As an Infor Delivery Partner, Surety Systems has continuously monitored changing trends, requirements, and a more recent technical pivot within the Infor landscape, from legacy foundations to current cloud-native innovations.
For decades, the Infor WFM Staffing Optimizer was known for clinical labor management, providing the reliable, rule-based foundation that healthcare organizations depended on for complex scheduling. However, Infor is officially moving away from these standalone solutions toward a unified, AI-driven cloud ecosystem.
With the decommissioning of the Staffing Optimizer and notable shifts in Infor’s 2026 landscape, organizations must transition from managing isolated on-premises servers to overseeing a mobile-first experience. For users still on legacy platforms, this shift is the final window to bridge the gap between operating on old hardware and optimizing with a fully integrated cloud strategy.
Critical Dates and Current Decommissioning Status
- Historical Milestone: December 31, 2024, marked a major turning point as “Supplementary Support” ended for most standalone versions of the Staffing Optimizer. This date marked the end of proactive bug fixing and minor enhancements, leaving the software in a static state.
- Sustained Support: The Staffing Optimizer officially entered the “Sustaining Maintenance” phase in early 2026. This means Infor is no longer developing new features or releasing non-critical patches or bug fixes to maximize functionality in the Staffing Optimizer.
- Technical Hard Stop: Throughout 2026, Infor users will face both a lack of general support for their Infor software and a hard infrastructure wall for key dependencies (e.g., legacy Java, Silverlight) that have reached end-of-life. Running the Optimizer on unsupported stacks creates a massive security vulnerability that modern firewalls and compliance audits can no longer ignore.
What Does This Mean for You?
Drivers for Change
The end of support for Infor’s Staffing Optimizer is driven by changing requirements for managing organizational data, labor, and security standards. Legacy on-premises systems have become prime targets for cyber threats, requiring optimized patching, encryption, and security tools to maintain compliance.
Beyond security, Infor is addressing the long-standing Data Silo Problem. While older tools relied on complex, manual interfaces to navigate the master schedule, modern tools are natively integrated, providing a single version of truth across the entire enterprise.
In addition, the legacy Optimizer was inherently reactive, constrained by static, “if-then” rules that couldn’t keep pace with the modern healthcare landscape. New cloud-native tools are predictive, utilizing machine learning to anticipate staffing needs before they become crises.
Key Technology Replacements
As the legacy Infor Staffing Optimizer moves into its “Sustaining Maintenance” phase, the shift represents a complete reimagining of labor management for the Infor landscape in 2026 and beyond. Here’s a closer look at a few key software replacements:
Infor Clinical Bridge:
Unlike the standalone Optimizer, which required manual data entry, Clinical Science uses the Infor Clinical Bridge to pull real-time workload and acuity data directly from EMRs like Epic and Oracle Health. Using the GRASP (General Responsibility Assignment Software Patterns) methodology, the system automatically calculates the amount of care required based on live patient documentation, ensuring staffing levels align with actual patient needs.
AI-Powered Forecasting:
Modern Infor WFM uses machine learning models that analyze years of historical trends, real-time census data, and external variables (e.g., local flu outbreaks or weather events). This allows hospital leadership to see staffing needs weeks in advance, thereby improving labor cost management and preventing clinician burnout.
Mobile-First Engagement:
The outdated desktop interface in the Staffing Optimizer has been replaced by intuitive, mobile-first tools. This gives frontline staff self-service autonomy, enabling them to bid on open shifts, swap assignments, and manage their availability directly from their smartphones. For organizations, this means faster shift fulfillment, higher employee retention, and increased flexibility.
Best Practices for Navigating the Migration Path
For previous Infor Staffing Optimizer users who are migrating to Infor Clinical Science, the modern, cloud-native pillar of the broader Infor Workforce Management suite.
- Readiness Assessment: Audit current state workflows and validate data integrity. This assessment allows you to identify which legacy configurations are still serving your business and which have become technical debt.
- Data Retention & Disposal Authority: Before deleting anything, map legacy records to regulatory requirements (i.e., GDPR, HIPAA, or local state records). Identify what must be moved, what must be archived, and what can be safely destroyed.
- Data Cleanup: Before moving to the cloud, archive historical data that is no longer needed for daily operations. Migrating uncleaned or outdated data only slows down the new system and complicates compliance initiatives.
- Process Mapping: Transition from manual, rule-based optimization logic to automated Clinical Science workflows. This involves mapping your clinical requirements to modern best practices, ensuring your new system is built for evolving healthcare demands.
- Phase-Out Operations: Gradually move departments or facilities to the new system, keeping the legacy Optimizer in a “read-only” state for a buffer period to handle historical audits.
- Implement Clinical Bridge Early: The Clinical Science module relies on real-time EMR data from systems like Epic and Cerner. Prioritize the HL7v2 or FHIR integration early in the project to ensure Optimizer logic has the data it needs to function effectively.
- Parallel Testing: Before decommissioning your legacy Staffing Optimizer, run the new cloud system in parallel. This allows you to validate staffing outputs against the old system’s results, ensuring the AI-driven forecasts and automated suggestions are accurate.
Additionally, the Infor Leap Program is specifically designed to help on-premise customers transition to the cloud using a fixed-fee service model, mitigating the financial and operational risks associated with large-scale ERP upgrades. By following this phased approach, organizations can ensure their entire staffing strategy evolves as they tap into new functionality within their modern Infor landscape.
Optimizing Your Long-Term Infor WFM Investment
By moving to a unified cloud environment, organizations can replace the burden of outdated infrastructure with scalability that evolves alongside their clinical needs.
If your team lacks the bandwidth to navigate complex decommissioning timelines and new 2026 Infor landscape requirements, we can help. Partner with Surety Systems to optimize your enterprise systems and ensure a seamless transition for your workforce.
