Process Management News Round-Up: October 2025 Edition

As we move deeper into 2025, business process management continues to evolve beyond automation. This month’s Process Management News Round-Up highlights a clear shift in focus — from chasing the next AI breakthrough to reinforcing the ethical, secure, and sustainable foundations that make intelligent automation truly reliable.

Balancing Accuracy and Fairness in Predictive Process Monitoring

A new paper from KU Leuven’s Research Center for Information Systems Engineering, Achieving Group Fairness through Independence in Predictive Process Monitoring by Jari Peeperkorn and Simon De Vos, tackles one of the most important challenges in modern process intelligence: algorithmic fairness.

Predictive Process Monitoring (PPM) uses historical process data to forecast future outcomes — such as predicting whether a loan application will be approved or if a shipment will be delayed. But when the data behind these models reflect existing inequalities, the predictions risk reinforcing them.

The researchers propose a framework to detect and mitigate bias in predictive models using independence metrics — namely ΔDP (demographic parity), ABPC, and ABCC — and a composite loss function combining the Wasserstein distance with binary cross-entropy. This approach allows organizations to balance fairness and predictive performance rather than trading one for the other.

Beyond the technical details, the paper echoes a broader regulatory momentum: the EU AI Act requires demonstrable fairness and explainability in automated decision systems. Peeperkorn and De Vos provide concrete methods for compliance and transparency — a step toward truly responsible process intelligence.

Action points:

• Integrate fairness metrics into your PPM model evaluation pipeline.
• Use distribution-based (threshold-free) fairness measures for a more reliable assessment.
• Regularly test models for demographic parity violations before deployment.

ERP Systems Under Attack: Why Process Security Matters

A recent article on ERP Today warns that enterprise resource planning systems — the digital backbone of most organizations — are facing a wave of increasingly sophisticated cyberattacks. The interconnectedness of ERP systems with AI, supply chains, and IoT has expanded both efficiency and vulnerability.

Traditional perimeter defenses are no longer enough. Attackers exploit workflow misconfigurations, weak user permissions, and unpatched integrations to gain access to critical business processes. The result: downtime, data loss, and process corruption.

From a BPM perspective, ERP cybersecurity isn’t just an IT concern — it’s a process resilience challenge. Ensuring that process data flows securely across departments and partners must become part of standard process design.

Practical steps for stronger ERP processes:

• Map and monitor end-to-end ERP workflows to detect unusual patterns early.
• Integrate process mining and security monitoring for real-time anomaly detection.
• Establish a closed feedback loop between IT security and process management teams.

In essence, resilience in 2025 will come not from isolation, but from visibility and control.

Sustainable BPM: Modeling Processes for ESG Impact

FlowWright’s recent feature on Sustainable BPM underlines a critical shift in how organizations define “optimization.” Efficiency alone is no longer enough; businesses are now measuring process success by how it supports Environmental, Social, and Governance (ESG) goals.

By integrating sustainability indicators into business process models — such as CO₂ emissions per process instance, resource consumption, or inclusivity measures — BPM systems can make sustainability operational rather than aspirational.

For example, mapping an order fulfillment process doesn’t just highlight delivery speed; it can also expose carbon hotspots or supplier compliance gaps. This evolution is turning BPM into a driver of measurable ESG progress.

Implementation ideas:

• Include sustainability KPIs directly in process dashboards.
• Simulate the impact of process redesigns on environmental and social metrics.
• Use process mining to identify steps with disproportionate energy or material use.

The result is a new form of operational intelligence — one that connects productivity with purpose.

Process Debt Meets AI: The Hidden Bottleneck

As organizations push AI deeper into operations, a recurring theme emerges: AI fails where processes are broken. “Process debt” — the accumulation of outdated, inconsistent, or poorly documented workflows — is increasingly recognized as a major obstacle to successful automation.

Even the most advanced models can’t deliver value if they’re fed inconsistent process data. Fragmented approval chains, redundant handovers, and missing audit trails create noise that AI can’t interpret reliably.

Cleaning up process debt, therefore, isn’t a maintenance exercise — it’s a strategic enabler. Organizations investing in AI transformation must first establish process hygiene: standardization, ownership, and measurable governance.

Examples of process debt symptoms:

• Duplicate or shadow processes across regions.
• Unclear escalation paths causing approval loops.
• Legacy process logic that’s incompatible with current systems.

Process mining tools can help surface these inefficiencies and quantify their cost — turning “process cleanup” from a one-off project into a continuous discipline.

Food for Thought

Fairness, security, and sustainability aren’t side projects — they’re the building blocks of trustworthy process intelligence. Each reinforces the other: fairness makes outcomes ethical, security makes them dependable, and sustainability makes them enduring. The future of BPM will belong to organizations that can align all three without compromise.

Summary

This month’s business process management news reflects a clear trend: 2025 is not about expanding automation at all costs, but about reinforcing its ethical, secure, and sustainable foundation.

Whether it’s fairness in predictive models, protecting ERP systems, embedding sustainability into process design, or tackling legacy debt before AI transformation — the message is consistent. The future of BPM belongs to those who treat transparency and reliability as the real sources of competitive advantage.

If you’re exploring how to strengthen your process intelligence strategy along these lines, let’s talk — the team at Noreja is always open for a conversation or demo.

FAQ

What are the main business process management trends for 2025?

In 2025, BPM is shifting from pure automation toward responsible, resilient process design — focusing on fairness in predictive models, cybersecurity in ERP systems, sustainability through ESG-driven BPM, and reducing process debt before scaling AI.

Why is fairness important in predictive process monitoring?

Fairness ensures that AI models used in process management do not reinforce historical bias. It’s a regulatory and ethical requirement under frameworks like the EU AI Act.

How can organizations improve ERP process security?

By continuously monitoring workflows, integrating anomaly detection, and aligning IT security with BPM governance, organizations can protect ERP systems from evolving cyber threats.

What is Sustainable BPM?

Sustainable BPM integrates environmental, social, and governance (ESG) goals directly into process design — measuring not only efficiency but also long-term impact.

What does “process debt” mean?

Process debt refers to outdated, inconsistent, or poorly documented workflows that hinder automation and create unreliable data for AI systems. Cleaning it up is key for scalable transformation.