5 Ways LLM Workflows Transform Business Analytics

Five illustrative workflow patterns for analytics teams, with review controls and measures to test before wider use.

Jason Rae

Commercial Analytics & Applied AI Leader

Reading time: 3 minutes

These are design examples, not claims of deployments or measured outcomes at my employer. Each pattern needs a defined owner, an evaluation set and a human review step before wider use.

1. Draft an executive narrative from reviewed tables

Provide a metric dictionary, reconciled variances and source references. Ask for a draft that separates observed changes from possible explanations. Have an analyst check every number and causal statement before it reaches a management deck.

2. Review a proposed query with a qualified SQL author

A proposed SQL query can be a discussion aid for an analyst who can validate joins, filters and aggregation. Jason can read SQL but does not currently write it. Treat this example as a workflow design, not evidence of personal SQL coding proficiency.

3. Explain a controlled scenario calculation

Keep calculations and assumptions in a versioned model. Let the language model explain the inputs and outputs, with links to the calculation. Label hypothetical inputs and avoid presenting a simulated change as an observed business result.

4. Draft documentation from a recorded change

Compare an approved schema or metric definition with a proposed update. Generate a suggested documentation patch and route it to the owner. Keep the source change, proposed text and review decision together.

5. Practice with a coaching workflow

Use synthetic or approved training material and a clear rubric. Review coaching feedback for accuracy and usefulness. Jason's Smart Training project is a text-first sales roleplay MVP with buyer simulation, coaching and persisted transcripts; its voice lab is experimental.

Measure before making an outcome claim

Record task completion, correction rates and preparation time before and during a pilot. Define the unit of work and observation period. Report observed results with their limitations; a planned rollout or tool dependency cannot establish adoption, savings or production readiness.

See the project portfolio for the scope and maturity of the individual research systems, workflows and prototypes.

Fix the decision loop before you scale the prompt.

I help teams decide which analyst workflow is worth formalizing, where the guardrails are missing, and whether the first step is enablement, foundation repair, or one controlled deployment.