White paper: logistics network optimization requires focusing on hard questions, not just collecting data
Naugatuck, CT September 19, 2003 Logistics network optimization can yield significant systems-wide warehousing, transportation and inventory savings, but many companies mistakenly conduct optimization studies that are almost exclusively data driven, according to a new white paper from USCO Logistics.
Logistics network optimization involves an analysis of strategy and data elements to determine the number, size and location of required distribution centers in order to achieve the optimal balance between service levels and logistics costs.
"While it's a sizable undertaking, network optimization can yield service improvements and significant savings in system-wide warehouse, transportation and inventory costs," said Ashutosh Dekhne, USCO Logistics' supply chain engineer and the author of the white paper.
Many companies mistakenly conduct optimization studies that are almost exclusively data-driven, according to USCO. "Their assumption is that you just plug in the relevant data on size, weight, volumes, ship-to points and other factors and output the ideal network design," Dekhne said. "However, in focusing too much on the modeling exercise itself, companies can miss the strategic and practical context for the analysis."
Consider the company that conducted a "successful" supply chain network modeling exercise and revamped its entire distribution network. Just three months after implementation, however, it purchased another company with distribution center locations that overlapped its own. The result: redundant distribution centers and inventory duplication.
"By considering the strong likelihood of an imminent acquisition, the company could have better positioned itself by either delaying the optimization implementation or considering potential harmonization of the two supply chains," Dekhne said.
Dekhne suggests a six-step approach, outlined in the white paper, which weighs the strategic and practical, in conjunction with data analysis, to deliver optimal results.
"Logistics professionals should rely on modeling tools as decision support, not as infallible oracles of the 'perfect' distribution solution," Dekhne said. "Only by blending such tools into a detailed understanding of the company's present and future business strategy and the practical implementation requirements that could impact the recommendation, can a network optimization generate real logistics cost savings."