A resource library for supply chain analytics teams.

Tools, references, and frameworks built by practitioners. Free to use. Shaped by real enterprise consulting engagements.

Explore the librarySee the reference builds

For supply chain leaders in MedTech, consumer goods, footwear, and manufacturing: how the practice works

Explore by business problem

Metric definitions, dashboard patterns, and working reference builds, organized by the question they answer.

Inventory & Working Capital

What you're holding, why it's there, and what it costs to hold it.

Reference build

Inventory Health & Working Capital

On-hand units · 365 days

Everything for this domain

Demand Planning & Forecasting

How wrong the forecast is, in which direction, and where the error is worth fixing.

Reference build

Demand Forecast Accuracy

Forecast vs. actual units · 28 months

Also a reference build: S&OP / Demand Review

Everything for this domain

Customer Service & Fulfillment

Whether the order arrived complete, on the date you committed to.

Reference build

Service & Delivery Performance

OTIF by month vs. internal goal

Also a reference build: Lead Time & Reliability

Everything for this domain

Procurement & Supply

What's on order, when it lands, and how the supplier actually performs.

Reference build

Supplier Scorecard

Supplier OTD by month vs. internal goal

Everything for this domain

Manufacturing & Production

Whether the plant built what the plan said it would build.

Reference build

Production Schedule Performance

Mix vs. volume attainment · 52 weeks

Everything for this domain

Data Foundation & Governance

Landing ERP data in a lakehouse without losing deletes, history, or control of who reads it.

Everything for this domain

Simulated data, frozen snapshot — not a live client system.

All 8 reference builds

Start from the system you run

The same library, entered by source system — each reference documents the tables, the quirks an analyst will hit, and the extraction path into Databricks. All of it free and ungated.

SAP

Flagship

158 tables · 92 t-codes · 11 modules

The supply-chain core: tables, t-codes, relationships, and S/4HANA status on every table.

SAP EWM

68 tables · 25 t-codes · 9 modules

Warehouse structure, tasks, handling units, and the yard — embedded and decentralized EWM.

JD Edwards

94 tables · 92 programs · 18 modules

EnterpriseOne from orders to manufacturing — Julian dates and implied decimals already decoded.

Dynamics 365 F&O

62 tables · 26 data entities · 10 modules

Tables and data entities for Finance & Supply Chain Management, with the Synapse / Fabric Link path.

Infor M3

33 tables · 36 programs · 9 modules

Items to finance in CloudSuite M3 — column prefixes, CONO scoping, and numeric dates decoded.

Oracle EBS

104 tables · 12 modules

R12 from items to financials — the two org columns, flexfields, and translation tables untangled.

Oracle Fusion

85 tables · 11 modules

The tables behind Fusion Cloud SCM, mapped to the BICC extract surfaces that reach them.

NetSuite

70 tables · 11 modules

The NetSuite2.com analytics schema: the transaction spine and the record map for every document.

Browse the full library

Straight out of the library.

One real entry from each reference, pulled live from the same data that powers the library. Every entry carries field-level detail, relationships, and copy-ready Databricks SQL with each system’s quirks already handled.

From the F4211 entry: the Julian decode, ready to paste into Databricks.

3 parameters not filled: <catalog>, <schema_data>, <KCOO>

-- F4211 sales order lines, quirks handled
SELECT
  d.SDDOCO AS order_number,
  d.SDLITM AS item_number,
  CASE WHEN d.SDTRDJ IS NULL OR d.SDTRDJ = 0 THEN NULL
       ELSE DATE_ADD(MAKE_DATE(1900 + CAST(d.SDTRDJ AS INT) DIV 1000, 1, 1),
                     CAST(d.SDTRDJ AS INT) % 1000 - 1)
  END AS order_date,  -- CYYDDD Julian → DATE
  d.SDUORG AS qty_ordered,
  d.SDUPRC / POWER(10, 4) AS unit_price,  -- 4 implied decimals
  d.SDAEXP / POWER(10, 2) AS extended_price
FROM <catalog>.<schema_data>.f4211 d
WHERE d.SDKCOO = '<KCOO>'

Shaped by real work.

Analytics investments stick when the people building them understand the supply chain, not just the tools.

Nothing here started as content. Every reference in the library came out of enterprise consulting engagements — supply chains where exactly that gap was the problem, until someone got hands-on with both the business and the data.

The practice builds on Databricks and stays engaged through implementation, which is why the references read like working notes rather than vendor collateral. Consulting availability is selective; the library is how the work becomes public.

See the services
Industries
MedTech, consumer goods, footwear, manufacturing
Platform
Databricks — Unity Catalog, Delta Lake, AI/BI dashboards
Method
Medallion architecture into Kimball-style dimensional gold

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