datasynth-runtime 3.1.1

Runtime orchestration, parallel execution, and memory management
Documentation 
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# Retail Causal DAG
#
# Focus: Order-to-Cash (O2C) dynamics — how seasonality, promotion intensity,
# foot traffic, and shrinkage drive revenue recognition, DSO, and return-rate
# risk. Designed for scenario packs covering seasonal shocks, promotion-heavy
# quarters, and shrinkage outbreaks.

nodes:
  # ── Macro / External ───────────────────────────────────────────
  - id: gdp_growth
    label: "GDP Growth Rate"
    category: macro
    baseline_value: 0.025
    bounds: [-0.10, 0.15]
    interventionable: true
    config_bindings: []

  - id: consumer_confidence_index
    label: "Consumer Confidence Index"
    category: macro
    baseline_value: 100.0
    bounds: [40.0, 160.0]
    interventionable: true
    config_bindings: []

  - id: seasonal_demand_multiplier
    label: "Seasonal Demand Multiplier"
    category: macro
    baseline_value: 1.0
    bounds: [0.5, 2.5]
    interventionable: true
    config_bindings:
      - temporal_patterns.period_end.month_end.peak_multiplier

  # ── O2C operational ────────────────────────────────────────────
  - id: foot_traffic
    label: "Store Foot Traffic"
    category: operational
    baseline_value: 1.0
    bounds: [0.2, 3.0]
    interventionable: false
    config_bindings: []

  - id: conversion_rate
    label: "Browser → Buyer Conversion"
    category: operational
    baseline_value: 0.22
    bounds: [0.05, 0.55]
    interventionable: false
    config_bindings: []

  - id: basket_size
    label: "Average Basket Size"
    category: operational
    baseline_value: 1.0
    bounds: [0.4, 2.5]
    interventionable: true
    config_bindings: []

  - id: promotion_intensity
    label: "Promotion Intensity"
    category: operational
    baseline_value: 0.10
    bounds: [0.0, 0.60]
    interventionable: true
    config_bindings:
      - distributions.amounts.components[0].mu

  - id: stockout_rate
    label: "Stockout Rate"
    category: operational
    baseline_value: 0.05
    bounds: [0.0, 0.40]
    interventionable: false
    config_bindings: []

  - id: online_share
    label: "Online Sales Share"
    category: operational
    baseline_value: 0.30
    bounds: [0.0, 1.0]
    interventionable: true
    config_bindings: []

  # ── Controls ───────────────────────────────────────────────────
  - id: return_authorization_compliance
    label: "Return-Auth Control Compliance"
    category: control
    baseline_value: 0.95
    bounds: [0.5, 1.0]
    interventionable: true
    config_bindings:
      - internal_controls.exception_rate

  - id: shrinkage_control_strength
    label: "Shrinkage Control Strength"
    category: control
    baseline_value: 0.80
    bounds: [0.0, 1.0]
    interventionable: true
    config_bindings: []

  # ── Outcomes / Financial ───────────────────────────────────────
  - id: return_rate
    label: "Product Return Rate"
    category: outcome
    baseline_value: 0.08
    bounds: [0.0, 0.50]
    interventionable: false
    config_bindings: []

  - id: shrinkage_rate
    label: "Inventory Shrinkage Rate"
    category: outcome
    baseline_value: 0.015
    bounds: [0.0, 0.15]
    interventionable: false
    config_bindings: []

  - id: revenue_growth
    label: "Revenue Growth"
    category: financial
    baseline_value: 0.04
    bounds: [-0.30, 0.40]
    interventionable: false
    config_bindings:
      - distributions.drift.amount_mean_drift

  - id: gross_margin
    label: "Gross Margin"
    category: financial
    baseline_value: 0.38
    bounds: [-0.2, 0.8]
    interventionable: false
    config_bindings: []

  - id: days_sales_outstanding
    label: "Days Sales Outstanding"
    category: financial
    baseline_value: 15.0
    bounds: [1.0, 120.0]
    interventionable: false
    config_bindings: []

  - id: revenue_cutoff_risk
    label: "Revenue Cut-off Risk"
    category: outcome
    baseline_value: 0.03
    bounds: [0.0, 0.50]
    interventionable: false
    config_bindings: []

