Stora Enso improves OTIF delivery performance by 20% with Celonis order fulfillment automation
The problem
Stora Enso's order fulfillment relied on manual data search, manual email communication for order changes, and manual analytics, with no unified system for delivery scheduling or customer notification, threatening on-time delivery and customer experience.
Workflow diagram · grounded in source
1
Process mining identifies pinch points
Ai action
The in-house team used process mining to identify order fulfillment pinch points.
▾ source quote
“the in-house team used process mining to identify order fulfillment pinch points”
2
Proactive delay alert generated
Output
Teams receive proactive alerts about the risk of delivery delays.
▾ source quote
“Stora Enso's teams receive proactive alerts about the risk of delivery delays”
3
Automated order status update
Integration
Order status is updated in source systems and the front-office team is informed about required changes in delivery date.
▾ source quote
“updating order status in source systems and informing the front-office team about required changes in the delivery date, with sufficient notice to mitigate the risk of late delivery”
4
OFE receives delay notification
Trigger
The back-office Order Fulfillment Experts team receives a delivery delay notification in Celonis.
▾ source quote
“The back-office Order Fulfillment Experts (OFE) team receives a delivery delay notification in Celonis”
5
Case created in Salesforce
Integration
The OFE creates a case in Salesforce to trigger the front-office Customer Excellence Team to correspond with the customer.
▾ source quote
“The OFE creates a case in Salesforce to trigger the front-office Customer Excellence Team (CET) to correspond with the customer”
6
Customer response fed back to CET
Feedback loop
Customer response to the delivery date shift is fed back to the Customer Excellence Team.
▾ source quote
“Customer response to the delivery date shift is fed back to the CET”
7
Order updated via Salesforce to Celonis
Integration
The Customer Excellence Team passes updated order information back through Salesforce to the Celonis platform.
▾ source quote
“The CET pass it back through Salesforce to the Celonis platform by updating the orders in the source system”
8
New OFE tasks created
Output
New tasks are created for the OFE team to optimize delivery scheduling.
▾ source quote
“New tasks are created for the OFE team to optimize delivery scheduling”
Reported outcome
Stora Enso achieved a 20% increase in OTIF performance, with 1,000 tasks managed through Celonis and 50% of users reporting reduced manual handling time. Order update delivery time dropped from several days to within one working day.
Reported metrics
tasks managed through Celonis platform1,000
OTIF performance increase20%
Users reporting reduced manual handling time50%
Order update delivery timewithin one working day
Show all 5 reported metrics
tasks managed through Celonis platform1,000
OTIF performance increase20%
users reporting reduced manual handling time50%
order update delivery timewithin one working day
active Celonis end usersover 50
Reported stack
CelonisCelonis Studioprocess miningSalesforce
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Stora Enso achieved a 20% increase in OTIF performance, with 1,000 tasks managed through Celonis and 50% of users reporting reduced manual handling time.
What tools did this team use?
Celonis, Celonis Studio, process mining, Salesforce.
What results were reported?
tasks managed through Celonis platform: 1,000; OTIF performance increase: 20%; Users reporting reduced manual handling time: 50%; Order update delivery time: within one working day (source-reported, not independently verified).
How is this order processing AI workflow structured?
Process mining identifies pinch points → Proactive delay alert generated → Automated order status update → OFE receives delay notification → Case created in Salesforce → Customer response fed back to CET → Order updated via Salesforce to Celonis → New OFE tasks created.
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