Measure swarm · Per-Location Rollup + Executive Reporting Agent · Drivers-analysis skill · Build pillar · Published September 8, 2026

How to build revenue drivers analysis for multi-location operators

When monthly revenue moves +12% YoY across 200 locations, the board asks “why?” The CFO who answers “same-store-sales were strong” gets “but why?” The drivers-analysis skill decomposes that 12% into per-driver contribution shares across 30+ drivers with true causal-decomposition (not mathematical-identity decomposition) + counter-factual + confidence intervals. This guide explains how to architect the drivers-analysis skill on the Per-Location Rollup + Executive Reporting Agent end-to-end at multi-location revenue-drivers scale: per-portfolio per-banner per-period per-driver per-canonical-driver-class-pointer + per-canonical-causal-decomposition-spec + per-canonical-Shapley-attribution-spec + per-canonical-Granger-causality-spec + per-canonical-counter-factual-spec + per-canonical-confidence-interval-spec + per-canonical-cross-banner-aggregation-spec + per-canonical-per-vertical-seasonality-spec + per-canonical-Reg-G-non-GAAP-compliance-overlay + per-canonical-audit-trail + per-portfolio-audit-trail.

Engage the rollup-reporting agent See the 32-agent swarm

What you will build

Per-portfolio per-banner per-period per-driver per-canonical-driver-class-pointer across 30+ drivers — customer-count + AOV + frequency + conversion-rate + channel-mix + product-mix + promotional-lift + pricing-change + cannibalization + FX + weather + seasonality + new-location-opening + comp-store-vs-non-comp + cohort-tenure-shift + loyalty-tier-mix-shift + new-customer-acquisition + reactivation-rate + churn-rate + promotional-cannibalization + cross-banner-cannibalization + organic-vs-paid-mix + multi-touch-attribution-shift + iOS 14 ATT impact + Google Privacy Sandbox impact + FX + supply-chain-disruption + labor-shortage.
Per-canonical-causal-decomposition-spec— Shapley value (Aumann-Shapley + Banzhaf + Owen-coalitional + SHAP Lundberg-Lee 2017) + Granger causality (VAR + Toda-Yamamoto + Diks-Panchenko nonparametric + multivariate Granger + block-exogeneity Wald) + counter-factual (CATE T-learner + S-learner + X-learner + DR-learner + CausalML + DoubleML + EconML + Causal Forest + BART + Bayesian causal inference PyMC/Stan/NumPyro) + instrumental variable (2SLS + GMM + Anderson-Hsiao + Arellano-Bond + Blundell-Bond) + difference-in-differences (DiD + event study + Callaway-Sant'Anna staggered treatment + de Chaisemartin-D'Haultfoeuille + Goodman-Bacon decomposition) + synthetic control (Abadie-Gardeazabal + Doudchenko-Imbens + Ferman-Pinto) + regression-discontinuity-design + propensity-score-matching (nearest-neighbor + kernel + stratified + radius) + IPW + augmented-IPW + targeted MLE.
Per-canonical-Shapley-attribution-spec + per-canonical-Granger-causality-spec — SHAP + LIME + anchor explanations + counterfactual explanations + Integrated Gradients + DeepLIFT + Shapley-Lorenz + Shapley additive explanation + lag-order selection AIC/BIC/HQC/FPE + stationarity ADF/KPSS/PP/DF-GLS + cointegration Engle-Granger/Johansen/Phillips-Ouliaris + impulse-response-function + variance decomposition.
Per-canonical-counter-factual-spec + per-canonical-confidence-interval-spec — do-calculus Pearl + Rubin causal model + potential outcomes + ATE/ATT/ATC + CATE + heterogeneous treatment effects + uplift modeling + bootstrap (percentile + BCa + Studentized) + Bayesian credible interval + asymptotic normal + Wald + Wilson + Agresti-Coull + Clopper-Pearson + Jeffreys + Hodges-Lehmann + Hettmansperger-McKean.
Per-canonical-cross-banner-aggregation-spec + per-canonical-per-vertical-seasonality-spec — Simpson paradox detection + Yule-Simpson + aggregation bias + base-rate fallacy + collider bias + Berkson paradox + confounding-variable detection + stratification + marginalization + multiple-comparisons correction (Bonferroni + Holm-Bonferroni + Benjamini-Hochberg FDR + Benjamini-Yekutieli + Tukey HSD + Dunnett + Scheffe) + per-vertical seasonality (retail Black-Friday/Cyber-Monday + restaurant football-season/NCAA-March-Madness/Super-Bowl + fitness January-resolution + medical cold-flu-Q4/deductible-reset + tax Q1-Q2/October-extension + tourism summer-peak + back-to-school late-July + cannabis 420 + alcohol Cinco-de-Mayo/St-Patrick's/Memorial/July-4/Labor + Federal-Reserve-rate CRE cycle + election-year-pause + supply-chain-disruption + labor-shortage + FX EUR/GBP/CAD/AUD/JPY/CNY/MXN/INR).
Per-canonical-Reg-G-non-GAAP-compliance-overlay— SEC Regulation G 17 CFR 244 (Adjusted EBITDA + same-store-sales + comp-sales + 4-wall EBITDA + unit economics + FCF + EBITDAR + ARR + cohort-LTV reconciliation + equal-or-greater-prominence + purpose-disclosure when public-co; SEC C&DI Question 100/101/102) + Sarbanes-Oxley Section 302/404/906 (CEO + CFO certification + ICFR + Section 906 criminal certification $1M + 10 years knowing + $5M + 20 years willful) + SEC Regulation S-K Item 303 MD&A + FASB ASC 606 revenue recognition 5-step model (drivers analysis output must align with revenue recognition timing) + FASB ASC 842 leases + FASB ASC 326 CECL + AICPA non-GAAP + PCAOB AS 2410 + AICPA SSAE + forensic accounting + FDD Item 19 financial performance representations + FTC Franchise Rule 16 CFR 436 + 15-state franchise registration + 7-state franchise disclosure + multiple-comparisons-correction family-wise error rate + FDR control + pre-registration AsPredicted/OSF + CCPA/CPRA + CCPA right-to-opt-out-of-automated-decisionmaking + GDPR Article 22 + EU AI Act Article 50 + Connecticut CTDPA + Texas DPSA + Virginia CDPA + Colorado CPA + Utah CPA + NIST AI RMF + ISO 42001/27001 + SOC 2 Type II + OPA/Cedar/Casbin/Cerbos/Oso.
Per-canonical-cross-skill-handoff + per-canonical-audit-trail — per-handoff-to-28-sibling-skills + per-per-driver-canonical-audit-record + per-immutable-WORM-storage + per-7-year-IRS-tax-retention + per-7-year-FTC-substantiation-retention + per-6-year-SEC-record-retention + per-7-year-Sarbanes-Oxley-Section-802-retention + per-5-year-PCAOB-record-retention + per-3-year-FDD-Item-19-record-retention + per-7-year-state-franchise-registration-record-retention.

