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MsShawnP/README.md

Hey, I'm Shawn.

I work where three things overlap: data hygiene, process hygiene, and business intelligence.

Most people treat those as separate problems. They aren't. A dashboard is only as honest as the records feeding it, and those records are only as clean as the process that produced them. Clean the data and skip the process, and you'll clean it again next quarter.

I'm the Principal Consultant at Lailara LLC — data hygiene and analytics for specialty food and CPG brands scaling into national retail. I find the money leaking through product data, deductions, and trade spend, and tell you exactly which field it's leaking from.

I'm not a software engineer by training. Twenty-five years of operations and incentive-fulfillment work taught me to build the tool when the thing I need doesn't exist — and to publish it so other people can use it too.

The tools below find the money: ~$380K/yr in recoverable deduction waste, $894K in three-year short-ship costs, a $1.35M deduction backlog, and a $6.7M gross-to-net gap — all traced to the field, form, or process that leaks it. 41 public tools, 32 live in your browser right now, two on PyPI. No login, no demo request, no gate.

Everything below is grouped by which of the three problems it solves.

On the numbers below: every figure comes from a modeled dataset built to realistic CPG data shapes, not from client data. The failure modes are real — they are what I spent twenty-five years handling in incentive fulfillment and operational data.


1 · Data hygiene

Is the data right? Audits, profilers, and validators that tell you what's actually in the file.

ToolWhat it doesLive / install
data-hygiene-auditorA linter for your data — mixed formats, misused fields, placeholder floods, phantom duplicates. HTML, Excel, and PDF reports.pip install data-hygiene-auditor · PyPI
datascopeProfiles every column in a spreadsheet and explains the data-quality problems in plain English. Catches mixed-type columns pandas silently coerces.pip install datascope-dq · PyPI
GTIN ValidatorProduct data checked against GS1 standards with retailer-specific context. Branded PDF with a fix roadmap.gtin.lailarallc.com
Product Data Health AuditFive artifacts from one R + Quarto pipeline: HTML report, executive tearsheet, dashboard, workbook, Shiny calculator.audit.lailarallc.com
Data Differences ToolCompare two tabular files: rows added, removed, modified, with before/after values.diff.lailarallc.com
Dimension & Weight IntegrityCatches the dim-weight defects behind freight chargebacks and compliance fines.dimensions.lailarallc.com
Data Standards Cheat SheetOne-page reference on GTIN, GDSN, item-setup, and freight-class rules. Downloadable PDF.
Internal Data AnonymizerColumn-by-column anonymization with deterministic mappings, format-preserving fakes, and reverse lookup.

2 · Process hygiene

Will it still be right next quarter? Catch it before it ships, reconcile what actually happened, and hold the standard so the same defect doesn't come back.

ToolWhat it doesLive / install
EDI PreflightParses 850s and validates 856s against Walmart, Amazon, UNFI, KeHE, and Costco specs.edi.lailarallc.com
Item Setup Form PreflightTyped validation against codified retailer schemas. Catches new-item rejections before you submit.preflight.lailarallc.com
EDI Reconciliation ToolContent-level reconciliation across the full PO lifecycle. Every mismatch, dollar-ranked.reconcile.lailarallc.com
OTIF Blind SpotReconciles internal fulfillment metrics against retailer scorecards and quantifies the gap.otif.lailarallc.com
Retail Readiness Scorecard12–18 adaptive questions across eight dimensions. Downloadable PDF verdict on launch readiness.lailarallc.com/scorecard
Recall Blast RadiusLot-genealogy tracer that answers "how big is our recall?" in seconds.recall.lailarallc.com
Product Master Data ModelThe data model a product master should have — documented, contracted, running on Postgres + dbt.master.lailarallc.com
Cinderhaven Data PlatformThe platform underneath it all — source-to-mart pipelines, quality testing, orchestration, lineage. Python · Postgres · dbt · Dagster.

3 · Business intelligence

What should we do about it? Once the data is right and stays right, these are the questions worth asking of it.

Where the money leaks

Deductions, trade spend, and the gap between invoiced and collected.

ToolWhat it doesLive / install
Retailer Deduction Recovery16,917 deductions traced through five compounding failures. ~42% win rate per disputed dollar — but two-thirds are never filed.deductions.lailarallc.com
Chargeback Prediction ModelPredicts which retailer deductions escalate and which are recoverable. Python + scikit-learn.chargeback.lailarallc.com
Trade Spend LeakageForensic detection of double-funded promos, phantom promos, and rate discrepancies. Reranks retailers by net revenue.trade-spend.lailarallc.com
Contract to CashTraces where money leaks between invoice and cash receipt. For every dollar invoiced, 87 cents arrived.cash.lailarallc.com
Channel Profitability AnalysisFive-layer cost waterfall. Contribution margin across 10 retail, distributor, and DTC channels.channels.lailarallc.com
Where the Money Comes FromWhich channel actually pays after all deductions — and is the capital allocation wrong? React + D3.capital.lailarallc.com
Remittance Stub ParsingParses Walmart, Costco, UNFI, and KeHE remittance PDFs into a reconciled deduction ledger, flagging what to dispute before the window closes.remittance.lailarallc.com
Trade Spend Data Diagnostic7-tab workbook: executive pulse, leak diagnostic, promo ROI, retailer risk, deduction ledger.

