Ecommerce ops · Production

The Warehouse Group scales retail operations with Blue Prism digital workers across pricing optimisation, product content and pallet management

The problem

As TWG's business grew, the volume and complexity of work increased beyond what hiring more people or outsourcing could solve, with some processes needing to run at a speed and scale that people alone could not manage.

Workflow diagram · grounded in source
1
Daily competitor price ingestion
trigger
“Each day, a third-party tool reads competitor pricing on nearly 4,000 SKUs”
2
Guardrail-bounded price evaluation
ai_action
“A digital worker ingests this data, applies buyer-defined commercial guardrails and runs it through a rules engine that evaluates pricing strategy, category rules and margin thresholds”
3
Automated price updates to stores
output
“The system automatically calculates up to 1,100+ promotional price changes per day and bulk-loads them into the pricing platform, where updates are instantly pushed to electronic shelf-edge labels across all Noel Leeming stores. The enti…”
4
AI product content generation
ai_action
“AI handles content generation and validation. Together, they support three core activities: creating web copy for new products, identifying and correcting errors in existing content, and generating descriptions for products with missing …”
5
Employee review before publish
human_review
“Digital workers route AI-generated content and corrections to employees for review before publishing anything, keeping human oversight built into the process”
6
Pallet data multi-system consolidation
integration
“Digital workers now bring together data from multiple systems to create a single, clear view of pallet movements”
7
Daily pallet transfer validation
validation
“Each day, digital workers review up to 400 transfers, check them against internal records and flag incorrect dates, quantities, pallet types and ownership mismatches. More than 60% of transfers are identified for correction or rejection,…”
Reported outcome

TWG's automation program supports 16 business functions and more than 80 processes, delivering over 5,000 workdays of capacity per year and $15.3 million in estimated annual business value, including $2.5 million in net margin impact from price optimisation and $860,000 in annual pallet savings.

Reported metrics
Annual capacity deliveredover 5,000 workdays
Estimated annual business value$15.3 million
Manual effort removed from pricing6,000 hours (750 workdays)
Net margin impact from price optimisation$2.5 million
Show all 10 reported metrics
annual capacity deliveredover 5,000 workdays
estimated annual business value$15.3 million
manual effort removed from pricing6,000 hours (750 workdays)
net margin impact from price optimisation$2.5 million
pallet transfers identified for correction or rejectionMore than 60%
pallet management annual savings$860,000
promotional price changes per dayup to 1,100+
business functions supported16
processes automatedmore than 80
customer satisfactionincreases customer satisfaction
Reported stack
SS&C Blue Prism digital workersrules engine
Source
https://www.blueprism.com/resources/case-studies/warehouse-group-retail-ai-automation/
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

TWG's automation program supports 16 business functions and more than 80 processes, delivering over 5,000 workdays of capacity per year and $15.3 million in estimated annual business value, including $2.5 million in n…

What tools did this team use?

SS&C Blue Prism digital workers, rules engine.

What results were reported?

Annual capacity delivered: over 5,000 workdays; Estimated annual business value: $15.3 million; Manual effort removed from pricing: 6,000 hours (750 workdays); Net margin impact from price optimisation: $2.5 million (source-reported, not independently verified).

How is this ecommerce ops AI workflow structured?

Daily competitor price ingestion → Guardrail-bounded price evaluation → Automated price updates to stores → AI product content generation → Employee review before publish → Pallet data multi-system consolidation → Daily pallet transfer validation.

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