Overview

Nakisa Workforce Planning Software is a comprehensive, AI-driven solution tailored for large enterprises managing complex and dynamic organizational structures. It provides end-to-end functionality that supports strategic and operational workforce planning, organizational design, and real-time org chart visualization. The platform combines advanced analytics and scenario modeling to help organizations forecast workforce needs, optimize talent allocation, and adapt quickly to changing business demands. By connecting long-term strategic goals with day-to-day operational agility, Nakisa enables businesses to maintain workforce alignment with evolving corporate objectives and market conditions.

Features and Capabilities

• Strategic Workforce Planning: Enables creation of detailed, data-driven annual headcount plans aligned with business objectives and future growth strategies.
• Operational Workforce Planning: Supports short-term workforce adjustments by aligning current staffing with immediate business needs and operational realities.
• Organizational Design: Provides advanced scenario modeling tools to visualize, simulate, and optimize organizational structures before implementation.
• Org Chart Visualization: Offers clear, real-time visibility into complex organizational hierarchies, facilitating communication and transparency.
• Advanced Analytics: Harnesses AI-driven insights for forecasting workforce trends, identifying gaps, and supporting informed decision-making.
• Collaboration Tools: Facilitates cross-functional team collaboration and streamlines approval workflows to ensure alignment across stakeholders.
• Integration Capabilities: Seamlessly connects with existing ERP and human capital management (HCM) systems for unified data management.
• User-Friendly Interface: Features an intuitive, easy-to-navigate user experience that reduces training time and improves adoption.
• Scalability: Designed to meet the demands of enterprise-scale organizations, supporting large datasets and complex organizational models with ease.