Oracle ERP Testing Tool > Test Library > SCM > Supply Planning

Syntra Standard Oracle Test Library

Oracle Fusion Demand Forecast Test Cases

Validate that demand forecasts used as input to supply planning can be created, loaded from a statistical method or historical data, manually adjusted and consumed by sales orders in Oracle Fusion SCM Supply Planning, including forecast set creation and organization/item assignment, without assuming a single universal forecast method applies to every item.

Test ID	ORCL.SCM.PLAN.FORECAST
Application	Oracle Fusion Cloud
Product	SCM
Module	Supply Planning
Process	Demand Forecast
Business Flow	Plan-to-Produce
Scenario Type	Positive / Functional
Test Usage	Functional Testing / Regression Testing / UAT
Priority	High
Automation	SyntraFlow Ready
Library	Syntra Standard

Note on test design: SyntraFlow executes the detailed Oracle Fusion UI interactions automatically while presenting the scenario as business-readable test steps for documentation, review and reporting. This scenario is presented as 6 business-readable test steps; SyntraFlow's automation executes approximately 21 underlying Oracle Fusion UI actions to complete it.

Test Objective

The objective of this test is to validate that demand forecasts used as input to supply planning can be created, loaded, manually adjusted and consumed by sales orders in Oracle Fusion SCM Supply Planning, including forecast set creation and organization/item assignment, without assuming a single universal forecast method applies to every item.

The scenario should confirm that:

the demand forecast is correctly created or loaded using the selected method — manual entry, a statistical method or historical data — as configured for the item
the forecast set is correctly scoped to the specified organization and item
forecast accuracy can be reviewed and the forecast is correctly published as an input to the supply plan
consumption of the forecast by incoming sales orders correctly reduces the open forecast quantity
the published forecast is available to downstream Supply Planning processes such as Run Supply Plan and Supply Demand Balance
Oracle correctly enforces validation when invalid, negative or unauthorized forecast data or changes are introduced (DATA_ERROR, CONFIGURATION_ERROR, SECURITY_ERROR, EXPECTED_VALIDATION)

This scenario covers creation, loading, adjustment and consumption of demand forecasts within the forecast sets, organizations and items configured in the target Oracle Fusion SCM Supply Planning TEST/UAT environment. It does not cover generation of the supply plan itself or review of the resulting supply/demand balance, which are covered by the separate Run Supply Plan and Supply Demand Balance scenarios in the same Supply Planning cluster.

When to Use This Test

Functional testing of demand forecast creation and loading for a new Oracle Fusion SCM Supply Planning implementation
Regression testing of forecast adjustment and consumption behavior after an Oracle quarterly update
UAT sign-off for demand planners who maintain and adjust forecasts used as supply plan input
Baseline case referenced by the Run Supply Plan and Supply Demand Balance scenarios within the same Supply Planning cluster
Diagnosing DATA_ERROR, CONFIGURATION_ERROR and SECURITY_ERROR conditions surfaced during forecast loading or adjustment before escalating as a possible APPLICATION_ERROR

Where This Test Fits in the Supply Planning Process

Collect Planning Data

→

Create/Load Demand Forecast

→

Adjust Forecast

→

Publish to Supply Plan

→

Run Supply Plan

→

Review Supply/Demand Balance

Demand Forecast sits between Collect Planning Data and Run Supply Plan in the Plan-to-Produce business flow. Once a forecast is created, loaded and published, it becomes a demand input consumed by the supply plan and is progressively reduced as sales orders are entered — covered by the Run Supply Plan and Supply Demand Balance scenarios in this same cluster. Exact forecast methods, fields available and consumption behavior depend on the forecast set, item and customer-specific Oracle Fusion configuration.

← Previous Stage

Collect Planning Data

Next Stage →

Run Supply Plan

Preconditions

The test user has appropriate Demand Planner or Planning Manager access to create, load and adjust demand forecasts.
Required forecast sets are configured and active in the target Oracle Fusion environment.
Items and organizations referenced in test data are configured and enabled for demand planning.
The forecast method(s) — manual, statistical or history-based — to be tested are configured and available for the item(s) under test.
Sales orders used to validate forecast consumption reference items and organizations included in the forecast set.