Sales penetration

Five ways to answer the same question: is growth real, or are we buying it?

ToolWhat it doesLive / install
SpinRateSeparates distribution gains from velocity gains. SPPD, ACV%, door counts.spinrate.lailarallc.com
Void FinderAuthorized but not scanning. Every void dollarized from comparable-store median velocity and ranked into a broker work list.voidfinder.lailarallc.com
DoorMathDoor counts, ACV%, TDP trends, and authorization gap analysis.doormath.lailarallc.com
DecomposeSplits period-over-period sales change into households × frequency × spend per trip, reconciled to the exact delta with a Shapley allocation.decompose.lailarallc.com
Trial vs. RepeatHow many triers came back — and whether penetration growth is adoption or expensive sampling.leakybucket.lailarallc.com

Decision tools

The calls that cost real money when made by reflex instead of analysis.

ToolWhat it doesLive / install
The Ten DecisionsThe framework: ten operating decisions that cost a growing brand $1.4M–$2.3M a year.lailarallc.com/the-ten-decisions
The Question EngineThe questions every specialty-food CEO asks, each answered in 30 seconds with a verdict, one chart, three numbers.ask.lailarallc.com
Retail Velocity Decision ToolEight decisions — shelf defense, production planning, promo ROI, expansion, pricing power — on a 1.2M-row dataset.velocity.lailarallc.com
The Cost of Saying YesFirst-year economics of a major retailer launch. Cash trough, break-even month, CFO-grade export.launch-cost.lailarallc.com
Short Ship CostFour cost dimensions of short-shipping, with buffer simulation and exportable PDF.shortships.lailarallc.com
Retailer Scorecard Renegotiation SimulatorCost-to-serve model you can renegotiate against. React + Python.retailer-scorecard.lailarallc.com
SKU Rationalization FrameworkFive scoring dimensions, four action buckets, interactive portfolio view.sku.lailarallc.com
Production Demand ForecastS&OP planning: demand signals, capacity constraints, seasonal patterns.forecast.lailarallc.com
Competitive Shelf IntelligencePricing, placement, and assortment tracked across retailers.competitive.lailarallc.com
Monday Morning ReportThree critical Monday numbers, tiered by growth stage. Python + openpyxl.

How I build

RepoWhat it does
claude-solo-dev-workflowTemplates, slash commands, and reference material for running portfolio projects solo.
claude-solo-dev-project-improvement-workflowPhase-gated improvement workflow — audit, plan, code review, dependency audit, README refresh.

Every tool above targets a failure mode I have spent twenty-five years dealing with in incentive fulfillment and operational data. If one of them describes your week, that's usually a good sign we should talk.

lailarallc.com · Selected work · LinkedIn · shawn@lailarallc.com

Pinned Loading

  1. data-hygiene-auditordata-hygiene-auditorPublic

    Audits messy Excel workbooks for the data-quality issues that show up in real consulting engagements: mixed formats, misused fields, placeholder floods, and phantom duplicates. Generates HTML, Exce…

    Python

  2. gtin-validatorgtin-validatorPublic

    Product data validation tool for specialty food brands preparing for national retail

    Python 1 1

  3. retailer-deduction-recoveryretailer-deduction-recoveryPublic

    Interactive decision tool that makes retailer deduction losses visible and actionable. Traces deductions through five compounding failures and shows what's recoverable, what's preventable, and what…

    TypeScript

  4. edi-preflightedi-preflightPublic

    Free web tool for specialty food brands doing EDI by hand. Parses 850 Purchase Orders and validates 856 Advance Ship Notices against retailer-specific specs. Supports Walmart, Amazon, UNFI, KeHE, a…

    Python

  5. otif-blind-spototif-blind-spotPublic

    OTIF blind spot diagnostic — reconciles internal fulfillment metrics against retailer scorecards and quantifies the gap. Python + Dash.

    TypeScript

  6. the-ten-decisionsthe-ten-decisionsPublic

    The Ten Decisions framework — ten operating decisions that cost a growing specialty food brand $1.4M–$2.3M/year when made by reflex instead of analysis.

    SCSS