The Web of Logistics

The permutations in logistics are infinite. A decision support system can help identify the best options quickly.

Should a new distribution center be built in a rapidly growing international market — or should the capacity of existing remote storage or manufacturing facilities be expanded?

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Should working capital be reduced by adopting a layered approach, with warehouses exclusively focused on high- or low-turnover products — or should both types of inventory be maintained in multiple locations to ensure redundancy?

Should decisions regarding the distribution network be based on operational costs or capital investment considerations?

Logistical issues are multifaceted and almost always involve trade-offs — rarely are there only two options to choose from. The combination of business objectives, available options, and operational or commercial constraints results in a complex mathematical problem.

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The Need for a Decision Support System with Advanced Analytics

Given the complexity of logistics, operations directors and logistics leaders need a mechanism for decision-making — something to help them choose among the various available solutions. A good decision support system can also reveal interactions that a logistics executive may not have considered.

Competitive Objectives

Here lies the core of what makes logistics so difficult to optimize.

• Number of different options and their cost impact: What is the best way to transport your products? Maritime, rail, road, or air transportation each have their place. The goal should generally be to choose the most cost-effective transportation method. But even this simple rule requires detailed analysis, whether due to specific logistical needs, risk considerations, or evaluating different logistics partners versus in-house operations (make vs. buy). The solution space can become so deep that it feels incomprehensible.

• Service levels: Intertwined with costs are service levels — and there are always trade-offs between the two. For example, an internal guideline to release trucks only when they are fully loaded may be the most economical choice — but it can lead to slow deliveries and jeopardize customer relationships.

• Reducing the carbon footprint: The pressure on companies to manage their CO2 emissions has increased considerably in recent years, with the public and many governments demanding that logistics networks become more sustainable. In an ideal scenario, reducing emissions should be straightforward — once again through a rule (mentioned above) of trucks and shipping containers departing only when fully loaded. However, reducing delivery frequency can negatively impact delivery times. This highlights how sustainability goals, as well as cost-saving goals, can conflict with service objectives.

Complexity Amplified by Retail and International Trade

Logistics becomes especially complex when it involves operations in different countries (or continents) or when dealing with retail customers. When products are transported internationally, differences in wages, import tariffs, taxes, and geopolitical considerations must be taken into account. Retail logistics is further complicated by the need for omnichannel services, ensuring that products are available at specific stores at specific times or with last-mile delivery to customers.

Overcoming the Technical Challenges of Decision Support Systems

The effort required to perform this type of analysis and establish a decision support system in the logistics environment cannot be understated. Common logistics data may need to be collected internally or externally, digitized, and harmonized if not readily available. If your IT infrastructure is not yet configured for data analysis, implementing a complete data integration layer may be necessary. New processes and operational models for data handling, modeling, result validation, and implementation monitoring need to be established.

What makes the effort worthwhile is the enormous return that optimization can bring. Compared to manual planning, a good decision support system enables the evaluation of an almost unlimited number of boundary conditions. It allows for the rapid parallel analysis of possible scenarios without requiring an elaborate business analysis exercise for each case. For these benefits, such systems are expected to become a business standard in the coming years.