Why per-vendor-Anaplan-account-flat-driver-table breaks at multi-location revenue-drivers scale

Per-vendor-Anaplan-canonical-account-flat-driver-table ships per-account per-flat-formula-tree primitive. The planner manually authors a flat driver formula tree (Revenue = Customer Count × AOV × Frequency) and the system computes the variance. Per-vendor-Pigment + Causal + Cube + Mosaic.tech + Workday-Adaptive + Oracle-Hyperion + OneStream + Vena + Planful + Prophix + IBM-Planning-Analytics + SAP-BPC-canonical-account-flat-driver-table ship per-vendor per-native account-flat-driver-table primitives. None resolves true causal-decomposition (only mathematical-identity decomposition); none surfaces counter-factual (“what would revenue have been without the promotion?”); none provides confidence intervals on attribution. At 1-account-1-flat-driver-table scale per-account per-flat-driver-table primitive is enough. At multi-location revenue-drivers scale per-canonical-driver-class-pointer + per-canonical-causal-decomposition-spec + per-canonical-Shapley-attribution-spec + per-canonical-Granger-causality-spec + per-canonical-counter-factual-spec + per-canonical-confidence-interval-spec + per-canonical-cross-banner-aggregation-spec + per-canonical-per-vertical-seasonality-spec + per-canonical-Reg-G-non-GAAP-compliance-overlay + per-canonical-audit-trail.

The SEC-Regulation-G-non-GAAP anchor is the first operationally distinctive constraint. 17 CFR 244 requires non-GAAP financial measures including Adjusted EBITDA + same-store-sales + comp-sales + 4-wall EBITDA + unit economics + FCF + EBITDAR + ARR + cohort-LTV to reconcile to most directly comparable GAAP measure + provide equal-or-greater-prominence + disclose purpose when reported by a public company. SEC C&DI Question 100/101/102 enforcement. Drivers analysis outputs that report these measures are subject to Reg G.

The Sarbanes-Oxley-Section-302-404-906 anchor is the second distinctive constraint. Section 302 CEO + CFO certification of disclosure controls (quarterly + annual). Section 404 internal controls over financial reporting (management assertion + auditor attestation per AS 2201). Section 906 criminal certification — $1M + 10 years for knowing false certification; $5M + 20 years for willful false certification. Drivers analysis is part of the disclosure-control universe.

The FASB-ASC-606-revenue-recognition anchor is the third distinctive constraint. The 5-step model — identify contract + identify performance obligations + determine transaction price + allocate transaction price + recognize revenue when or as performance obligation satisfied — constrains how drivers analysis decomposes subscription + franchise-fee + gift-card + loyalty + multi-element-arrangement revenue. The drivers-analysis output must align with revenue recognition timing.

The Simpson-paradox + multiple-comparisons anchor is the fourth distinctive constraint. Cross-banner aggregation can flip the sign of a driver effect (Simpson paradox). Multiple-comparisons-correction (Bonferroni + Holm-Bonferroni + Benjamini-Hochberg FDR + Benjamini-Yekutieli + Tukey HSD + Dunnett + Scheffe) prevents false-discovery inflation when reporting many drivers. Family-wise error rate and FDR control matter when the analyst tests 30+ driver hypotheses. Pre-registration via AsPredicted or OSF is a defensible practice in the replication-crisis context.

The FDD-Item-19-financial-performance-representations anchor is the fifth distinctive constraint when the operator is a franchisor. FTC Franchise Rule 16 CFR 436. FDD Item 19 is voluntary but if included must have reasonable basis + written substantiation + actual outlet data not projections + per-class disclosure + statistical-significance-when-applicable. NASAA Commentary on FPRs. 15-state franchise registration (NY + CA + IL + MD + MI + MN + NB + ND + RI + SD + VA + WA + WI + HI + IN).

The operator-side architecture above per-vendor-flat-driver-table primitive is canonical-driver-class-pointer + causal-decomposition-spec + Shapley-attribution-spec + Granger-causality-spec + counter-factual-spec + confidence-interval-spec + cross-banner-aggregation-spec + per-vertical-seasonality-spec + Reg-G-non-GAAP-compliance-overlay + cross-skill-handoff + audit-trail + portfolio-audit-trail.

What is in market today

Per-platform per-FP&A-driver-vendor

Anaplan, Pigment, Causal, Cube, Mosaic.tech, Workday Adaptive Planning, Oracle Hyperion, OneStream, Vena, Planful, Prophix, IBM Planning Analytics, SAP BPC, BlackLine, FloQast, Workiva. Per-account per-flat-formula-tree primitive — flat driver tree authored by the planner; mathematical-identity decomposition only. No true causal decomposition. No counter-factual. No confidence intervals. Per-canonical-driver-class-pointer-canonical-causal-decomposition-canonical-Shapley-attribution-canonical-Granger-causality-canonical-counter-factual-canonical-confidence-interval-canonical-cross-banner-aggregation-canonical-per-vertical-seasonality-canonical-Reg-G-non-GAAP-compliance-overlay-canonical-audit-trail is not the primitive.

