How Celonis Can Enhance Inventory Management Through Process Mining

Inventory issues rarely start in the warehouse. They begin in broken processes.

If your organization struggles with stockouts, excess inventory, inaccurate forecasts, or high carrying costs, the root cause is often hidden inside your systems. Celonis inventory management solutions, powered by process mining, uncover those hidden inefficiencies and turn operational data into measurable improvements.

In this article, you’ll learn how Celonis enhances inventory management, what practical use cases look like, and how companies reduce working capital while improving service levels.

What Is Process Mining — and Why It Matters for Inventory?

Process mining is a data-driven technique that analyzes event logs from ERP systems (such as SAP or Oracle) to visualize how processes actually run — not how they are designed.

Instead of relying on assumptions, spreadsheets, or manual audits, process mining:

Extracts real transaction data
Maps end-to-end workflows
Identifies bottlenecks and deviations
Quantifies financial impact

When applied to inventory management, this provides complete transparency across:

Purchase-to-Pay (P2P)
Order-to-Cash (O2C)
Replenishment processes
Warehouse operations
Master data management

The result? Faster decisions, lower inventory costs, and improved service levels.

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How Celonis Enhances Inventory Management

1. Identifying Root Causes of Stockouts

Stockouts often appear as a supply problem. In reality, they may be caused by:

Late purchase order approvals
Incorrect safety stock settings
Supplier delays
Forecast inaccuracies
Manual workarounds

Celonis inventory management analytics trace every stockout back to its process origin. Instead of reacting, companies fix systemic causes.

Example:
Celonis can reveal that 35% of delayed orders are caused by approval bottlenecks exceeding SLA targets.

This shifts inventory management from reactive firefighting to structural improvement.

2. Reducing Excess and Slow-Moving Inventory

Excess stock ties up working capital and increases storage costs.

Using process mining for inventory, Celonis helps companies:

Detect over-ordering patterns
Identify duplicate suppliers
Flag materials with low turnover
Analyze demand variability

By correlating purchasing behavior with actual consumption, businesses can adjust reorder points and safety stock levels intelligently.

3. Improving Inventory Turnover & Working Capital

Inventory turnover is a direct reflection of process efficiency.

Celonis enables:

Real-time KPI tracking
Automated alerts for deviations
Scenario simulations for optimization
Working capital benchmarking

Companies can identify:

Payment term mismatches
Procurement inefficiencies
Replenishment delays
Process variants increasing lead time

By optimizing these, organizations often free up millions in working capital without increasing risk.

4. Enhancing Supplier Performance & Lead Time Reliability

Inventory problems frequently originate upstream.

Celonis process mining evaluates:

Supplier lead time adherence
Purchase order change frequency
Contract compliance
Invoice discrepancies

By identifying unreliable suppliers or inefficient procurement steps, organizations stabilize inventory flow and reduce emergency orders.

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Case Study: Manufacturing Company Reduces Inventory by 18%

A global manufacturing company faced:

High safety stock levels
Frequent stockouts in high-demand SKUs
Slow-moving inventory buildup

Using Celonis inventory management analytics, they discovered:

42% of purchase orders were changed after creation
Approval delays increased replenishment time by 5 days
Demand signals were not consistently reflected in ERP

After redesigning procurement workflows and automating approval thresholds:

Inventory levels reduced by 18%
Service levels improved by 6%
Working capital improved significantly

The transformation was not about buying more stock — it was about fixing broken processes.

Why Traditional Inventory Optimization Falls Short

Most inventory optimization tools rely on forecasting and mathematical models. While important, they often ignore process behavior.

Process mining adds the missing layer:

Traditional Approach	Process Mining Approach
Focus on forecasts	Focus on real execution data
Static reporting	Real-time monitoring
Reactive adjustments	Continuous improvement
Limited root cause visibility	Full process transparency

Celonis inventory management stands out because it connects operational data directly to financial outcomes.

Key Benefits of Celonis for Inventory Management

Reduce stockouts and excess inventory
Improve demand planning accuracy
Increase inventory turnover
Free working capital
Enhance supplier reliability
Enable data-driven decision-making

Most importantly, it creates a culture of continuous process improvement.

How Celonis Improves Inventory Management Fast