AI-enabled compensation-planning redesign

Context

A slow, error-prone, governance-sensitive process — every bonus and incentive payout sat under both efficiency and ethics scrutiny. Disrupting payroll continuity for the workforce on the legacy system was not an option during the redesign.

Approach

Framed the redesign as a sequencing problem. Ran capability analysis to identify which process segments were safe to automate via AI agents, then structured the target operating model so AI handles routine calculation-and-payout decisions while humans retain review on edge cases. Coordinated requirements from ~10 cross-departmental stakeholders into a single executable specification.

Outcome

Cut a major Middle East oil & gas operator’s compensation-planning cycle from 11 weeks to 1–2 weeks (10× faster) via an AI-enabled target operating model.

• 10× faster cycle: 11 weeks → 1–2 weeks.
• Material reduction in error and governance-risk exposure (process redesign + AI handoff).
• Ready-to-implement AI agent specifications delivered — moved the client from “exploring AI” to “ready to deploy.”

Key result

Compressed an oil & gas operator’s compensation-planning cycle from 11 weeks to 1–2 weeks (10×) via an AI-enabled target operating model and ready-to-implement AI agent specifications, delivered in a 2-month engagement.