Per-platform per-causal-inference-vendor

CausalML (Uber), DoubleML, EconML (Microsoft), CausalNex (QuantumBlack), DoWhy (Microsoft), Causal Forest (Athey Wager), BART (Chipman George McCulloch), PyMC, Stan, NumPyro, Edward2, bambi, brms-R, RStan, AzCausal, CausalPy. Per-account per-flat-causal-model primitive (typically blind to per-driver Shapley-Aumann-Banzhaf-Owen + Granger-VAR-Toda-Yamamoto + DiD-Callaway-Sant'Anna + synthetic-control-Abadie-Gardeazabal + RDD + PSM + IPW + targeted-MLE semantics). Per-canonical-per-driver-Shapley-Aumann-Banzhaf-Owen-canonical-per-driver-Granger-VAR-Toda-Yamamoto-Diks-Panchenko-canonical-per-driver-counter-factual-CATE-T-S-X-DR-CausalML-DoubleML-EconML-Causal-Forest-BART-canonical-per-driver-instrumental-variable-canonical-per-driver-DiD-Callaway-SantAnna-Goodman-Bacon-canonical-per-driver-synthetic-control-canonical-per-driver-regression-discontinuity-canonical-per-driver-propensity-score-matching-canonical-per-driver-IPW is not the primitive.

Per-platform per-BI-vendor

Domo, Tableau, Power BI, Looker, ThoughtSpot, Qlik, Sisense, Mode, Hex, Sigma, Hyperquery, Metabase, Preset, Holistics. Per-account per-flat-dashboard primitive (typically blind to per-driver cross-banner aggregation Simpson-paradox/Yule-Simpson/aggregation-bias/base-rate-fallacy/collider-bias/Berkson-paradox/confounding-variable + multiple-comparisons-correction Bonferroni/Holm-Bonferroni/Benjamini-Hochberg-FDR/Tukey-HSD + per-vertical seasonality semantics). Per-canonical-per-driver-Simpson-paradox-Yule-Simpson-aggregation-bias-base-rate-fallacy-collider-bias-Berkson-paradox-confounding-variable-canonical-per-driver-multiple-comparisons-Bonferroni-Holm-Benjamini-Hochberg-Benjamini-Yekutieli-Tukey-HSD-Dunnett-Scheffe-canonical-per-driver-stratification-marginalization is not the primitive.

Per-platform per-financial-reporting-compliance-vendor

Workiva, BlackLine, FloQast, Trintech, AuditBoard, Hyperproof, Drata, Vanta, Thoropass, Tugboat Logic, Wdesk. Per-account per-flat-XBRL-tagging-or-disclosure-management primitive (typically blind to per-driver SEC Reg G non-GAAP + Sarbanes-Oxley 302/404/906 + FASB ASC 606 revenue recognition + AICPA non-GAAP + PCAOB AS 2410 + FDD Item 19 + pre-registration AsPredicted/OSF + multiple-comparisons-correction family-wise error rate + FDR control semantics). Per-canonical-per-driver-SEC-Reg-G-canonical-per-driver-Sarbanes-Oxley-302-404-906-canonical-per-driver-FASB-ASC-606-canonical-per-driver-FASB-ASC-842-canonical-per-driver-FASB-ASC-326-canonical-per-driver-AICPA-non-GAAP-canonical-per-driver-PCAOB-AS-2410-canonical-per-driver-FDD-Item-19-canonical-per-driver-pre-registration-AsPredicted-OSF-canonical-per-driver-multiple-comparisons-correction is not the primitive.

