Ricardo ToroSupply-chain analytics
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Tools I have built

All of these run on synthetic data for fictional companies. They show how I approach a supply-chain question, and none of them contains client data.

Live demos

ATLAS briefing page: a world map of distribution centres with uncovered demand marked, next to a stock coverage balance and the actions that close the gap.

ATLAS

Synthetic data, fictional company

A supply-chain control tower for a fictional footwear brand: stock coverage, inbound orders, demand and stress tests, with every figure checked and traceable.

Open the live demo
Voyager in-flight book: container shipment counts, delay exposure tiles, a risk alert and expected arrival windows by trade lane.

Voyager

Synthetic data, fictional company

Freight intelligence for a fictional importer: arrival ranges, demurrage and detention exposure, carrier scorecards and an invoice audit.

Open the live demo
SQL Detective: a list of cases on the left, a case question with a SQL editor in the middle, and the available data tables on the right.

SQL Detective

Synthetic data, fictional company

Six cases built on ATLAS's data. Rebuild each headline number in SQL, in the browser, and check it against ATLAS.

Open the live demo
Forecast Arena: forecast against actual demand for several methods, with an accuracy leaderboard ranking them by error.

Forecast Arena

Synthetic data, fictional company

Six forecasting methods tested on the same demand history and ranked by forecast error. Which method wins depends on the series.

Open the live demo
Supply Chain Simulation Lab start page: the questions the tool answers and its modules for inbound lead time, warehouse capacity and boundary maps.

Supply Chain Simulation Lab

Synthetic data, fictional company

A warehouse and network simulation that injects disruptions, such as a port closure or a demand spike, and shows where the system starts to fail.

Open the live demo
Monte Carlo Modeling Studio: an empty model ready for variables, with controls to add variables and run the simulation.

Monte Carlo Modeling Studio

Synthetic data, fictional company

Build probability ranges for lead times, yields and transit times, and see which uncertainty drives the result.

Open the live demo

Open-source freight tools (GitHub)

Small tools, each answering one freight question with a worked example.

  • lane-forecast

    Book against the transit percentile that actually holds, not the average.

  • rate-erosion

    You negotiated -8%. You paid +3%. Here is where it went.

  • carrier-spread

    Your 0%-on-time carrier may be the only one you can plan on.

  • carrier-personas

    Your carriers have pricing personalities. Negotiate accordingly.

  • lane-drill

    Your building has fire drills. Your supply chain doesn't.

  • sea-or-air

    Air freight isn't your failure mode. It's your best decision, made too late.

  • port-queue

    The typhoon closed the port for two days. The queue lasted a week.

  • ship-from

    The nearest plant is the right one to ship from, until the month capacity runs out.

Want something like this built on your own data? Write to me at [email protected].