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Using Advanced Analytics to Transform the End-to-End DoD Distribution Network
The Department of Defense’s (DoD) global supply, distribution, disposition and transportation network possesses scale and complexity like no other. From combat operations to peacekeeping duties to humanitarian relief, it is the lifeline for warfighters’ missions.
As today’s military must protect national security and maintain readiness in a declining budget environment, this network must evolve to the next level. Accenture can help spur this evolution with an advanced analytics framework that combines defense logistics knowledge with commercial leading practices.
With the Pentagon’s widespread cost cutting and operational efficiency agenda, the DoD’s end-to-end distribution network is under intense pressure. Former Defense Secretary Robert Gates mandated that leadership identify significant cost savings—$100 billion in overhead over five years—to lower the cost to serve and reinvest savings back into mission critical needs.1 The US military must operate in a federal budget environment that many observers think will require future, perhaps significant, cuts to defense spending.
In addition, defense logistics organizations must respond to the department’s emphasis on inventory management improvement. This includes meeting the requirements of Section 328 of the National Defense Authorization Act of 2010 that mandate “reducing the acquisition and storage of secondary inventory that is in excess to requirements.” 2
The Defense Logistics Agency, the United States Transportation Command and the military services have undertaken optimization initiatives. Decision makers recognize the imperative for change, and they know that if they do not act to reduce costs, the U.S. Congress will do so for them in the form of budget cuts.
Despite this understanding, defense logistics organizations have faced barriers. The first has been the lack of a holistic view of the problem. Traditionally, defense organizations have assessed supply chain variables in isolation. This narrow view has been due to difficulty breaking through institutional “stovepipes,” as well as a lack of the right analytical tools, processes and resources.
The second optimization challenge rests in the sheer complexity of the DoD network:
1. Gates, Robert M. (August 9, 2010). Statement on Department Efficiencies Initiative. In U.S. Department of Defense website. Retrieved March 8, 2011, from http://www.defense.gov/speeches/speech.aspx?speechid=1496.2. National Defense Authorization Act of 2010, Section 328.
The key to attaining globally optimized cost and performance outcomes within the DoD network is to strategically align supply chain processes across organizations.
Accenture recognizes that advanced analytics can help defense organizations and achieve this critical alignment. A commercial business technique now gaining traction across the public sector, advanced analytics is the scientific application of quantitative and statistical techniques to drive business value and cost savings.Advanced analytics goes beyond typical business intelligence dashboards—because the insights gained address more than just “what happened.” They reveal “why it happened” and allow organizations to drive insights back into the business or mission to realize new outcomes.3
Our experience suggests that by applying Accenture’s advanced analytics framework to end-to-end distribution network challenges, defense organizations can:
3. Davenport, Thomas H. and Jeanne G. Harris. Competing on Analytics: The New Science of Winning, Harvard Business School Press, 2007.
Accenture’s distribution network optimization framework combines commercial best practices with our deep understanding of defense logistics. The framework provides an iterative process that involves three phases:
Accenture conducts this process with best-in-class analytics tools and software that meet each organization’s unique needs. We bring an experienced team that know how to make the most out of the software and the advanced analytics framework. We also help implement change across people, processes, technologies and organizational cultures that is necessary to realize and sustain optimization outcomes.
August 17, 2011
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