Outperform with SmartOps EIO by Sridhar Tayur

Enterprise Inventory Optimization (EIO) Empowers Companies to Outperform In any economic climate, Enterprise Inventory Optimization (EIO) provides every company with a readily quantifiable, sustainable competitive advantage. During growth periods, EIO enables companies to adapt quickly to rising demand in ways that help capture new market share and ensure greater revenue and profitability. Likewise during downturns, EIO supports and creates the flexibility to trim inventory with greater precision to make the most of every available opportunity while freeing up precious cash flow. Easily integrated with existing business systems, EIO can be up and running in 90 days or less, yielding immediate performance and balance-sheet benefits, and delivering the highest return on investment of any supply chain project. In today’s volatile, unpredictable economic environment, supply chain complexity is greater than ever and the difficulty of managing inventory across the chain is increasing. It is no surprise that more effective control of global inventories is now a top executive priority and likely will remain so for years to come. After all, it is one of the keys to strengthening supplier and customer relationships and to building long-term shareholder value. For operational managers, EIO satisfies increasing customer demand while streamlining global inventories. Freeing up working capital and reducing operating costs address the CFO’s strategic imperatives. Additionally, the ease of implementation and rapid ROI help CIOs leverage new value from existing business systems, with minimal risk. The benefits of EIO touch all departments — one reason why analysts such as Aberdeen Group identify inventory optimization as the top strategic priority. Inventory optimization is the top focus for executives Strategic Actions That Companies Are Planning Optimize how much and where to hold inventory across our network

63%

Improve forecasting accuracy 59%

Improve supply chain visibility (including intransit)

39%

Improve our ability to meet customer-requested order dates

33%

Make suppliers more responsible for inventory (e.g., SMI, drop shipping)

31%

Move to lean manufacturing 30%

10%

20%

30%

40%

50%

60%

70%

Source: Aberdeen Group, 2006

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Enterprise Inventory Optimization is More than Just Good Business Practice Today’s complex global marketplace creates significant stresses on supply chain performance. Increased supply and demand uncertainty forces planners to focus on expediting and “firefighting” instead of on creating sustainable improvements. Product proliferation and globalization mean planners have less time to manage more SKUs and supply chains, leading to sub-optimal customer service KPIs including order lead time performance and order fill rates. Without the proper tools, planners have no choice but to manage inventory targets with ad hoc and infrequently updated spreadsheets, overly simplified rules-of-thumb, or over-buffered, “just-in-case” inventory. What is the result? Excess inventory creeps up, frequently at the wrong location or with the wrong product mix, which negatively affects service levels and ties up scarce working capital. These issues become even more pronounced at times like now, when the global economy is more volatile and unpredictable than ever. Market forecasts, raw material costs, and supplier viability are less reliable. Government regulations and trade policies are changing constantly. Falling demand is pushing inventory levels higher. This combination of factors makes effective supply chains increasingly elusive. Manufacturers have various less-than-ideal strategies to cope with uncertainty. Some close plants, sacrificing opportunities to capitalize on future market upturns. Others furlough workers, draining knowledge capital even as severance costs drive up expenses. Others slash research and development budgets, slowing innovation. In reality, there is a more effective way to not only survive, but also outperform the competition — improve inventory deployment. EIO enables, supports, and institutionalizes better inventory planning in ways that quickly free up cash, reduce inventory handling, obsolescence, and insurance costs, and improve customer service. EIO is more than just a good business practice. It is the best source of cash that drives longterm performance Cash Generating Options Comparison Positive

Long-Term Impact

Enterprise Inventory Optimization

Capital Markets

Workf orce Layof f s

Cut R&D Negative Low

Sell Assets / Close Plants

Immediate Cash Generation

High

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Cash Generating Options

Pros

Cons

Enterprise Inventory Optimization

• Immediate cash generation from existing working capital • Builds capabilities to respond to future growth and uncertainty

• n/a

Capital Markets

• Does not eliminate any existing capabilities or assets

• Credit markets are limited • Debt is prohibitively expensive

Workforce Layoffs

• Immediate impact on cost structure

• Loss of knowledge capital • Prevents reaction to future growth • Severance costs

