Supply Chain Logistics Systems of the Many

Supply Chain Logistics Systems

Of the many functional areas of an enterprise, supply chain logistics systems are among the most valuable to any business in differentiating their unique competitive advantages in turbulent, uncertain markets. From controlling the costs of production and service to delighting customers by having products in stock when they want to buy them, supply chain logistics systems often are the strongest differentiating element organizations in commodity-based industries have for competing with one another (Ballou, 2007). The intent of this overview of supply chain logistics systems is to explain the strategic role of competitive, product and spatial relationships play in logistics, what the relationship is between logistics systems and cost, and the techniques organizations are using today to perform logistics system analysis. This overview concluded with a summarization of approaches being used to analyze supply chain logistics systems.

Assessing the Strategic Role of Supply Chain Logistics Systems

The profitability of any business is primarily dependent on how well the many processes, systems and roles within their supply chain logistics systems are synchronized to ensure high performance and customer expectations being consistently met. The competitive role of these systems is apparent when the profitability of companies competing in commodity businesses is compared. The highly automated and streamlined supply chain logistics systems of Dell were a pivotal factor in cost reductions achieved that eventually drove Compaq into a weaker competitive position, eventually leading to their sales to Hewlett-Packard (Gunasekaran, 2005).

From a product standpoint the more coordinated and synchronized the supply chain logistic system, the greater agility and flexibility a manufacturer or service provider will have relative to competitors as well. The example of how well Dell has created their supply chain logistics systems to coordinate their increasingly complex and demanding requirements of their build-to-order PC strategy is a case in point (Gunasekaran, 2005). Dell continually strives for an inventory turns level of 40 or more times a year, nearly one complete inventory turn every week (Dell Investor Relations, 2013). Only with a synchronized and highly efficient supply chain logistics system could Dell attain this level of corporate performance. The very rapid product lifecycles in consumer electronics, clothing and textiles, and in electronic circuitry also show how effective well-coordinated supply chain logistics systems are in managing risk while also orchestrating diverse suppliers across global distances.

From a spatial relationships perspective, supply chain logistics systems seek to optimize interlinking functions under time, cost, and distance constraints. The use of linear programming techniques for optimizing performance of globally-based logistics systems has shown the potential to transform under-performing networks into profitable ones (Colledani, Tolio, 2011). Spatial constraints are also capable of creating entirely new business models for organizations as well, making it possible to enter new markets more efficiently as well. Partnering with 3rd party logistics providers, organizations are able to more efficiently and economically enter new markets while serving existing ones (Colledani, Tolio, 2011). Spatial constraints to logistics performance have also forced more innovation into the areas of supply chain logistics performance than had been slow to otherwise evolve (Fabbe-Costes, Jahre, Roussat, 2009). Constraints of supply chain logistics performance have led to greater innovations in how costs and resources are managed than any other factor in this field (Fabbe-Costes, Jahre, Roussat, 2009).

In terms of the relationship between logistics systems and costs, the greater an organizations' ability to manage the constraints of their unique supply chain logistics the greater the visibility into costs. The advanced planning and scheduling aspects of logistics systems require greater precision in how they manage cost variations by 3rd party and 4th party logistics providers however (Fabbe-Costes, Jahre, Roussat, 2009). The cost aspects of supply chain logistics management is also going through an evolutionary phase of providing greater insight into p[profitability on a per shipment and per product line basis (Colledani, Tolio, 2011). This will in turn make the operation of advanced supply chain logistics systems more efficient and targeted to specific goals.

Techniques For Performing Logistics Systems Analysis

There are a myriad of techniques for performing logistics systems analysis, from the highly complex and data driven including simulations to the use of standardized analytics that can quickly define the financial health of a given logistics system over time. The most common techniques to performing logistics systems analysis include the use of statistical modeling techniques including multivariate time series and the use of Bayesian modeling techniques (Colledani, Tolio, 2011). Organizations are also turning to the use of multivariate time series analysis and the creation of unique, highly tailored models to their specific constraints faced during logistics events throughout their businesses (Fabbe-Costes, Jahre, Roussat, 2009). The pervasive use of statistical modeling for supply chain logistics system optimization and constraint-based modeling is occurring today as advanced software applications are available for managing these systemic challenges companies face.