How the architecture is built

Per-portfolio per-banner per-period per-driver per-canonical-driver-class-pointer-substrate. Per-30+-canonical-driver-class canonical-driver.
Per-portfolio per-canonical-causal-decomposition-spec. Per-Shapley-Aumann-Banzhaf-Owen + per-Granger-VAR-Toda-Yamamoto-Diks-Panchenko + per-counter-factual-CATE-T-S-X-DR-CausalML-DoubleML-EconML-Causal-Forest-BART + per-instrumental-variable-2SLS-GMM-Anderson-Hsiao-Arellano-Bond-Blundell-Bond + per-DiD-event-study-Callaway-SantAnna-de-Chaisemartin-DHaultfoeuille-Goodman-Bacon + per-synthetic-control-Abadie-Doudchenko-Ferman + per-RDD + per-PSM + per-IPW-augmented-IPW-targeted-MLE + per-causal-decomposition-confidence-tier canonical-causal-decomposition.
Per-portfolio per-canonical-Shapley-attribution-spec + per-canonical-Granger-causality-spec. Per-feature-contribution + per-SHAP + per-LIME + per-anchor + per-counterfactual + per-Integrated-Gradients + per-DeepLIFT + per-Shapley-Lorenz + per-lag-order-AIC-BIC-HQC-FPE + per-stationarity-ADF-KPSS-PP-DF-GLS + per-cointegration-Engle-Granger-Johansen-Phillips-Ouliaris + per-impulse-response-function + per-variance-decomposition canonical-Shapley-Granger.
Per-portfolio per-canonical-counter-factual-spec + per-canonical-confidence-interval-spec. Per-do-calculus-Pearl + per-Rubin-causal-model + per-potential-outcomes + per-ATE-ATT-ATC-CATE + per-heterogeneous-treatment-effects + per-uplift-modeling + per-bootstrap-percentile-BCa-Studentized + per-Bayesian-credible + per-asymptotic-normal + per-Wald + per-Wilson + per-Agresti-Coull + per-Clopper-Pearson + per-Jeffreys + per-Hodges-Lehmann + per-Hettmansperger-McKean canonical-counter-factual-CI.
Per-portfolio per-canonical-cross-banner-aggregation-spec + per-canonical-per-vertical-seasonality-spec. Per-Simpson-paradox + per-Yule-Simpson + per-aggregation-bias + per-base-rate-fallacy + per-collider-bias + per-Berkson-paradox + per-confounding-variable + per-stratification + per-marginalization + per-multiple-comparisons-Bonferroni-Holm-Benjamini-Hochberg-Benjamini-Yekutieli-Tukey-HSD-Dunnett-Scheffe + per-retail-Black-Friday-Christmas-Mother-Father-Valentine-Halloween + per-restaurant-football-NCAA-Super-Bowl-St-Patrick-Cinco-Memorial-July-4-Labor + per-fitness-January-resolution + per-medical-cold-flu-deductible-reset + per-tax-Q1-Q2-October + per-tourism-summer-shoulder-winter + per-back-to-school-late-July-August + per-cannabis-420-Green-Wednesday-7-10 + per-alcohol-Cinco-St-Patrick-Memorial-July-4-Labor-Halloween-Thanksgiving-NYE + per-Federal-Reserve-rate-CRE-cycle + per-election-year-pause + per-supply-chain-disruption + per-labor-shortage + per-FX-EUR-GBP-CAD-AUD-JPY-CNY-MXN-INR canonical-cross-banner-seasonality.
Per-portfolio per-canonical-Reg-G-non-GAAP-compliance-overlay. Per-SEC-Regulation-G + per-Sarbanes-Oxley-302-404-906 + per-SEC-Regulation-S-K-Item-303-MD&A + per-FASB-ASC-606 + per-FASB-ASC-842 + per-FASB-ASC-326 + per-AICPA-non-GAAP + per-PCAOB-AS-2410 + per-AICPA-SSAE + per-forensic-accounting + per-FDD-Item-19 + per-FTC-Franchise-Rule-16-CFR-436 + per-15-state-franchise-registration + per-7-state-franchise-disclosure + per-multiple-comparisons-correction-family-wise-error-rate-FDR-control + per-pre-registration-AsPredicted-OSF + per-CCPA-CPRA + per-CCPA-right-to-opt-out + per-GDPR-Article-22 + per-EU-AI-Act-Article-50 + per-Connecticut-CTDPA + per-Texas-DPSA + per-Virginia-CDPA + per-Colorado-CPA + per-Utah-CPA + per-NIST-AI-RMF + per-ISO-42001 + per-ISO-27001 + per-SOC-2-Type-II + per-OPA-Cedar-Casbin-Cerbos-Oso canonical-compliance.
Per-portfolio per-canonical-cross-skill-handoff. Per-handoff-to-28-sibling-skills canonical-handoff.
Per-portfolio per-canonical-audit-trail + per-portfolio-audit-trail. Per-per-driver-canonical-audit-record + per-immutable-WORM-storage + per-7-year-IRS-tax-retention + per-7-year-FTC-substantiation-retention + per-6-year-SEC-record-retention + per-7-year-Sarbanes-Oxley-Section-802-retention + per-5-year-PCAOB-record-retention + per-3-year-FDD-Item-19-record-retention + per-7-year-state-franchise-registration-record-retention canonical-audit.

Frequently asked questions

What is revenue drivers analysis for multi-location operators — and what is the board-asks-why-and-the-CFO-has-no-answer problem?

When monthly revenue moves +12% YoY across 200 locations, the board asks “why?” The CFO who answers “same-store-sales were strong” gets a follow-up “but why?” The drivers-analysis skill decomposes that 12% into per-driver contribution shares: per-customer-count + per-AOV + per-frequency + per-conversion-rate + per-channel-mix + per-product-mix + per-promotional-lift + per-pricing-change + per-cannibalization + per-FX + per-weather + per-seasonality + per-new-location-opening + per-comp-store-vs-non-comp + per-cohort-tenure-shift + per-loyalty-tier-mix-shift + per-new-customer-acquisition + per-reactivation-rate + per-churn-rate + per-AOV-mix-shift + per-promotional-cannibalization + per-cross-banner-cannibalization + per-organic-vs-paid-mix + per-multi-touch-attribution-shift + per-iOS-14-ATT-impact + per-Google-Privacy-Sandbox-impact + per-FX-EUR-GBP-CAD-AUD-JPY-CNY + per-supply-chain-disruption + per-labor-shortage. Per-portfolio per-banner per-period per-driver per-canonical-driver-class-pointer + per-canonical-causal-decomposition-spec + per-canonical-Shapley-attribution-spec + per-canonical-Granger-causality-spec + per-canonical-counter-factual-spec + per-canonical-confidence-interval-spec + per-canonical-cross-banner-aggregation-spec + per-canonical-per-vertical-seasonality-spec + per-canonical-Reg-G-non-GAAP-compliance-overlay + per-canonical-audit-trail.

Why does per-vendor-Anaplan-canonical-account-flat-driver-table break at multi-location revenue-drivers scale?

