Spend Analytics Cookbook: Build Your Own Spend Cube with Claude Code
A recipe collection for turning scattered ERP exports into a spend cube you trust. Classify spend, detect leakage, benchmark against markets and automate monthly reporting, one hands-on recipe at a time, with no coding background required.
11 chapters, 11 lessons
14-day refund on the yearly plan. Real pricing on the plans page, no surprises.
11
lessons, yours to run
Easy to pick up, built to get you the next job
No coding background needed, and you write code with Claude as you go.
Every section below turns into something a hiring manager recognises, not just notes.
Consolidate Spend Data from Every Source You Actually Have
- Pull PO lines from Oracle EBS, Oracle Fusion, SAP, and shadow P-card spreadsheets into a single reconciled spend mart, using plain-English prompts to Claude Code rather than hand-written scripts.
- Map mismatched column names across systems automatically, including German SAP field names like Menge and Nettowert, so your unified file is consistent from day one.
- Validate row counts and total spend against each source system so Finance cannot reject your numbers.
- This is the foundational skill hiring managers list when they post senior category analyst and spend analytics roles.
Classify, Enrich, and Profile Spend Like a Data-Savvy Category Manager
- Join raw PO data to a supplier master and business-unit hierarchy to add parent companies, regions, and organisational roll-ups that turn a flat file into a proper spend cube.
- Generate a data-quality profile that shows completeness by column, spend by source, and top suppliers before any stakeholder sees a number.
- No prior coding experience needed: every step is a prompt you type, and Claude Code writes and runs the script for you.
Detect Leakage and Spot the Spend That Should Not Be There
- Identify tail spend, off-contract purchasing, and duplicate supplier records hidden inside the consolidated mart.
- Flag policy violations and category leakage using structured prompts, producing findings a CPO or category director can act on immediately.
- These are exactly the outputs a hiring manager expects from a candidate who lists spend analytics on their CV.
Automate Monthly Reporting So It Runs in Hours, Not Weeks
- Build a Claude Code skills file that stores your column mappings, validation rules, and enrichment logic so next month's consolidation runs from a single instruction.
- Produce a repeatable, auditable workflow you can hand to a colleague or demonstrate in an interview as a live working artefact.
- Walk away with a portfolio of real procurement outputs, not slides about theory.
Finish this course and you can do all of this, no prior background required:
- You will be able to consolidate PO data from Oracle EBS, Oracle Fusion, SAP, and P-card spreadsheets into a single reconciled spend mart, the core deliverable every spend analytics role requires.
- You will be able to auto-map mismatched column schemas across source systems using Claude Code prompts, eliminating the manual ETL work that used to take a data-engineering team weeks.
- You will be able to validate spend totals and row counts against source systems so your numbers survive Finance scrutiny, a non-negotiable in any category management or procurement operations role.
- You will be able to enrich raw PO data with supplier master attributes and organisational hierarchies, producing the roll-up views category directors and CPOs use for sourcing decisions.
- You will be able to detect tail spend, off-contract leakage, and duplicate supplier records inside a consolidated spend cube, a skill that directly supports supplier rationalisation and savings delive
- You will be able to build a Claude Code skills file that re-runs the entire consolidation and reporting workflow monthly from a single instruction, cutting reporting cycle time from weeks to hours and
11 lessons, 11 chapters
Built from real implementation work
Every agent, skill file, and dataset is drawn from 25+ years and 50+ Oracle ERP implementations across pharma, manufacturing, semiconductor, and distribution.
Kept current with the stack
Claude Code, skills, and MCP move fast. Your licence includes every system update for as long as you're subscribed, so what you build keeps working as the tools change.
This spend analytics cookbook starts where the data is messy. Your spend sits in at least three systems (Oracle EBS, SAP, Fusion) plus a handful of buyer spreadsheets, and the Finance roll-up arrives weeks late with columns that never match. You know what your category managers need: supplier rationalisation, contract compliance and tail-spend exposure. Without one trusted spend view, every meeting stalls on arguments about the numbers. The recipes focus on the data work underneath: consolidating exports, classifying spend, finding leakage and replacing the monthly copy-paste report with an automated one.
