Process - Project

Process Analysis

As-Is Workflow vs. To-Be Optimization

Current manufacturing fulfillment relies on manual handoffs and fragmented systems. Our proposed model automates the entire chain for speed.

as_is_fulfillment.bpmn

Cycle: 3 – 5 Hours

Current As-Is Process

High latency due to manual data entry, siloed communication, and lack of real-time inventory visibility.

1. Manual Order Entry

Manual data entry, email parsing, spreadsheet updates

High Latency

Time: 45 – 60 min12% entry error

2. Inventory Verification

Manual stock checks, warehouse email requests

Bottleneck

Time: 30 – 90 minStockout risk

3. Logistics Coordination

Carrier booking, manual tracking updates

Fragmented

Time: 60 – 120 minDelay risk

4. Invoice Processing

Manual billing, payment reconciliation

Manual Sync

Time: 30 – 60 minBilling lag

Total Process Friction4 Manual Handoffs

Avg. delay: 4.2 hrs/orderHigh error risk

Requires manual interventionInefficient

to_be_optimized.bpmn

Latency: < 300ms

Proposed To-Be Process

Automated fulfillment pipeline. Direct ERP integration and real-time inventory sync eliminate manual delays.

Click to simulate process flow

erp_sync_v2.0 (active)

AutomatedVerified

Automated Order Capture

0.1s capture

Direct ERP integration for instant order ingestion.

Real-time Inventory Sync

99.9% accuracy

Automated stock validation against live WMS data.

Dynamic Route Optimization

< 200ms latency

AI-driven carrier selection and automated booking.

ERP/WMS Integrated

View Requirements

92%Cycle time reduction

100%Inventory visibility

0Manual handoffs

< 1sOrder processing

Project Roadmap

The Optimization Roadmap

A phased approach to reducing order-to-delivery delays. We move from data ingestion to process mapping, requirements definition, and final implementation.

PHASE_01

Week 1 – 2Data Audit

Data Ingestion

Baseline supply chain data extraction and integrity validation.

We aggregate raw order logs, warehouse throughput metrics, and delivery timestamps into a secure analytical environment to identify primary latency drivers.

Key Deliverables:

Raw ERP data extraction

Data quality validation

Latency baseline mapping

INGEST_BUFFER // ANALYTICAL

>SNAPSHOT: raw_order_logs… [VALIDATED]

>SANDBOX: Data environment initialized

>STATUS: Ingestion complete. Audit active.

Validation Passed200 OK

PHASE_02

Week 3 – 4BPMN Analysis

Process Mapping

As-Is process modeling and bottleneck identification.

We map the current order-to-delivery workflow using BPMN 2.0, pinpointing manual handoffs and system delays that impede operational velocity.

Key Deliverables:

As-Is BPMN process maps

Bottleneck root cause analysis

Stakeholder interview synthesis

AUDIT_TELEMETRY // BPMN_TRACE

>DETECTED: 4 manual handoff delays

>PURGED: Redundant approval steps

>VALIDATED: Process flow mapped 1:1

Validation Passed200 OK

PHASE_03

Week 5 – 6BRD Finalized

Requirements Definition

Business requirements and KPI target setting.

We define the To-Be state, establishing clear user stories and acceptance criteria to ensure the proposed solution meets manufacturing efficiency goals.

Key Deliverables:

Business Requirements Document

10 prioritized user stories

KPI target definitions

ASSET_PARSER // REQUIREMENTS

>SCHEMAS: 10 user stories mapped

>METRICS: KPI targets established

>URLS: Requirements traceability set

Validation Passed200 OK

PHASE_04

Week 7 – 8Architecture Build

Solution Design

Analytical dashboard and automation logic design.

We architect the Power BI dashboard and automated dispatching logic, ensuring seamless integration with existing warehouse management systems.

Key Deliverables:

Power BI dashboard layout

Automation logic flowcharts

Implementation roadmap

BUILD_PIPELINE // ANALYTICS

>FRAMEWORK: Dashboard logic compiled

>PERFORMANCE: KPI tracking enabled

>SECURITY: Access control integrated

Validation Passed200 OK

PHASE_05

Week 9 – 10Deployment Ready

Implementation

Phased rollout and performance monitoring.

We execute the implementation plan, monitoring real-time improvements in cycle time and on-time delivery rates against established benchmarks.

Key Deliverables:

Phased rollout execution

Real-time KPI monitoring

Final project documentation

DEPLOY_GATEWAY // LIVE

>PREFLIGHT: 0 critical risks reported

>DNS_PROPAGATION: Dashboard live

>RESULT: Optimization plan operational

Validation Passed200 OK

Project Status

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Explore the complete business case, process maps, and KPI definitions for this supply chain optimization project.

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Portfolio project for the University of Debrecen. Focused on optimizing manufacturing supply chains through rigorous business analysis and data-driven process improvement.

Analysis Active

MNC Ready

Project documentation, BPMN workflows, and KPI definitions for supply chain optimization.

Navigation

Standards

Data-Driven Analysis

Supply Chain Audit

Process Compliance

Validated Metrics

Contact

Debrecen, Hungary

Academic Hours