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Realizing Higher Delivery Productivity Utilizing Work Measurement and Real-Time Data

Realizing Higher Delivery Productivity Utilizing Work Measurement and Real-Time Data. Chris Maughan Project Manager – Workforce Optimization Practice B.S. Industrial and Systems Engineering – The Ohio State University. Presentation Agenda. Introduction

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Realizing Higher Delivery Productivity Utilizing Work Measurement and Real-Time Data

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  1. Realizing Higher Delivery Productivity Utilizing Work Measurement and Real-Time Data Chris Maughan Project Manager – Workforce Optimization Practice B.S. Industrial and Systems Engineering – The Ohio State University

  2. Presentation Agenda • Introduction • Current and Future Operational Challenges in the Delivery and Transportation Industries • Technology • Work Measurement Applications • Examples of Success

  3. Introduction

  4. What are the key factors in a successful supply chain? What are the major pieces of a typical supply chain? FOCUS: Transportation, Delivery, Pickup FOCUS: Productivity Introduction

  5. Current and Future Operational Challenges in the Delivery and Transportation Industry

  6. Labor Cost • Aging Workforce • Higher Wages • More Restrictions • Cost of Healthcare and Benefits Current and Future Operational Challenges in the Delivery and Transportation Industry

  7. Equipment Cost • Upgrading to better equipment • Replacing aging equipment • Regulatory costs • Maintenance • Fuel Current and Future Operational Challenges in the Delivery and Transportation Industry

  8. Network Complexity • Customer Demands • Innovation and Competition • E-Commerce Current and Future Operational Challenges in the Delivery and Transportation Industry

  9. Growth • Uncomfortably fast rates of growth • E-Commerce • Customer Habits Current and Future Operational Challenges in the Delivery and Transportation Industry

  10. Technology

  11. Barcode Scanning • Specific timestamp • Carries data such as quantity, time, equipment ID, employee ID, product and location data, etc. • Innovation in scanning – 3D barcodes, wearable units, paperless labeling Technology

  12. GPS • Real-time location data • Historical location data and movement • Utilizing GPS for short-range RFID • Ability to track almost anything or anyone via a small chip • Provides visibility and data linked to chip Technology

  13. Data Accessibility and Storage • Advantages • Reduction in cost to store data • Data is more easily accessible • WMS and LMS systems utilize more data inputs • Challenges • Overwhelming amount of historical data • How should it be organized? • Using the right data Technology

  14. Work Measurement Applications

  15. Engineered Labor Standards • Labor Management System • Organized and accessible data is in place • Organizes and reads multiple data inputs in multiple formats • Dynamic formulas that link to data inputs • Fully customizable for true discrete calculations • Built in Reporting functions Work Measurement Applications

  16. Engineered Labor Standards • Engineering • Traditional time studies and work measurement at elemental level • Build fixed and variable relationships between characteristics of work that is being performed. • Variable relationships – Key Factor • Typical: per case, per item, per stop, per day, per trip • Possible: per vehicle movement, per scan type, per… Work Measurement Applications

  17. Engineered Labor Standards • Engineering – Cont’d • Design relationships between data inputs and engineered elemental data • Customize LMS to integrate all data inputs and engineering data • Output accurate process models and discrete goal times • Custom-designed productivity reports Work Measurement Applications

  18. Engineered Labor Standards • Engineering – Cont’d • Conduct process improvement via simulation within LMS by changing data inputs to achieve optimal outcomes • Make process-design decisions based on virtual models then implement for real operations Work Measurement Applications

  19. Reporting, Planning, Executing • Reporting • LMS creates customizable operational reports • Utilize data to compare planned vs. actuals • Analyze trends and cross-references • Identify optimal relationships in data • Use for planning Work Measurement Applications

  20. Reporting, Planning, Executing • Planning • Design more efficient routes • Model different plans in real-time to choose the optimal setup based on data inputs • Continuous improvement capabilities • Positively impacts quality and service metrics Work Measurement Applications

  21. Reporting, Planning, Executing • Executing • Monitor variance from plan at the elemental level and address issues • “Fire fighting” can be replaced by proactive operations management and supervision. • Link incentive pay to productivity as well as quality metrics Work Measurement Applications

  22. Examples of Success

  23. Reduced percentage of re-handled cases from 12% to 7%. Reduced steps per case delivered from 55 to 45. Re-configured load inside trailer to decrease time at delivery by 14%. Re-designed packaging on certain cases to reduce driver handling time. Decreased average planned day of driver from 9.5 hours to 8.2 hours. Reduced average routes per day from 110 to 95. Increased stops per mile driven from 1.7 to 2.0. Examples of Success

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