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AUTOMOTIVE AFTERMARKET · CASE STUDY

Systems Modernization for a $50M Automotive Parts Distributor

This case study illustrates how a mid-market aftermarket distributor unified ERP, commerce, and EDI operations using a centralized central integration layer. Over a structured 16-week program, DataShip delivered a governed architecture that transformed order flow, increased inventory accuracy to 99.3%, reduced order cycle time by 43%, and eliminated $650K in annual operational overhead.

Client Profile

The client is a national automotive aftermarket parts distributor with 40,000+ active SKUs, three U.S. distribution centers, and multi-channel revenue across Shopify DTC, B2B portals, Amazon, Walmart, eBay, and several large retail partners via EDI.

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Their catalog spans braking systems, suspension components, exhaust and emissions parts, performance upgrades, and hard-to-find SKUs for both domestic and import vehicles. Customers include repair shops, regional distributors, e-commerce buyers, and marketplace consumers who all expect accurate availability and tight delivery windows.

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Business Challenges

  • Inventory mismatches across ERP (Dynamics 365), Shopify, Amazon, Walmart, and EDI channels.

  • Manual CSV- and portal-based workflows created bottlenecks every day.

  • Legacy scripts tied systems together with no clear ownership or observability.

  • Order routing was inconsistent—warehouse/3PL assignments often required manual intervention.

  • No unified DEV → UAT → PROD environment strategy existed.

 

Root Causes

  • Dynamics 365 Business Central had become the de facto system of record, but channels were not integrated in real time.

  • Each new marketplace or retail partner introduced its own custom script or file workflow.

  • Monitoring was reactive—issues were discovered only after customers complained or finance flagged discrepancies.

Technical Deep Dive

The central integration layer standardizes system communication via governed layers that ensure consistency, recovery, observability, and predictable onboarding of new partners.

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Core Components

  • API Gateway (Azure API Management): authentication, throttling, schema validation, routing.

  • Event Bus & Queues (Azure Service Bus): decouples ERP, Shopify, marketplaces, 3PLs, and EDI flows.

  • Azure Functions: lightweight compute for transformations, orchestration, and enrichment.

  • Error Pipeline: automated retries, alerting, dead-letter routing, dashboards via Application Insights.

  • Mapping Engine: SKU, pricing, inventory, and order-level transformations maintained in source control.

Environment Architecture (DEV → UAT → PROD)

To avoid fragile deployments, the client adopted a three-environment strategy. Every integration change flows DEV → UAT → PROD using CI/CD, with clear approval points and automated test coverage around critical paths.

DEV

Feature work · Integration tests

Sandboxed environment for rapid iteration and connector development using sample data.

UAT

Partner testing · Validation

​Shared with key partners to validate end-to-end flows, SLAs, and edge cases before go-live.

PROD

Live traffic · Observability

Protected environment with dashboards, alerts, and SLO-based monitoring integrated into Power BI.

Order & Inventory Flow Swimlane

This swimlane illustrates the flow of an order from marketplaces → Integration Hub → Dynamics 365 ERP → Warehouse → 3PL → back to the channel with tracking and status updates. In the animated version, each lane pulses as the order transitions stages, making technical walkthroughs intuitive for non-technical stakeholders.

SWIMLANE OVERVIEW

  1. Channel emits order → Integration Hub validates and transforms.

  2. Hub pushes normalized order into Dynamics 365 with routing metadata.

  3. ERP routes to the correct warehouse based on inventory, region, and business rules.

  4. Warehouse generates pick/pack instructions and shipping label details.

  5. Tracking flows back through the Hub → Shopify / marketplaces / EDI partners in near real time.

Before vs. After Transformation

Before

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  • Point-to-point scripts between Dynamics 365, Shopify, marketplaces, and EDI portals.

  • No consolidated observability or standardized error handling.

  • Unpredictable onboarding timelines for new channels or partners.

  • Daily reconciliation spreadsheets and manual portal updates.

  • Inventory accuracy hovering around ~88% across channels.

