When a tissue bank or Organ Procurement Organization (OPO) introduces AI into its donor eligibility and suitability workflow, an important question follows: What actually happens
Artificial intelligence is transforming donor eligibility and suitability review by helping tissue banks and organ procurement organizations (OPOs) optimize the time to process complex donor
IBM has officially retired TM1 Architect and Perspectives as of October 31, 2025, concluding a significant chapter for TM1 users. Over the years, these interfaces became essential for development and reporting but lagged in modernization. Their retirement allows IBM to focus on advancements like Planning Analytics for Excel and Planning Analytics Workspace, promoting a future with enhanced capabilities and intelligence in analytics.
IBM Planning Analytics Workspace released a Git integration feature that allows users to interact with a Git repository directly from the Data and Models interface. This integration feature can significantly improve version control, server management, and collaboration.
IBM Planning Analytics is a multi-dimensional, in-memory, online analytical processing (OLAP) business performance management solution that facilitates strategic business planning, budgeting, reporting, and forecasting.
In the ever-evolving landscape of modern business, harnessing the power of cutting-edge technologies is not just advantageous—it’s essential. Leveraging AI for business can position you for sustained success in today’s dynamic marketplace.
IBM Planning Analytics for Excel (PAfE) is a Microsoft Excel add-in that empowers users to build sophisticated reports and perform ad-hoc analysis using real-time Planning Analytics data. The add-in offers five unique report types for users to create.
IBM Planning Analytics Workspace is the web-based interface for Planning Analytics. The tool expands on the capabilities of Architect and Planning Analytics for Excel (PAfE).
TM1py enables IBM Planning Analytics users to do more with their data than ever before by leveraging Python’s abilities, expanding on IBM’s TurboIntegrator functionality, and integrating with previously incompatible systems.