Exact forecast methods, field availability and consumption behavior may vary by Oracle Fusion implementation, forecast set configuration and customer-specific setup. No single forecast method should be assumed to apply universally to every item.

Sample Test Data

Forecast Set	${FORECAST_SET}
Item	${ITEM}
Organization	${ORGANIZATION}
Forecast Quantity	${FORECAST_QUANTITY}
Forecast Method	${FORECAST_METHOD}
Sales Order	${SALES_ORDER}
Forecast Period	${FORECAST_PERIOD}
User Role	${USER_ROLE}

Sample values are illustrative placeholder tokens. Replace with valid data from the target Oracle Fusion SCM TEST/UAT environment. Not every field applies to every forecast set or item — for example, forecast method may default from the forecast set rather than requiring re-entry.

Test Steps

6 business-readable steps. SyntraFlow's automation executes ~21 underlying UI actions to complete these steps — see How SyntraFlow Automates This Test.

#	User Action	Expected Result
1	Sign In and Navigate to Supply Planning Sign in to Oracle Fusion using an authorised Supply Planning test user and navigate to the Demand Forecast work area.	The Demand Forecast work area opens successfully.
2	Navigate to the Forecast Set Open or select the forecast set ${FORECAST_SET} that will contain the demand forecast. ${FORECAST_SET}	The selected forecast set opens and is available for forecast creation or loading.
3	Create or Load the Forecast Using the Selected Method Create the demand forecast manually, or load it using the selected method — for example a statistical method or historical sales/shipment data — for item ${ITEM}. ${FORECAST_METHOD} / ${FORECAST_QUANTITY} / ${FORECAST_PERIOD} Not every item uses the same forecast method — the method used depends on how the item and forecast set are configured.	The forecast is created or loaded successfully using the selected method for the specified period.
4	Assign Forecast to Organization and Item Assign the demand forecast to organization ${ORGANIZATION} and item ${ITEM} within the forecast set. ${ORGANIZATION} / ${ITEM}	The forecast is correctly scoped to the specified organization and item.
5	Review Accuracy and Publish Forecast to Supply Plan Review forecast accuracy against prior actuals where available, then publish the forecast so it can be consumed as input to the supply plan. Publishing makes the forecast available to supply planning; it does not by itself run the supply plan.	The forecast is published and available as an input to the supply plan.
6	Verify Consumption Behavior as Sales Orders Are EnteredBusiness assertion Enter or reference sales order ${SALES_ORDER} for item ${ITEM} and verify that the open demand forecast quantity is reduced through forecast consumption. ${SALES_ORDER} This is the primary business assertion for the scenario — correct consumption behavior, not merely a successful save, is the expected pass condition.	The open forecast quantity for item ${ITEM} is correctly reduced by the consuming sales order, as configured.

Expected Results

The demand forecast is correctly created and loaded via the selected method — manual entry, statistical method or history-based loading.
The forecast set is correctly scoped to the specified organization and item.
Forecast accuracy is reviewed and the forecast is correctly published as supply plan input.
Consumption by sales orders correctly reduces the open forecast quantity, as configured.
Invalid or negative forecast data is correctly rejected by Oracle Fusion validation.
Unauthorized forecast changes are correctly blocked.

Key Validation Checkpoints

Forecast correctly created and loaded via the selected method.
Forecast set correctly scoped to organization and item.
Forecast correctly published as supply plan input.
Consumption by sales orders correctly reduces the open forecast quantity.
Invalid or negative forecast data correctly rejected.
Unauthorized forecast change correctly blocked.

Core Business Scenario

Demand Forecast

Business Steps

Test Variations

AI-Generated

Test Data

DataVault-Driven

Execution

On-Demand / Scheduled / Batch

Automation

SyntraFlow Ready

Jarvis AI

Go Beyond the Standard Test with Jarvis AI

The Syntra Standard Test Library defines the core Demand Forecast business scenario. Jarvis AI can extend this scenario by generating additional forecast method, adjustment, consumption and security variations using customer-specific test data and configuration available through Syntra DataVault.

