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Case Study: Logistics Network Design - PC Comp

Logistics Network Design#

Finding the optimal manufacturing and distribution footprint to meet service level requirements at the lowest possible cost


  • 8% saving in total costs, representing tens of millions of dollars
  • 30% reduction in manufacturing costs
  • Consolidation strategy realizing reductions in material costs of 3% (through centralized purchasing) and inventories of 28% (through shared risk)
  • High customer service level requirements met
PC Comp* is a global computer components manufacturer. The Fortune 500 company is currently the market leader, but facing strong and aggressive competition from numerous OEMs in different markets. It is paramount that they achieve and maintain excellent customer service levels at the lowest total landed costs.


Customer service levels were a key success factor in industry, and their existing supply chain was set-up with that in mind, with 4 manufacturing and 12 distribution facilities close to the end customer. This strategy offered very high customer service levels, but was not the most cost effective solution. Downward cost pressures in the industry forced a rethink of this approach, and a supply chain consolidation was required. SimFlex was engaged in order to find the lowest manufacturing and distribution strategy that would fulfill both customer requirements and management's stipulation that a maximum of 2 manufacturing plants, and 5 distribution centers be utilized.


SimFlex built PC Comp's global manufacturing and distribution network, and considered all possible material flows i.e. all products could be made in all plants, all plants could supply all DCs and all DCs could supply all customers. Each plant also had an on-site DC. Customers were grouped on a country level and segmented according to delivery time requirements - 2-day, 4-day and 10-day. Also considered were 4 alternative transport options with varying lead times and cost structures. The project involved a two-stage approach:

  • Stage 1 removed all constraints to find the absolute minimum cost solution. This was to identify what the additional cost of serving customers was, and what savings could be made if contracts could be re-negotiated.
  • Stage 2 involved restricting the number of sites in the optimal solution to a maximum of 2 plants (from a possible 4) and 5 DCs (from a possible 12), and required that customer service levels were met.


The unconstrained solution found the absolute minimum cost at which all markets could be served, and identified approximately 14% savings over current costs. The necessary constraints were then applied, and an optimal solution was found that met customer delivery requirements as well as management's requirements. Costly investments in capital equipment for some of the products meant that a single-site manufacturing strategy was required. For the remaining products, a dual-site strategy was optimal. Three DCs closer to the major markets were used. The optimal constrained solution presented opportunities to reduce total costs by 8%, which represented tens of millions of dollars. The major savings came from manufacturing as production was shifted to low-cost geographies. A consolidated strategy also brought savings in material costs of 3% (through centralized purchasing), and a reduction in inventories of 28% (through shared risk).

*Company name disguised to retain confidentiality