Per-vendor-Anaplan-canonical-account-flat-driver-table ships per-account per-flat-formula-tree primitive — the planner manually authors a flat driver formula tree (e.g., Revenue = Customer Count × AOV × Frequency) and the system computes the variance. Per-vendor-Pigment + Causal + Cube + Mosaic.tech + Workday-Adaptive + Oracle-Hyperion + OneStream + Vena + Planful + Prophix + IBM-Planning-Analytics + SAP-BPC-canonical-account-flat-driver-table ship per-vendor per-native account-flat-driver-table primitives. None resolves true causal-decomposition (only mathematical-identity decomposition); none surfaces counter-factual (“what would revenue have been without the promotion?”); none provides confidence intervals on attribution. No per-canonical-driver-class taxonomy across the 30+ driver classes, no per-canonical-causal-decomposition-spec resolving per-Shapley-value-decomposition (per-cooperative-game-theory + per-Aumann-Shapley + per-Banzhaf + per-Owen-coalitional-Shapley) + per-Granger-causality (per-VAR + per-Toda-Yamamoto + per-Diks-Panchenko-nonparametric) + per-counter-factual (per-CATE-T-learner + per-S-learner + per-X-learner + per-DR-learner + per-CausalML + per-DoubleML + per-EconML + per-Causal-Forest + per-Bayesian-Additive-Regression-Trees-BART) + per-instrumental-variable (per-2SLS + per-GMM + per-Anderson-Hsiao) + per-difference-in-differences (per-DiD + per-event-study + per-Callaway-Sant'Anna + per-de-Chaisemartin-D'Haultfoeuille) + per-synthetic-control + per-regression-discontinuity-design + per-propensity-score-matching + per-IPW-inverse-propensity-weighting, no per-canonical-Shapley-attribution-spec resolving per-feature-contribution + per-SHAP + per-LIME + per-anchor-explanations + per-counterfactual-explanations + per-Integrated-Gradients + per-DeepLIFT + per-Shapley-Lorenz + per-Shapley-additive-explanation-Lundberg-Lee-2017, no per-canonical-Granger-causality-spec resolving per-lag-order-selection (per-AIC + per-BIC + per-HQC + per-FPE) + per-stationarity-test (per-ADF + per-KPSS + per-PP + per-DF-GLS) + per-cointegration-test (per-Engle-Granger + per-Johansen + per-Johansen-Juselius) + per-impulse-response-function + per-variance-decomposition + per-multivariate-Granger + per-block-exogeneity-Wald-test, no per-canonical-counter-factual-spec resolving per-do-calculus-Pearl + per-Rubin-causal-model + per-potential-outcomes + per-ATE-ATT-ATC + per-CATE-conditional-average-treatment-effect + per-heterogeneous-treatment-effects + per-uplift-modeling + per-Bayesian-causal-inference + per-PyMC-causal + per-Stan-causal + per-NumPyro-causal, no per-canonical-confidence-interval-spec resolving per-bootstrap-confidence-interval + per-Bayesian-credible-interval + per-asymptotic-normal + per-percentile + per-BCa-bias-corrected-accelerated + per-Wald + per-Wilson + per-Agresti-Coull + per-Clopper-Pearson + per-Jeffreys + per-Hodges-Lehmann + per-Hettmansperger-McKean, no per-canonical-cross-banner-aggregation resolving per-Simpson-paradox-detection + per-Yule-Simpson-paradox + per-aggregation-bias-detection + per-base-rate-fallacy-detection + per-collider-bias-detection + per-Berkson-paradox + per-confounding-variable-detection + per-stratification + per-marginalization, no per-canonical-per-vertical-seasonality-spec resolving per-retail-Black-Friday-Cyber-Monday-Christmas-Mother's-Father's-Valentine's-Halloween + per-restaurant-football-season-NCAA-March-Madness-Super-Bowl + per-fitness-January-resolution-spring-summer-prep + per-medical-cold-flu-allergy-Q4-deductible-reset + per-tax-season-Q1-Q2-extension-October + per-tourism-summer-shoulder-winter + per-back-to-school-late-July-August + per-cannabis-420 + per-alcohol-Cinco-de-Mayo-St-Patrick-Memorial-July-Labor + per-Federal-Reserve-rate-CRE-cycle + per-election-year-pause, no per-canonical-Reg-G-non-GAAP-compliance-overlay (the operationally distinctive anchor: SEC Regulation G + non-GAAP financial measures reconciliation + equal-or-greater-prominence + purpose-disclosure + C&DI Question 100/101/102 enforcement + adjusted EBITDA + same-store-sales + comp-sales + 4-wall EBITDA + unit economics + FCF + EBITDAR + ARR + cohort-LTV subject to Reg G when public-co), no per-driver audit trail with regulatory-defense retention. At 1-account-1-flat-driver-table scale per-account per-flat-driver-table primitive is enough. At multi-location revenue-drivers scale per-canonical-driver-class-pointer + per-canonical-causal-decomposition-spec + per-canonical-Shapley-attribution-spec + per-canonical-Granger-causality-spec + per-canonical-counter-factual-spec + per-canonical-confidence-interval-spec + per-canonical-cross-banner-aggregation-spec + per-canonical-per-vertical-seasonality-spec + per-canonical-Reg-G-non-GAAP-compliance-overlay + per-canonical-audit-trail.

How does per-driver causal-decomposition engine + Shapley-attribution + Granger-causality + counter-factual + confidence-interval work?

Per-portfolio per-banner per-period per-driver per-canonical-causal-decomposition-spec runs per-portfolio per-canonical-per-driver-Shapley-value-decomposition (per-cooperative-game-theory + per-Aumann-Shapley + per-Banzhaf + per-Owen-coalitional-Shapley + per-SHAP-Lundberg-Lee-2017) + per-canonical-per-driver-Granger-causality (per-VAR + per-Toda-Yamamoto + per-Diks-Panchenko-nonparametric + per-multivariate-Granger + per-block-exogeneity-Wald) + per-canonical-per-driver-counter-factual (per-CATE-T-learner + per-S-learner + per-X-learner + per-DR-learner + per-CausalML + per-DoubleML + per-EconML + per-Causal-Forest + per-Bayesian-Additive-Regression-Trees-BART + per-Bayesian-causal-inference + per-PyMC-causal + per-Stan-causal + per-NumPyro-causal) + per-canonical-per-driver-instrumental-variable (per-2SLS + per-GMM + per-Anderson-Hsiao + per-Arellano-Bond + per-Blundell-Bond) + per-canonical-per-driver-difference-in-differences (per-DiD + per-event-study + per-Callaway-Sant'Anna-staggered-treatment + per-de-Chaisemartin-D'Haultfoeuille + per-Goodman-Bacon-decomposition) + per-canonical-per-driver-synthetic-control (per-Abadie-Gardeazabal + per-Doudchenko-Imbens + per-Ferman-Pinto) + per-canonical-per-driver-regression-discontinuity-design + per-canonical-per-driver-propensity-score-matching (per-nearest-neighbor + per-kernel + per-stratified + per-radius) + per-canonical-per-driver-IPW (per-inverse-propensity-weighting + per-augmented-IPW + per-targeted-MLE) + per-canonical-per-driver-causal-decomposition-confidence-tier + per-canonical-per-driver-causal-decomposition-explainability. Per-canonical-Shapley-attribution-spec runs per-portfolio per-canonical-per-driver-feature-contribution + per-canonical-per-driver-SHAP + per-canonical-per-driver-LIME + per-canonical-per-driver-anchor-explanations + per-canonical-per-driver-counterfactual-explanations + per-canonical-per-driver-Integrated-Gradients + per-canonical-per-driver-DeepLIFT + per-canonical-per-driver-Shapley-Lorenz + per-canonical-per-driver-Shapley-additive-explanation + per-canonical-per-driver-attribution-confidence-tier. Per-canonical-Granger-causality-spec runs per-portfolio per-canonical-per-driver-lag-order-selection (per-AIC + per-BIC + per-HQC + per-FPE) + per-canonical-per-driver-stationarity-test (per-ADF + per-KPSS + per-PP + per-DF-GLS) + per-canonical-per-driver-cointegration-test (per-Engle-Granger + per-Johansen + per-Johansen-Juselius + per-Phillips-Ouliaris) + per-canonical-per-driver-impulse-response-function + per-canonical-per-driver-variance-decomposition + per-canonical-per-driver-Granger-confidence-tier. Per-canonical-counter-factual-spec runs per-portfolio per-canonical-per-driver-do-calculus-Pearl + per-canonical-per-driver-Rubin-causal-model + per-canonical-per-driver-potential-outcomes + per-canonical-per-driver-ATE-ATT-ATC + per-canonical-per-driver-CATE + per-canonical-per-driver-heterogeneous-treatment-effects + per-canonical-per-driver-uplift-modeling + per-canonical-per-driver-counter-factual-confidence-tier. Per-canonical-confidence-interval-spec runs per-portfolio per-canonical-per-driver-bootstrap-CI (per-percentile + per-BCa + per-Studentized) + per-canonical-per-driver-Bayesian-credible-interval + per-canonical-per-driver-asymptotic-normal + per-canonical-per-driver-Wald + per-canonical-per-driver-Wilson + per-canonical-per-driver-Agresti-Coull + per-canonical-per-driver-Clopper-Pearson + per-canonical-per-driver-Jeffreys + per-canonical-per-driver-Hodges-Lehmann + per-canonical-per-driver-Hettmansperger-McKean + per-canonical-per-driver-confidence-interval-confidence-tier.

