Supply Chain Disruption Events

This dataset provides detailed records of supply chain disruption events, including delays, shortages, causes, severity, affected products and suppliers, locations, and financial impact. Designed for risk modeling and predictive logistics, it enables comprehensive analysis of supply chain vulnerabilities and response effectiveness. The dataset supports scenario planning, supplier risk assessment, and operational resilience studies.

  • opened 18 times
  • last updated 12 Jul 2025
  • by GoMask
The brief that made it

Supply chain risk modeling and scenario analysis

Sample rows

preview · 8 of 200 rows · all 19 columns
event_idstringevent_typestringdelay_duration_hoursfloatresolvedbooleanlocation_countrystringevent_datedateseverity_levelstringcausestringaffected_product_idstringaffected_product_namestringaffected_supplier_idstringaffected_supplier_namestringlocation_statestringlocation_citystringshortage_quantityintegerfinancial_impact_usdfloatresolution_datedatedescriptionstringresolution_notesstring
EVT-00001delay7.5trueUS2023-12-18minorweatherP-10001Stainless Steel ScrewsS-2001North Star MetalsMinnesotaMinneapolisblank12002023-12-19Severe snowstorm in Minnesota delayed shipment by several hours.Shipment rerouted and delivered the next day.
EVT-00002shortageblankfalseCN2024-01-10criticalsupplier_issueP-10002Ball BearingsS-2002Zhengzhou Bearings Ltd.HenanZhengzhou1200002500000blankAcute shortage of ball bearings due to supplier insolvency.blank
EVT-00003quality_issueblanktrueGB2022-11-04moderateequipment_failureP-10003Organic Tea BagsS-2003FreshLeaf PackagingEnglandLondon3001840.52022-11-09Packaging machine malfunction led to defective packaging for entire batch.Machine repaired and new batch produced within five days.
EVT-00004delay12trueUS2023-08-28moderatedemand_spikeP-10004HDMI CablesS-2004CableWorksTexasHoustonblank34002023-08-28Unexpected demand caused backlog in outbound shipments.Temporary staff added to clear backlog in one day.
EVT-00005transportation_failure21falseUS2022-03-14criticalequipment_failureP-10005Electric MotorsS-2005Prime Motors Inc.IllinoisChicagoblank43000blankMajor truck breakdown on interstate delayed high-value shipment.blank
EVT-00006natural_disasterblankfalseIN2024-03-02criticalweatherP-10006Plastic ContainersS-2006Mumbai PlasticsMaharashtraMumbai350001250000blankSevere flooding in Mumbai halted all warehousing operations.blank
EVT-00007delay4trueDE2021-09-15minorweatherP-10007Medical Test KitsS-2007MediTest GroupHessenFrankfurtblank6002021-09-16Fog at Frankfurt airport delayed international outbound flight.Cargo rerouted on next available flight.
EVT-00008shortageblankfalseBR2023-07-19severelabor_strikeP-10008Coffee BeansblankblankSão PauloCampinas54000410000blankNationwide trucker strike in Brazil caused supply shortages.blank

What the 200 rows show

from the 200-row sample

Delay (event type) stands out: mean delay_duration_hours is 7.1, against 28.9 for the rest.

  • 67%resolved = true
  • 8.0median delay_duration_hours
  • 4severity levels
  • 8causes
  • 15,800median shortage_quantity
  • 2,200median financial_impact_usd
Mean delay_duration_hours by event_type112 rows
0501007.1delay80 rows28.9transportation_fail…32 rows
delay_duration_hours112 rows, in bands of 10
030606029104800100050100delay_duration_hours →

Median 8.0, from 1.5 to 72.0.

location_country200 rows · top 10 of 19 values
  1. US55
  2. DE20
  3. FR17
  4. CN15
  5. UK12
  6. JP11
  7. IN10
  8. BR10
  9. KR10
  10. IT9
19 columns by typefrom the column list below
  • string 13
  • integer 1
  • float 2
  • date 2
  • boolean 1

