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Zug, Switzerland · Feel free to ping me

I turn commodity markets into P&L decisions and build the tools that make them stick.

I'm Vazgen, Senior Manager for Global Commodity Risk Management at Kenvue. I forecast inflation on €4bn of procurement spend, translate it into brand-level gross-profit impact, and build the data and AI tools that get the answer to leadership 40–60 days earlier.

Get in touch See the work
Gross profit bridge €M
Seeing the orange bar two months early is the job.
€4bnannual procurement spend under my inflation forecast
40–60days of extra visibility from the forecasting redesign I led
100+sourcing managers aligned behind one monthly forecast
10+years across finance, FP&A and procurement

Why hire me

Most people can forecast the number or build the tool. I do both, and get the room to agree on it.

Commodity risk that speaks P&L

18-month inflation forecasts across packaging, chemicals, freight and warehousing, converted into brand-level gross-profit impact the CPO and finance can act on.

I build, not just analyse

Azure SQL, automated pipelines, Alteryx, Power BI and multi-agent AI. When US tariffs hit, I had a working exposure model in days, not a project plan.

I bring people with me

A forecast is only useful if people trust it. I validate assumptions with 100+ sourcing managers and defend the rationale with category leads, finance and the CPO.

Selected work

What changed because I was there.

Kenvue · Global Procurement

Rebuilding the inflation forecast

Problem
The forecast for €4bn of spend was consolidated in Excel from financial actuals, so the business saw price moves late, and finance rebuilt the numbers by hand in every region.
Did
Led the full redesign: an Azure SQL backend with automated pipelines and, more importantly, a forecast built on supplier pricelists instead of actuals.
Result
40–60 days of extra visibility. Sourcing managers spend their time on decisions, finance dropped manual consolidation, and leadership gets earlier numbers that are already agreed.

Kenvue · Commercial decisions

From raw material to brand P&L

Problem
Price forecasts lived in procurement; gross-profit decisions lived in commercial. Nobody could see what a resin or freight move meant for a specific brand.
Did
Connected the forecast to brand-level gross profit. When US tariffs landed, built an exposure model in days that combined several data sources and re-ran scenarios as policy shifted.
Result
Leadership has a direct line from raw-material shifts to P&L exposure, and could react to tariff news the same week.

Kenvue · AI

A multi-agent market-intelligence system

Problem
Numbers without context don't convince a category leader; context without numbers doesn't convince finance.
Did
On top of the new data foundation, built a multi-agent AI system that combines the quantitative models with qualitative market intelligence.
Result
Layered summaries for each audience, from CPO to buyer, with a chat interface for follow-up questions.

Johnson & Johnson · Procurement finance

Reporting for $3bn of spend, rebuilt

Problem
Month-end reporting ran through 100+ linked files, which left little time to explain what happened and why.
Did
Moved all transformations, blending and mappings into Alteryx workflows that feed Power BI directly, with every planning cycle in one place.
Result
100+ files down to 6, 14 hours saved each close, 40× more data with no slowdown. The approach was then rolled out regionally, with me advising.

Apps I've built

Proof beyond the day job. Each one started with a real problem.

Built on my own time with public or synthetic data. New apps land here first, with a short write-up on LinkedIn.

How I work

Three habits that keep showing up.

  1. 1

    Start from the decision

    Who has to decide what, and when? The model, the data and the tool follow from that, not the other way round.

  2. 2

    Fix the process, then the tech

    The biggest win in my forecast redesign wasn't SQL. It was changing what we forecast from, which bought two months.

  3. 3

    Build alignment into the numbers

    When the people who own the assumptions have shaped them, the meeting is about the decision, not about whose spreadsheet is right.

Path

From aircraft load sheets to commodity curves.

More detail on LinkedIn.

Toolbox

Domain first, tech second.

Risk & finance

  • Commodity risk management
  • Inflation forecasting
  • Pricelist & contract analysis
  • Gross-profit impact
  • Price-volume analysis
  • Tariff scenarios
  • Financial modeling
  • Statistical modeling
  • Strategic planning

Build

  • SQL & Azure SQL
  • Data pipelines
  • Alteryx
  • Power BI
  • Qlik Sense
  • Anaplan
  • Agentic AI
  • React & Svelte
  • Excel, seriously

Languages

  • English
  • Russian
  • Czech
  • Spanish (basic)

Contact

Let’s talk.

Working on commodity risk, procurement finance or putting AI to work in either? I'm always happy to compare notes.

vazgen.cham@gmail.com LinkedIn