E-commerce
18 columns
120 rows
8 formats

E-commerce Supplier ESG Risk Profiles

This dataset provides detailed ESG risk profiles for e-commerce suppliers, including compliance status, risk scores, audit results, corrective actions, and key sustainability indicators. It empowers sustainability coordinators and supply chain managers to assess, compare, and monitor supplier ESG performance for responsible sourcing and proactive risk management.

last updated 29 Jan 2026
by GoMask

The brief that made it

Supplier ESG risk assessment and benchmarking

Sample rows

preview · 8 of 120 rows · all 18 columns

supplier_idstring	esg_compliance_statusstring	corrective_actions_openinteger	industry_sectorstring	supplier_namestring	supplier_countrystring	supplier_citystring	esg_risk_scorefloat	last_audit_datedate	audit_resultstring	number_of_corrective_actionsinteger	corrective_actions_closedinteger	improvement_trendstring	esg_risk_categorystring	last_esg_updatedatetime	contact_person_namestring	contact_person_emailstring	key_sustainability_indicatorsstring
SUPP-0001	Compliant	0	Apparel	Global Apparel Solutions	Vietnam	Ho Chi Minh	10.8	2023-09-11	Pass	2	2	Improving	Low	2023-09-12T10:15:22	Minh Tran	minh.tran@globalapparel.vn	carbon footprint, water usage
SUPP-0002	Compliant	0	Electronics	Eco Electronics Corp	Germany	Berlin	21.5	2023-06-03	Pass	1	1	Stable	Low	2023-06-04T09:20:18	Clara Becker	clara.becker@ecoelec.de	energy efficiency, hazardous waste
SUPP-0003	Compliant	1	Apparel	Green Textile Mills	Bangladesh	Dhaka	4.3	2023-10-20	Conditional Pass	3	2	Improving	Low	2023-10-21T11:45:09	Ayesha Rahman	ayesha.rahman@greentextile.com	water usage, chemical management
SUPP-0004	Compliant	0	Urban Infrastructure	Urban Infrastructure Ltd	United Kingdom	London	16.7	2023-08-14	Pass	0	0	Stable	Low	2023-08-15T15:32:45	George Evans	george.evans@urbaninfra.co.uk	site emissions, energy use
SUPP-0005	Compliant	0	Chemicals	Chemical Solutions Group	Belgium	Antwerp	23.9	2023-12-02	Pass	1	1	Improving	Low	2023-12-02T17:11:41	Elsa De Wilde	elsa.dewilde@chemgroup.be	chemical management, waste reduction
SUPP-0006	Compliant	0	Logistics	Logistics Forwarders Inc	USA	Chicago	12.5	2023-07-21	Pass	2	2	Stable	Low	2023-07-22T13:56:30	Megan Harris	megan.harris@logisticsforwarders.com	fuel efficiency, emissions
SUPP-0007	Compliant	0	Maritime	Maritime Global Partners	Norway	Oslo	19.3	2023-11-04	Pass	1	1	Stable	Low	2023-11-05T14:40:58	Henrik Larsen	henrik.larsen@maritimeglobal.no	oil spill prevention, waste reduction
SUPP-0008	Compliant	0	Manufacturing	GreenTech Manufacturing	Poland	Warsaw	14.9	2023-10-12	Pass	3	3	Improving	Low	2023-10-13T09:06:17	Zofia Kowalska	zofia.kowalska@greentech.pl	energy use, water recycling
SUPP-0009	Compliant	0	Plastics	Sustainable Plastics Ltd	Canada	Montreal	24.7	2023-09-30	Pass	2	2	Stable	Low	2023-09-30T16:22:12	Luc Tremblay	luc.tremblay@splastics.ca	plastic recycling, energy consumption
SUPP-0010	Compliant	0	Technology	BlueSky Technology	Japan	Osaka	6.2	2023-08-10	Pass	0	0	Improving	Low	2023-08-11T12:20:50	Yuki Watanabe	yuki.watanabe@blueskytech.jp	energy efficiency, e-waste
SUPP-0011	Compliant	2	Food & Beverage	AgroFood Suppliers	Brazil	Sao Paulo	31	2023-12-21	Conditional Pass	4	2	Stable	Medium	2023-12-22T09:14:33	Amanda Souza	amanda.souza@agrofood.com.br	water usage, pesticide management
SUPP-0012	Compliant	1	Forestry	ForestWise Group	Finland	Tampere	29.7	2023-10-19	Conditional Pass	3	2	Stable	Medium	2023-10-20T08:01:16	Johanna Lahti	johanna.lahti@forestwise.fi	biodiversity, land use
SUPP-0013	Compliant	3	Metals & Mining	SupplyMetals Partners	South Africa	Johannesburg	43.8	2023-10-01	Conditional Pass	6	3	Stable	Medium	2023-10-02T17:03:54	Sipho Dlamini	sipho.dlamini@supplymetals.co.za	mineral traceability, water usage
SUPP-0014	Compliant	1	Agriculture	AgriSmart Holdings	Netherlands	Rotterdam	38.2	2023-07-24	Pass	5	4	Improving	Medium	2023-07-25T11:35:46	Femke de Vries	femke.devries@agrismart.nl	crop rotation, water conservation
SUPP-0015	Compliant	1	Technology	TechInnovate Partners	India	Bangalore	47.6	2023-04-02	Pass	2	1	Stable	Medium	2023-04-03T16:17:31	Rahul Nair	rahul.nair@techinnovate.in	data center efficiency, e-waste
SUPP-0016	Compliant	2	Logistics	LogiChain Transport	Mexico	Monterrey	32.1	2023-06-17	Conditional Pass	5	3	Stable	Medium	2023-06-17T18:22:17	Carlos Jimenez	carlos.jimenez@logichain.mx	fleet efficiency, carbon offset
SUPP-0017	Compliant	1	Maritime	OceanSafe Maritime	Singapore	Singapore	39.5	2023-09-29	Pass	3	2	Stable	Medium	2023-09-30T08:57:40	Wei Ming Tan	wei.tan@oceansafe.sg	marine emissions, ballast water
SUPP-0018	Compliant	2	Food & Beverage	FreshHarvest Foods	France	Lyon	41.2	2023-11-09	Conditional Pass	4	2	Stable	Medium	2023-11-09T12:42:38	Sophie Martin	sophie.martin@freshharvest.fr	local sourcing, water use
SUPP-0019	Compliant	0	Manufacturing	EcoMaterials Ltd	Australia	Sydney	28.4	2023-09-08	Pass	1	1	Improving	Medium	2023-09-09T11:50:13	Oliver Bennett	oliver.bennett@ecomaterials.com.au	recycled materials, energy use
SUPP-0020	Compliant	2	Chemicals	PureChem Industries	India	Mumbai	35.6	2023-07-07	Conditional Pass	5	3	Stable	Medium	2023-07-08T10:00:44	Priya Agarwal	priya.agarwal@purechem.in	waste minimization, chemical safety

