Saving Billions? How Far the ‘Center for Innovation in Logistics Systems’ Might Take the US Army

The Smart Forecaster

Pursuing best practices in demand planning,

forecasting and inventory optimization

Contributed to The Smart Forecaster by Dr. Greg Parlier (Colonel, U.S. Army, retired). Details on Dr. Parlier’s background conclude the post.

For over two decades, the General Accounting Office (GAO) has indicated that the Defense Department’s logistics management has been ineffective and wasteful, and that the Services lack strategic plans to improve overall inventory management and supply chain performance.

For the US Army, this problem is directly related to a persistent inability to link inventory investment levels and policies with supply chain effectiveness to achieve combat equipment readiness objectives required for globally deployed forces. This shortcoming has been attributed to numerous complexities associated with managing geographically dispersed, independently operating organizations, further compounded by a lack of visibility, authority and accountability across this vast global enterprise.

Unlike the corporate world, where powerful forces encourage innovation to drive competitiveness and efficiency, the Army is not a revenue generating organization focused on “quarterly earnings” and profitability. Certainly, the Army wants to be an efficient consumer of resources—but unlike the private sector’s focus on profit as a bottom line, the surrogate motivator for the Army is ‘force readiness’. This includes equipment availability and weapon system readiness for current operations in Afghanistan, as well as future capability requirements directed by the National Command Authority.

To sustain that equipment availability, the Army must synchronize disparate organizational components using myriad processes with disconnected legacy management information systems across numerous supply support activities which frequently relocate to support deploying forces.

Today, while still engaged in Afghanistan, the Army is also committed to a comprehensive and ongoing transformation. Central to this effort is recognition that dramatic improvements must be achieved in logistics operations and supply chain management. Owning one of the world’s largest and most complex supply chains, the Army is now investing in historically unprecedented efforts to fully capitalize on the promises offered by new information-based technologies. For example, the “Single Army Logistics Enterprise” is believed to be the most ambitious and expensive Enterprise Resource Planning (ERP) implementation project ever undertaken.

These ERP implementation projects have met with very mixed results. While the evidence suggests that dramatic performance improvements for competitive advantage can be achieved in the commercial sector, this has occurred only where so called “IT solutions” are applied to an underlying foundation of mature, efficient and appropriate business processes.

The reality of most cases in recent years, however, has not been this success. Rather, attempts have been made to “bolt on” a solution (like an ERP system, for example) to existing business processes, in misguided efforts to replicate legacy management practices. Such efforts to automate existing processes have, all too often, simply created chaos. In fact, these attempts have not only failed to achieve anticipated improvements, but have actually resulted in reduced performance.

The general pattern has been: the greater the IT investment and organizational scope, the more likely “failure” occurs, in the form of cost overruns, missed schedules, and even project failure—where the effort has finally been abandoned.

We believe the way to enable a coordinated, comprehensive approach for logistics transformation is by creating an “engine for innovation” to accelerate and sustain continuous performance improvement for Army logistics and supply chain management. We are developing a ‘Center for Innovation in Logistics Systems’ to systematically evaluate major organizational components, conduct root cause analyses, diagnose structural disorders and prescribe integrated solutions. We have now identified several ‘catalysts for innovation’ to reduce supply side variability and demand uncertainty—the proximate causes of the notorious ‘bull whip effect’. These include what we refer to as the ‘readiness equation’, ‘mission-based forecasting’, ‘readiness-based sparing’ and ‘readiness responsive retrograde’.

Our goal is to develop a comprehensive modeling capacity to generate and test these innovation catalysts along with several other initiatives in order to estimate cost effective approaches before they are adopted as policy and implemented in practice. We are looking at performance analysis, organizational design, management information and decision support concepts, enterprise systems engineering and workforce considerations including human capital investment needs.

