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Using Data Analytics to Uncover Savings Potential and Reduce Costs

Professionals who work outside of the realm of logistics are starting to hear the word a lot more often these days. This is because of another smaller but powerful word: costs.

 

Logistics costs today represent a larger number of sales than in the past. They are being driven up by both internal and external factors. The increasing trend toward global sourcing has resulted in a great deal of network complexity, adding to internal costs. High fuel, labor, real estate and other market prices are driving up external costs. Supply and demand curves, tight schedules and capacity levels for ocean shipping contribute to the problem even further. Companies source globally to keep costs down, but how do they keep the savings they achieve from eroding due to rising shipping costs, longer transit times and other complexities associated with global logistics?

 

Companies must closely examine their shipping options. It is important to use a model that accounts for all aspects of shipping practices so that appropriate decisions can be made when it comes to which forms of transportation to use. Optimizing costs by integrating high-level business decision-making usually means that logistics professionals must transform logistics operations in order to support overall business goals. Logistics is considered a horizontal business function, supporting other key areas of business, including product development, global sourcing, procurement and finance.

 

The chief function of data analytics is to help reduce costs. In the world of logistics, costs can rarely be significantly reduced without them. Statistics that allow for the mathematical calculation of data that is collected, analyzed and interpreted are the basis of data analytics. Reports show the output of the overall analysis and provide analysts with different ways of viewing and understanding data. Pictorial representations or graphs provide analysts with snapshots that can aid quicker understanding of data, depending upon their scope.

 

After initial analyses have been performed, other applications can serve as other cost-saving tools. Middleware that works in conjunction with a company’s internal applications can keep track of multiple shipments heading toward one destination, making them hundredweight shipments. Advanced data feeds can send data directly via almost any communication method, allowing a user to view inventory reports within any department prior to the arrival of new inventory. Merge-in-transit middleware allows you to process orders from clients who have inventory at several locations. Orders can go to the client based on destination, without being sent to the warehouse until the day of shipment, so that all packages going to a particular destination are delivered together. Furthermore, inventory prealerts can send vendor shipping records based on client orders directly to the carrier. The data, which can be filtered through a separate server for inventory compilation and control, can send the data to the proper client location, allowing clients to view incoming items and packages.

 

Admittedly, these applications require high-level capabilities from your company’s logistics departments and are almost impossible for one person or department with other goals and day-to-day priorities to oversee. It is important to be aware of them, however, as potential ongoing cost-saving tools that can be implemented once an initial analysis of your shipping data has been performed and savings potential located.

 

Utilized appropriately and applied effectively, all of these tools can provide analysts and logistics professionals with the information they need to identify shipping methods and suggest improvements. They can focus on lean manufacturing or procuring goods according to demand. This allows operations professionals to operate on an on-demand basis. Analysts can also make higher level cross-functional decisions. For example, a vendor or manufacturing location may be changed, because the manner in which a move will affect or reduce logistics costs is now visible. In short, supply chain management is made easier and more efficient.

 

Data analytics can also allow for rate analysis, auditing and the generation of multipurpose reports for different purposes at different levels of complexity.

 

How do you know if your data has been successfully analyzed? Whether you perform analysis in house or outsource the work to another, in the end, you should be able to identify the potential savings, achieve a reduction in shipping costs, enhance the visibility of your company’s shipping practices and acquire the methodology that will enable you to move forward with confidence.


Niko Michas is president and CEO of BridgeNet Solutions, Inc.

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