What the 120 rows show

from the 120-row sample

Non-Compliant (esg compliance status) stands out: mean corrective_actions_open is 11.3, against 0.78 for the rest.

1median corrective_actions_open
4audit results
4improvement trends
4esg risk categories
39.5median esg_risk_score
3median number_of_corrective_actions

Mean corrective_actions_open by esg_compliance_status120 rows

corrective_actions_open120 rows, in bands of 2

Median 1, from 0 to 18.

industry_sector120 rows · top 10 of 17 values

Apparel13
Metals & Mining11
Chemicals10
Logistics10
Plastics10
Food & Beverage10
Agriculture10
Electronics8
Forestry8
Urban Infrastructure7

18 columns by typefrom the column list below

string 12
integer 3
float 1
date 1
datetime 1

Columns

18 columns in three groups

blueprint · 18 columns
column	type	description	example
Text 12 columns
`supplier_id`	string	Unique identifier for each supplierunique	SUPP-0001
`supplier_name`	string	Official name of the supplier	Global Apparel Solutions
`supplier_country`	string	Country where the supplier is based	Vietnam
`supplier_city`	string	City where the supplier is locatedoptional	Ho Chi Minh
`industry_sector`	string	Industry sector of the supplier (e.g., Apparel, Electronics)	Apparel
`esg_compliance_status`	string	Current ESG compliance status of the supplierCompliant · Non-Compliant · Pending · Under Review	Compliant
`audit_result`	string	Result of the most recent ESG auditPass · Fail · Conditional Pass · Not Audited · optional	Pass
`key_sustainability_indicators`	string	Comma-separated list of key sustainability indicators tracked (e.g., carbon footprint, water usage)optional	biodiversity, land use
`improvement_trend`	string	Supplier's ESG improvement trend over timeImproving · Stable · Declining · Unknown · optional	Improving
`esg_risk_category`	string	Categorical ESG risk level (e.g., Low, Medium, High, Critical)Low · Medium · High · Critical	Low
`contact_person_name`	string	Name of the main ESG contact at the supplieroptional	Minh Tran
`contact_person_email`	string	Email address of the main ESG contactoptional	clara.becker@ecoelec.de
Numbers 4 columns
`esg_risk_score`	float	Numerical risk score indicating supplier's ESG risk (lower is better)0 to 100	10.8
`number_of_corrective_actions`	integer	Number of corrective actions identified in the last audit0 or more · optional	2
`corrective_actions_open`	integer	Number of corrective actions still open0 or more · optional	0
`corrective_actions_closed`	integer	Number of corrective actions closed since last audit0 or more · optional	2
Dates and times 2 columns
`last_audit_date`	date	Date of the most recent ESG auditoptional	2023-09-11
`last_esg_update`	datetime	Timestamp of the last ESG data update for the supplier	2023-09-12T10:15:22

Use it for

An e-commerce dashboard
Corrective_actions_open by esg_compliance_status and a breakdown of industry_sector. Excel, Power BI or Tableau.
Why do the 26 Non-Compliant rows have a mean corrective_actions_open of 11.3?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Suppliers120
SUPP-00010Compliant
SUPP-00020Compliant
SUPP-00031Compliant
A software demo
Believable suppliers with supplier_name, supplier_country and supplier_city to fill a screen in front of a buyer.

This dataset120 rows18 columns

Yours10,000 rows18 columnssupplier_country: UK only

blueprint · e-commerce-supplier-esg-risk-profiles

Behind this dataset

Same schema. As many rows as you need.

These 120 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

Each supplier must have a unique ID and region
ESG audit frequency and most recent audit date are included
Risk rating is calculated from latest ESG score and incident count
Corrective actions are required for scores below threshold
Suppliers flagged for repeat non-compliance over two periods
Supplier category and material risk must be indicated

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. New accounts start with 25 free credits.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: e-commerce-supplier-esg-risk-profiles

What should your data show?

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Sample rows

What the 120 rows show

Columns

Use it for

An e-commerce dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in E-commerce

What should your data show?