What does per-driver cross-banner aggregation + per-vertical seasonality + Reg-G-non-GAAP compliance overlay do — and what are the SEC-Reg-G + Sarbanes-Oxley + FASB-ASC-606 + AICPA-non-GAAP + Simpson-paradox + multiple-comparisons anchors?

Per-portfolio per-banner per-period per-driver per-canonical-cross-banner-aggregation-spec runs per-portfolio per-canonical-per-driver-Simpson-paradox-detection + per-canonical-per-driver-Yule-Simpson-paradox + per-canonical-per-driver-aggregation-bias-detection + per-canonical-per-driver-base-rate-fallacy-detection + per-canonical-per-driver-collider-bias-detection + per-canonical-per-driver-Berkson-paradox + per-canonical-per-driver-confounding-variable-detection + per-canonical-per-driver-stratification + per-canonical-per-driver-marginalization + per-canonical-per-driver-multiple-comparisons-correction (per-Bonferroni + per-Holm-Bonferroni + per-Benjamini-Hochberg-FDR + per-Benjamini-Yekutieli + per-Tukey-HSD + per-Dunnett + per-Scheffe) + per-canonical-per-driver-Simpson-confidence-tier. Per-canonical-per-vertical-seasonality-spec runs per-portfolio per-canonical-per-vertical-retail (Black-Friday + Cyber-Monday + Christmas-Eve + Mother's-Day + Father's-Day + Valentine's-Day + Halloween) + per-canonical-per-vertical-restaurant (football-season + NCAA-March-Madness + Super-Bowl + St-Patrick's-Day + Cinco-de-Mayo + Mother's-Day-brunch + Memorial-Day + July-4 + Labor-Day + Thanksgiving + Christmas-Eve + New-Year's-Eve) + per-canonical-per-vertical-fitness (January-resolution + spring-summer-body-prep + post-Thanksgiving-pre-holiday) + per-canonical-per-vertical-medical (cold-flu-Q4 + allergy-spring + deductible-reset-January) + per-canonical-per-vertical-tax (Q1-Q2-rush + October-extension) + per-canonical-per-vertical-tourism (summer-peak + shoulder-spring-fall + winter-trough) + per-canonical-per-vertical-back-to-school (late-July + August + early-September) + per-canonical-per-vertical-cannabis (420 + Green-Wednesday + 7/10) + per-canonical-per-vertical-alcohol (Cinco-de-Mayo + St-Patrick's-Day + Memorial-Day + July-4 + Labor-Day + Halloween + Thanksgiving + New-Year's-Eve) + per-canonical-per-vertical-Federal-Reserve-rate-CRE-cycle + per-canonical-per-vertical-election-year-pause + per-canonical-per-vertical-supply-chain-disruption + per-canonical-per-vertical-labor-shortage + per-canonical-per-vertical-FX-EUR-GBP-CAD-AUD-JPY-CNY-MXN-INR. Per-canonical-Reg-G-non-GAAP-compliance-overlay runs per-portfolio per-canonical-per-driver-SEC-Regulation-G (the first operationally distinctive anchor — 17 CFR 244; non-GAAP financial measures including Adjusted EBITDA + same-store-sales + comp-sales + 4-wall EBITDA + unit economics + FCF + EBITDAR + ARR + cohort-LTV require reconciliation to most directly comparable GAAP measure + equal-or-greater-prominence + purpose-disclosure when public-co; SEC C&DI Question 100 + 101 + 102 enforcement) + per-canonical-per-driver-Sarbanes-Oxley-Section-302-404-906 (CEO + CFO certification of disclosure controls + ICFR + Section 906 criminal certification $1M + 10 years knowing + $5M + 20 years willful) + per-canonical-per-driver-SEC-Regulation-S-K-Item-303-MD&A + per-canonical-per-driver-FASB-ASC-606-revenue-recognition (5-step model — drivers analysis output must align with revenue recognition timing; multi-element-arrangement + variable-consideration + significant-financing-component) + per-canonical-per-driver-FASB-ASC-842-leases + per-canonical-per-driver-FASB-ASC-326-CECL + per-canonical-per-driver-AICPA-non-GAAP-financial-measures + per-canonical-per-driver-PCAOB-AS-2410 + per-canonical-per-driver-AICPA-SSAE-attestation + per-canonical-per-driver-forensic-accounting-fraud-detection + per-canonical-per-driver-FDD-Item-19-financial-performance-representations (when franchisor; FTC Franchise Rule 16 CFR 436; NASAA Commentary) + per-canonical-per-driver-15-state-franchise-registration + per-canonical-per-driver-7-state-franchise-disclosure + per-canonical-per-driver-multiple-comparisons-correction (when reporting many drivers; family-wise error rate; FDR control; replication crisis context) + per-canonical-per-driver-pre-registration-AsPredicted-OSF + per-canonical-per-driver-CCPA-CPRA + per-canonical-per-driver-CCPA-right-to-opt-out-of-automated-decisionmaking + per-canonical-per-driver-GDPR-Article-22 + per-canonical-per-driver-EU-AI-Act-Article-50-AI-disclosure + per-canonical-per-driver-Connecticut-CTDPA + per-canonical-per-driver-Texas-DPSA + per-canonical-per-driver-Virginia-CDPA + per-canonical-per-driver-Colorado-CPA + per-canonical-per-driver-Utah-CPA + per-canonical-per-driver-NIST-AI-RMF + per-canonical-per-driver-ISO-42001 + per-canonical-per-driver-ISO-27001 + per-canonical-per-driver-SOC-2-Type-II + per-canonical-per-driver-OPA-Cedar-Casbin-Cerbos-Oso-policy-as-code + per-canonical-per-driver-compliance-confidence-tier.

