Does the RGM agent change prices or trade spend automatically?

No. Analysis and simulations are READ_ONLY; price, allocation, or trade-spend adjustments are FINANCIAL actions requiring approval.

What makes this different from an analytics dashboard?

The agent packages account variance, promo compliance, velocity, and recommendation rationale into an approval-ready workflow with audit evidence.

How often should promo recommendations be reviewed?

Most RGM workflows benefit from a weekly operating cadence, with CLEAR and AgentOps drift checks comparing recommendation quality against the baseline.

Revenue · RGM

RGM Promo Optimisation

A governed RGM agent analyses promo compliance, SKU velocity, account variance, and trade-spend signals, then produces recommendations for human commercial decision.

The operational problem

Promo and RGM teams operate across fragmented data: account plans, promo calendars, scan data, sales-out, field observations, and margin assumptions.

Manual analysis is slow, but fully automated pricing or trade-spend changes are too consequential to hand to an agent without governance.

The useful agent does the heavy analytical work: detect compliance gaps, explain variance, simulate options, and package recommendations. The commercial decision remains human.

Proof artifact

Promo recommendation receipt

Analysis and simulation are READ_ONLY; price, spend, and allocation changes require human approval.

Review risk classes →

Governed workflow

Load promo calendar, account plan, SKU velocity, margin rules, and field compliance data.
Detect promo execution gaps, cannibalisation signals, stock risk, and account variance.
Generate ranked recommendations with commercial rationale and confidence.
Flag price, spend, or allocation changes as FINANCIAL actions requiring approval.
Track post-decision results in AgentOps and compare against the baseline.

HARNEXA Harness controls

Analysis and simulation are READ_ONLY; commercial changes are FINANCIAL.
Recommendations include data lineage and business rationale.
Budget and tool-call limits keep analysis cost visible.
Human approval is required before any pricing, allocation, or trade-spend adjustment.
Drift monitoring compares weekly recommendation quality against CLEAR baselines.

CLEAR scorecard

Measured before it scales.

Decision speedFaster

Commercial teams receive ranked actions without manual spreadsheet assembly.

Promo complianceVisible

Execution gaps are surfaced by account and SKU.

Margin protectionGated

Trade-spend and price changes require human approval.

Accuracy>= 0.85

Recommendations align with data and commercial constraints.

DriftWeekly

AgentOps reviews recommendation quality over time.

RGM pattern

WeeklyRGM teams need repeated operating cadence, not one-off analytics. HARNEXA packages promo intelligence into a governed weekly workflow with auditable recommendations.

Sprint output

What the client receives

Promo compliance and account-variance workflow
SKU velocity and margin-rule data contract
Recommendation explanation and confidence format
Approval matrix for pricing, spend, and allocation decisions
AgentOps drift and post-decision review cadence

Operator FAQ

Questions buyers ask before scoping.

Ready to scope this workflow with governance from day one?

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