Teams do not need to manually build a separate test for every forecast method, adjustment or consumption combination. Jarvis uses the standard scenario as the foundation and generates relevant Positive, Negative, Boundary and Security variations for the customer's environment — including negative forecast quantities, forecast set conflicts, forecast load failures and unauthorized forecast changes, since correctly enforced validation and access control is an important part of what this scenario proves.

From Standard Test to Executed Regression Pack

Syntra Standard Test

Reusable Demand Forecast business process and automation logic.

Customer DataVault

Provides approved customer-specific test data and configuration required for scenario generation — Forecast Sets, Items, Organizations and Forecast Methods.

Jarvis AI

Analyses the standard scenario together with available test data and generates relevant forecast method, adjustment, consumption and security variations.

Positive + Negative Test Variations

Valid forecast creation and loading scenarios and edge cases such as negative quantities, invalid forecast data or forecast set conflicts.

Regression Pack

Selected variations can be grouped into an executable suite.

On-Demand / Scheduled / Batch Execution

Execute immediately or schedule the regression pack for unattended batch execution.

Results + Evidence + Exceptions

Capture execution results, business assertions, screenshots/evidence and exceptions.

Rather than maintaining a separate test page for every possible forecast method, adjustment or consumption combination, SyntraFlow maintains one core Demand Forecast scenario and allows Jarvis AI to generate forecast method, adjustment, consumption and security-specific variations using the customer's available test data.

AI-Generated Test Variations

The same Demand Forecast business scenario can produce many test variations without creating separate public library pages. Below is a real slice of SyntraFlow's Build Scripts library, filtered to SCM Supply Planning.

Positive Scenarios

Create and load a demand forecast using a statistical or history-based method
Create a forecast set and assign the forecast to an organization and item
Review forecast accuracy against prior actuals
Publish the forecast to the supply plan as demand input
Manually adjust a demand forecast quantity
Consume the demand forecast through an incoming sales order

Negative Scenarios

Attempt to load a demand forecast with invalid forecast data
Attempt to create a forecast set that conflicts with an existing forecast set
Attempt to enter a negative forecast quantity
Attempt to load a forecast that fails during load processing
Attempt an unauthorized demand forecast change

These are representative examples only. Negative-scenario behavior and available field combinations can depend on the customer's Oracle Fusion configuration, forecast sets, items and security — not every Oracle configuration behaves identically.

Generated Using Your DataVault Test Data

Generic test data rarely represents every forecast set, item, organization and forecast method combination in a real Oracle Fusion SCM Supply Planning environment. Where connected, Jarvis can use approved test data available through Syntra DataVault to construct Demand Forecast scenarios relevant to the customer's actual implementation.

Standard Library Definition

Forecast Set      ${FORECAST_SET}
Item              ${ITEM}
Organization      ${ORGANIZATION}
Forecast Quantity ${FORECAST_QUANTITY}
Forecast Method   ${FORECAST_METHOD}
Sales Order       ${SALES_ORDER}
Forecast Period   ${FORECAST_PERIOD}
User Role         ${USER_ROLE}

DataVault

Forecast Sets
  Active forecast sets and their configured methods
Items
  Items enabled for demand planning by organization
Organizations
  Organizations enabled for demand forecasting
Sales Orders
  Representative sales orders used to test forecast consumption
User Roles
  Demand Planner, Planning Manager and restricted personas

Jarvis AI Generates

Scenario 01 — Create Demand Forecast, Forecast Set A
Scenario 02 — Load Forecast from Statistical Method
Scenario 03 — Manual Forecast Adjustment
Scenario 04 — Forecast Consumption by Sales Order
Scenario 05 — Negative Forecast Quantity
Scenario 06 — Unauthorized User Attempts Forecast Change
...

Demand Forecast test data can include forecast quantities, item and sales order information tied to customer demand and planning configuration. The public Syntra Standard Test Library uses illustrative placeholder data only. Where DataVault is connected, customer-specific forecast and demand data used in testing remain masked and synthetic within the customer's controlled SyntraFlow environment, protected according to DataVault's data masking policies. See /datavault/data-masking/ for details.

Example Test Variations

Representative examples of 15 individual Demand Forecast test scenarios spanning forecast creation, statistical and history-based loading, consumption and negative/security forecast testing that Jarvis can generate from this business scenario. These are illustrative, not separate indexable pages — the canonical page for all of them remains this one.