After

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  • One governed central integration layer servicing all systems.

  • Full telemetry with dashboards, alerts, and replayable queues in Azure and Power BI.

  • Standardized onboarding playbook for new channels and partners.

  • Real-time or near-real-time feeds replace manual workflows.

  • Inventory accuracy at 99.3% with clear exception management and root-cause analysis.

Monitored Results & Business Impact

Results are not just anecdotal—they are continuously monitored. The central integration layer publishes key metrics into Azure Application Insights and exposes curated views in Power BI so operations, IT, and finance leaders can track improvements week over week.

99.3%

Inventory accuracy across Shopify, marketplaces, and EDI.

Monitored via daily reconciliation dashboards.

43%

Reduction in order-to-ship cycle time.

Tracked by order lifecycle duration tiles in Power BI.

$650K

Annualized run-rate savings.

Validated by finance through cost-to-serve analysis.

  • Inventory accuracy increased from ~88% to 99.3% across all digital channels.

  • Order-to-ship cycle time improved by 43% for marketplace and DTC orders.

  • Support tickets related to order status and stock availability dropped by 27%.

  • Annualized savings of approximately $650,000 from labor and error reduction.

  • New channels can now be onboarded in weeks instead of months.

 

For automotive aftermarket brands and distributors with similar complexity, this pattern can be reused with different ERPs (Dynamics 365, NetSuite, or others), commerce platforms, or EDI providers while preserving the same backbone principles: one governed integration layer, clear environments, deep observability, and measurable business outcomes.

Technology Stack & Tools

The client modernization leveraged a unified Microsoft- and cloud-native toolset to ensure maintainability, auditability, and repeatability across integrations.

ERP

Dynamics 365 Business Central

Monitoring

Azure Application Insights · Power BI

Commerce

Shopify · B2B Portals

EDI / Retail

SPS Commerce · DSCO · Custom Retail Portals

$650K

Azure API Management · Functions · Service Bus

CI/CD

GitHub Actions · Azure DevOps Pipelines

Work Order Flow Diagram (Illustrated)

The following conceptual diagram demonstrates the lifecycle of a work order from initial channel capture to warehouse execution, label generation, and final confirmation back to the selling platform. A dedicated Warehouse Management System (WMS) sits between ERP and warehouse execution to coordinate tasks and inventory movements.

1. Order Capture

Shopify · Amazon · Walmart · EDI

2. Integration Hub

Validation · Transform · Enrich

3. ERP Processing

Dynamics 365 · Routing · Allocation

4. WMS

Wave planning · Task creation · Bin moves

5. Warehouse Ops

Pick · Pack · Scan · Label

6. Confirmation

Tracking → Channels

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Workflow stages can be animated sequentially in the PDF or web version to show order progression end-to-end.

Returns & RMA Workflow

A parallel workflow handles returns and RMAs, ensuring that inventory integrity is preserved and customers receive quick resolutions. The same central integration layer coordinates authorization, transportation, inspection, and financial outcomes.

1. RMA Request

Customer initiates return via portal or channel.

2. Validation

Hub checks eligibility, time windows, and reason codes.

3. ERP & WMS

RMA created in D365; WMS prepares receiving tasks.

4. Inspection

Warehouse inspects, grades, and updates disposition.

5. Resolution

Refund, credit, or replacement reflected in channel.

Exceptions & Escalations Flow

No integration is perfect—what matters is how quickly exceptions are detected, triaged, and resolved. The central integration layer defines structured exception types and escalation paths, so operations teams spend their time on the few orders that truly need attention.

Detection

Failed webhooks, API errors, and SLA breaches are surfaced via alerts.

Classification

Errors tagged by type: mapping, partner, capacity, data-quality, or external outage.

Automated Actions

Retries, quarantining of bad messages, and self-healing rules where appropriate.

Escalation

Clear routing to operations, IT, or partner contacts with full event context attached.

In the animated diagram, exceptions flow down a vertical column with color transitions and subtle motion cues, making it easy for executives to understand how resilience is engineered into the integration layer.

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