The document discusses a new approach to inventory optimization using a stochastic multistage model that addresses supply chain inefficiencies caused by outdated inventory management practices. It emphasizes the dynamic nature of modern supply chains and the need for data-driven decision-making to improve operational efficiency. Additionally, it outlines the requirements for effective inventory management applications to support planners in adapting to changing demands and optimizing stock levels across multiple locations.

1. SAP Thought Leadership Paper
Supply Chain Management
Inventory Optimization
A New Approach to Operational Inventory Planning

2. Table of Contents
4 Executive Summary
5 Inventory Management Has
Changed
The Science
The Business Requirements
The Application

3. Inventory targets at one location affect, and
are affected by, targets at different locations.
But if those targets are out of sync with
your business needs, excess safety stock
at multiple locations can result in costly
inventory inefficiencies across the supply
chain. To minimize the need for excess stock,
SAP offers a stochastic multistage model
that solves multiple mathematical equations
simultaneously to reveal optimal inventory
targets.

4. On the Road to Optimization
Executive Summary
In today’s ultracompetitive business This paper examines how the stochas-
environment, companies can ill afford tic multistage, multi-inventory model
supply chain inefficiencies. But if plan- supports inventory optimization. It
ners are using outdated inventory also looks at how the SAP® Enterprise
management models, it can be challeng- Inventory Optimization application by
ing to run a tight ship. SmartOps uses the model to help supply
To boost efficiency, run leaner, and planners execute more effectively. The
drive down supply costs, many organiza- software enables a collaborative approach
tions are exploring inventory optimiza- that extends beyond organizational
tion. This technique improves inventory boundaries while helping planners predict
targets to address the realities of today’s demand patterns more accurately. And
complex, ever-evolving global supply an option that provides analytics for
chains. the application delivers executive-level
insights and reporting using a focused
dashboard.
No planner knows everything, and the
models that planners work with should
reflect this reality.
4 SAP Thought Leadership Paper– Inventory Optimization

5. The Multistage Model
Inventory Management Has Changed
Traditional approaches to inventory plan- The Science Dynamic, Not Static
ning are based largely on rules of thumb. To accommodate constantly changing
Planners develop a set of heuristics The science behind inventory optimiza- demand, inventory planners often cobble
for determining safety stock levels, and tion involves stochastic (probabilistic) together sets of unconnected static
these rules get handed down. Some multistage, multi-inventory modeling in models to ensure proper levels of safety
organizations also use rudimentary which a sophisticated algorithm is used stock. In contrast, the multistage model
analysis, in which items are weighted to assess vast amounts of historic and is dynamic and can accommodate shift-
on an A-B-C scale with the priority of real-time information while accounting ing demand so that peaks and troughs
keeping A-level items in stock. The as- for multiple variabilities and interdepen- are balanced out over time. The dynamic
sumptions made for this sort of analysis, dencies. By enabling the analysis of a character of the model also allows orga-
however, are typically revisited rarely. staggering number of variables, con- nizations to model seasonality, promo-
In fast-changing environments, this straints, and what-if scenarios, this tions, and end-of-quarter spikes. It ac-
approach can lead to out-of-stock situa- model empowers planners to manage commodates the fact that uncertainty
tions and supply chain inefficiencies. the complexity of today’s supply chains. is greater when a company looks farther
The complexities and uncertainties in This approach differs from traditional ahead in time – something traditional
today’s constantly evolving global supply inventory management models that approaches cannot do.
chains demand a dynamic new approach. depend on deterministic, discrete-time
The inventory optimization approach inventory theory in the following ways. Data Driven, Not Assumption Based
augments existing enterprise resource The multistage model recognizes that
planning (ERP) and advanced planning Molecular, Not Atomic organizations work only with finite histor-
and scheduling systems, helping plan- Traditional inventory management views ical data. Traditional models, on the other
ners improve operational inventory the supply chain according to a single- hand, start with an idealized assumption
targets with item-location-period granu- stage, single-item model. This model that planners possess complete knowl-
larity for finished goods, intermediate sees each stock item and each stage or edge of demand distribution. No planner
items, or raw materials and components. stock location as isolated entities with knows everything, and the models that
The result is better visibility into demand, few, if any, meaningful dependencies. planners use should reflect this reality.
enabling planners to modify inventory The multistage model, in contrast,
and reduce carrying costs without im- views the supply chain in terms of mole- Variable, Not Unvarying
pacting customer service levels or sacri- cules made up of atoms. This reflects Traditional models lack the mechanisms
ficing product availability. This approach the reality of today’s multistage supply to dynamically capture changing values
empowers organizations to improve chains that include suppliers, numerous or correct for errors over time. The multi-
performance and more effectively meet manufacturing stages, subcontractors, stage model, by contrast, is flexible
the terms of service-level agreements. vendor-managed inventory, central enough to continuously incorporate the
warehouses, and multiple distribution results of ongoing data analysis. This
centers. analysis helps identify forecast errors
and biases so that planners can correct
values and modify assumptions.
SAP Thought Leadership Paper– Inventory Optimization 5