ID	Variation	Type	Key Difference	Execution
PLAN-FC-001	Create Demand Forecast	Positive	Demand forecast is created within forecast set ${FORECAST_SET} for item ${ITEM} using forecast method ${FORECAST_METHOD}.	SyntraFlow Ready
PLAN-FC-002	Load Forecast from Statistical Method	Positive	Forecast is loaded for item ${ITEM} using statistical forecast method ${FORECAST_METHOD} for period ${FORECAST_PERIOD}.	SyntraFlow Ready
PLAN-FC-003	Load Forecast from History	Positive	Forecast is loaded for item ${ITEM} from historical sales or shipment data for period ${FORECAST_PERIOD}.	SyntraFlow Ready
PLAN-FC-004	Create Forecast Set	Positive	A new forecast set ${FORECAST_SET} is created to hold demand forecasts for organization ${ORGANIZATION}.	SyntraFlow Ready
PLAN-FC-005	Assign Forecast to Organization	Positive	The demand forecast in ${FORECAST_SET} is assigned to organization ${ORGANIZATION}.	SyntraFlow Ready
PLAN-FC-006	Assign Forecast to Item	Positive	The demand forecast in ${FORECAST_SET} is assigned to item ${ITEM}.	SyntraFlow Ready
PLAN-FC-007	Review Forecast Accuracy	Positive	Forecast accuracy for item ${ITEM} is reviewed against prior actual demand for period ${FORECAST_PERIOD}.	SyntraFlow Ready
PLAN-FC-008	Publish Forecast to Supply Plan	Positive	The demand forecast for item ${ITEM} is published from ${FORECAST_SET} as input to the supply plan.	SyntraFlow Ready
PLAN-FC-009	Manual Forecast Adjustment	Positive	Forecast quantity ${FORECAST_QUANTITY} for item ${ITEM} is manually adjusted by a user with role ${USER_ROLE}.	SyntraFlow Ready
PLAN-FC-010	Forecast Consumption by Sales Order	Positive	Sales order ${SALES_ORDER} for item ${ITEM} consumes the open demand forecast quantity.	SyntraFlow Ready
PLAN-FC-011	Invalid Forecast Data	Negative	Forecast load is attempted using invalid forecast data for item ${ITEM} in forecast set ${FORECAST_SET}.	SyntraFlow Ready
PLAN-FC-012	Forecast Set Conflict	Negative	Forecast creation is attempted in a way that conflicts with an existing forecast set ${FORECAST_SET}.	SyntraFlow Ready
PLAN-FC-013	Negative Forecast Quantity	Negative/Boundary	Forecast quantity ${FORECAST_QUANTITY} entered for item ${ITEM} is negative.	SyntraFlow Ready
PLAN-FC-014	Forecast Load Failure	Negative	Forecast load for forecast set ${FORECAST_SET} fails during load processing for item ${ITEM}.	SyntraFlow Ready
PLAN-FC-015	Unauthorized Forecast Change	Negative/Security	A user with role ${USER_ROLE} without required access attempts to change the demand forecast for item ${ITEM}.	SyntraFlow Ready

Automatically Expand Positive and Negative Demand Forecast Coverage

Positive Testing

Jarvis generates scenarios using forecast set, item, organization, method and quantity combinations expected to successfully create, load, adjust or consume a demand forecast in Oracle Fusion.

Valid Forecast Set + Valid Item + Valid Forecast Method → Forecast Created

Negative Testing

Jarvis can also generate scenarios designed to exercise Oracle's validations around forecast data, forecast set configuration, quantity boundaries and security.

Invalid Forecast Data → Expected Data Validation
Forecast Set Conflict → Expected Configuration Validation
Negative Forecast Quantity → Expected Quantity Validation
Forecast Load Failure → Expected Load Error Handling
Unauthorized User → Expected Access Restriction

A negative supply planning scenario passes when Oracle correctly enforces the expected data, configuration or security rule

Scenario	Oracle Outcome	Test Result
Valid planning data	Plan generated	PASS
Missing or stale collected data	Validation or warning occurs	PASS
Invalid plan configuration	Validation occurs	PASS
Unauthorized user	Access prevented	PASS
Unexpected application exception	Unexpected failure	FAIL

Turn AI-Generated Variations into a Regression Pack

Users can select generated Demand Forecast scenarios and group them into reusable execution packs.