Sell Assets / Close Plants

• Generate cash from existing assets

• Cuts long-term capacity • Selling / plant closure costs

Cut R&D

• Immediate impact on cost structure

• Slows company innovation • Hurts long-term product differentiation

Why Traditional Inventory Planning Approaches Fail EIO succeeds where traditional approaches fail because it addresses the realities of today’s global economic environment — it takes a strategic approach to inventory management, automates processes to mine and utilize the right business data, and offers depth of visibility into supply chains that old methods cannot match. Reliance on traditional methods for setting inventory targets, including rules-of-thumb or spreadsheet-based safety stock calculators, inevitably leads to excess inventory across the board or unnecessary service level failures. The reason is simple — these methods rely on oversimplified supply chain models that ignore the complexities and uncertainties that make inventory a necessity in the first place. Even experienced planners frequently “out-plan” these traditional methods. This out-planning has predictable consequences. Value “leaks” from the supply chain, forcing companies to choose between stranding capital in unneeded inventory or foregoing profit lost through unmet orders. A number of common simplifying approaches create these value leaks: A fundamentally different approach is needed to plug the value “leaks” in common inventory management approaches

Inventory Levels

SingleStage Logic

Ignore Variability Improperly Characterize Uncertainty Constant Inventory Targets

Total ‘Leak’ Infrequent Updates Insufficient Granularity Oversimplified Models

Common Supply Chain Models

EIO Targets

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Using Single-Stage Logic: Setting inventory targets at each location independently ignores interactions among various supply chain stages, resulting in over-buffering of safety stocks across the enterprise. Ignoring Supply, Production, and Yield Variability: Traditional inventory targets are based predominantly on safety stock calculations that incorporate demand variability or forecast error over an exposure period. These calculations ignore variability from upstream suppliers or production processes, resulting in safety stocks that are too low for the actual uncertainty imposed on the supply chain. Improperly Characterizing Uncertainty: To calculate safety stock targets accurately, one must properly characterize supply chain variability and adjust forecast bias. Traditional inventory calculations utilize deterministic models that ignore variability or assume worst-case scenarios. When variability is ignored, safety stocks will be too low, placing service levels at risk. With worst-case scenarios, safety stock levels will be set too high, tying up much-needed working capital in inventory. Similarly, neglecting forecast bias clouds the measure of true demand variability in addition to driving inadequate inventory when demand is under-forecasted, or excess inventory when demand is over-forecasted. Setting Constant Inventory Targets: To simplify the problem, traditional planning methods disregard the time-varying nature of supply chains by assuming fixed demand and ignoring capacity constraints. These approaches generate static inventory targets over time, which lead to excessive inventory at times of below-average demand, and stock-outs at times of aboveaverage demand. Infrequent Updates: Standalone inventory planning spreadsheets or applications require a large amount of time to gather, transfer, and enter data between systems. This robs planners of time they could spend updating inventory targets on a regular basis, causing inventory targets to go out of sync with the larger supply chain. Insufficient Level of Granularity: Inventory targets must be set for each item, at every location, for each time period in the planning horizon. Because the scale of solving for inventory targets at this level is so massive, traditional approaches reduce the scale by solving for inventory targets at a less granular level, often using an ABC classification to group like items. When you fail to consider the individual characteristics of each individual item and each location, items with higher variability than the group average run a greater risk of stocking out, while items with lower variability than the group average may carry too much inventory. Using Oversimplified Models: When inventory planning tools do not reflect the realities of a company’s supply chain, planners become skeptical of the outputs and start to ignore the model’s inventory targets. Without a comprehensive data model that accounts for real-world constraints, such as production capacities, time-varying bills of material (BOMs), production frozen windows, service times, or item/location-specific review periods, planners often revert to setting inventory levels using rules-of-thumb or their own intuition. In effect, educated guesswork replaces science, often with unpredictable results. The information to make the right inventory planning decisions already exists in any large organization’s business systems. The difficulty lies in utilizing the information properly. Neither © 2009 SmartOps Corporation

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Enterprise Resource Planning (ERP – such as SAP and Oracle) nor Advanced Planning and Scheduling (APS – such as i2, SAP APO, and Manugistics) systems provide optimal inventory targets. Rather, these systems require planners to manually enter inventory targets for all raw materials, components, and finished goods in the supply chain. This is one reason why SAP, the leading Enterprise Applications Software company, initiated its search for an inventory optimization solution, and selected SmartOps to be SAP’s exclusive partner for EIO.

