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Optimizing Inventory Management - WERC

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8<br />

<strong>Optimizing</strong> <strong>Inventory</strong> <strong>Management</strong> continued from page 3<br />

are shared by Bursa and based on the experiences of<br />

Logility customers include:<br />

Freeing millions of dollars of working capital trapped<br />

in excess inventory<br />

Meeting required service levels during business<br />

cycle upswings without creating excess inventory<br />

Managing better during difficult economic<br />

conditions, having the ability to bring down<br />

inventory more quickly to a normalized level and<br />

able to more quickly respond to increases in demand<br />

during a recovery<br />

Understanding the true cost required to increase<br />

service levels Improve inventory turns (which<br />

increases competitiveness, noticed by analysts)<br />

Reducing costly obsolescence, stock-outs, and<br />

expediting<br />

Handling changing demand without creating<br />

unnecessarily large inventory buffers<br />

Anticipating time-phased demand changes caused<br />

by seasonality and business cycles<br />

Creating more confident inventory decisions based<br />

on facts rather than opinions<br />

Developing more successful S&OP processes with<br />

parties mutually agreeing on best practices<br />

Having a common view/understanding of the supply<br />

chain (literally everyone has the same “map”)<br />

Extending smart inventory policies to stock held at<br />

customer locations and/or supplier DCs (better<br />

demand sensing, better lead time control)<br />

“An IO solution should offer opportunities for supply<br />

chain professionals to understand the causes of inventory,<br />

accept or reject recommendations, and build trust<br />

in fact-based decision-making,” explains Bursa. “As this<br />

trust is built/earned, we will see further expansion of IO<br />

into DCs.”<br />

Ellis and IDC Manufacturing Insights believe that<br />

IO technology will eventually morph into a broader<br />

category consisting of supply chain related business<br />

analytics and decision-support applications. In addition<br />

to IO, these applications would include: strategic supply<br />

chain network design and simulation; sourcing and<br />

procurement spend management analytics; and analytics<br />

that integrate supply demand sensing, real-time<br />

execution information, and global transportation and<br />

logistics landed cost information.<br />

2010 © Copyright, <strong>WERC</strong>. All rights reserved.<br />

Simon D. Ellis, IDC Manufacturing Insights, www.idc-mi.com<br />

R. Michael Donovan, R. Michael Donovan & Co., Inc.<br />

www.rmdonovan.com<br />

Karin Bursa, Logility, www.logility.com<br />

/ September–October 2010<br />

Justifying the IO<br />

technology solution<br />

<strong>Inventory</strong> optimization (IO) is a tool that is managed centrally<br />

by a company’s inventory planning department, rather<br />

than the warehouse, maintains Simon D. Ellis, practice director,<br />

supply chain strategies, IDC Manufacturing Insights, Framingham,<br />

Mass. “From a warehousing perspective, the operation of<br />

the inventory optimization tool will be transparent,” he<br />

explains.<br />

The cost of an IO implementation is quite variable, says<br />

Ellis, “with vendors in the space pricing quite differently.”<br />

Although the cost of software has been coming down, a typical<br />

implementation should be expected to be in the $300,000 to<br />

$600,000 range for software, with a project timeline of<br />

typically six to nine months, he offers. Implementation costs<br />

also will be variable, and are dependent upon the use of outsourced<br />

consulting resources and the size/duration of any<br />

internal resources. “But these should be in the same range as<br />

software costs,” according to Ellis.<br />

The benefits of an IO implementation can be significant.<br />

“The magnitude of actual savings will depend upon the preimplementation<br />

level of inventory control and the magnitude<br />

of supply network complexity,’ notes Ellis, “but it is not unusual<br />

for a global supply chain to see inventory levels reduced by as<br />

much as 15 to 25 percent.” While actual costs and savings for<br />

specific implementations are proprietary, he reports that the<br />

manufacturing companies surveyed indicated that a one- to<br />

two-year payback is not unusual, with a discounted cash flow<br />

ROI above the 50 percent range.<br />

“In the current economic climate,” he concludes, “the investment<br />

in inventory optimization is compelling.”<br />

Meanwhile, when launching a search for an IO tool, Karin<br />

Bursa, vice president, marketing, Logility, Atlanta, recommends<br />

gathering answers to the following:<br />

Is this solution truly capable of multi-echelon IO (MEIO)?<br />

Does it provide the ability to optimize more than one<br />

location or stage (the MEIO of IO) of the supply chain<br />

produces significantly greater savings and service level<br />

improvements?<br />

Does the IO software assign monetary as well as volumetric<br />

values to all aspects of the supply chain so that economic<br />

impacts of different scenarios at various stages are<br />

accurately predicted?<br />

Does the solution include time-phased capabilities to<br />

optimize inventory with a cyclical demand signal (such<br />

as seasonality)?<br />

With the complex mathematical calculations involved, not<br />

all IO tools operate as well (or at all) above a certain number<br />

of SKUs. Can this solution handle growing complexity as we<br />

roll it out?<br />

Does the IO tool monitor targets on an exception basis, so<br />

planners can spend more time on problem solving and<br />

high-value activities?

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