MFG Consulting Select Projects and Results
Organizations are increasingly looking for ways to maximize the value of their assets, earn additional revenues from customers, and find ways for cost avoidance. Using analytics for integrated decision-making through business optimization can average $35 saved for every $1 spent on operational improvements; delivering the same or better service for more efficient cost with dramatic impact to an organization’s bottom line.
Specializing in data in dynamic situations that combine optimization modeling with simulation, statistical analysis and forecasting, organizations can benefit by address opportunities in the areas of:
Specializing in data in dynamic situations that combine optimization modeling with simulation, statistical analysis and forecasting, organizations can benefit by address opportunities in the areas of:
- Managing fleet capacity and optimization in transportation
- Decision support system development for asset allocation
- Scheduling system development
- Yield and pricing models
- Rationalized capacity based on current and anticipated market conditions
- Cost efficient routing decisions and capacity maximization
Completed Projects & Testimonials for MFG Consulting:
Project 1: Railway Equipment Distribution Optimization: BNSF Railway, CSX Transportation
($8Billion Revenue; nine month model development)
Railroads distribute empty railcars to shippers prior to shipment. The scale and complexity of this challenge is huge, measured in the thousands of cars per day and due to a number of matching and feasibility rules. The data is dynamic and constantly changing as new railcars become available and new orders are tendered. An optimization-based decision support system was developed to improve service, increase car utilization, and reduce empty miles.
Result: $15-30 million per year in car mile savings, and nearly a billion dollars in capital avoidance from reduced fleet size requirements.
"The system helps CSX efficiently manage its fleet of 90,000 railcars, resulting in reduced costs, and improved customer service."
- Michael Ward, CEO, CSX Transportation
($8Billion Revenue; nine month model development)
Railroads distribute empty railcars to shippers prior to shipment. The scale and complexity of this challenge is huge, measured in the thousands of cars per day and due to a number of matching and feasibility rules. The data is dynamic and constantly changing as new railcars become available and new orders are tendered. An optimization-based decision support system was developed to improve service, increase car utilization, and reduce empty miles.
Result: $15-30 million per year in car mile savings, and nearly a billion dollars in capital avoidance from reduced fleet size requirements.
"The system helps CSX efficiently manage its fleet of 90,000 railcars, resulting in reduced costs, and improved customer service."
- Michael Ward, CEO, CSX Transportation
Project 2: Intermodal Order Acceptance and Dispatching: Hub Group, Pacer International
($3Billion Revenue; six month model development)
Intermodal marketing companies sell container shipments on a combination of rail and truck. Due to scarce capacity in geographic regions and the potential to affect future capacities, tendered orders should be carefully accepted in order to maximize the yield on this asset. Further, different container choices result in different cost structures of the shipment. An optimization model was developed to assist in the selection and dispatch of customer orders.
Result: $11 million per year cost savings with increased container velocity.
“Our network optimization program, based on SAS/OR, lets dispatchers and customer service representatives make more profitable decisions for Hub on a day-to-day basis. The system enables Hub to make more accurate decisions because it gives staff a clearer and broader picture of the network’s current and future conditions.”
- Gregg Grabijas, Assistant Vice President, Hub Group
($3Billion Revenue; six month model development)
Intermodal marketing companies sell container shipments on a combination of rail and truck. Due to scarce capacity in geographic regions and the potential to affect future capacities, tendered orders should be carefully accepted in order to maximize the yield on this asset. Further, different container choices result in different cost structures of the shipment. An optimization model was developed to assist in the selection and dispatch of customer orders.
Result: $11 million per year cost savings with increased container velocity.
“Our network optimization program, based on SAS/OR, lets dispatchers and customer service representatives make more profitable decisions for Hub on a day-to-day basis. The system enables Hub to make more accurate decisions because it gives staff a clearer and broader picture of the network’s current and future conditions.”
- Gregg Grabijas, Assistant Vice President, Hub Group
Project 3: Service Vehicle Inventory Optimization: General Electric
($257 Billion Revenue; four month model development)
The service vehicles of a major appliance manufacturer must have the correct parts to complete a repair for a customer. If the required part is not in the vehicle, it is ordered and the technician must revisit the repair at higher cost, and lower satisfaction of the customer. Inventory optimization methods were used to provide better service to the customer at a lower cost.
Result: $3.2 million per year in savings from reduced revisit costs, coupled with a soft benefit from a 25% improvement in customer service as first-visit repair rates rose.
"We were looking for ways to improve inventory levels in our service vehicles which are responsible for warranty and other repairs on our appliances. Our predisposition was towards reducing inventory on each truck. However, after careful modeling and quantification of the costs and benefits of inventory, we found that smaller parts had a lower opportunity cost in terms of space taken in these vehicles, and that holding more of them and fewer large parts reduced our total cost of service.
Based solely on reduced revisit costs, we estimate a save potential of $3.2 million across our network of service vehicles. Additionally, we project a soft benefit from a 25% improvement in “fix it the first time” percentage, improving our customer satisfaction. Based on this study, we have piloted the recommendations and hope to employ them network-wide."