What does per-driver cross-skill-handoff + per-driver audit-trail + per-canonical-end-to-end-replay do?

Per-portfolio per-driver per-canonical-per-driver-cross-skill-handoff runs per-portfolio per-canonical-per-driver-handoff-to-revenue-drivers-analysis (parent commercial pillar) + per-canonical-per-driver-handoff-to-per-location-rollup-reporting (parent agent) + per-canonical-per-driver-handoff-to-monthly-executive-summary-drafting-build-pillar (sibling shipped #351 — drivers feed monthly executive variance commentary) + per-canonical-per-driver-handoff-to-quarterly-board-deck-generation + per-canonical-per-driver-handoff-to-pe-sponsor-lp-letter-drafting-build-pillar (sibling #317) + per-canonical-per-driver-handoff-to-cohort-framed-benchmark-reports-build-pillar + per-canonical-per-driver-handoff-to-cohort-framed-per-location-kpi-rollup-build-pillar + per-canonical-per-driver-handoff-to-per-franchisee-accountability-views-build-pillar + per-canonical-per-driver-handoff-to-architect-real-time-multi-location-agent-scorecards-build-pillar + per-canonical-per-driver-handoff-to-per-location-benchmarking-skill + per-canonical-per-driver-handoff-to-anomaly-detection + per-canonical-per-driver-handoff-to-false-positive-suppression-build-pillar + per-canonical-per-driver-handoff-to-cross-stream-correlation-build-pillar + per-canonical-per-driver-handoff-to-multi-stream-severity-routing-build-pillar + per-canonical-per-driver-handoff-to-per-location-per-cohort-two-sigma-anomaly-detection-build-pillar + per-canonical-per-driver-handoff-to-root-cause-attribution-sketch-build-pillar + per-canonical-per-driver-handoff-to-per-location-mmm-driven-budget-recommendation-engine-build-pillar + per-canonical-per-driver-handoff-to-per-location-mmm-for-multi-store-marketing-budget-allocation-build-pillar + per-canonical-per-driver-handoff-to-per-location-multi-model-attribution-build-pillar + per-canonical-per-driver-handoff-to-per-location-cross-channel-attribution-rollup-build-pillar + per-canonical-per-driver-handoff-to-multi-source-attribution-preserving-lead-ingestion-build-pillar + per-canonical-per-driver-handoff-to-foot-traffic-integration-build-pillar + per-canonical-per-driver-handoff-to-multi-vendor-call-tracking-integration-build-pillar + per-canonical-per-driver-handoff-to-multi-vendor-receipt-joining-build-pillar + per-canonical-per-driver-handoff-to-master-record-build-pillar + per-canonical-per-driver-handoff-to-versioned-history-regulatory-defense-build-pillar + per-canonical-per-driver-handoff-to-per-jurisdiction-compliance-multi-state-franchise-build-pillar + per-canonical-per-driver-handoff-to-per-vertical-compliance-overlay-build-pillar. Per-canonical-end-to-end-SLA runs per-canonical-per-driver-class-pointer-resolve-to-causal-decomposition-to-Shapley-attribution-to-Granger-causality-to-counter-factual-to-confidence-interval-to-cross-banner-aggregation-to-per-vertical-seasonality-to-Reg-G-non-GAAP-compliance-overlay-to-SEC-Reg-G-Sarbanes-Oxley-FASB-ASC-606-AICPA-non-GAAP-Simpson-paradox-multiple-comparisons-anchors-to-FBC-feedback-loop-SLA. Per-portfolio per-driver per-canonical-audit-trail runs per-portfolio per-canonical-per-driver-canonical-audit-record (per-driver-ID + per-banner-pointer + per-period-pointer + per-canonical-driver-class-snapshot + per-causal-decomposition-snapshot + per-Shapley-Aumann-Banzhaf-Owen-snapshot + per-Granger-VAR-Toda-Yamamoto-Diks-Panchenko-snapshot + per-counter-factual-CATE-T-S-X-DR-CausalML-DoubleML-EconML-Causal-Forest-BART-snapshot + per-instrumental-variable-2SLS-GMM-Anderson-Hsiao-snapshot + per-DiD-event-study-Callaway-SantAnna-de-Chaisemartin-DHaultfoeuille-Goodman-Bacon-snapshot + per-synthetic-control-snapshot + per-regression-discontinuity-snapshot + per-propensity-score-matching-snapshot + per-IPW-snapshot + per-Shapley-attribution-snapshot + per-SHAP-LIME-anchor-counterfactual-Integrated-Gradients-DeepLIFT-snapshot + per-Granger-causality-snapshot + per-lag-order-AIC-BIC-HQC-FPE-snapshot + per-stationarity-ADF-KPSS-PP-DF-GLS-snapshot + per-cointegration-Engle-Granger-Johansen-Phillips-Ouliaris-snapshot + per-impulse-response-function-snapshot + per-variance-decomposition-snapshot + per-counter-factual-do-calculus-Pearl-Rubin-causal-model-potential-outcomes-snapshot + per-ATE-ATT-ATC-CATE-snapshot + per-confidence-interval-snapshot + per-bootstrap-percentile-BCa-Studentized-snapshot + per-Bayesian-credible-snapshot + per-Wald-Wilson-Agresti-Coull-Clopper-Pearson-Jeffreys-Hodges-Lehmann-Hettmansperger-McKean-snapshot + per-cross-banner-aggregation-snapshot + per-Simpson-paradox-Yule-Simpson-aggregation-bias-base-rate-fallacy-collider-bias-Berkson-paradox-confounding-snapshot + per-multiple-comparisons-Bonferroni-Holm-Benjamini-Hochberg-Benjamini-Yekutieli-Tukey-HSD-Dunnett-Scheffe-snapshot + per-per-vertical-seasonality-snapshot + per-retail-restaurant-fitness-medical-tax-tourism-back-to-school-cannabis-alcohol-Federal-Reserve-rate-election-year-supply-chain-labor-FX-snapshot + per-compliance-overlay-snapshot + per-SEC-Reg-G-non-GAAP-snapshot + per-Sarbanes-Oxley-302-404-906-snapshot + per-SEC-Reg-S-K-Item-303-MD&A-snapshot + per-FASB-ASC-606-revenue-recognition-snapshot + per-FASB-ASC-842-leases-snapshot + per-FASB-ASC-326-CECL-snapshot + per-AICPA-non-GAAP-snapshot + per-PCAOB-AS-2410-snapshot + per-AICPA-SSAE-snapshot + per-forensic-accounting-snapshot + per-FDD-Item-19-snapshot + per-FTC-Franchise-Rule-16-CFR-436-snapshot + per-15-state-franchise-registration-snapshot + per-7-state-franchise-disclosure-snapshot + per-pre-registration-AsPredicted-OSF-snapshot + per-CCPA-CPRA-snapshot + per-CCPA-right-to-opt-out-snapshot + per-GDPR-Article-22-snapshot + per-EU-AI-Act-Article-50-snapshot + per-Connecticut-CTDPA-Texas-DPSA-Virginia-CDPA-Colorado-CPA-Utah-CPA-snapshot + per-NIST-AI-RMF-snapshot + per-ISO-42001-ISO-27001-SOC-2-Type-II-snapshot + per-OPA-Cedar-Casbin-Cerbos-Oso-policy-snapshot + per-compliance-confidence-tier-snapshot + per-canonical-audit-record) + per-canonical-immutable-WORM-storage + per-canonical-7-year-IRS-tax-retention + per-canonical-7-year-FTC-substantiation-retention + per-canonical-6-year-SEC-record-retention + per-canonical-7-year-Sarbanes-Oxley-Section-802-retention + per-canonical-5-year-PCAOB-record-retention + per-canonical-3-year-FDD-Item-19-record-retention + per-canonical-7-year-state-franchise-registration-record-retention. Per-canonical-end-to-end-replay runs per-portfolio per-canonical-per-driver-causal-decomposition-rewind + per-canonical-per-driver-Shapley-attribution-rewind + per-canonical-per-driver-Granger-causality-rewind + per-canonical-per-driver-counter-factual-rewind + per-canonical-per-driver-confidence-interval-rewind + per-canonical-per-driver-cross-banner-aggregation-rewind + per-canonical-per-driver-per-vertical-seasonality-rewind + per-canonical-per-driver-Reg-G-non-GAAP-compliance-overlay-rewind + per-canonical-per-driver-SEC-Reg-G-Sarbanes-Oxley-FASB-ASC-606-AICPA-non-GAAP-Simpson-paradox-multiple-comparisons-anchors-rewind + per-canonical-per-driver-replay-confidence-tier + per-canonical-per-driver-replay-explainability.

