Smart Operations by Transforming Data Into Value

Transforming Data Into Value

With data, companies can:

• Describe what has happened through data visualization,
• Predict what will happen through forecasting, and
• Prescribe what should happen through optimization.

Transforming Data Into Value

With data, companies can:

• Descriptive: performance dashboards (e.g., spend analysis to find ways for savings), disruption alerts (to avoid costly down time)
• Predictive: forecasting, customer classification/clustering (to better serve and retain customers), recommendation (for cross selling)
• Prescriptive: worker scheduling/production planning (to achieve minimum labor/production costs), pricing and revenue management (to obtain maximum revenue given limited capacity)

 

Cost-Benefit Analysis of Radio-Frequency Identification (RFID)

• Conducted quantitative analysis of implementing a RFID inventory tracking system to reduce human error in lost inventory and mis-shipment for a steel manufacturing company
• Estimated return-on-investment (ROI): 80% (first year) and 300% (subsequent years)

Work Measurement, Simulation and Optimization Study

• Applied time and motion study technique, simulation and optimization methods to measure, analyze and propose recommendations to improve technicians' work and on-time performance for a healthcare provider
• Prevented a potential 20% increase in technician labor cost