Thursday, June 9th, 2011 - 21:28
Tuesday, June 7, 2011 - 21:23
The final principle that we’ll address in this blog series is Optimization. This principle supports using advanced inventory analytics, along with traditional planning systems, to drive immediate and meaningful results in “right sizing” of inventories.
Taking the Guess Work Out of Identifying Excess Inventory
According to several Government Accountability Office (GAO) reports (January 2011, May 2011 and one from 2005), some government organizations have 18% or more of their current inventories classified as “excess.” Government supply chains are seeking ways to eliminate acquisition and storage of items with a history of no demand and a low probability of future demand - unless there is an overriding reason to retain it. A key factor driving this excess inventory is the inadequacy of current government systems to support analysis required to achieve optimal forecast accuracy.
However, we have found that advanced analytics and optimization that automate and self-actuate supply chain transactions can significantly improve the ability to:
- draw-down existing overages in inventories
- identify items appropriate for reutilization or surplus sales
- leverage real time, on-going inventory analysis to augment demand planning practices
Having developed nearly 70 inventory management patents, we’ve learned traditional “Push” methods, like those used in the systems described above, are inadequate by themselves. Analyzing actual consumption, or the “Pull” method, must also be considered.
With this in mind, our advanced analytics and optimization capability eliminates excess inventory by determining the optimal inventory at the item-location level. It considers factors including service levels, demand variation, supplier/manufacturing lead times, and variation in lead times, batch size, and overage/underage levels in optimizing inventory levels.
But, What If…
Of course, unexpected needs and situations occur and being prepared—without being overstocked—can be a fine line to walk. But, our advanced planning processes speed up analysis, even for tens of thousands of unique items across many inventory locations, allowing us to generate alternative safety stock calculations. Processes have also been specifically developed to efficiently manage highly sporadic demands and support the ability to simulate the results of “what-if” planning scenarios.
The “what-if” simulation analysis quickly and easily examines the impact of service level changes or supplier lead-times, which in turn might affect cost, budget and inventory levels. These simulations allow the comparison of how inventory metrics compare with different policy and safety stock levels.
The advantages of these advanced analytics tools are as follows:
- Strategically: Establish inventory policies and levels; evaluate service levels; and forecast long-term storage capacities. This may facilitate changes to inventory policies to improve efficiencies.
- Tactically: Improve customer service levels; identify stock overages and underages; evaluate inventory policies and operations; forecast near-term stock consumption; evaluate stock/service level trade-offs; operate within budget constraints.
- Operationally: Optimize inventory for each and every Item; calculate cycle and safety (buffer) stock to prevent stock-outs due to fluctuations in demand and production lead-times; create replenishment orders based on customer specific logic; and combine demand forecasting and inventory policies.
A Real Life Application
The use of analytics is truly driving cost reduction results. The Los Angeles (LA) Metropolitan Transit Authority (Metro), for example, is responsible for supporting the continuous operations of nearly 2,500 metro buses and over 250 rail cars/buses in one of the most populous counties in the United States. Significant budget pressures recently forced the management team to review their operations. Metro was able to use advanced inventory optimization concepts mentioned in this blog to identify ‘quick win’ opportunities that could generate savings through minimal changes to current processes or practices.
According to Metro’s Chief Operating Officer (COO), Lonnie Mitchell, “The pilot has given us deep insight and confidence that an inventory reduction of 28% is achievable. We expect to realize a significant portion of this reduction within the next 12 months.”
A Solution for Public and Private Sector Organizations
In this time of serious budget deficits, government organizations that own inventory cannot ignore the opportunities for optimizing performance. Using these three principles, government organizations can work to cut spending and optimize their inventories. Furthermore, our experience shows that these efforts can be self-funded through rapid return on investment—a total win-win.
Let Us Hear Your Thoughts
Now that we’ve wrapped up this series on smarter inventory management, help us with your comments and questions. Would these three principles work at your organization? Why or why not?
Eric Strauss is an Associate Partner and Service Area Leader (SAL) within IBM’s Global Business Services’ Public Sector. Mr. Strauss has more than 15 years of experience supporting Public and Commercial clients. He currently serves as the Supply Chain Planning SAL and leads projects within the US Army. Over the past seven years, Mr. Strauss has served as an Account Manager, Project Executive, Program Manager, and Project Manager for more than two-dozen Public Sector projects and launched a new IBM solution offering called the Impact of Future Technology (IoFT).
Mr. Strauss has been recognized repeatedly for excellence in project delivery and sales. He earned his MBA from Indiana University’s Kelly School of Business in 2008 and graduated with a BS in Management from the University of Minnesota’s Carlson School of Management in 1995. Mr. Strauss also completed the Defense Acquisition University’s Executive Program Manager Course in 2009 and received a Certificate in Logistics from the University of North Carolina – Chapel Hill’s Kenan-Flagler Business School in 2008.
Eric Strauss (firstname.lastname@example.org)