Excel - OpenText Decision Service Integration and Automation

Common Integration Use Cases Between Microsoft Excel and OpenText Decision Service

1. Excel-Based Rule Authoring and Bulk Rule Upload

Business analysts maintain decision tables, eligibility matrices, pricing thresholds, or approval rules in Microsoft Excel, then upload the structured file into OpenText Decision Service for execution. This approach lets non-technical teams manage rule content in a familiar spreadsheet format while keeping the decision logic centralized and governed in OpenText Decision Service.

• Data flow: Microsoft Excel to OpenText Decision Service
• Business value: Faster rule updates, reduced dependency on developers, and fewer errors from manual re-entry

2. Policy and Eligibility Screening for High-Volume Transactions

Operational teams use Excel to prepare reference data such as customer segments, product attributes, or exception lists, which are then loaded into OpenText Decision Service to evaluate transactions against business rules. This is useful for credit checks, discount eligibility, order validation, or claims triage where decisions must be consistent and auditable.

• Data flow: Microsoft Excel to OpenText Decision Service
• Business value: Consistent decisioning across channels and faster processing of large transaction volumes

3. Exception Review and Decision Override Management

When OpenText Decision Service flags cases that require manual review, analysts export the exception set to Excel for investigation, enrichment, and commentary. After review, the updated spreadsheet is imported back into the decision service or downstream workflow to apply approved overrides, supporting controlled exception handling.

• Data flow: OpenText Decision Service to Microsoft Excel and back to OpenText Decision Service
• Business value: Better exception governance, improved analyst productivity, and traceable override decisions

4. Rule Testing and Scenario Simulation

Teams use Excel to build test scenarios with input variables such as customer profile, order amount, region, or risk score. These scenarios are passed to OpenText Decision Service to validate how rule changes affect outcomes before deployment. Results can be exported back to Excel for comparison, analysis, and sign-off by business stakeholders.

• Data flow: Microsoft Excel to OpenText Decision Service to Microsoft Excel
• Business value: Safer rule changes, improved testing coverage, and faster business approval cycles

5. Periodic Rule Performance Reporting and Analysis

OpenText Decision Service generates decision outcomes, rule hit rates, approval rates, and exception counts that are exported to Excel for reporting and trend analysis. Finance, operations, and compliance teams can use Excel pivot tables and charts to identify rule effectiveness, bottlenecks, and policy drift over time.

• Data flow: OpenText Decision Service to Microsoft Excel
• Business value: Better visibility into decision performance and easier reporting for business and audit teams

6. Master Data Validation Before Decision Execution

Master data such as product codes, customer tiers, supplier categories, or regional mappings is maintained in Excel and validated before being used by OpenText Decision Service. This ensures the decision engine evaluates transactions against clean and approved reference data, reducing false declines, incorrect routing, or policy misapplication.

• Data flow: Microsoft Excel to OpenText Decision Service
• Business value: Higher data quality, fewer decision errors, and stronger operational control

7. Cross-Functional Policy Collaboration and Approval Workflow

Policy owners draft rule changes in Excel, where legal, compliance, operations, and finance teams can review and annotate the proposed logic. Once approved, the final spreadsheet is published into OpenText Decision Service, creating a controlled handoff from business review to automated execution.

• Data flow: Microsoft Excel to OpenText Decision Service
• Business value: Better cross-team collaboration, clearer approvals, and reduced policy implementation delays