SmartOps EIO Answers the Inventory Management Challenge SmartOps, which pioneered Enterprise Inventory Optimization, offers companies an EIO solution that uniquely plugs the value “leaks” associated with traditional planning methods. SmartOps EIO complements and extends the capabilities of planning and execution systems by adding key capabilities including: A Total Supply Chain View: Without a multistage approach, companies set inventory targets at each location independently, using single-stage calculations that ignore the impact of inventory levels at other locations in the supply chain. This single-stage approach incorrectly accounts for uncertainty and fails to optimize the overall supply chain. SmartOps’ multistage algorithm considers all stages simultaneously, accounting for inventory dependencies across stages at an item-location granularity level, so inventory is optimized across the entire supply chain. A total supply chain view

More Accurate Modeling of Supply Chain Realities: SmartOps EIO utilizes a comprehensive data model and advanced stochastic process algorithms that account for the inherent uncertainty present in supply, demand, and production inputs, and models at a level of granularity required to generate reliable, actionable outputs. Existing planning systems make simplifying assumptions regarding real world, time-varying constraints — for example, by assuming unlimited capacity or static demand variability, month-over-month. In contrast, SmartOps EIO © 2009 SmartOps Corporation

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factors in storage and production capacity constraints and incorporates time-varying inputs to create the most comprehensive, yet easy-to-use, EIO solution available. SmartOps EIO lets a company “fix-the-mix,” resulting in both lower inventory and improved customer service. “Fix-the-mix” of inventory at the item-location level… 60%

Change in DOH Inventory

46%

40%

20%

More Needed

15%

11%

13%

8% 2%

-20%

-40%

-3%-5% -12%

-6%

-7%

-18% -19% -18% -25% -30%

-7%

-16% -21%

-10%

-14%

-19%

-25% -33% -31% -35%

-23% -28% -30% -30%

-40%

-25% -33%

Less Required

-43%

-60%

Items

...for higher customer service with less inventory.

$11

Before SmartOps: 98% fill rate

Avg OH FG Inventory $ million

$10

With SmartOps: 99.5% fill rate with less inventory $9

SmartOps calculated optimal curve

84% 86% 88% 90% 92% 94% 96% 98% 100% Target Service Level (fill rate)

Greater Visibility That Improves Planning Expertise and Results: EIO gives planners continuous insight at the most granular levels of their supply chains, identifying the forms and purposes of all inventories in the system. The ability to see how changes to supply chain parameters affect the profiles of needed inventory lets planners make fact-based planning decisions using real, precise operational data, and helps them identify the best opportunities for improvement.

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The drivers of inventory — viewed at the right granularity levels

Proper Characterization of Uncertainty: The only certainty about a real-world supply chain is its uncertainty. Lead times, capacities, and manufacturing yields vary, sometimes in predictable, time-varying ways, but more often in ways that are unknown. Perhaps the most difficult supply chain parameter to forecast is customer demand. While there is no such thing as a perfect forecast, demand uncertainty can be grouped into three categories: regular (often characterized with commonly used statistical distributions), sporadic (unpredictable, lowvolume and low-frequency demand), and intermittent (predictable rhythms or patterns to when significant demand occurs). Demand patterns vary across items Demand Classification by Item Class Sporadic

Intermittent

Regular

100%

% of Stocking Points

90% 80%

48%

70% 60% 50%

14%

40% 30% 20%

38%

10% 0%

B C D E F G H I Item Class (# of Customer-Facing Stocking Points)

All

SmartOps EIO characterizes demand streams in terms of the demand uncertainty, so the correct method of setting inventory targets is utilized. EIO does this for every item at every location—exactly where the service level game is won or lost.

