Metadata-Version: 2.4
Name: erpflow-miner
Version: 0.1.0
Summary: ERP and SAP process mining toolkit for Procure-to-Pay workflows, bottleneck detection, and automation candidates.
Author: Jagadeesh Vasanthada
License: MIT
Project-URL: Homepage, https://github.com/raghavachellu/erpflow-miner
Project-URL: Repository, https://github.com/raghavachellu/erpflow-miner
Project-URL: Issues, https://github.com/raghavachellu/erpflow-miner/issues
Keywords: sap,ariba,erp,procurement,supply-chain,analytics,ai,automation,p2p
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: typer>=0.12.0
Requires-Dist: rich>=13.7.0
Provides-Extra: dev
Requires-Dist: pytest>=8.0.0; extra == "dev"
Requires-Dist: build>=1.2.0; extra == "dev"
Requires-Dist: twine>=5.0.0; extra == "dev"
Dynamic: license-file

# ERPFlow Miner

**ERP and SAP process mining toolkit for Procure-to-Pay workflows, bottleneck detection, and automation candidates.**

ERP and SAP Process Mining Toolkit for Procure-to-Pay (P2P), Bottleneck Detection, and Automation Insights

ERPFlow Miner is an open-source, production-ready Python library designed to analyze ERP, SAP, SAP Ariba, and Procure-to-Pay (P2P) workflows using process mining techniques.

It helps organizations identify process inefficiencies, bottlenecks, delays, and automation opportunities across enterprise systems.

## Overview
```
Modern enterprise workflows—especially in procurement and finance—often suffer from:

Delayed approvals
Manual handoffs
Process inefficiencies
Lack of visibility across systems
Limited automation insight

ERPFlow Miner enables teams to analyze event logs and uncover:

Where delays occur
Which transitions take the longest
Which processes can be automated
How workflows can be optimized
```

## Key Use Cases
```
Procure-to-Pay (P2P) process analysis
SAP / SAP Ariba workflow optimization
Procurement cycle time reduction
Bottleneck detection in approvals and workflows
Automation candidate identification (RPA / AI)
Process compliance and audit support
ERP analytics and digital transformation initiatives
```
## Features
```
Process mining for ERP and SAP workflows
Bottleneck detection based on event durations
Threshold-based delay identification
Lightweight and fast execution
CLI + Python SDK support
Easy integration with CSV-based event logs
Extensible for ML-based process intelligence
```

## Core capabilities

```
Event Log Analysis: Process structured logs from ERP/SAP systems
Bottleneck Detection: Identify slow transitions between workflow stages
Process Visibility: Understand real execution paths vs expected flows
Automation Insights: Highlight steps suitable for RPA or AI automation
Cycle Time Analysis: Measure time between key procurement stages
ERP Integration Ready: Compatible with SAP, SAP Ariba, and P2P workflows
Audit & Compliance Support: Provide insights into process delays and exceptions
```


## Install

```bash
pip install erpflow-miner
```

## Python Usage

```
from datetime import datetime
from erpflow_miner.core import Event, mine_bottlenecks

events = [
    Event("PO-1", "Requisition Created", datetime.fromisoformat("2026-01-01T09:00:00")),
    Event("PO-1", "PO Approved", datetime.fromisoformat("2026-01-03T09:00:00")),
]

bottlenecks = mine_bottlenecks(events)

for b in bottlenecks:
    print(f"{b.from_activity} → {b.to_activity}: {b.duration_hours} hours")
```

## CLI Usage

```bash
erpflow mine p2p_events.csv --threshold-hours 24
```

CSV columns: `case_id,activity,timestamp` where timestamp is ISO format.

## Build and Publish

```bash
python -m pip install --upgrade build twine
python -m build
twine check dist/*
twine upload dist/*
```

## MIT License

Author: Jagadeesh Vasanthada
