Supply chain · Production

Real customer successes: 4 tried-and-true tactics to build a more sustainable supply chain

The problem

Enterprises face a persistent gap between ESG sustainability targets and real-world supply chain execution; emissions have historically been hard to precisely measure at scale, and manual supplier sustainability reviews are burdensome.

Workflow diagram · grounded in source
1
Supply chain data centralized
integration
“centralizing data across all processes to give realistic lead-time predictions”
2
Process Intelligence gap analysis
ai_action
“Celonis customers can analyze supply chain processes to understand exactly where sustainability opportunities are hiding, and how to capture them”
3
Real-time emission detection
ai_action
“real-time detection and quantification of unsustainable shipping practices and subsequent process improvements to increase efficiency”
4
Supplier sustainability data consolidated
integration
“The Sustainable Spend Management app consolidates supplier sustainability data so teams can evaluate and prioritize based on risk, rating coverage, and specific ESG criteria”
5
Transport option simulation
ai_action
“simulates the impact of different transport methods and routes, and can provide recommendations on the most carbon-optimized options”
6
Automated review actions triggered
integration
“automate much of the manual ongoing action required in supplier sustainability reviews, including requesting ratings and triggering reassessment when the expiration date is approaching”
7
Emissions baseline established
output
“Archroma now has a performance baseline for outbound shipping emissions. This kind of global supply chain data isn't easy for most businesses to find, much less use, but with Celonis, it's now a central pillar of Archroma's emission redu…”
Reported outcome

Freudenberg reduced working capital and lead times by about 10% across the business; Archroma quantified carbon emissions across more than 150,000 shipments and reduced outbound shipping emissions by more than 6% in less than 12 months; Heidelberg Materials accelerated sorting and selection of over 120,000 vendors.

Reported metrics
Freudenberg working capital and lead times reductionabout 10%
Archroma outbound shipping emissions reductionmore than 6%
Archroma shipments with quantified carbon emissionsmore than 150,000
Archroma time to pinpoint major carbon contributorsless than 12 months
Show all 7 reported metrics
Freudenberg working capital and lead times reductionabout 10%
Archroma outbound shipping emissions reductionmore than 6%
Archroma shipments with quantified carbon emissionsmore than 150,000
Archroma time to pinpoint major carbon contributorsless than 12 months
Heidelberg Materials vendors sorted and selectedover 120,000
consumer trust in brands with transparent supply chains32%
Lufthansa CityLine fuel savings per flight with accurate fuel order96 kilos
Reported stack
Celonis Process Intelligence GraphEnd-to-End Lead Times AppSustainable Spend Management AppShipping Emissions Reduction appdigital twin
Source
https://www.celonis.com/blog/real-customer-successes-4-tried-and-true-tactics-to-build-a-more-sustainable-supply-chain
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Freudenberg reduced working capital and lead times by about 10% across the business; Archroma quantified carbon emissions across more than 150,000 shipments and reduced outbound shipping emissions by more than 6% in l…

What tools did this team use?

Celonis Process Intelligence Graph, End-to-End Lead Times App, Sustainable Spend Management App, Shipping Emissions Reduction app, digital twin.

What results were reported?

Freudenberg working capital and lead times reduction: about 10%; Archroma outbound shipping emissions reduction: more than 6%; Archroma shipments with quantified carbon emissions: more than 150,000; Archroma time to pinpoint major carbon contributors: less than 12 months (source-reported, not independently verified).

How is this supply chain AI workflow structured?

Supply chain data centralized → Process Intelligence gap analysis → Real-time emission detection → Supplier sustainability data consolidated → Transport option simulation → Automated review actions triggered → Emissions baseline established.

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