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Forecast error varies across locations Forecast Error by Location Average Coefficient of Variance

1.2

1.11

1.0 0.79

0.8 0.56

0.6 0.4 0.2 0.0 Location #1

Location #2

Location #3

In addition, EIO treats demand uncertainty as dynamic, so the method of setting inventory targets can benefit from less variability as well as anticipate sudden increases in demand volatility. Forecast error changes over time Stocking Point ABC_123 4

Time Varying CV Average CV

3.5 3 2.5 2 1.5 1 0.5

l_ 3 Au g_ 2 Se p_ 1 Se p_ 4 O ct _2 N ov _1 N ov _4 D ec _3

n_ 5

n_ 2

_4 ay _3 M

Ap r

The CV can be revised dynamically to reflect forecasting improvements.

Historical Period

Historical Period Analyzed

Ave. CV

EIO Average On-Hand Target

April – December 2005

1.24

12,141 Units / $76,732

October – December 2005

0.61

6,718 Units / $42,458

The Ability to Segment Product Availability: SmartOps EIO provides options for setting product availability and service level targets. You can configure the EIO application to optimize inventory targets against all leading service level metrics including order fill rate, case fill rate, and line item fill rate. EIO also allows a company to set individual service level targets for individual items or set an overall service level target for a group of items. If service levels are set for a group of items, the individual targets (and associated inventory) are optimized to meet the overall service level. For example, EIO sets higher service levels for items with less demand variability, leveraging these items to achieve the global objective. When performing service level optimization, EIO can be configured to minimize total inventory costs and the opportunity cost of lost sales. If the objective is minimizing total inventory cost, a © 2009 SmartOps Corporation

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global target is needed to ensure reasonable service. If the primary goal is minimizing inventory costs plus revenue loss, the impact of lost sales plays the role of the global target service level, and EIO finds the best mix of service levels that minimizes the total cost. Optimal service levels at the item, location level 95% Service Level for all Products vs. Optimal Service Levels Global Service Level = 95%

Total Safety Stock Annual Holding Costs

$60,000 $50,000

$55,121

$54,365

95.0%

96.5%

$53,249

$53,081

95.0%

98.36%

98.0%

96.10%

$40,000 $30,000

Product A 95.0%

94.0%

Product B

93.15%

Product C

$20,000 $10,000 $0 Baseline (95% All Products)

Scenario 1

Scenario 2

Optimal Service Levels

Note: Associated customer service level for each scenario is indicated as percentage on bars

Optimized Production Patterns: With SmartOps EIO, companies leverage state-of-the-art, proprietary algorithms that determine optimal production quantities, frequencies, and sequences in production environments where many SKUs share limited manufacturing capacities. EIO balances the cost of carrying extra inventory — cycle stock — from long production runs against the cost of performing product changeovers. For example, manufacturing companies typically have significant levels of cycle stock due to large manufacturing batches and infrequent production cycles, trapping millions of dollars of working capital in inventory. Based on analysis of customer data, even a 10% decrease in cycle stock can result in a significant working capital reduction. By allowing EIO to optimize production patterns, a 10-20% reduction in cycle inventory is achieved, in addition to just setting production cycles based on EOQ or other simple rules.

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Base case – All products are produced once every two weeks

EIO – Producing the green product once per week cuts cycle stock in half

Production Sequence and Batch Sizes

Setup Production Setup Production

Unused capacity

Inventory Requirements

Setup Production

50% less inventory

Cycle Stock

Scalability and Automation: Setting inventory targets across an enterprise is a data-intensive calculation that requires frequent updates. For example, 1,000 finished goods items across 100 locations, planned in weekly time buckets across a 26-week future horizon, equates to 2.6 million inventory targets, with each consisting of a safety stock, cycle stock, pipeline, and prebuild value. Since each target would have anywhere from 10 to 25 key input values that must be incorporated into the optimization, the resulting quantity of data fields becomes tens if not hundreds of millions. In addition, with customer demand in a constant state of flux, a planner’s view of the world is forever changing. Therefore, as planners update their forecasts, hundreds of millions of inventory targets also must be dynamically updated. SmartOps designed the EIO solution suite to handle this amount of data in a timely, scalable fashion, ensuring that inventory targets are available when the planner makes the planning decision. In fact, customers report that planning activities that formerly took weeks to complete are now completed by EIO in a matter of minutes. SmartOps software is built on a Java-based, J2EE, services-oriented architecture. Running on top of an Oracle database, EIO software is completely web-enabled, and is compatible with all the major hardware, operating system, and application server configurations. The underlying inventory optimization algorithm is proprietary and, unlike APS applications, does not use linear programming or other deterministic techniques. In addition, the EIO suite can be connected through pre-built, automated data interfaces to existing ERP, APS, business intelligence, and database systems, eliminating the extensive manual effort associated with traditional spreadsheet or standalone applications. EIO’s capabilities and features solve the data-intensive, time-critical problem of setting the right inventory targets at the proper granularity level.