6. The Business Requirements Data Input Connectivity ment processes. Planners should have
Better outputs require better inputs. the ability to play out what-if scenarios
The purpose of the multistage model is Thus, an inventory optimization applica- and study the ramifications of proposed
to help planners in real-world supply tion should include data connectivity actions. Tools that support the visualiza-
planning scenarios. Any application that modules that can work with a wide range tion of alternative strategies and the
seeks to leverage the multistage model of data sources to transform and load comparison of planned and actual sce-
must meet the following requirements. raw data easily and automatically. These narios help businesses predict possible
modules should also accommodate the outcomes. In this way, they can identify
Enterprise Readiness supply chain network structure itself, effective actions to improve supply chain
Many inventory optimization applica- which is often the most challenging efficiency.
tions fail to address the fact that supply aspect of data connectivity.
planning is a collaborative activity that Executive Visibility
extends beyond enterprise boundaries. Built-in Intelligence Information is of no value if it is not read-
They are neither scalable nor capable of The ability to access data is important. ily accessible to the people who need it.
automating planning processes. What’s But planners also need to work with that At-a-glance update mechanisms such
needed is an application that leverages data. An inventory optimization applica- as executive dashboards are vital for
the multistage model at an enterprise tion, then, must support robust analysis helping planners and senior managers
level. Requirements include visibility to help planners understand issues in- to focus on and evaluate supply chain
across multiple ERP applications and volving forecast bias and accuracy, sup- performance in regard to established
planning systems, along with support plier uncertainty, schedule adherence, targets.
for global inventory planning. This and more.
allows planners to understand inventory The Application
liabilities, maintain service levels, and op- Approval Workflow
erate according to supplier- and vendor- Planners need to review updated inputs The SAP Enterprise Inventory Optimiza-
managed inventory business models. (such as forecasts), perform due dili- tion application addresses these require-
gence, and approve any modified targets ments, helping organizations strike the
Flexibility in order to avoid problems downstream. right balance between service levels and
An inventory optimization application An inventory optimization application inventory investment. The application
needs to be flexible enough to accom- should accommodate this requirement can be used on a stand-alone basis, if
modate industries as varied as consum- with automated workflow and alerts that desired, or as an integrated part of the
er products, chemicals, manufacturing, allow planners to manage by exception. SAP ERP application or the SAP Advanced
and high tech. It requires reporting tools Planning & Optimization component.
that can help validate, analyze, and im- Continuous Improvement In either case, it enables planners to
prove industry-specific supply chain Supply chains are in constant flux. This is dynamically determine optimal demand-
information regarding demand, supply, why inventory optimization applications driven, time-phased inventory targets for
and production elements. need to support continuous improve- every item at every location throughout
the supply chain.
6 SAP Thought Leadership Paper– Inventory Optimization

7. Learn More
SAP also provides an option for analytics •• Accurately track and streamline inven-
that helps planners monitor demand, tory positions throughout the order- To learn more about how SAP Enterprise
inventory, and supply data against pre- to-cash value chain, using advanced Inventory Optimization can help your
scribed targets. The option uses SAP algorithms that eliminate waste and organization compete more effectively,
BusinessObjects™ business intelligence help the organization run leanly contact your SAP representative today
or visit us online at
solutions with preconfigured data analy- •• Access real-time, at-a-glance updates
www.sap.com/lines-of-business/scm
sis functionality to populate executive on supply chain performance, identify- /inventory-optimization.
dashboards and performance reports. ing trends and deviations from pre-
defined targets and refining inventory
The Right Inventory strategy accordingly
Specifically, planners can: •• Use flexible data filtering to pinpoint
•• Coordinate capacity, inventory, demand, issues at a granular level, allowing re-
lead time, and product availability vari- medial measures to be implemented
ables to gauge how much inventory to meet key performance targets
should be carried by item, location, •• Visualize “what-if” scenarios, compare
and time period historical trends, and analyze the im-
•• Leverage a multistage modeling pact of alternative supply chain
approach to calculate the relationships strategies
among inventories, service levels,
capacity, and costs across all stocking In the end, these functionalities enable
locations and stages – and across your planners to optimize inventory
different types of supply chains within levels throughout the organization,
organizations and beyond enterprise helping you improve customer service
boundaries to support supplier- and levels while minimizing working capital
vendor-managed inventory requirements. This makes you more
•• Set and manage targets such as safety efficient and far more competitive.
stocks more frequently at a more gran-
ular level, supporting lean processes
SAP Thought Leadership Paper– Inventory Optimization 7

8. www.sap.com/contactsap
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