Examining the ‘catalysts’ in isolation, we have seen significant potential for improvement which could yield hundreds of millions of dollars in savings. When combined into new, integrated management practices, however, the potential magnitude for improvement is truly dramatic—billions of dollars in further savings are likely. More importantly, it becomes possible to relate investment levels to current readiness and future capabilities.

The center is capable of developing ‘management innovation as a strategic technology’ by integrating advanced analytics with transformational strategic planning. By harnessing, focusing and applying the power of analysis, we are promoting both qualitative and quantitative common sense—the compelling analytical arguments for necessary change to pursue a common vision. With this power, we are beginning to educate the Army’s leadership, motivate logistics managers to action and provide a source for innovation the culture can embrace. During our journey, we have certainly adapted and applied much from both academic domains and the corporate sector. They, in turn, might now benefit from what we have been able to learn and achieve as well.

Prior to his retirement, Colonel Parlier was the Army’s senior, most experienced operations research analyst and served as Army Aviation and Missile Command’s (AMCOM) Deputy Commander for Transformation. He is the author of Transforming U.S. Army Supply Chains: Strategies for Management Innovation, describing the analytical framework of a multi-year Army Materiel Command (AMC) research and development project providing operations research insights for use by the Army and Department of Defense.

Leave a Comment

Related Posts

Make AI-Driven Inventory Optimization an Ally for Your Organization

Make AI-Driven Inventory Optimization an Ally for Your Organization

In this blog, we will explore how organizations can achieve exceptional efficiency and accuracy with AI-driven inventory optimization. Traditional inventory management methods often fall short due to their reactive nature and reliance on manual processes. Maintaining optimal inventory levels is fundamental for meeting customer demand while minimizing costs. The introduction of AI-driven inventory optimization can significantly reduce the burden of manual processes, providing relief to supply chain managers from tedious tasks.

Future-Proofing Utilities: Advanced Analytics for Supply Chain Optimization

Future-Proofing Utilities: Advanced Analytics for Supply Chain Optimization

Utilities in the electrical, natural gas, urban water, and telecommunications fields are all asset-intensive and reliant on physical infrastructure that must be properly maintained, updated, and upgraded over time. Maximizing asset uptime and the reliability of physical infrastructure demands effective inventory management, spare parts forecasting, and supplier management. A utility that executes these processes effectively will outperform its peers, provide better returns for its investors and higher service levels for its customers, while reducing its environmental impact.

Daily Demand Scenarios

Daily Demand Scenarios

In this Videoblog, we will explain how time series forecasting has emerged as a pivotal tool, particularly at the daily level, which Smart Software has been pioneering since its inception over forty years ago. The evolution of business practices from annual to more refined temporal increments like monthly and now daily data analysis illustrates a significant shift in operational strategies.