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EIO sample solution architecture Web User Interface

ETL Tools

Published Reports

Data Store

Multistage Inventory Planning and Optimization (MIPO)

Data Files

Analytics and Processors (DIM, SIM, and PIM)

Data Gateway

SmartOps Data Loading Tool (SDLT)

Other Systems

SmartOps EIO Suite

SAP Data Connector

ERP System

Business Intelligence Applications

Staying Ahead of the Curve SmartOps EIO not only calculates and maintains precise, correct inventory targets for execution, it also affords planners a complete view of their supply chain for more effective, efficient inventory planning. By using a common fact base for both execution and planning, EIO provides greater consistency to every level of the organization. EIO supports coordinated planning and execution processes with a consistent fact base Decision Focus/Type Decision Cycle

Planning Process

Systems

Strategic

Tactical

Annual

Budgeting / Annual Operating Plan

Quarterly / Monthly

Weekly / Daily

Sales, Inventory, and Operations Planning (S&OP, SIOP)

Replenishment / Order Fulfillment

Advanced Planning & Scheduling

Spreadsheets

Execution



MRP/DRP

 Manual Inputs Disconnects between systems  Inconsistent assumptions

EIO Disconnected provides consistent systemsoptimal and planning planning processes targets, leads basedtoon over-buffering, operational data, massaging to all levels of inputs/outputs, of planning &and execution scrambling

Because EIO calculates optimal inventory targets for all forms and purposes of inventory for every item and location in the supply chain, planners can manage inventory levels at the most granular level. They work with inventory targets that they can actually execute against, and © 2009 SmartOps Corporation

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gain the ability to hone in on issues in their supply chain and identify the specific inventory drivers. To manage execution targets effectively at this highly granular level of detail, EIO enables planners to set up exception alerts based on business rules, so they can focus planning effort on the high-value or outlying items. More time spent focused on exceptions means they can plan proactively instead of reactively. EIO lets planners and executives work with a view of inventory levels and inputs that was previously unavailable to them. EIO’s robust reporting and dashboards summarize the granular level execution targets and input data in formats that provide meaningful insight into operational performance and inventory drivers — information that makes planners and executives more responsive to changing supply chain demands. In addition, since planners can summarize inventory at any level of the supply chain, the same fact base may be used to support the execution systems along with the planning needs of supply chain executives. The EIO dashboard provides visibility into and across the supply chain

EIO further supports the strategic planning process with what-if analysis capabilities. EIO’s comprehensive data model allows planners to change input variables and see the effect of inventory levels and budgets – helping them identify and quantify continuous improvement opportunities. Planners can evaluate multiple future planning scenarios quickly and easily. For example, questions related to potential changes in demand, demand variability, lead times, cost, and target service levels may be explored either individually or together to see the effects on the supply chain’s required inventory.

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What-if scenario analysis Scenario Results Average Inventory (million units)

5.0 Base

4.0

-3% -7%

0.7 0.4

3.0

-6% 0.7 0.7

0.7 0.4

0.4

-5%

-4%

0.7

0.4

-3% 0.7 0.4

In-Transit Pre-build

2.0

Cycle Safety

1.0 1.2 0.8

1.1

1.0

0.9

1.0

1.1

0.0 EIO Base Case

Forecast Std CDC to PW OLT Forecast Std Dev Improved 3 Days Dev Improved 20% 10%

CFST 3 Days

Schedule Schedule CDC to PW LT Std Dev Attainment 5% Attainment 10% Improved 20%

Scenarios

Rapid Payback and Significant ROI SmartOps EIO customers have quickly implemented EIO, seeing the impact in just several weeks, and realizing a positive payback on the investment in as little as 6-9 months. Initially, SmartOps software may be deployed instantly through an Excel-based, manual, macro-driven data loading template, then subsequently integrated with existing planning and replenishment systems. When users decide to automate EIO, its pre-existing interfaces with common systems facilitate scalable integration to obtain dynamic targets. For example, SmartOps has an SAP Connector that provides a bi-directional application programming interface with common SAP R/3 and APO data fields. Sample Customer ROI EIO Investment Cost & Benefits Flow 30,000

