Custom development or off-the-shelf: when to build or buy
Finding the balance between rapid off-the-shelf software deployment and custom development freedom, evaluating TCO, and avoiding technical debt traps.
AUTHOR / FinTraining Academy
Digital Practices Editor
Serhiy Boiko. Digital Practices Editor. The profile covers practical publications and professional commentary on corporate learning, digital transformation, and team development.
Finding the balance between rapid off-the-shelf software deployment and custom development freedom, evaluating TCO, and avoiding technical debt traps.
Process Mining methodology reconstructs real task flows using digital footprints, revealing hidden bottlenecks and unauthorized workarounds invisible to management.
How to avoid cementing inefficiencies, replace fragile RPA scenarios with reliable API integrations, and safely implement AI into operational workflows using BPMN and DMN standards.
An analysis of architectural approaches to business process automation. Comparing Scriptum, Camunda, Bonita, and UiPath to eliminate shadow processes and enable flexible modeling.
Effective enterprise process automation requires separating workflow orchestration, flexible case management, and business rules. Learn how to avoid hardcoded logic and identify shadow routes.
A guide to BPM, RPA, and workflow automation for IT architects. Learn how to combine BPMN, DMN, and Process Mining to avoid technical debt and achieve end-to-end orchestration.
RPA is a useful temporary bridge to legacy systems following an ERP deployment. However, automating Excel-based workflows, email approvals, and fragmented responsibilities often accelerates technical debt rather than resolving it.
Phased migration of legacy ERP systems in the public sector helps avoid downtime and ensures process continuity by focusing on automation and data.
By 2026, over 70% of successful digital transformation initiatives will rely on an effective Data Governance strategy integrated with artificial intelligence capabilities. This will enable addressing data quality issues critical for system integration. The increasing complexity of enterprise IT land
Increasing data volumes and stricter regulatory requirements necessitate that organizations implement comprehensive Data Governance approaches. Effective system integration is a key factor in realizing these strategies.
The challenge of disparate data and the absence of a single source of truth for key entities is critical to business efficiency. System integration and MDM are key to resolving this.