A-EC-DynamicPrice
Audited BPS: 8386Executive Summary
The pre-agentic pricing workflow was a fragmented, human-dependent process anchored in Microsoft Excel and ERP systems: a senior pricing analyst (typically an MBA-credentialed professional earning $165-210K annually) would manually construct demand forecasts by copying historical sales data from the data warehouse into Excel pivot tables, then cross-reference competitor prices harvested from web scraping tools or manually visited competitor websites, then calculate margin impact using hardcoded formulas, then circulate the proposed price changes through a Slack/email approval chain involving the supply chain manager, finance controller, and category director—a process consuming 6-8 hours per major pricing decision and occurring quarterly or ad-hoc during crisis events. The analyst was chained to SAP or Oracle ERP systems for inventory validation (requiring 15-minute manual queries), to Tableau dashboards for demand trending (requiring interpretation and judgment calls), to Google Sheets for competitor tracking (requiring manual updates from browser tabs), and to Salesforce for approval workflows—creating a Byzantine dependency graph where a single data latency or human absence could delay pricing decisions by 24-48 hours. The elasticity component was particularly brutal: pricing teams would commission quarterly econometric studies from external consultants ($15-40K per study) to estimate price elasticity, then manually apply those coefficients to category-level pricing rules, with no real-time recalibration capability. This architecture was fundamentally incapable of responding to demand shocks (a 3x velocity spike would take 6+ hours to detect and price), inventory crises (stockouts were discovered post-facto), or competitive threats (Amazon price changes were detected by humans checking the website, not by systematic feeds). The synthesis engine eliminates this entire human-dependent stack by automating the five multiplier calculations, embedding elasticity inference directly into the model stack, and executing the complete pricing decision in 47 milliseconds with full audit traceability—transforming pricing from a quarterly strategic exercise into a continuous, data-driven optimization process that operates at machine speed and human-proof reliability.
{
"request_id": "550e8400-e29b-41d4-a716-446655440000",
"timestamp": "2024-01-15T14:32:47.823Z",
"product": {
"sku": "ELEC-987654321",
"base_price": 249.99,
"category_id": 4521,
"listing_timestamp": "2024-01-08T09:15:22.000Z",
"shelf_life_hours": 2160
},
"demand_signals": {
"current_velocity": 487.3,
"baseline_velocity": 156.8,
"velocity_window_seconds": 300,
"signal_confidence": 0.94
},
"inventory_state": {
"current_units": 342,
"optimal_units": 500,
"warehouse_id": "WH-CA-0847",
"last_sync_timestamp": "2024-01-15T14:31:12.000Z",
"sync_confidence": 0.98
},
"pricing_context": {
"competitor_prices": [
{
"competitor_id": "AMZN-VENDOR-4521",
"price": 239.99,
"timestamp": "2024-01-15T14:28:33.000Z",
"weight": 0.85
},
{
"competitor_id": "WLMT-DIRECT-4521",
"price": 244.5,
"timestamp": "2024-01-15T14:29:15.000Z",
"weight": 0.72
},
{
"competitor_id": "EBAY-SELLER-PRO",
"price": 252,
"timestamp": "2024-01-15T14:27:48.000Z",
"weight": 0.58
},
{
"competitor_id": "BESTBUY-RETAIL",
"price": 259.99,
"timestamp": "2024-01-15T14:30:01.000Z",
"weight": 0.81
},
{
"competitor_id": "NEWEGG-MARKETPLACE",
"price": 235.75,
"timestamp": "2024-01-15T14:26:44.000Z",
"weight": 0.67
}
],
"elasticity_override": {
"ped_observed": -1.23,
"ped_baseline": -0.95
},
"price_floor": 189.99,
"price_ceiling": 349.99,
"margin_floor_percent": 8.5
},
"metadata": {
"client_version": "2.3.1",
"trace_id": "trace-550e8400-e29b-41d4-a716-446655440000-001",
"experiment_ids": [
"EXP-042187",
"EXP-051923"
]
}
}{
"synthesis_id": "SYNTH-550e8400-e29b-41d4-a716-446655440000",
"logic_id": "A-EC-DynamicPrice",
"bps_verified": 8386,
"model_stack": [
"PriceCalculationEngine-v2.3.0",
"DemandSignalProcessor-v1.8.2",
"InventorySyncService-v3.1.4",
"CompetitorPriceFeed-v2.0.1",
"MLElasticityModel-v4.2.7",
"PriceValidationLayer-v1.5.3",
"RedisCache-v6.2.11",
"PostgreSQL-PriceStore-v13.8"
],
"processing_ms": 47.3,
"timestamp": "2024-01-15T14:32:47.891Z",
"price_applied": 287.43,
"multiplier_decomposition": {
"demand_multiplier": {
"value": 1.6847,
"calculation": "1 + (0.23 × ln(487.3 / 156.8))",
"ratio": 3.1048,
"boundary_applied": false,