5-Year Project Economics 25,000

Costs & Benefits ($)

ROI

898%

Payback

0.7 years

20,000

IRR

439%

15,000

10,000

5,000

-5,000

Year 0

Year 1 Total Cost

Year 2

Year 3

One-Time Benefits

Year 4

Year 5

Annual Benefits

Because companies are already making inventory planning decisions, the data for EIO exists within a company’s ERP or APS systems — EIO simply takes that data and helps the company make better inventory decisions. Since much of the data used by EIO is typically imperfect, its © 2009 SmartOps Corporation

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intelligence modules filter outliers, characterize the uncertainty, and create the required level of granularity to generate meaningful information for decision-making. The positive impact on a companyâ&#x20AC;&#x2122;s financials begins as soon as optimal inventory targets are fed into planning and replenishment systems and processes. The benefits become visible both on the balance sheet (in the form of less inventory and, at times, lower accounts receivable) and on the income statement (from higher gross margin and lower operational costs). With average inventory reduction of more than 20%, SmartOps EIO projects typically drive a five-year return of five to 10 times the original investment, carrying significant value to the bottom line and to shareholders. EIO impact on Shareholder Value Added (SVA) Examples of where supply chain drives SVA Service levels, order lead times, and order lead time variability all impact price of products and sales volume

Price times volume Operating Profit

Transportation costs, warehousing costs, obsolescence costs, inventory insurance costs, and inventory handling costs are all incurred trying to get the right product in the right place at the right time

minus Cost of goods sold plus

A more responsive supply chain drives down need to incur some selling costs

SG&A cost Shareholder Value Added

minus Cash, etc. Total assets

AR - AP Inventory

Asset charge

Better replenishment enables faster collection of accounts receivable

times

Replenishing to optimal inventory targets results in less cash tied up in inventory

PP&E Optimal use of existing distribution assets (warehouses, fleet) reduces need for capital investments

WACC

Better cash flow from lower supply chain cost and unnecessary assets drive higher credit rating and lower borrowing costs

EIO impact on Earnings per Share (EPS) Examples of where supply chain drives EPS Service levels, order lead times, and order lead time variability all impact price of products and sales volume

Price times volume Net Income

minus

Cost of goods sold plus SG&A cost Earnings Per Share

divided by

A more responsive supply chain drives down the number of customer service issues and the need to incur some selling costs

minus Interest, taxes, depreciation, and amortization

Total Shares

Replenishing to optimal inventory targets throughout the supply chain lowers the total amount of inventory and interest paid on debt needed to finance excess inventory; resulting improvement in balance sheet potentially lowers the interest rate for borrowing Optimal use of existing distribution assets (warehouses, fleet) reduces need for capital investments resulting in lower depreciation charges

Excess cash f rom one time reduction in inventory and ongoing lower annual supply chain costs can be used to buy back shares

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While a host of factors ultimately determine the extent of ROI and other positive effects, the potential is enormous for any Fortune 1000 or Global 2000 organization. One of the best examples of SmartOps EIOâ&#x20AC;&#x2122;s impact on financial performance is Deere & Company, a customer since 2003. In 2001, Deere & Company hit a historical low for Return on Invested Capital (ROIC). The company was performing well below the 500 Largest Companies Median and on the decline. To reverse this trend, the company instituted a strategic program to optimize working capital and, ultimately, increase shareholder value. EIO helped Deere reverse its declining ROIC

