Given the provided process variants and their frequencies and performance data, identifying root causes for performance issues requires a detailed analysis of where bottlenecks, inefficiencies, or high variations in performance exist. Performance, in this context, may refer to how fast or efficiently a process is completed from start to end. Here are some specific considerations based on the provided data:

1. **Complexity of Rejection and Resubmission Cycles**:
   - Processes involving rejection by ADMINISTRATION, PRE_APPROVER, SUPERVISOR, or BUDGET OWNER, followed by resubmission by the EMPLOYEE, are significantly less efficient. These steps add additional complexity, time, and likely rework to the process, which could lead to performance issues. Variants where rejections and resubmissions occur multiple times demonstrate higher performance times and should be analyzed for root causes of initial rejections to minimize these cycles.

2. **Exception Handling and Variability**:
   - Variants with high variability, specifically those with multiple approval/rejection cycles or those involving more roles (e.g., BUDGET OWNER, PRE_APPROVER), tend to have higher performance values, suggesting inefficiency. These paths may indicate that the process is not standardized or is too flexible, causing delays due to the unpredictability in handling.

3. **Role of Pre-Approval and Budget Owner Approvals**:
   - Processes that require additional approvals from BUDGET OWNER or PRE_APPROVER show varied performance impact. In some cases, these additional approvals lead to higher performance, likely due to added scrutiny and decision-making time. Analyzing the decision criteria or efficiency of these roles could provide insights into how to streamline approvals without compromising control.

4. **Initial Submission Quality**:
   - The frequency of rejections by different roles suggests a potential issue with the quality or completeness of initial declarations submitted by EMPLOYEES. Improving initial submission criteria, providing better guidelines, or automated pre-validation could reduce the number of rejections and rework, improving overall process performance.

5. **Impact of SUPERVISOR Final Approval**:
   - Variants where the SUPERVISORs FINAL_APPROVAL is a significant step hint at possible bottlenecks in the approval chain. If the SUPERVISOR is a common bottleneck across many process variants, it suggests a need for capacity planning, delegation of authority, or process optimization to reduce dependency on this step.

6. **Performance Outliers and Process Variability**:
   - Some variants, especially those with exceptionally high or low performance numbers, should be examined closely. High performance could be due to complex decision pathways, while low performance could indicate streamlined, efficient processes. Understanding why certain paths perform better can provide insights into best practices within the process.

7. **Efficiency of Payment Handling Stage**:
   - While not explicitly highlighted as an issue in the data provided, the final stage of handling payments is common to all process variants. Analisys of this stage for delays or inefficiencies could yield improvements that benefit all process variants.

In conclusion, focusing on reducing the need for rejections and resubmissions, streamlining approval processes, enhancing the quality of initial submissions, and managing the variability in process paths will address the root causes of performance issues in the process. Additionally, applying Lean principles such as eliminating waste (non-value-added activities) and Six Sigma methodologies for reducing variation can help improve overall process performance.