SCM Supply Planning Demand Forecast Regression Pack

Create Demand Forecast
Load Forecast from Statistical Method
Load Forecast from History
Create Forecast Set
Manual Forecast Adjustment
Forecast Consumption by Sales Order
Invalid Forecast Data
Negative Forecast Quantity
Forecast Load Failure
Security Restriction — Unauthorized Forecast Change

Add Selected to Regression Pack(coming soon)Run Now(coming soon)Schedule(coming soon)

Run On-Demand or Schedule Automated Batch Execution

SyntraFlow can execute selected Demand Forecast scenarios individually or as a batch. Users can schedule regression packs according to their testing cycle.

Once scheduled, SyntraFlow executes the selected Demand Forecast scenarios unattended and records the outcome of each test and business assertion.

Run immediatelyNightly regressionWeekly regressionBefore releaseAfter configuration changesAfter environment refreshQuarterly Oracle update testingPre-UAT validation

Pack	SCM Supply Planning Demand Forecast Regression Pack
Schedule	Quarterly Update Regression
Tests	15 scenarios
Execution	Batch Mode
Start	10:00 PM
Environment	Oracle Fusion TEST
Status	Scheduled

Illustrative example — not a live schedule.

Review Results Across the Entire Test Pack

Users can drill from the regression pack into a scenario, its business steps, the underlying automation actions, and the evidence captured for each.

Illustrative example data — not actual production metrics.

Total Scenarios

Passed

Failed

Exceptions

Positive Tests

Negative Tests

Business Assertions

Regression Pack → Scenario → Business Step → Automation Action → Evidence

Security & Approval Variations

Access to create, adjust and publish demand forecasts is controlled by Oracle Fusion's security configuration, which varies by customer. Jarvis can generate representative persona-based variations to confirm that demand forecast access behaves as expected for each role — not to assert a single universal Oracle security model.

Persona	Action	Expected	Syntra Result
Demand Planner	Create and Adjust Demand Forecast	Allowed	PASS
Planning Manager	Publish Forecast to Supply Plan	Allowed	PASS
Unauthorized User	Attempts to Change Forecast	Access prevented	PASS

Understand Why a Test Failed

SyntraFlow execution evidence can help distinguish business-data failures, configuration issues, automation problems and potential application defects.

DataConfigurationSecurityAutomationApplicationEnvironmentExpected Validation

Jarvis Failure Intelligence — Coming Soon

From Business Scenario to Execution Evidence

Business teams get readable test documentation; automation teams retain detailed execution traceability.

Standard Business Scenario

AI-Generated Variation

Regression Pack

Business Test Step

Automation Actions

Business Assertion

Screenshot / Evidence

Execution Result

Meet Jarvis — SyntraFlow's AI Testing Engine

Jarvis extends the Syntra Standard Test Library by analysing the Demand Forecast scenario, available DataVault test data and expected business outcomes to generate additional Positive, Negative, Boundary and Security coverage for the customer's environment.

Generate

Positive and negative variations.

Parameterize

Use relevant test data from DataVault.

Assemble

Build reusable regression packs.

Execute

Run scenarios autonomously.

Schedule

Execute unattended test batches.

Validate

Evaluate expected business outcomes.

How SyntraFlow Automates This Test

The Standard Test defines the scenario; DataVault, Jarvis AI and SyntraFlow's execution engine take it from a single reusable business definition to executed, evidenced regression coverage.