Columns

19 columns in four groups
blueprint · 19 columns
columntypedescriptionexample
Text 13 columns
event_idstringUnique identifier for each supply chain disruption eventuniqueEVT-00001
event_typestringType of supply chain event (e.g., delay, shortage, quality_issue, transportation_failure, natural_disaster)6 valuesdelay
severity_levelstringSeverity of the disruption event (e.g., minor, moderate, severe, critical)minor · moderate · severe · criticalminor
causestringPrimary cause of the disruption (e.g., weather, supplier_issue, labor_strike, equipment_failure, demand_spike, regulatory, unknown)8 valuesweather
descriptionstringDetailed description of the disruption eventoptionalSevere snowstorm in Minne…
affected_product_idstringIdentifier for the affected product or SKUoptionalP-10001
affected_product_namestringName of the affected productoptionalStainless Steel Screws
affected_supplier_idstringIdentifier for the supplier involved in the disruptionoptionalS-2001
affected_supplier_namestringName of the supplier involved in the disruptionoptionalNorth Star Metals
location_countrystringCountry where the disruption occurredoptionalUS
location_statestringState or region where the disruption occurredoptionalMinnesota
location_citystringCity where the disruption occurredoptionalMinneapolis
resolution_notesstringAdditional notes about the resolution of the eventoptionalShipment rerouted and del…
Numbers 3 columns
delay_duration_hoursfloatDuration of delay in hours, if applicable0 or more · optional7.5
shortage_quantityintegerQuantity of product shorted due to the disruption, if applicable0 or more · optional120000
financial_impact_usdfloatEstimated financial impact of the event in USD0 or more · optional1200
Dates and times 2 columns
event_datedateDate when the disruption event occurred or was reported2023-12-18
resolution_datedateDate when the disruption was resolved, if applicableoptional2023-12-19
True or false 1 column
resolvedbooleanIndicates if the disruption event has been resolvedtrue

15 SQL practice questions for the Supply Chain Disruption Events

Written for this data and checked against it: 12 SQL and 3 Power BI exercises from beginner to advanced. Try the first three free; the practice kit has all 15, a starter .sql file and an answer key with every expected result.

  1. 01BeginnerFreeSELECT · WHERE · ORDER BY

    Critical events list

    Return event_id, event_date, event_type and financial_impact_usd for every event whose severity_level is 'critical'. Order the results by financial_impact_usd from highest to lowest, then by event_id ascending.

    Tables: supply_chain_disruption_events · your result: 4 columns, 49 rows
  2. 02BeginnerFreeDISTINCT · ORDER BY

    Distinct causes

    Return each distinct cause found in the data as a single column named cause, sorted alphabetically.

    Tables: supply_chain_disruption_events · your result: 1 columns, 8 rows
  3. 03BeginnerFreeGROUP BY · COUNT

    Events per type

    Count the events for each event_type. Return event_type and event_count, ordered by event_count from highest to lowest, then by event_type ascending.

    Tables: supply_chain_disruption_events · your result: 2 columns, 5 rows
  1. 04Total impact by countryBeginner
  2. 05Average delay by severityPower BI
  3. 06Causes with high total impactIntermediate
  4. 07Impact size bucketsIntermediate
  5. 08Events by yearIntermediate
  6. 09Event types above overall averageIntermediate
  7. 10Resolution rate by countryPower BI
  8. 11Top 2 events per typeAdvanced
  9. 12Yearly impact changeAdvanced
  10. 13Running total of impactAdvanced
  11. 14Percent of total by causeAdvanced
  12. 15Impact anomalies per event typePower BI

Get the practice kit: the full dataset, all 15 exercises, a starter .sql and the answer key. One-time $3.99.

Get the practice kit · $3.99

Use it for

  • resolved67%134 of 200 rowsmean delay duration h…7.1delay28.9transp…

    A logistics dashboard

    The resolved rate, delay_duration_hours by event_type and a breakdown of location_country. Excel, Power BI or Tableau.

  • Why do the 80 delay rows have a mean delay_duration_hours of 7.1?

    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 events with event_date, event_type and severity_level to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 19 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset200 rows19 columns
Yours1,000 rows19 columnslocation_country: UK only

blueprint · supply-chain-disruption-events

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 19 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
  • Events include delays, shortages, and diversions
  • Each event linked to product type and supplier
  • Timestamp and location details included
  • Include disruption cause and impact severity
  • Optional: downstream effects on delivery time
Rows
Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

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

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