Recent Posts

  • Two employees checking inventory in temporary storage in a distribution warehouse.12 Causes of Overstocking and Practical Solutions
    Managing inventory effectively is critical for maintaining a healthy balance sheet and ensuring that resources are optimally allocated. Here is an in-depth exploration of the main causes of overstocking, their implications, and possible solutions. […]
  • FAQ Mastering Smart IP&O for Better Inventory ManagementFAQ: Mastering Smart IP&O for Better Inventory Management.
    Effective supply chain and inventory management are essential for achieving operational efficiency and customer satisfaction. This blog provides clear and concise answers to some basic and other common questions from our Smart IP&O customers, offering practical insights to overcome typical challenges and enhance your inventory management practices. Focusing on these key areas, we help you transform complex inventory issues into strategic, manageable actions that reduce costs and improve overall performance with Smart IP&O. […]
  • 7 Key Demand Planning Trends Shaping the Future7 Key Demand Planning Trends Shaping the Future
    Demand planning goes beyond simply forecasting product needs; it's about ensuring your business meets customer demands with precision, efficiency, and cost-effectiveness. Latest demand planning technology addresses key challenges like forecast accuracy, inventory management, and market responsiveness. In this blog, we will introduce critical demand planning trends, including data-driven insights, probabilistic forecasting, consensus planning, predictive analytics, scenario modeling, real-time visibility, and multilevel forecasting. These trends will help you stay ahead of the curve, optimize your supply chain, reduce costs, and enhance customer satisfaction, positioning your business for long-term success. […]
  • Innovating the OEM Aftermarket with AI-Driven Inventory Optimization XLInnovating the OEM Aftermarket with AI-Driven Inventory Optimization
    The aftermarket sector provides OEMs with a decisive advantage by offering a steady revenue stream and fostering customer loyalty through the reliable and timely delivery of service parts. However, managing inventory and forecasting demand in the aftermarket is fraught with challenges, including unpredictable demand patterns, vast product ranges, and the necessity for quick turnarounds. Traditional methods often fall short due to the complexity and variability of demand in the aftermarket. The latest technologies can analyze large datasets to predict future demand more accurately and optimize inventory levels, leading to better service and lower costs. […]
  • Mastering Automatic Forecasting for Time Series Data copyMastering Automatic Forecasting for Time Series Data
    In this blog, we will explore the automatic forecasting for time series demand projections. There are multiple methods to predict future demand for an item, and this becomes complex when dealing with thousands of items, each requiring a different forecasting technique due to their unique demand patterns. […]

    Inventory Optimization for Manufacturers, Distributors, and MRO

    • Innovating the OEM Aftermarket with AI-Driven Inventory Optimization XLInnovating the OEM Aftermarket with AI-Driven Inventory Optimization
      The aftermarket sector provides OEMs with a decisive advantage by offering a steady revenue stream and fostering customer loyalty through the reliable and timely delivery of service parts. However, managing inventory and forecasting demand in the aftermarket is fraught with challenges, including unpredictable demand patterns, vast product ranges, and the necessity for quick turnarounds. Traditional methods often fall short due to the complexity and variability of demand in the aftermarket. The latest technologies can analyze large datasets to predict future demand more accurately and optimize inventory levels, leading to better service and lower costs. […]
    • Future-Proofing Utilities. Advanced Analytics for Supply Chain OptimizationFuture-Proofing Utilities: Advanced Analytics for Supply Chain Optimization
      Utilities in the electrical, natural gas, urban water, and telecommunications fields are all asset-intensive and reliant on physical infrastructure that must be properly maintained, updated, and upgraded over time. Maximizing asset uptime and the reliability of physical infrastructure demands effective inventory management, spare parts forecasting, and supplier management. A utility that executes these processes effectively will outperform its peers, provide better returns for its investors and higher service levels for its customers, while reducing its environmental impact. […]
    • Centering Act Spare Parts Timing Pricing and ReliabilityCentering Act: Spare Parts Timing, Pricing, and Reliability
      In this article, we'll walk you through the process of crafting a spare parts inventory plan that prioritizes availability metrics such as service levels and fill rates while ensuring cost efficiency. We'll focus on an approach to inventory planning called Service Level-Driven Inventory Optimization. Next, we'll discuss how to determine what parts you should include in your inventory and those that might not be necessary. Lastly, we'll explore ways to enhance your service-level-driven inventory plan consistently. […]
    • Why MRO Businesses Need Add-on Service Parts Planning & Inventory SoftwareWhy MRO Businesses Need Add-on Service Parts Planning & Inventory Software
      MRO organizations exist in a wide range of industries, including public transit, electrical utilities, wastewater, hydro power, aviation, and mining. To get their work done, MRO professionals use Enterprise Asset Management (EAM) and Enterprise Resource Planning (ERP) systems. These systems are designed to do a lot of jobs. Given their features, cost, and extensive implementation requirements, there is an assumption that EAM and ERP systems can do it all. In this post, we summarize the need for add-on software that addresses specialized analytics for inventory optimization, forecasting, and service parts planning. […]