What is the recurring 30-driver per-vertical-overlay pattern?

Every per-driver inherits the same canonical-driver-class-pointer + canonical-causal-decomposition-spec + canonical-Shapley-attribution-spec + canonical-Granger-causality-spec + canonical-counter-factual-spec + canonical-confidence-interval-spec + canonical-cross-banner-aggregation-spec primitives, but each vertical overlays a vertical-specific per-canonical-per-vertical-seasonality-spec (retail Black-Friday + restaurant football-season + fitness January-resolution + medical cold-flu-Q4 + tax Q1-Q2 + tourism summer-peak + back-to-school late-July + cannabis 420 + alcohol Cinco-de-Mayo/St-Patrick's/Memorial/July-4/Labor + CRE Federal-Reserve-rate + election-year + supply-chain + labor-shortage + FX EUR/GBP/CAD/AUD/JPY/CNY/MXN/INR). Same canonical pattern across all verticals; only the per-vertical seasonality overlay differs. The Reg-G non-GAAP compliance overlay applies uniformly when public-co or when the franchisor reports FDD Item 19.

Engage the rollup-reporting agent

Per-portfolio per-banner per-period per-driver per-canonical-driver-class-pointer + per-canonical-causal-decomposition-spec + per-canonical-Shapley-attribution-spec + per-canonical-Granger-causality-spec + per-canonical-counter-factual-spec + per-canonical-confidence-interval-spec + per-canonical-cross-banner-aggregation-spec + per-canonical-per-vertical-seasonality-spec + per-canonical-Reg-G-non-GAAP-compliance-overlay + per-canonical-audit-trail + per-portfolio-audit-trail shipped as the orchestration layer above your existing per-FP&A-driver-vendor + per-causal-inference-vendor + per-BI-vendor + per-financial-reporting-compliance-vendor primitive.

Book a scope call Browse the 32-agent catalog