Operational Workload Reduction and Optimization

The Business & The Challenge

An industrial real estate firm with global operations was struggling with:

• Non-standardized operator roles and responsibilities
• Excessive and inconsistent workload distribution
• Overburdened frontline operators, leading to inefficiencies and performance variability

The primary objective:
➡️ Reduce workload, decrease variability, and define best practices to improve operational effectiveness.

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Approach & Methodology

Falconi applied a structured methodology to assess and optimize operational workload across frontline teams:

Step-by-Step Process

1. Pre-Work & Planning
   
    
   • Collected initial data, mapped operator workload, and scheduled observations
2. Discovery Interviews
   
    
   • Conducted 1-on-1 interviews remotely with operators to understand job dynamics
3. Observations
   
    
   • Shadowed daily activities and captured detailed time-motion data
4. Data Consolidation & Root Cause Analysis
   
    
   • Analyzed variability across roles, identified root causes of inefficiencies
5. Driver Definition & Categorization
   
    
   • Mapped 22 Activity Drivers contributing to workload differences
 
6. Pain Point Mapping & Prioritization
   
    
   • Identified 42 operational pain points, including 19 Quick Wins
    
   • Prioritized based on impact, complexity, financial investment, and time burden
 
7. Final Report & Recommendation Delivery
   
    
   • Provided a detailed plan for process improvement and workload balance

Results Achieved

Metric                                                                                            Outcome

Operational Activities  Mapped                                         47

Total Observations  Conducted                                        308

Operator Working Hours  Observed                               171.2 hrs (over 6 weeks)

Pain Points Identified                                                             42 (including 19 Quick  Wins)

High-Priority Pain  Points                                                     5

Priority-Level Pain  Points                                                   11

Estimated Annual  Time-Saving per Operator           168–278.4 hours

Estimated Annual Cost  Savings                                      $242,137 – $401,797

✅ Standardized and simplified routine roles
✅ Reduced unnecessary variability in daily operations
✅ Delivered a clear roadmap for improving operational efficiency and employee experience

Why It Worked

• Data-backed assessment of real operational behaviors, not just assumptions
• Focus on quick wins combined with deeper structural changes
• Cleat prioritization framework allowed high-impact actions to be     implemented swiftly
• Direct input from operators ensured realistic and practical solutions

 Conclusion

Falconi helped a leading real estate industrial firm transform an overloaded and inconsistent operational model into a streamlined, standardized, and efficient workforce structure. With over $400K in annual savings potential and major reductions in workload, the project not only improved performance but also boosted workforce sustainability.

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