automated data reconciliation between VIAX and SAP ECC, providing immediate alerts when discrepancies occur so IT and business teams can quickly correct mismatches.

Results: Reduced discrepancy detection time from days or weeks to minutes, eliminated unknown revenue leakage, and provided full visibility into discount accuracy.

Data Infrastructure and Discounting Process

System Architecture
The organization operates two core systems for B2B commerce:

  • SAP ECC: The central system of record that manages operations across publishing, marketing, and finance. This is the authoritative source for all discount rules and pricing data.
  • VIAX: The primary B2B ecommerce platform that processes customer orders and applies discounts based on eligibility criteria.

The Discount Process

Figure 1: VIAX applies discounts using its local discount table

When customers place orders through VIAX, the system checks its local discount table to determine eligibility based on three criteria:

  • Transaction Value or Quantity: Volume-based discounts for bulk purchases
  • Customer Category: Discounts based on referrals, society memberships, promotional offers, or geographic location
  • Order Period: Time-limited discounts available only during designated promotional windows

The Challenge: Discount Data Sync Failures

The VIAX discount table is regularly updated with data from SAP ECC. However, the client discovered that for various reasons, the discount data in VIAX frequently fell out of sync with the SAP system of record.

Figure 2: Discount data mismatches between VIAX and SAP ECC led to incorrect pricing

This synchronization gap created several critical business problems:

  • Revenue Leakage: Customers received discounts they were no longer eligible for, resulting in undercharging
  • Customer Dissatisfaction: Eligible customers were overcharged when valid discounts were not applied
  • Zero Visibility: Neither IT nor business teams knew how long mismatches had existed or their scope
  • Unknown Financial Impact: The dollar value of transactions affected by incorrect discounts was completely unknown

The Solution: iceDQ Data Reconciliation

iceDQ implemented an automated data reconciliation solution by connecting directly to both the VIAX ecommerce platform and SAP ECC. The solution continuously compares discount records between the two systems and immediately alerts IT and business teams when discrepancies are detected.

Figure 3: iceDQ reconciles discount data and notifies teams of breaks

Key capabilities of the iceDQ solution include:

  • Real-time comparison of discount tables between VIAX and SAP ECC
  • Immediate alerts when data discrepancies are detected
  • Detailed reporting on affected orders and financial impact
  • Rapid remediation through timely notification to appropriate teams

Results

Prior to implementing iceDQ, the organization had no visibility into discount accuracy. Discrepancies could persist for hours, days, or even weeks before being discovered, leading to significant but unmeasurable financial losses.
The table below summarizes the transformation:

Metric Before iceDQ After iceDQ
Undercharging Customers Occurring (unknown frequency) Eliminated
Overcharging Customers Occurring (unknown frequency) Eliminated
Impacted Order Value Unknown Zero or known and limited
Financial Impact Unknown dollar value Zero or known and limited
Time to Detect Discrepancy Days or weeks Minutes

Conclusion

By implementing iceDQ, the client closed the loop on their discounting process. The solution detects and enables rapid resolution of discrepancies in the discount table, eliminating revenue leakage and ensuring customers are charged accurately. What was once an invisible problem with unknown financial impact is now a controlled, monitored process with full visibility.

About the author

Sandesh Gawande

Sandesh Gawande is the Founder and CEO of iceDQ, a unified Data Reliability Platform for automated data testing, monitoring, and observability. With over 25 years of experience in data engineering and architecture, Sandesh has led large-scale data initiatives for Fortune 500 companies across banking, insurance, and healthcare, including Deutsche Bank, JPMorgan Chase, and MetLife.

Know More

Sandesh Gawande - CTO iceDQ

Sandesh Gawande

CEO and Founder at iceDQ.
First to introduce automated data testing. Advocate for data reliability engineering.

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