Standard Library — Demand Forecast, 6 Business Steps

↓

DataVault — Customer-Specific Test Data

↓

Jarvis AI — Generate Positive + Negative + Boundary + Security Variations

↓

Regression Pack — Select Relevant Coverage

↓

SyntraFlow Execution — Each Variation

↓

Detailed UI Actions

↓

Business Assertions

↓

Evidence

↓

PASS / FAIL

Business Step → Underlying UI Actions

Business Step

Create or Load the Forecast Using the Selected Method

May internally include

Open Forecast Set → Select Load Type → Choose Forecast Method → Enter/Load Forecast Quantities → Validate Period → Save Forecast

Business Step

Verify Consumption Behavior as Sales Orders Are Entered

May internally include

Open Sales Order → Enter Order Line for Item → Trigger Forecast Consumption → Query Open Forecast Quantity → Compare Before/After → Capture Evidence

What SyntraFlow Captures Per Run

Parameterised input valuesReusable navigationAutomation action traceScreenshots / evidence captureExecution timingPass / fail statusBusiness assertionsEnvironment-independent test data

Action Status vs. Business Validation

A successful UI interaction does not automatically prove the forecast was correctly created, adjusted or consumed — this is illustrative of how SyntraFlow separates action success from business validation; it does not reflect a specific live execution. When a step fails, SyntraFlow's evidence trail is designed to help a tester classify the likely cause — for example DATA_ERROR, CONFIGURATION_ERROR, SECURITY_ERROR, EXPECTED_VALIDATION, INTEGRATION_ERROR, AUTOMATION_ERROR, ENVIRONMENT_ERROR or APPLICATION_ERROR — without asserting the cause automatically. For example: Forecast Load Failed — Likely category: DATA_ERROR — Evidence: Forecast quantity ${FORECAST_QUANTITY} is negative for item ${ITEM} — Recommendation: Correct source forecast data before reloading. A failure should never be labeled as an Oracle defect without eliminating data, configuration, security, automation and integration causes first.

Step	Action Status	Business Validation
Assign Forecast to Organization and Item	Pass	—
Review Accuracy and Publish Forecast to Supply Plan	Pass	—
Verify Consumption Behavior as Sales Orders Are Entered	Pass	Pass

Related Supply Planning Tests

Demand Forecast provides the demand input consumed by the supply plan — explore the related Supply Planning scenarios below.

Run Supply Plan Supply Demand Balance Collect Planning Data

Turn This Standard Test into Your Oracle SCM Demand Forecast Regression Suite

Start with the Syntra Standard Demand Forecast test, use DataVault to provide environment-specific test data, let Jarvis generate additional forecast method, adjustment, consumption and security variations, and execute the resulting regression pack automatically with SyntraFlow.

Automate with SyntraFlow Explore SCM Supply Planning Test Library

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Related Oracle Testing Resources

Oracle ERP Testing Tool Test Library SCM Test Library Supply Planning Test Library Syntra DataVault DataVault Data Masking

Frequently Asked Questions

Is the same forecast method used for every item in Oracle Fusion Demand Forecast?

No. The forecast method — manual entry, a statistical method or history-based loading — depends on how the item and forecast set are configured in Oracle Fusion Supply Planning. This scenario is designed to validate forecast creation and loading as configured in the target environment rather than assuming a single universal forecast method applies to every item.

How is manual forecast adjustment tested?

SyntraFlow can validate that a demand planner with the appropriate access can manually adjust a forecast quantity — such as ${FORECAST_QUANTITY} for item ${ITEM} — and that the adjusted value is correctly reflected on the forecast.

How does sales-order consumption of the demand forecast work?

As sales orders are entered against a forecasted item, Oracle Fusion consumption logic reduces the open forecast quantity. SyntraFlow validates this by entering or referencing a sales order such as ${SALES_ORDER} for item ${ITEM} and confirming the open forecast quantity is correctly reduced, as configured for the forecast set.

What do the failure intelligence categories mean when a demand forecast test fails?

SyntraFlow's evidence trail is designed to help classify a failure as DATA_ERROR, CONFIGURATION_ERROR, SECURITY_ERROR, EXPECTED_VALIDATION, INTEGRATION_ERROR, AUTOMATION_ERROR, ENVIRONMENT_ERROR or APPLICATION_ERROR — for example, a negative forecast quantity is typically a DATA_ERROR. A failure should never be labeled as an Oracle defect without first eliminating data, configuration, security, automation and integration causes.

How is security tested for demand forecast changes?

Access to create, adjust and publish demand forecasts is controlled by Oracle Fusion's security configuration, which varies by customer. SyntraFlow can execute representative persona-based variations — such as a Demand Planner, a Planning Manager and an unauthorized user — to confirm that demand forecast access behaves as expected, without asserting a single universal Oracle security model.