What you'll be able to do, module by module
Every module leaves you able to build and run something real. Here is the syllabus, in the order you work through it.
Curriculum
11 chapters · 11 lessons
Spend Analytics Cookbook Using Claude Code
Consolidate PO lines from Oracle EBS, Oracle Fusion, SAP, and shadow spreadsheets into a single reconciled spend mart, classify and enrich spend with supplier and business-unit master data, detect leakage, and save a reusable skills file that automates the entire monthly workflow from a single Claud
Data Files1 item
- Data Files for All the Chapters🔒
Consolidate Spend Data from Multiple ERPs1 item
- Use Claude Code to Consolidate Spend Data from Multiple ERPs into a Single Trusted Spend Mart🔒
Dedupe and Normalize Supplier Names1 item
- Use Claude Code to Dedupe and Normalize Supplier Names Using Semantic Intelligence🔒
Auto-Classify PO Lines into UNSPSC Taxonomy1 item
- Use Claude Code to Auto-Classify Thousands of PO Lines into UNSPSC Taxonomy at Scale🔒
Near-Real-Time Spend Dashboard1 item
- Use Claude Code to Build a Near-Real-Time Spend Dashboard Without a BI Team🔒
Identify Tail Spend Consolidation Opportunities1 item
- Use Claude Code to Identify Tail Spend Consolidation Opportunities and Quantify the Savings🔒
Detect Maverick and Off-Contract Spend1 item
- Use Claude Code to Detect Maverick and Off-Contract Spend Before it Becomes a Bigger Problem🔒
Automate Monthly Spend Cube Generation1 item
- Use Claude Code to Automate Monthly Spend Cube Generation from 3 Days to 10 Minutes🔒
Normalize Multi-Currency Spend for Global Reporting1 item
- Use Claude Code to Normalize Multi-Currency Spend for Accurate Global Reporting🔒
Benchmark Spend Against Market Commodity Indices1 item
- Use Claude Code to Benchmark Your Category Spend Against Live Market Commodity Indices🔒
Enable Drill-Down from Spend Anomaly to Root Cause1 item
- Use Claude Code to Drill Down from Any Spend Anomaly to its Root Cause in Minutes🔒
Spend analytics job postings ask for hands-on experience with automation and data consolidation. After this course you can point Claude Code at four ERP exports and produce a reconciled, enriched spend mart with a reusable automation workflow attached. That's something you can show in an interview, alongside your procurement knowledge.
From subscribing to running your first artifact
Subscribe and get instant access
Create your account and you are in. The course materials, demonstration datasets, and a free preview lesson are available immediately. No waiting for a cohort start date.
Open the course and follow the recipe
Every lesson is a hands-on recipe with a clear pain point, a set of plain-English Claude Code prompts you can copy, and a defined output. You do not need to know Python or any scripting language. You type a prompt, Claude Code writes and runs the script, and you review the result.
Run your first spend consolidation and keep the artefact
By the end of the opening lesson you have loaded PO lines from four source systems, reconciled them to source totals, enriched them with a supplier master, and saved a unified spend mart you can open in Excel or use in every subsequent lesson. That file is yours to keep and show in your next interview.
Building a Spend Mart from Three ERPs and a Buyer Spreadsheet
Survey the source files
You open Claude Code and ask it to read your four source exports: 300 rows from Oracle EBS, 200 from Oracle Fusion, 150 from SAP, and 50 rows of P-card shadow spend. Claude returns a side-by-side comparison of column names, row counts, and data types, showing immediately that SAP uses German field names (Menge for quantity, Nettowert for line amount) while EBS uses AMOUNT and VENDOR_NAME.
Map fields to a common schema
You prompt Claude to propose a unified target schema with 13 standard columns: source_system, po_number, po_line, supplier_id, supplier_name, category, line_amount, and so on. Claude produces a Python mapping dictionary. You spot that it has mapped Menge to line_amount instead of quantity and correct it in one follow-up prompt. Claude saves the corrected mapping as column_mapping.py.
