Tenure and Promotion Dossier Assembly and Review Workflow Automation

The tenure and promotion process is a critical administrative bottleneck, consuming weeks of faculty and committee time manually aggregating publications, teaching evaluations, and service records from disparate systems like HRIS, digital repositories, and LMS platforms. A custom automation workflow orchestrates specialized agents to retrieve, validate, and format this data into a standardized dossier. This eliminates repetitive compilation work, ensures policy compliance, and allows committees to focus on substantive review, directly translating to significant labor savings and faster decision cycles.

Implementation leverages an orchestration framework like LangGraph to manage state across retrieval, validation, and routing agents. The workflow integrates with enterprise systems via APIs or RPA, embedding approval gates at the completeness check and final committee stage. A secure portal provides the review interface and immutable audit trail. Key constraints include managing data quality variances, handling missing records via exception routing to administrators, and ensuring strict access controls and versioning for this sensitive, career-defining process.

This workflow automates the manual, error-prone assembly of tenure dossiers by orchestrating specialized agents to aggregate publications from Scopus, teaching evaluations from Canvas, and service records from SAP. It eliminates weeks of administrative labor per candidate, reduces compliance risk from missing documentation, and ensures committee reviews begin with complete, standardized portfolios. The architecture ingests data from disparate APIs and file shares, applies completeness checks, and formats materials into a unified, policy-compliant package.

Implementation requires a LangGraph-based orchestrator managing agentic retrieval from each system of record, with validation logic against institutional tenure policy. Critical controls include human-in-the-loop approval for dossier finalization, exception routing for ambiguous records, and immutable audit logs for each data point. The system integrates with SharePoint or similar for final dossier storage and committee workflow tools, ensuring a defensible, scalable process that preserves academic governance while eliminating manual compilation drudgery.

Phase one establishes the core data aggregation layer, integrating with systems like Banner, Digital Measures, and the institutional repository via APIs and scheduled crawls. Orchestrators, built on LangGraph, trigger the initial dossier assembly, pulling publications, teaching evaluations, and service records into a structured portfolio. This phase delivers immediate value by eliminating manual data hunting, reducing compilation time from weeks to hours, and ensuring a consistent, auditable data foundation for committee review.

Subsequent phases introduce validation agents for completeness checks and CV formatting, followed by secure routing to a committee portal with configurable approval gates. Each phase incorporates mandatory human review checkpoints and immutable audit trails, ensuring the automation supports—rather than replaces—faculty governance. The final architecture reduces dossier preparation labor by over 80%, accelerates review cycles, and provides defensible, policy-aligned documentation for high-stakes personnel decisions.

Automating tenure dossier assembly directly attacks a costly administrative bottleneck, where faculty and staff spend weeks manually aggregating publications, teaching evaluations, and service records from fragmented systems like Digital Measures, Interfolio, Banner, and LMS platforms. The operational upside comes from compressing compilation time by 80%, ensuring policy-compliant formatting, and freeing committee members to focus on substantive review rather than document chasing. A custom workflow orchestrates agents to extract, validate, and structure candidate data, but requires robust exception routing and preliminary completeness checks before any committee touchpoint.

Implementation requires a phased rollout, starting with a pilot department to refine extraction logic and approval gates. Governance controls are paramount: every dossier version is immutably logged, all AI-generated validations require a human-in-the-loop sign-off before committee routing, and the entire workflow integrates with existing identity and access management for audit trails. The final architecture, built on orchestration frameworks like LangGraph, must support configurable review stages, secure document handling, and seamless integration with legacy academic systems to ensure defensibility and user trust.