Workforce OS | Operations Automation

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Operations

Workforce Management OS

Unified platform for scheduling, shift management, time tracking, and payroll validation for 1,000+ employees.

Operations automation case study featuring workflow automation and ai implementation.

-70%

Scheduling Time

-92%

Payroll Errors

12-18%

Labor Cost Savings

Overview

A services company with over 1,000 hourly employees needed a unified platform for scheduling, shift management, time tracking, and payroll validation. The system achieved unified visibility across all business units with significant labor cost savings.

Business Context

The services company operated across 15 locations with a primarily hourly workforce spanning multiple departments including facilities management, security, hospitality, and maintenance. Each location manager maintained their own scheduling spreadsheets, leading to inconsistent practices, coverage gaps, and no visibility into company-wide staffing patterns. The legacy payroll system required manual data entry from these disparate spreadsheets, creating a monthly reconciliation nightmare that consumed the HR team for days and frequently resulted in pay discrepancies that damaged employee trust. Overtime costs were spiraling because managers couldn't see when employees were approaching overtime thresholds until it was too late. The leadership team recognized they were losing money to inefficient scheduling and payroll errors, and more importantly, they couldn't scale their operations without solving the workforce management problem first.

How We Built It

We built a comprehensive workforce management platform using Node.js microservices architecture with MongoDB providing flexible document storage optimized for the varied scheduling patterns across different business units. GraphQL serves as the API layer, enabling efficient queries that can fetch complex scheduling views without multiple round-trips. The Next.js frontend delivers a responsive experience optimized for both desktop use by schedulers and mobile access for frontline managers and employees. Azure AD SSO integration ensures secure access while maintaining the company's existing identity management infrastructure. The overtime and payroll validation engine applies complex rules including union agreements, state-specific overtime calculations, and meal break requirements, automatically flagging potential violations before they occur. The shift planning interface features an availability matrix that visualizes employee preferences, certifications, and conflict constraints, making optimal scheduling decisions intuitive. Real-time coverage heatmaps show staffing levels across all locations simultaneously, enabling rapid identification of gaps and over-staffing situations. We implemented an AI workforce assistant that uses skill-based matching to recommend optimal shift assignments, considering factors like employee tenure, performance ratings, certification requirements, and scheduling preferences.

Challenges

Scheduling done in spreadsheets

Legacy payroll system with limited integrations

Frequent payroll discrepancies

No visibility of staffing shortages

High administrative workload

What We Delivered

Workforce backend with Node.js microservices

Overtime and payroll validation engine

Shift planning interface with availability matrix

Real-time coverage heatmaps

AI workforce assistant with skill-based matching

Azure AD SSO with full audit trail

GDPR-compliant access control

Tech Stack

Node.js, MongoDB, GraphQL, Next.js, Azure AD SSO, Docker, Kubernetes

Results

-70%

Scheduling Time

-92%

Payroll Errors

12-18%

Labor Cost Savings

Strategic Impact

The 70% reduction in scheduling time gave managers back hours every week that they now invest in operations and team development rather than spreadsheet manipulation. Payroll errors dropped by 92%, virtually eliminating the pay discrepancy complaints that had been damaging employee morale and creating administrative burden for the HR team. The labor cost savings of 12-18% came from multiple sources: better overtime management through proactive visibility, optimized staffing levels that reduced both over-staffing and costly last-minute coverage gaps, and improved retention as employees experienced more consistent and fair scheduling. For the first time, the company gained unified visibility across all business units, enabling strategic workforce planning and the ability to flex staff across locations based on demand. The GDPR-compliant access controls and full audit trail satisfied compliance requirements while providing accountability for scheduling decisions. The AI workforce assistant's skill-based matching improved service quality by ensuring appropriately qualified employees were assigned to specialized tasks. Employee satisfaction improved as the self-service portal gave workers visibility into their schedules, the ability to request swaps, and transparency into how scheduling decisions were made. The reduction in scheduling conflicts and last-minute changes also decreased no-show rates and improved overall team morale. The platform positioned the company to scale their operations confidently, with new locations now integrated into the workforce management system in days rather than developing their own isolated scheduling processes. Management now has data-driven insights into workforce utilization patterns, enabling strategic decisions about hiring, training investments, and capacity planning that were previously impossible.