Create and reconcile the unified spend mart
Claude writes and runs a script that applies the mapping, tags each row with its source system, coerces dates and amounts to the right types, concatenates all four files, and saves unified_spend_mart.csv. You then ask for a reconciliation table: row count and total spend per source versus the mart. The mart shows 695 rows instead of 700. Claude identifies five SAP rows that were dropped because of a formatting mismatch in the po_number field and fixes it.
Enrich with supplier master and business-unit hierarchy
You ask Claude to left-join the mart to suppliers.csv on supplier_id, adding parent company, country, and DUNS number, then join to business_units.csv to add region and division. Claude reports that 12 rows had no supplier match due to leading zeros in the SAP supplier ID. One further prompt strips the zeros from both files and the match rate improves. The enriched mart now has 15 columns and is ready for category analysis.
Save the workflow as a skills file for next month
You ask Claude to create .claude/skills.md with a section titled Spend Consolidation Workflow, capturing the source file paths, column mapping, enrichment joins, and reconciliation rules. Next month you open Claude Code and type Run the spend consolidation workflow. Claude reads the skills file and executes every step without further explanation, cutting what used to be a two-week manual process to under an hour.
The toolkit you'll build and run in this program
You leave with working assets, not notes.
Real things you can demo in an interview.
A working unified_spend_mart.csv built from four real source files and fully reconciled to source totals, ready to use as a portfolio demonstration.
A Python column-mapping file (column_mapping.py) that translates Oracle, SAP, and shadow-spreadsheet schemas to a single standard model.
A data-quality profile report showing completeness by column, spend by source system, top suppliers, and date-range coverage.
A Claude Code skills file (.claude/skills.md) encoding the full consolidation workflow so any colleague can re-run it next month with fresh extracts.
A hands-on recipe collection of structured Claude Code prompts covering consolidation, enrichment, validation, leakage detection, and reporting that you can adapt to your own organisation's data.
You'll get the most from this if
Category managers and senior buyers who are tired of waiting weeks for a spend report they don't fully trust.
Procurement analysts who want to move from manual Excel consolidation to automated, repeatable spend data workflows.
Supply-chain professionals building their analytics credentials for spend intelligence, procurement operations or category leadership roles.
Students and early-career buyers who want a concrete skill set they can demonstrate in interviews.
Yearly plan: 14-day keep-the-system guarantee
14-day refund on the yearly plan. Finish the first two modules, and if you haven't run your first live pipeline, take a full refund.
Straight answers before you subscribe
How is this spend analytics cookbook different from a spend analysis course?
It's a set of hands-on recipes for the data work. You consolidate ERP exports into one spend mart, classify spend, detect leakage, benchmark against markets and automate monthly reporting. Each recipe produces an output you keep and reuse.
Do I need to know how to code or use a terminal?
No. Every step is driven by plain-English prompts you type into Claude Code. Claude writes and runs the scripts for you. The course is designed from lesson one for procurement professionals with no coding or technical background, and the recipe format means you produce real outputs from the first session.
Will this work with my organisation's data as well as the demonstration datasets?
Yes. The skills file you build stores your column mappings, source file paths and validation rules. Once you've completed the consolidation recipe with the provided datasets, you adapt the prompts to point at your own ERP exports. The workflow is system-agnostic: if your data is in a CSV or spreadsheet, Claude Code can work with it.
What if I get stuck or my output looks different from the examples?
The course materials say up front that your output will vary with your data files, and that you should focus on understanding the implementation rather than matching the example output exactly. Daily live sessions and mentor review are part of the course, so you can bring a specific problem and get it resolved.
What is the refund policy, and can I use what I build commercially?
Refunds depend on the plan. The yearly plan has a 14-day full refund. In India every plan is a one-time pass that isn't refunded, but it never renews without you, and you can try a free lesson before you buy. The refunds page has the full policy. The artefacts you build, including your spend mart, skills file and column-mapping scripts, are yours to use in your day job. The licence terms shown on enrolment have the full detail on commercial use.
How does the course stay up to date as Claude Code changes?
The curriculum is updated as the tools change. As a subscriber you get updated lessons and materials without paying again. The recipe steps are refreshed to match how Claude Code currently behaves, so you aren't following outdated instructions.