Today, when it comes to supply chain management, business decisions have never been more challenging.
At LF Logistics, Supply Chain Analytics brings the power of data-driven analysis, mathematical optimization, and collaboration to support decision making, and provide holistic and practical solutions.
With companies having to rethink strategies in the face of rising costs and shifting demand, we align business and supply chain strategies in order to provide solutions. These help our customers maximize profitability and growth by enhancing their ability to source their products, manage their inventory, and deliver finished goods in a timely and cost-effective fashion.
Supply Chain Network Design
We design the optimal configuration for our customers’ supply chains by specifying the ideal number and location of Distribution Center (DC) facilities and transport networks that connect product supply points and market demand. We address issues such as the value of logistics hubs as an alternative to direct deliveries from plants to markets and identifying the best distribution channels for particular products and choosing the best ports of exit and entry for international shipments. Benefits include optimized inventories to match supply with demand, reduced inventory holding costs and risks, and minimized costs of order fulfillment, warehousing, port and shipping, inland transportation, and business tax.
Applications:
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Supply chain cost evaluation of product sourcing alternatives
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Plant facilities location and capacity planning
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Location and sizing of DC and international hub facilities
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Optimal assignment of DCs to serve market areas and customer channels
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Transport network design and delivery strategies
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Feasibility analysis of cross-docking solutions
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Inventory positioning to balance cost and risks of demand fulfillment
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Carbon footprint analysis of alternative supply chain network designs
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Assessment of cost and service level impacts of changes in market demand, labor cost, fuel prices and transport capacities
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Development of capacity expansion strategies to support market growth
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Supply chain risk assessment
Lean Transport
Transportation is a significant component of the total supply chain cost. We design cost-effective transport networks and continuously improve operational efficiency by recommending optimal fleet capacity, shipment plans, and delivery strategies to help our customers minimize overall cost-to-deliver, meet customer service level requirements, and manage inherent risks and uncertainties in the transport marketplace. We consider our customers’ trade-offs with DC and inventory carrying costs when we develop transport strategies to achieve a holistic solution.
Applications:
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Optimization of fleet size and profile
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Daily local delivery routing and scheduling
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Container and truck load planning
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Determine the right mix of owned and outsourced trucks
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Improving truck availability and on-time delivery performance
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Achieving sustainable transport: reducing carbon emissions, minimizing fuel consumption and promoting the use of carbon neutral transport modes
Dynamic Simulation Modeling
We maximize the productivity of labor, equipment, and processes for warehousing and distribution operations by utilizing dynamic simulation modeling to account for statistical variations over the entire process cycle. This allows us to respond quickly to changing circumstances. We review current supply chain processes and optimize the process flow, thus allowing for flexible operations that reduce waste, eliminate delays, and highlight opportunities for improvement.
Applications:
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Dock and yard capacity planning and scheduling
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Inbound receiving capacity analysis
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DC picking strategy comparison and evaluation
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Dynamic warehouse space utilization
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Dynamic truck dispatch system
Geographic Information System (GIS) Analysis
We help our customers better understand the demand for their products by providing a robust view of the supply chain through the use of Geographic Information System (GIS) Analysis, which allows us to map the location of customer and logistics facilities. This enhanced view of their network reveals patterns, relationships, and trends in geographic data to aid in their decision-making.
Applications:
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Geocoding and mapping of supply chain facilities
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Demand mapping versus relevant demographics for market expansion
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Sales territory planning and design
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Geospatial analysis for customer channels
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Delivery order profile analysis
Predictive Analytics
We apply statistical modeling and forecasting techniques to a wide range of applications, which include developing forecasting models for sales and raw material availability, risk analysis of operational accidents and shipments, and establishing proper sampling sizes for issues such as shipment quality testing. We pinpoint operational situations that predict future performance and leverage these into functional models – for instance, forecasting potential sales to predict how fast and in which geographic direction the market will grow.
Applications:
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Statistical demand forecasting
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KPI analytics process design
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Labor requirements forecasting
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Inventory positioning
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Time series analysis