  - id: misstatement_risk
    label: "Material Misstatement Risk"
    category: outcome
    baseline_value: 0.02
    bounds: [0.0, 1.0]
    interventionable: false
    config_bindings: []

edges:
  # Macro → demand
  - from: consumer_confidence_index
    to: foot_traffic
    transfer: { type: linear, coefficient: 0.010, intercept: 0.0 }
    lag_months: 0
    strength: 0.7
    mechanism: "Confident consumers visit more stores"

  - from: consumer_confidence_index
    to: basket_size
    transfer: { type: linear, coefficient: 0.005, intercept: 0.5 }
    lag_months: 0
    strength: 0.5
    mechanism: "Higher confidence drives bigger baskets"

  - from: gdp_growth
    to: revenue_growth
    transfer: { type: linear, coefficient: 1.5, intercept: 0.0 }
    lag_months: 1
    strength: 0.6
    mechanism: "GDP growth lifts retail revenue with retail-sector amplification"

  - from: seasonal_demand_multiplier
    to: foot_traffic
    transfer: { type: linear, coefficient: 1.0, intercept: 0.0 }
    lag_months: 0
    strength: 0.8
    mechanism: "Holiday seasons push peak traffic"

  # Demand → sales
  - from: foot_traffic
    to: stockout_rate
    transfer: { type: threshold, threshold: 1.4, magnitude: 0.08, saturation: 0.35 }
    lag_months: 0
    strength: 0.7
    mechanism: "Peak demand above planned capacity → stockouts"

  - from: promotion_intensity
    to: basket_size
    transfer: { type: linear, coefficient: 0.8, intercept: 1.0 }
    lag_months: 0
    strength: 0.6
    mechanism: "Promotions lift basket size via attach rate"

  - from: promotion_intensity
    to: gross_margin
    transfer: { type: linear, coefficient: -0.6, intercept: 0.38 }
    lag_months: 0
    strength: 0.7
    mechanism: "Discounting compresses margin"

  # Returns and shrinkage
  - from: return_authorization_compliance
    to: return_rate
    transfer: { type: inverse_logistic, capacity: 0.30, midpoint: 0.80, steepness: 10.0 }
    lag_months: 0
    strength: 0.6
    mechanism: "Lax return-auth controls inflate returns"

  - from: promotion_intensity
    to: return_rate
    transfer: { type: linear, coefficient: 0.20, intercept: 0.05 }
    lag_months: 1
    strength: 0.5
    mechanism: "Discounted purchases are returned more often"

  - from: shrinkage_control_strength
    to: shrinkage_rate
    transfer: { type: inverse_logistic, capacity: 0.10, midpoint: 0.60, steepness: 8.0 }
    lag_months: 0
    strength: 0.8
    mechanism: "Strong controls suppress shrinkage (theft, admin loss)"

  # Revenue/cash cycle
  - from: online_share
    to: days_sales_outstanding
    transfer: { type: linear, coefficient: -10.0, intercept: 15.0 }
    lag_months: 0
    strength: 0.5
    mechanism: "Online card sales settle faster than invoiced B2B"

  - from: return_rate
    to: revenue_growth
    transfer: { type: linear, coefficient: -0.5, intercept: 0.04 }
    lag_months: 1
    strength: 0.6
    mechanism: "Returns directly reduce net revenue"

  - from: shrinkage_rate
    to: gross_margin
    transfer: { type: linear, coefficient: -1.5, intercept: 0.38 }
    lag_months: 0
    strength: 0.7
    mechanism: "Shrinkage consumes margin"

  # Audit risk
  - from: promotion_intensity
    to: revenue_cutoff_risk
    transfer: { type: threshold, threshold: 0.30, magnitude: 0.10, saturation: 0.35 }
    lag_months: 0
    strength: 0.5
    mechanism: "Heavy promos at period-end raise cut-off questions"

  - from: return_rate
    to: revenue_cutoff_risk
    transfer: { type: linear, coefficient: 0.5, intercept: 0.03 }
    lag_months: 0
    strength: 0.5
    mechanism: "High post-period returns suggest early revenue recognition"

  - from: revenue_cutoff_risk
    to: misstatement_risk
    transfer: { type: linear, coefficient: 1.0, intercept: 0.01 }
    lag_months: 0
    strength: 0.8
    mechanism: "Cut-off issues are a primary retail misstatement driver"