Rising fuel costs, labor shortages, capacity constraints, and ever-increasing customer demands make it critical to have full transparency of freight costs by customer order, delivery, and individual product. For companies that own the means of transportation, this information provides important efficiency measures used to optimize routes, truck utilization, and service levels. For companies outsourcing transportation, a lack of this insight disconnects them from the cost of customer delivery demands and leads to an inability to audit freight carrier invoices or optimize freight charges through simulation.
Recent events have taught finance and costing leaders that unpredictability is the new norm—making effective cost planning a necessity. Cost data impacts organizational decisions from quoting new business, selecting vendors and suppliers, planning production, and servicing customers. The most innovative teams have enabled costing models that generate planned, forecasted, historical, and simulated cost data to drive commercial and operational decisions.
This session highlights use cases of cost analytics models that predict how market shifts are cost changes that impact profits, evaluate performance compared to benchmarks, determine the success of quotes to actual performance, and establish targeted cost management programs.