Knowing what kind of issue you have is only half the decision — the other half is knowing what to do with it. In this module, you'll work through a practical decision tree that tells you when to fix something yourself, when to complete a missing step, when to hand it off, and when to escalate immediately. You'll also learn the hard rule that overrides everything else: when filing deadline risk is in play, the answer is always escalate now.

This module is your field guide for the issues you'll actually encounter in tax workpapers — broken Excel links, trial balance mismatches, unmapped accounts, ONESOURCE input gaps, and more. You'll work through a troubleshooting playbook that shows you exactly what to check first, what to document, and where the line is between fixing something operationally and crossing into a judgment call that needs senior review.

A good escalation doesn't just flag a problem — it gives a reviewer everything they need to decide in one round. In this module, you'll learn a six-part escalation note structure and practice applying it to real CCP tax scenarios. By the end, you'll know how to write notes that are specific, decision-focused, and professional — the kind that get a clear answer fast instead of bouncing back with more questions.

Not everything should be automated. Learn to distinguish repetitive, rules-based tasks that benefit from automation from higher-risk activities that require human technical judgment — and to map your own workflow to find the safe automation candidates.

This module applies the automation decision framework to a practical quarterly tax provision workflow. It examines common provision steps, including trial balance import, account mapping, Schedule M-1 rollups, provision adjustments, financial statement reconciliation, memo drafting, journal entry posting, and workpaper documentation. Through workflow mapping activities, the module identifies which steps are strong automation candidates, which require partial automation and human review, and which fall inside firm risk boundaries. The module shows how tax teams can save time by automating repeatable mechanical work while keeping professional judgment and formal controls in place.

This module focuses on spreadsheet-based review controls that make recurring tax workpapers easier to verify and maintain. It explores common self-checking formula patterns, including tie-to-trial-balance checks, year-over-year variance flags, required-field checks, tax-category coverage checks, SUMIFS sanity checks, carryover ties, and round-trip rounding controls. The module emphasizes that formula-driven workpapers should not only calculate results, but also flag issues such as missing inputs, unmapped accounts, unusual movements, tie-out breaks, and rounding drift. It also covers how to select the right control for specific workpaper risks and place those controls where reviewers can use them effectively.

This module introduces safe, reusable AI prompt patterns for low-risk, repeatable tax support tasks. It examines prompt templates for weekly status updates, reviewer-note checklists, tax research framing, regulation summaries, and variance commentary. The module emphasizes that AI should support drafting and organization, not tax judgment, sign-off, or decision-making. It also covers practical guardrails such as factual tone, source limits, bracketed placeholders, no unsupported inference, and required human verification. The module closes by reinforcing key risk controls: use synthetic data only, document every automation aid, verify outputs before use, and respect firm automation boundaries.