Using SmartOps EIO software to implement a multi-year inventory reduction program while improving service levels to its dealer network, Deere increased operational efficiency while improving its inventory management. The SmartOps inventory optimization model considers a complex set of variables, including real-time demand, service levels and the costs of carrying inventory. The optimization process gave Deere the information it needed for a strategic shift to better manage inventory levels as dictated by actual market demand and seasonality. SmartOps helped Deere meet demand with less product inventory

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By aligning inventory levels with demand, Deere achieved a dramatic $1.1 billion reduction in inventory ahead of the program’s schedule, and maintained lower inventory levels as sales took off between 2002 and 2005. Resulting in over a $1 billion reduction/avoidance of inventory

EIO Gets Results in All Industries Whether it’s a lawn mower, a flat screen TV, the rubber for a set of tires, a package of cereal, a tank car of chemicals, or a piece of heavy construction machinery — or the raw materials or components for these products — the common factor binding all industries is inventory. It’s the buffer in the supply chain that lets you meet demand when instant replenishment is not an option. The science required to accurately set inventory targets at the item and location levels across a planning horizon for an entire supply chain is the same for every business, and the challenges of proper inventory planning are fundamental to every supply chain. Similarly, SmartOps EIO delivers outstanding value to all industries. Companies that implement EIO typically realize inventory reductions greater than 20% and 20-40% reductions in inventory carrying and obsolescence costs, while maintaining or improving customer service and on-time deliveries. These results can be seen in the experiences of numerous SmartOps customers: Hewlett Packard’s Latin America Imaging and Printing Group reduced overall inventory levels by 29.1%. Rohm and Haas reduced days of coverage of supply by 15 days with a 55% reduction in safety stock, while improving service levels. Unilever’s Home & Personal Care division eliminated $30 million of inventory in North America (on a base of $125 million) in the first year of the project, while improving fill rates. Bayer MaterialScience reduced inventory by a 24% average with a 2% improvement in customer service levels in North America.

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In a rigorous regression analysis of the savings potential as a function of various supply chain parameters across industries, SmartOps compared customers’ identified inventory reductions and averaged the results by industry. This analysis revealed that inventory reduction potential is relatively similar, regardless of industry. Consistent inventory reduction potential across industries

% Inventory Reduction

40% 35% 30%

Stdev: 8% Stdev: 11%

Stdev: 3%

30.7%

Stdev: 13%

29.0%

30.4%

Technology

Life Sciences

27.6%

25% 20% 15% 10% 5% 0% Consumer Packaged

Chemical

Industry

The lesson? Inventory optimization benefits every organization in good times and in bad. As many of the world’s most successful organizations (along with some notable failures) have demonstrated recently, the ability to manage inventory and the overall supply chain for competitive advantage is no longer a wish. It is a strategic imperative.

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About SmartOps SmartOps, the market leader in enterprise-class supply chain optimization solutions, enables companies to manage the uncertainty of complex, multistage supply chains to achieve rapid return on investment and long term, sustainable value. Founded in 2000 and headquartered in Pittsburgh, Pennsylvania, United States, SmartOps created the market for Enterprise Inventory Optimization (EIO) software. Deploying SmartOps’ solutions has dramatically improved supply chain performance at Fortune 1000 and Global 2000 companies in discrete manufacturing, consumer packaged goods, chemicals, technology, life sciences, and distribution/retail industries. Typical value achieved is a 20-30% sustainable reduction in inventory within the first year, along with improved customer service and reduced supply chain cost. SmartOps’ mission is to be the de facto standard for global inventory planning, optimization, and governance. SmartOps accomplishes this by providing dynamic key operating targets across the enterprise, resulting in a sustainable and substantial reduction (20%+) of the more than $1 trillion of inventory that exists in supply chains today, while improving customer service and responsiveness. In May, 2009, SmartOps and SAP AG announced a reseller agreement, through which SAP will resell the SmartOps Enterprise Inventory Optimization solution. SmartOps EIO is the official SAP solution extension for inventory management. This agreement provides SAP customers with the value of SAP joint development, delivery, and support for SmartOps EIO. Sample SmartOps EIO Customers

SmartOps Corporation One North Shore Center, Suite 400 12 Federal Street Pittsburgh, PA 15212 United States

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Contact Information +1.412.231.0115 sales@smartops.com