A proposed workflow to validate with your team. No customer results or improvement guarantees are implied.
Current pain
Teams spend hours assembling packs and reconciling numbers. The meeting ends with actions scattered across notes and no consistent follow-through.
Business impact
Slow decisions and unclear ownership prolong execution gaps. Reporting effort displaces problem solving and hides whether actions made a difference.
Redesigned Human + AI workflow
- AI prepares an exception-led briefing from approved KPIs with definitions, source dates and gaps.
- AI drafts decision options and checks whether previous actions have evidence of completion.
- Leaders resolve trade-offs, assign owners and confirm dates. AI records the approved decision and follow-up.
- Owners review action progress in the normal cadence. Finance verifies claimed value separately from activity completion.
Change and adoption
Agree KPI definitions and a common action log. Shift meeting time from status narration to decisions. Teach leaders to reject unsupported summaries and create space for frontline corrections.
Systems and data
Approved ERP/finance/CRM/MES metrics; KPI dictionary; action log and meeting decisions; business calendar and ownership map. Access must respect finance, employee and customer confidentiality.
KPIs with clear definitions
- Preparation effort = measured hours spent producing the management pack per cycle.
- Decision latency = elapsed time from a decision-ready exception to the recorded decision.
- Action closure = actions completed with evidence by due date / actions due.
- Verified value = finance-approved attributable benefit, reported separately from modeled exposure.
Measurable outcomes and verification
Observe several baseline review cycles, then compare preparation time, decision latency and closure quality over the proof period. Treat time released as capacity until redeployment or actual cost removal is evidenced.
Accelerators where relevant
PulseIQ can support evidence and outcome reviews. TalentPulse can add capacity context when workforce readiness affects delivery.