In This Article
Start Here: Identify the Symptom
- 1. Structural Issues
- 2. KPI Issues
- 3. Definition and View Issues
- 4. Roll-Up and Calculation Behaviour
- 5. Access and Visibility Issues
- 6. When Results Change Unexpectedly
Overview
This article helps you diagnose and resolve common issues when a Value Driver Tree (VDT) does not behave as expected. Issues typically fall into one of the following categories:
- Structural issues
- KPI and data issues
- Roll-up and calculation behaviour
- Definition and view mismatches
- Access and visibility issues
Analysis-specific issues (Sensitivity, Attribution, Variance) are covered in a separate article.
Start Here: Identify the Symptom
Before troubleshooting, identify what looks wrong:
- No values appear on KPI nodes
- Values exist in KPIs but not in the tree
- Parent or outcome nodes do not calculate
- Values look incorrect or extreme
- Changes to definitions do not appear in the tree
- Results changed unexpectedly
Once you know the symptom, use the sections below.
1. Structural Issues
Structural issues relate to how the Value Driver Tree is built and connected.
Common symptoms
- Parent nodes show no calculated value
- Dashed or broken connections between nodes
- Outcome node remains blank or zero
- Changes in one part of the tree do not affect the outcome
What to check
- Edit Mode: Ensure the tree is in Edit Mode when making changes.
- Node hierarchy: Confirm that all nodes are connected to the intended parent and that the structure reflects the intended logic.
- Calculation expressions: Check that parent nodes have valid formulas and that referenced nodes (A, B, C, etc.) exist and are ordered correctly.
- Node types: Confirm the correct node type is being used (KPI, calculation, constant, reference).
Typical fixes
- Reconnect nodes to the correct parent
- Correct or re-enter calculation expressions
- Replace incorrect node types
2. KPI Issues
KPI issues are the most common cause of missing or unexpected values in a Value Driver Tree.
Common symptoms
- KPI nodes show no values
- KPI nodes show zeros or blanks
- Values appear in the KPI but not in the tree
What to check
- KPI exists and is saved: Confirm the KPI has been created and saved successfully.
- KPI values exist: Open the KPI and check the Values tab to confirm values exist for the relevant period.
- Field alignment: Confirm the selected view in the Value Driver Tree references fields that actually contain values (for example, Actual, Target, Baseline).
- Time period alignment: Ensure the KPI's time configuration aligns with the VDT definition (for example, monthly vs daily).
- Imported data: If values were imported via Excel, confirm the import completed successfully and that there were no validation errors.
Example: Uploaded KPI values not displayed on the tree
- This commonly occurs when:
- Values exist in the KPI but for a different period
- The VDT view references a field with no data
- The KPI period does not match the VDT definition
Typical fix:
- Add values for the correct period or switch to a view that references populated fields.
3. Definition and View Issues
Value Driver Trees are created using a specific VDT Definition, which controls available fields and views.
Common symptoms
- New fields added to a definition do not appear in an existing tree
- Views do not update as expected
- Tree displays outdated field options
Why this happens
- Existing Value Driver Trees do not automatically update when the underlying definition is changed.
What to check
- Which definition the tree uses: Open the Value Driver Tree settings and confirm the referenced definition.
- Definition updates: Confirm what was changed in the definition (new fields, timeframes, views).
Example: Changing the definition of an existing VDT
- If you update a VDT Definition after a tree is created, the tree continues to use the original definition.
Typical fix:
- Use the Change Definition option on the Value Driver Tree to re-select the updated definition, then revalidate the tree.
4. Roll-Up and Calculation Behaviour
Roll-up issues occur when calculations produce unexpected or extreme results.
Common symptoms
- Parent or outcome values look too large or too small
- Small KPI changes cause large swings in the outcome
- One KPI appears to dominate the result
What to check
- Multiplicative logic: Identify calculations that multiply values (for example, rate × time × price). These amplify changes.
- Upstream drivers: KPIs placed high in the tree (such as availability or runtime) can dominate results.
- Double counting: Ensure the same concept is not represented more than once in the tree.
- Reference nodes: Confirm reference nodes point to the intended source.
Typical fixes
- Review and simplify calculation logic
- Reposition KPIs lower in the tree where appropriate
- Remove duplicated drivers
5. Access and Visibility Issues
Sometimes the issue is not the tree or data, but user access.
Common symptoms
- You cannot edit a node
- You cannot see certain KPIs or trees
- Results differ between users
What to check
- Permissions: Confirm your role allows editing or analysis.
- Tree access: Check whether the tree is private or public.
- Position context: Confirm your assigned position aligns with the data being analysed.
Typical fixes
- Request appropriate access
- Switch to a public tree if required
- Validate position assignment
6. When Results Change Unexpectedly
If results change without obvious edits:
What to check
- Recent KPI value changes (use KPI audit logs)
- Recent Idea changes that affect planning inputs
- Edits made by other users with edit permissions
Remember:
- KPI and Idea changes are auditable
- Value Driver Tree structural changes are governed, not logged
Key Point to Remember
Most Value Driver Tree issues are caused by missing KPI values, misaligned fields, or calculation structure — not system errors.
A structured check usually resolves the issue quickly.
What Happens Next
If issues persist:
- Review KPI and Idea audit logs
- Validate the tree structure with another user
- Rebuild a small section of the tree to isolate the issue
The next article covers Troubleshooting Value Hound Analysis, focusing on Sensitivity, Attribution, and Variance-specific behaviours.
Next Steps
To learn about troubleshooting Value Hound analysis, see: