Fourth Introduces iQ 2.1 to Deliver Smarter Workforce & Inventory Recommendations

Fourth has unveiled iQ 2.1, an upgraded version of its mobile platform designed to embed AI-driven recommendations directly into the manager’s workflow. With this update, hospitality operators gain new capabilities around labour forecasting, inventory alerts and HR-task automation in real-time.

What’s New in iQ 2.1

• A Forecast Labour Adjustment feature which monitors changes in sales forecasts, recalculates optimal staffing levels, and notifies managers when action is required such as opening shifts or reducing labour costs.
• Enhanced workforce-management actions: Managers can now approve or reject shift swaps, drop or give shifts, manage unavailability, and receive schedule-deadline alerts all from the app.
• HR automation enhancements: The update includes alerts for onboarding completion, right-to-work verification (via TrustID), and employee change-request status all within the mobile workflow.
• Inventory and quality alerts: For example, the app now notifies managers when wastage trends exceed expected norms and flags missing product line-item codes (PLUs) to reduce stock-out risk and margin leakage.
• App-wide enhancements: Building on the earlier launch of 20+ recommendations, iQ 2.1 expands the reach of Fourth’s AI-based guidance across workforce, HR and inventory management.

Why It Matters for Hospitality and Multi-Unit Operators

In a sector where staffing, inventory and operational costs are extremely tight, Fourth’s update offers several advantages:

• Proactive decision-making: Rather than reacting late to high labour costs or inventory waste, managers get alerts and recommendations ahead of time enabling faster corrective action.
• Operational alignment: By integrating workforce, HR and inventory functions into a single app with AI-driven guidance, organisations can break down silos and improve consistency across locations.
• Mobile-first empowerment: Store or restaurant managers gain richer insights on the go whether approving shifts or responding to stock issues without needing to pull separate reports or dashboards.
• Margin protection: The new inventory alerts and labour forecasts help operators guard against common cost-leakages in hospitality (over-staffing, waste, incorrect SKU coding).
• Scalability for growth: For operators with hundreds or thousands of locations, embedding intelligence into frontline workflows supports scaling performance without simply adding more resources.

Implementation & Practical Considerations

• Data readiness: To make full use of the AI recommendations, operators should ensure their forecasting, sales and workforce data are accurate and up to date forecast misalignment could diminish value.
• Change management: Shifting from manual or instinct-based decision-making to alerts and guided recommendations requires training and buy-in from managers and regional operations teams.
• Monitor results: Organisations should define metrics like labour-cost variance, inventory waste rate, shift fulfilment rate, and HR-onboarding completion and track pre- and post-deployment to measure impact.
• Mobile adoption: Since many recommendations are surfaced within the app, ensuring high usage and engagement among managers is critical for the value to materialise.
• Governance & oversight: While the AI provides suggestions, human review remains important. Operators should build workflows that allow managers to inspect, accept or adjust recommendations rather than relying entirely on automation.

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