One of the successful approaches developed to enhance our supply chain analytics capabilities is what we called “Geographic Analytics” (GA), a visualization technique that we describe more fully below. GA works. It reduced the time required for network optimization projects by up to 50 percent. In addition, projects driven by this approach were often better supported by the business groups.
The reason: Executives became involved much earlier than they would have in traditional, purely data-driven supply chain analysis work.
Although designed to support supply chain network optimization, Geographic Analytics has applications far beyond its original purpose. We received major interest in this technique from groups both inside and outside of HP, including from sales and after-sales organizations, enterprise risk management functions, and from supplier relationship managers. Each of these groups has a regular need for visualizing and analyzing location data for a variety of purposes ranging from studying after-sales networks to risk management of the supplier base.
What Is Geographic Analytics?
Let us now take a closer look at what Geographic Analytics is. In simple terms, GA is the visualization of network information on a map in order to drive supply chain optimization.
To get started, you map the relevant locations of the network, such as the distribution centers that you want to consolidate. Next, you add basic background information such as hosting business group, square footage, and volume information applicable to each location. Lastly, you apply a smart directory structure that allows you to categorize the locations and quickly filter them to give selective views of the map as needed.