"confidence": 0.94
},
"supply_multiplier": {
"value": 1.1234,
"calculation": "1 + (0.65 × (1 - (342 / 500)))",
"inventory_ratio": 0.684,
"boundary_applied": false,
"confidence": 0.98
},
"competition_multiplier": {
"value": 0.9156,
"calculation": "1 - (0.40 × ((245.65 - 249.99) / 249.99))",
"weighted_competitor_avg": 245.65,
"competitors_evaluated": 5,
"boundary_applied": false
},
"time_decay_multiplier": {
"value": 1.0821,
"calculation": "1 - (0.30 × (144 / 2160))",
"hours_elapsed": 144,
"shelf_life_hours": 2160,
"decay_ratio": 0.0667,
"boundary_applied": false
},
"elasticity_multiplier": {
"value": 1.0504,
"calculation": "1 + (0.18 × (-1.23 - (-0.95)))",
"ped_delta": -0.28,
"boundary_applied": false,
"model_inference_ms": 12.4
},
"composite_multiplier": 1.1497
},
"price_calculation_trace": {
"base_price": 249.99,
"intermediate_1_demand": 421.34,
"intermediate_2_supply": 473.48,
"intermediate_3_competition": 433.48,
"intermediate_4_time_decay": 469.02,
"intermediate_5_elasticity": 287.43,
"final_price_unconstrained": 287.43
},
"constraint_flags": {
"price_floor_applied": false,
"price_ceiling_applied": false,
"margin_floor_applied": false,
"out_of_stock_triggered": false,
"cascading_failure_detected": false,
"floor_value": 189.99,
"ceiling_value": 349.99,
"margin_floor_percent": 8.5,
"final_margin_percent": 14.9
},
"price_validity_ttl": {
"ttl_seconds": 45,
"valid_until": "2024-01-15T14:33:32.891Z",
"refresh_reason": "demand_signal_velocity_high",
"next_recalc_trigger": "demand_velocity_change > 15% OR inventory_sync_delta > 2%"
},
"bps_component_breakdown": {
"BPS-001_PriceCalculationEngine": {
"weight": 0.25,
"risk_probability": 0.002,
"impact_severity": 10,
"component_bps": 0.05,
"latency_ms": 8.2,
"error_rate": 0.0001,
"status": "NOMINAL"
},
"BPS-002_DemandSignalIngestion": {
"weight": 0.2,
"risk_probability": 0.008,
"impact_severity": 9,
"component_bps": 0.144,
"signal_lag_ms": 1200,
"data_staleness_ms": 3400,
"status": "NOMINAL"
},
"BPS-003_InventorySyncService": {
"weight": 0.18,
"risk_probability": 0.001,
"impact_severity": 8,
"component_bps": 0.0144,
"sync_delta_percent": 0.3,
"latency_ms": 87.4,
"status": "NOMINAL"
},
"BPS-004_CompetitorPriceFeed": {
"weight": 0.12,
"risk_probability": 0.005,
"impact_severity": 6,
"component_bps": 0.036,
"feed_age_seconds": 163,
"coverage_percent": 94.2,
"status": "NOMINAL"
},
"BPS-005_MLElasticityModel": {
"weight": 0.1,
"risk_probability": 0.003,
"impact_severity": 7,
"component_bps": 0.021,
"inference_latency_ms": 12.4,
"model_drift_percent": 3.8,
"status": "NOMINAL"
},
"BPS-006_PriceValidationLayer": {
"weight": 0.08,
"risk_probability": 0.001,
"impact_severity": 8,
"component_bps": 0.0064,
"rejection_rate_percent": 0.2,
"false_positive_rate_percent": 0.05,
"status": "NOMINAL"
},
"BPS-007_CacheLayer_Redis": {
"weight": 0.05,
"risk_probability": 0.002,
"impact_severity": 5,
"component_bps": 0.005,
"hit_rate_percent": 91.3,
"eviction_rate_per_min": 2.1,
"status": "NOMINAL"
},
"BPS-008_Database_PriceStore": {
"weight": 0.02,
"risk_probability": 0.0005,
"impact_severity": 9,
"component_bps": 0.00009,
"query_latency_ms": 4.8,
"connection_pool_utilization_percent": 34.2,
"status": "NOMINAL"
}
},
"bps_operational_state": {
"bps_total": 0.2769,
"state": "NOMINAL",
"cascading_failure_probability": 0.0342,
"preemptive_degradation_triggered": false,
"critical_path_health": {
"path_1_engine_demand_inventory": 0.0594,
"path_2_engine_model_feature_store": 0.0284,
"path_3_engine_validation_database": 0.0064
}
},
"audit_trail": {
"request_received_ms": 0,
"schema_validation_ms": 2.1,
"demand_calculation_ms": 8.2,
"supply_calculation_ms": 3.4,
"competition_calculation_ms": 5.7,
"time_decay_calculation_ms": 1.2,
"elasticity_calculation_ms": 12.4,
"constraint_application_ms": 2.8,
"validation_ms": 3.1,
"cache_write_ms": 1.4,
"database_write_ms": 4.8,
"response_serialization_ms": 2.2
},
"data_quality_metrics": {
"demand_signal_confidence": 0.94,
"inventory_sync_confidence": 0.98,
"competitor_data_coverage": 0.942,
"elasticity_model_confidence": 0.87,
"overall_synthesis_confidence": 0.9425
},
"recommendations": {
"pricing_action": "APPLY_COMPUTED_PRICE",
"monitoring_level": "STANDARD",
"next_recalc_priority": "HIGH",
"notes": "Strong demand signal (3.1x baseline) with healthy inventory levels. Competitive positioning favorable. Elasticity adjustment reflects observed market sensitivity. Price increase justified by demand surge."
}
}