Supply Chain Price Volatility

This dataset provides granular, time-stamped records of supply chain product prices, including supplier, origin, destination, transportation mode, and volatility metrics. It enables detailed risk analysis, price trend tracking, and forecasting for procurement and logistics optimization. The data structure supports multi-dimensional analysis across products, suppliers, geographies, and time periods.

  • last updated 22 Jul 2025
  • by GoMask
The brief that made it

Risk analysis and mitigation for procurement teams

Sample rows

preview · 8 of 200 rows · all 18 columns
price_record_idstringtransport_modestringlead_time_daysintegerorigin_countrystringproduct_idstringproduct_namestringsupplier_idstringsupplier_namestringdestination_countrystringprice_datedateunit_pricefloatcurrencystringquantityfloatunit_of_measurestringincotermstringprice_volatility_indexfloatexternal_factorsstringrecord_created_atdatetime
PRC-0001sea25CNP-001Premium Steel Rods XLS-101Metallurgica Ltd.US2023-04-141320.5USD80000tonFOB11.5Tariff fluctuations on steel imports2023-04-14T09:32:12
PRC-0002air3JPP-002High Precision Lens Type-AS-102OptiPrime Co.CA2023-04-158100USD14pieceDAP29.3Global chip shortage affecting optics2023-04-15T13:20:18
PRC-0003sea43UAP-003Organic Wheat Grain BulkS-103AgroExport SRLEG2023-04-16275USD100000tonCIF19.8Regional conflict delays2023-04-16T11:07:41
PRC-0004road2USP-004Pharmaceutical Grade EthanolS-104MedSol Inc.CA2023-04-172.15USD50000literDDP5.6Pandemic-driven demand spike2023-04-17T15:03:27
PRC-0005air2DEP-005Industrial Silicon Chip Type-7S-105NanoFab AGKR2023-04-1814500EUR10unitCIP58.1Semiconductor supply chain crisis2023-04-18T10:45:52
PRC-0006air1CNP-006Graphene Sheet Ultra-PureS-106GrapheneX PLCSG2023-04-19200000USD1sheetDDU300Ultra-premium R&D prototype2023-04-19T14:13:09
PRC-0007sea32MYP-007Palm Oil Refined Grade AS-107TropiPalm Ltd.IN2023-04-20916INR60000tonCFR13.6Weather impacting harvests2023-04-20T09:48:32
PRC-0008air2ITP-008Luxury Leather Hide PremiumS-108ItalHide S.A.JP2023-04-21930EUR18hideCPT41.7Premium product, supply chain delays2023-04-21T16:22:04

What the 200 rows show

from the 200-row sample

Sea (transport mode) stands out: mean lead_time_days is 32.1, against 5.2 for the rest.

  • 6median lead_time_days
  • 9currencies
  • 9unit of measures
  • 10incoterms
  • 14destination countries
  • 294.4median unit_price
Mean lead_time_days by transport_mode200 rows
0204032.1sea78 rows2.6air49 rows3.2road56 rows19.4rail17 rows
lead_time_days200 rows, in bands of 5
0459088174141615121312902550lead_time_days →

Median 6, from 0 to 47.

origin_country192 rows with a value · 8 left blank
  1. CN30
  2. DE24
  3. UA23
  4. US21
  5. IT19
  6. RU17
  7. MY14
  8. KE12
  9. JP11
  10. BR11
18 columns by typefrom the column list below
  • string 12
  • integer 1
  • float 3
  • date 1
  • datetime 1

Columns

18 columns in three groups
blueprint · 18 columns
columntypedescriptionexample
Text 12 columns
price_record_idstringUnique identifier for each price record entryuniquePRC-0001
product_idstringUnique identifier for the product or materialP-001
product_namestringName or description of the product or materialPremium Steel Rods XL
supplier_idstringUnique identifier for the supplierS-101
supplier_namestringName of the supplierMetallurgica Ltd.
origin_countrystringCountry where the product originates11 countries · optionalCN
destination_countrystringCountry where the product is deliveredoptionalUS
currencystringCurrency code for the unit price (ISO 4217 format, e.g., USD, EUR, CNY)9 currenciesUSD
unit_of_measurestringUnit of measure for the product (e.g., kg, ton, piece)9 measures · optionalton
transport_modestringMode of transportation used (e.g., sea, air, road, rail)sea · air · road · rail · other · optionalsea
incotermstringInternational commercial term (Incoterm) for the transaction (e.g., FOB, CIF, DDP)10 incoterms · optionalFOB
external_factorsstringShort description of relevant external factors impacting price (e.g., fuel cost, geopolitical event)optionalRegional conflict delays
Numbers 4 columns
unit_pricefloatPrice per unit of the product in the specified currency0 or more1320.5
quantityfloatQuantity of product for the price record (for bulk pricing analysis)0 or more · optional80000
lead_time_daysintegerLead time in days from order to delivery0 or more · optional25
price_volatility_indexfloatCalculated volatility index for the product price (e.g., standard deviation over a period)0 or more · optional11.5
Dates and times 2 columns
price_datedateDate when the price was recorded2023-04-14
record_created_atdatetimeTimestamp when this record was created in the system2023-04-14T09:32:12

Use it for

  • median lead ti…6200 rowsmean lead time days b…32.1sea2.6air3.2road19.4rail

    A logistics dashboard

    Lead_time_days by transport_mode and a breakdown of origin_country. Excel, Power BI or Tableau.

  • Why do the 78 sea rows have a mean lead_time_days of 32.1?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable price records with product_id, product_name and supplier_id to fill a screen in front of a buyer.

Not quite right?

Make it yours.

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This dataset200 rows18 columns
Yours1,000 rows18 columnsorigin_country: UK only

blueprint · supply-chain-price-volatility

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 18 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Tracks prices for 100+ product types
  • Price fluctuations modeled with seasonal and event-driven trends
  • Supplier contract terms included
  • Disruptions (e.g., shortages) periodically introduced
Rows
Open the blueprint in Data Factory

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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
supply-chain-price-volatility

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