Phased legacy ERP migration for uninterrupted transformation
Phased migration of legacy ERP systems in the public sector helps avoid downtime and ensures process continuity by focusing on automation and data.
AUTHOR / Synergy Consulting
Editorial contributor
Cross-team work, business processes, documents and enterprise technology implementation.
Phased migration of legacy ERP systems in the public sector helps avoid downtime and ensures process continuity by focusing on automation and data.
AI-driven Scriptum is set to transform document management and workflow automation by 2026, accelerating document processing and business process automation.
By 2026, over 80% of large enterprises will leverage a combination of RPA and low-code platforms to optimize business processes. This approach accelerates development time and enhances automation efficiency.
Discover how the combination of AI and low-code platforms enables CIOs to rapidly automate business processes, minimize risks, and optimize operations.
By 2026, over 75% of new enterprise applications are projected to be developed using low-code or no-code platforms. Integrating artificial intelligence into these platforms significantly speeds up the creation and optimization of BPM systems.
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
By 2026, over 80% of large enterprises plan to utilize integrated RPA and low-code solutions for business process automation, highlighting the critical role of platforms like Scriptum. This trend is driven by the need to enhance operational efficiency, reduce costs, and accelerate time-to-market for
Integrating enterprise systems via API is a key factor for quickly bringing new products and services to market. This approach ensures flexibility, scalability, and efficiency in data exchange across diverse IT landscapes.
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.
Integrating AI and low-code platforms significantly accelerates business processes and reduces operational costs for companies.
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.