Geographic Analytics: How HP Visualizes its Supply Chain

This is an excerpt of the original article. It was written for the January-February 2013 edition of Supply Chain Management Review. The full article is available to current subscribers.

January-February 2013

Supply chain management has a host of rules that most managers live by. But in certain cases, say authors Robert Sabath and Rich Sherman, true innovation comes only when those conventional rules are broken. By clearly understanding the nature of the rules and the details of your supply chain, you can know where and when rule-breaking makes sense.

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When HP launched its biggest supply chain transformation in history in 2010, it was evident that the challenging multi-billion year-to-year savings targets would be difficult
to reach in the traditional way. This transformation required new approaches to deliver substantial improvements across businesses, targeting cost reductions as well as structural streamlining in the form of partner, network and site consolidations. To meet these challenges, HP had to enhance its analysis toolbox to deliver supply chain projects faster and with better alignment across businesses and regions. (For more on the transformation initiative, see sidebar on “HP’s Transformation Challenge.”)

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.

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