- Dick Miller, General Director, General Electric Consumer Products
($257 Billion Revenue; four month model development)
The service vehicles of a major appliance manufacturer must have the correct parts to complete a repair for a customer. If the required part is not in the vehicle, it is ordered and the technician must revisit the repair at higher cost, and lower satisfaction of the customer. Inventory optimization methods were used to provide better service to the customer at a lower cost.
Result: $3.2 million per year in savings from reduced revisit costs, coupled with a soft benefit from a 25% improvement in customer service as first-visit repair rates rose.
"We were looking for ways to improve inventory levels in our service vehicles which are responsible for warranty and other repairs on our appliances. Our predisposition was towards reducing inventory on each truck. However, after careful modeling and quantification of the costs and benefits of inventory, we found that smaller parts had a lower opportunity cost in terms of space taken in these vehicles, and that holding more of them and fewer large parts reduced our total cost of service.
Based solely on reduced revisit costs, we estimate a save potential of $3.2 million across our network of service vehicles. Additionally, we project a soft benefit from a 25% improvement in “fix it the first time” percentage, improving our customer satisfaction. Based on this study, we have piloted the recommendations and hope to employ them network-wide."
- Dick Miller, General Director, General Electric Consumer Products
Project 4: Print Job Assignment Optimization: Standard Register
($720 Million Revenue; three month model development)
In the high-volume print industry, print jobs have a number of attributes such as job size and colors, which result in different cost structures and different printers. The Standard Register print capacity network locates printers in different geographic regions, with different levels of available capacity. An optimization model was developed to evaluate the cost and service impacts of considering a larger set of feasible printers for each job. As a result, Standard Register instituted a change in its operations and supply chain strategy to follow a “Performance Based Routing” concept, which better allocated customer orders to the appropriate facility location and press in order to minimize the total landed cost of each order while maintaining our high customer service levels.
Result: $10 million in savings in total landed costs for jobs, with no loss in customer service.
"The project identified an opportunity within one of our business segments to reduce production costs by 10% by re-routing customer orders, with small increase in transportation costs. The results were validated through both statistical analysis of the optimization results, and through simulation to assure that customer service would not falter. We are confident that a successful execution on this track will save Standard Register over $10 million across all of its lines of business."
- Bob Crescenzi - Vice President, Standard Register
($720 Million Revenue; three month model development)
In the high-volume print industry, print jobs have a number of attributes such as job size and colors, which result in different cost structures and different printers. The Standard Register print capacity network locates printers in different geographic regions, with different levels of available capacity. An optimization model was developed to evaluate the cost and service impacts of considering a larger set of feasible printers for each job. As a result, Standard Register instituted a change in its operations and supply chain strategy to follow a “Performance Based Routing” concept, which better allocated customer orders to the appropriate facility location and press in order to minimize the total landed cost of each order while maintaining our high customer service levels.
Result: $10 million in savings in total landed costs for jobs, with no loss in customer service.
"The project identified an opportunity within one of our business segments to reduce production costs by 10% by re-routing customer orders, with small increase in transportation costs. The results were validated through both statistical analysis of the optimization results, and through simulation to assure that customer service would not falter. We are confident that a successful execution on this track will save Standard Register over $10 million across all of its lines of business."
- Bob Crescenzi - Vice President, Standard Register
Project 5: Rail Pricing Optimization: BNSF Railway
($13 Billion Revenue; three month model development)
Because of shared equipment capacity, a portfolio of rail products has complementary and competing components; one market may enable or hinder capacity in other markets based on their origins and destinations. As such, all pricing decisions on these products are interdependent. Poor pricing leads to network imbalances and unnecessary costs. The problem is complicated by the highly uncertain nature of price responsiveness and future shifts in demand. A stochastic optimization model and monte carlo simulation considers individual market characteristics such as customer willingness to pay, as well as the network impacts in order to maximize network profits.
Result: A 10% empty miles holding trip miles constant, resulting in and more a 5% increase in equipment under load.
“Dr. Gorman has developed a pricing model to assist BNSF in establishing pricing strategies that will reduce repositioning and increase profitability. Perhaps the greatest usefulness of the IPM will be in the ability to fulfill the tactical pricing requirements brought to the forefront by the Internet."
- R. Mark Schmidt, Assistant Vice President, BNSF Railway
($13 Billion Revenue; three month model development)
Because of shared equipment capacity, a portfolio of rail products has complementary and competing components; one market may enable or hinder capacity in other markets based on their origins and destinations. As such, all pricing decisions on these products are interdependent. Poor pricing leads to network imbalances and unnecessary costs. The problem is complicated by the highly uncertain nature of price responsiveness and future shifts in demand. A stochastic optimization model and monte carlo simulation considers individual market characteristics such as customer willingness to pay, as well as the network impacts in order to maximize network profits.
Result: A 10% empty miles holding trip miles constant, resulting in and more a 5% increase in equipment under load.
“Dr. Gorman has developed a pricing model to assist BNSF in establishing pricing strategies that will reduce repositioning and increase profitability. Perhaps the greatest usefulness of the IPM will be in the ability to fulfill the tactical pricing requirements brought to the forefront by the Internet."
- R. Mark Schmidt, Assistant Vice President, BNSF Railway