Arun Raghubir A look at how Arun works — built and written with the AI he uses every day.
He rebuilt procurement into a financial and operational control engine — and shipped the AI tools that run it.
Twenty years across both sides of global supply chains — customer and supplier — through DHL, Kuehne+Nagel, and now as VP of Global Procurement and executive leadership team member at a PE-backed healthcare logistics company.
The foundation is operational, not theoretical: strategic sourcing and category management, 3PL/4PL partner governance, network and operating-model design, GDP cold-chain stand-ups, and large-scale operating-model transformation. The AI work sits on top of that — two decades of knowing how the work actually runs.
The pages below are the actual work — the systems, the numbers, and a tool you can open and use.
A working capital problem — solved without breaking service.
- $5M+ inventory reduction in partnership with Operations and Finance; days of inventory on hand improved from 98 to 94 while service levels held. Realized
- 36% reduction in weekly purchasing spend through a weekly PO governance review that aligns every order with real demand. Realized
- ~500 pallet positions freed across VMI, climate-control optimization, and inventory programs — avoiding warehouse expansion entirely. Implemented
- Material continuity protected through major customer ramp-ups, with no significant shortages during growth.
Systems that outlast their builder — that's his test.
- A five-stage savings governance framework — every claim graded Identified, Projected, Implemented, Realized, or Finance-Validated before it reaches executive reporting. Inflated numbers don't survive it.
- Vendor-managed inventory programs eliminating 328 pallet positions, including a 280-position reduction for a major diagnostics customer. Projected
- The Coupa business case and implementation roadmap — from supplier master cleanup to approval-delegation design, executive-aligned.
- The company's first sustainability roadmap, plus investor-facing ESG reporting for its private equity sponsor.
- Managed travel and fleet programs — rental rates cut 42% — and ~$100K in tariff recovery identified and in process. Identified
Twenty years of process design is what makes the AI work.
The hard part of an AI tool isn't the model — it's knowing the workflow well enough to build something real: mapping how work actually moves, where departments hand off, and where data and decisions connect. That's the same discipline as his years designing supply chains. The design background isn't separate from the AI work; it's the foundation under it.
His operating principle is human-in-the-loop: AI doesn't replace procurement professionals — it lets them operate at a much higher level. He builds governed tools around real pain points, where every answer shows its evidence, grades its own confidence, and admits what the data can't support.
Seven tools in production, including SPOT (a NetSuite-overlay procurement agent), an RFx response accelerator, a supplier MBR/QBR generator, raw material forecasting, and a team target tracker.
Procurement may not close the sale — it makes sure the company can deliver it.
- Supplier readiness and material continuity through expansion programs for national diagnostics, clinical research, and consumer brand customers — growth without supply becoming the bottleneck.
- Revenue ran ahead of plan during this period, with existing-customer growth roughly 8% above target; procurement was a named contributor to that enablement.
- Every ramp is a procurement event before it's a revenue event — onboarding and scaling new business starts with materials and suppliers being ready.
Procurement itself — from reactive purchasing to a governed, data-driven function.
Before
- Limited spend visibility
- Manual reporting
- Reactive purchasing
- Weak inventory controls
- No digital roadmap
After
- Executive dashboards, structured reporting
- AI-enabled workflows
- Weekly PO governance (−36% weekly spend)
- $5M+ inventory reduction, DIOH 98 → 94
- Coupa roadmap toward a procurement control tower
Modernization isn't a software purchase. It's governance people actually follow, made faster by tools they actually use.
His AI Tools
Built, shipped, and in production.
Every screenshot uses staged demo data — the tools run on governed company data that stays private. That discipline is part of the point.
SPOT — Supply & Procurement Operations Tracker
FlagshipA NetSuite-overlay AI agent that turns ERP reports into procurement decisions
Try the live demo → Runs on synthetic data — no company information.
SPOT works in two modes. Ask it anything — plain-English questions across eight NetSuite reports, covering inventory, open POs, shortages, work orders, vendor follow-ups, receipts, transfers, and expedite priorities — with every answer backed by an evidence table and a confidence rating. Or let it set the agenda: five risk-ranked worklists surface shortages, past-due POs, buy recommendations, slow-moving inventory, and supplier concentration risk, turning ERP data into a prioritized morning worklist instead of a report someone has to remember to pull. Every answer and board exports in one click — to Excel or the clipboard — so the output lands wherever the follow-up actually happens.
Why it matters: built around real procurement pain points, not AI novelty. Every answer is auditable — evidence, business rules, and explicit data-gap disclosure — so decisions made through SPOT hold up in an MBR. Hours of report-pulling now take one question.
Under the hood: Claude-powered reasoning over governed NetSuite data slices, with confidence scoring and gap detection built into every response.
RFx Response Accelerator
Turns every answered question into an asset that answers the next one
Sales and procurement teams lose days re-answering the same RFI, RFP, and vendor-questionnaire questions from scratch. RFx keeps a living database of every question the organization has already answered, matches each new incoming question against it, and generates a draft response template — AI-written from the approved prior answers, not invented — so the team edits and confirms instead of starting from a blank page.
Why it matters: RFx turnaround is a revenue lever, not an admin task — the faster and more consistent the response, the more competitive the bid. It enforces answer consistency so the organization stops contradicting itself across submissions, and institutional knowledge compounds instead of walking out the door.
Supplier MBR/QBR Generator
Business reviews in minutes, not afternoons
Assembles supplier performance, spend trends, and strategic recommendations into review-ready output — hours of prep per supplier automated, with the judgment calls left to people.
Raw Material Forecasting
The tool behind the inventory numbers
Demand-driven forecasting with BOM and reorder-point analysis — the analytical engine behind a $5M+ inventory reduction with no service disruption.
Inventory Risk Assessment
Finding tomorrow's shortage today
Flags items where demand, lead time, and inbound supply are about to collide — criticality-ranked so the team chases the right risks first.
Procurement Command Center
Every KPI, one screen
Spend, savings, supplier performance, and pipeline in a single executive view — the function's health at a glance instead of buried in month-end decks.
Team Target Tracker
An interactive goal tracker the team actually opens
A live dashboard of team targets across savings and other key result areas — editable and updatable in place, built for real review conversations rather than a spreadsheet nobody reopens after January. Targets, progress, and ownership stay visible, turning reviews into a shared, current picture instead of a once-a-year reconstruction.
The resume tells you what he did. This page shows you how he thinks.
Type a message below — it opens an email to Arun, pre-filled with your words.
A note from Arun
Thanks for reading this far. The third-person voice above was a bit of fun — fitting, given the subject. So let me say it plainly, in my own words: I love this work. Twenty years in, I’m more curious than ever, and AI has opened a door I can’t stop building through.
I’m also a certified AI practitioner and an AI educator — I train teams and run workshops on putting this technology to work responsibly, in the real world, with the guardrails it needs. If any of this resonates, I’m always glad to connect.
Arun Raghubir
Six Sigma Green Belt · Anthropic AI Fluency · AI Educator · Google Generative AI for Educators