Workflow automation and integration across 27 back-office processes at a retail group
Onboarding a store associate touched five systems and eleven manual handoffs. pronix.ai rebuilt 27 back-office workflows as governed, event-driven integrations with AI handling the judgment steps — 96% straight-through processing and cycle times cut by 2.7x.
Multi-brand retail group, 1,100 stores · Azure Logic Apps · Azure AI Foundry · SAP · Workday · ServiceNow
- Client
- Multi-brand retail group, 1,100 stores
- Industry
- Retail & Ecommerce
- Platform
- Azure Logic Apps · Azure AI Foundry · SAP · Workday · ServiceNow
*Representative outcome; results vary by client, scope and platform configuration.
The challenge
Hiring, transfers, store openings and supplier onboarding all ran on spreadsheets and email between SAP, Workday and ServiceNow. A single store associate onboarding took 6.5 days and eleven handoffs; 18% of cases needed rework because a step was missed or data was re-keyed incorrectly.
Our approach
Process mining before automation
Six weeks of event-log analysis showed the real paths, not the documented ones. Nine of the 27 processes were redesigned rather than automated as-is.
Event-driven integration, one contract per system
A single integration contract per system of record replaced point-to-point scripts, so a change in Workday no longer breaks four downstream flows.
AI on the judgment steps only
Classification, exception triage and document extraction use AI; deterministic steps stay deterministic. That boundary keeps the audit story simple.
Exceptions are designed, not accidental
Every workflow has a defined exception queue with an owner and an SLA — the 4% that does not go straight through is visible, not lost.
Idempotent and replayable
Every step is retry-safe and replayable from the event log, which is what made a phased rollout across 1,100 stores survivable.
“New associates are ready on day one instead of day seven. Store managers noticed before finance did.”
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Illustrative case study. Scenarios, metrics, quotes and client details are representative composites based on Pronix engagements and industry benchmarks unless a named client is shown with written consent. Outcomes vary by client, scope, data quality and platform configuration. Nothing on this page is a guarantee, warranty or professional advice. See our Terms of Use for the full disclaimer.
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