1. 1
Using Inventory Modeling to Develop
a Holistic Inventory Strategy
EBOOK
How supply chain modeling technology is
driving measurable improvements in complex
inventory challenges for global businesses
Most companies are trying to achieve two things
with an inventory strategy: service improvement
and reduction in on-hand inventory/working capital.
It’s often difficult and sometimes impossible to do
both simultaneously. This ebook addresses some of
today’s biggest inventory challenges and offers new
approaches to achieve holistic inventory optimization
for “right-sized” inventory levels.
2. 2
The modern supply chain is an increasingly complex and
volatile network that often stretches across continents and
supports numerous market segments. With this complexity,
the impacts of change are harder to determine and the
risks involved with being unprepared increase. Changes in
demand, shifts in commodity prices, supply disruptions,
variability in transportation availability, natural disasters,
geopolitical change and regulatory issues all impact the flow
of goods to market.
Top supply chain officers across the industry were recently
surveyed1
on their biggest barriers to effective inventory
management. The number one response was
“Can’t Optimize Network Holistically”. Often inventory
placement and policies are the last detail of the supply
chain to be addressed. Rather than analyzing the impact
across the supply chain, companies are making decisions
in a vacuum. The second largest barrier was “Demand
Volatility.” Product demand has become more volatile and
hard to predict over time. How do you predict how much
inventory to build when you can’t predict the demand?
INTRODUCTION
Roadblocks to Effective
Inventory Management
3. 3
Similarly, executives identify demand volatility and
operational complexity as major risk factors over the
next five years.2
Without a way to digitally model
supply chain operations and inventory policies,
companies would need to experiment in the real world
which is time-consuming and extremely costly.
Supply chain design enables companies to create living
models of the end-to-end supply chain, encompassing
physical infrastructure, policies, demand and inventory.
These models provide a true holistic view of all the
interdependencies and trade-offs with each supply chain
question and enables true data-backed decision support
instead of risky and often costly real-world testing.
Case Example
Managing Inventory Levels at
Dealers and Distribution Centers
Challenge: A large construction equipment manufacturer
needs to improve service performance and inventory
levels for high value product lines. They were holding a
lot of inventory in finished goods at dealers and needed
to understand where to hold safety stock, how much and
what to hold in order to meet service requirements. They
also needed to identify more effective postponement
and risk-pooling strategies to enable overall reductions in
working capital.
Solution: Network optimization helped identify optimal
DC locations and understand the overall impact on both
network costs and safety stock levels. The construction
equipment manufacturer created new postponement
strategies on product inventory levels at dealers and DCs.
Results: After creating a step-by-step plan to implement
recommendations they have identified opportunities to
implement relocation of distribution centers, improve
manufacturer and dealer response times, create effective
postponement strategies and achieve significant savings
per year in inventory costs along with improved customer
service levels.
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Influencing Factors and Interdependencies
There are many varied questions that need to be addressed
as you begin to build an inventory strategy, including:
• What service levels should we have?
• Where should we stock our inventory?
• How much do we need to stock?
• Where should our stock flow through and with what
production and distribution network?
• How do I consider product shelf life & short product life
cycles when right sizing inventory?
Most people automatically think about safety stock when
talking about inventory optimization as a way to address
demand and supply variability and uncertainty. However,
that isn’t the whole story. There are many other aspects of
stock that need to be considered in addition to safety stock.
Considerations for
Inventory Strategy
Development
Cardinal Health Cuts Inventory
Cost by $4.5 Million Using
LLamasoft Supply Chain
ModelingTechnology
DOWNLOAD PDF
5. 5
Customer Demand
Orders
Products
Locations
Desired Dates
Quantities
Manufacturing Network
Products
Locations
MTS vs. MTO
Capacities/Capabilities
On Hand Policies
Service Level Policies
Manufacturing
Frequencies and Lead
Times
Lot Sizes
Facility Costs
Operational Costs
Product Value
Distribution Network
Products
Locations
Capacities/Capabilities
On Hand Policies
Service Level Policies
Replenishment Polices
Return Processes
Facility Costs
Operational Costs
Product Value
Transportation Network
Modes
Tariffs/Rates
Shipment Frequency
Transit Times
Shipment Sizes
Merchandising
Products
Substitutions
Channels/Format/
Location
Open-to-Buy
On Hand Policies/VMI
Availability Policies
Margins
Store Operations
Receiving Policies
Handling Costs
Storage Areas
Return Processes
Considerations for Inventory Strategy Development
6. 6
• For most companies cycle stock is a large missed
opportunity. So many overall supply chain design decisions
affect cycle stock levels and accounts for lot/batch/
shipment sizes, minimum order quantities, and production/
replenishment frequencies and lead times. By not
considering impacts on cycle stock, many companies are
overlooking potential money saving adjustments.
• Prebuild inventory is to account for insufficient
capacity to support seasonal demand spikes. Inventory
needs to be prebuilt because the decision has already
been made to not have the production capacity to cover
all demand during seasonal demand spikes.
• Promotional inventory to account for created spikes in
demand driven by marketing and/or customers.
All of these stock considerations are interdependent and are
directly related to supply chain network design decisions that
often have already been made. It is essential to have tools
that enable you to not only look at these decisions from an
inventory perspective but analyze how changes in inventory
effect the entire supply chain network and performance.
From customer demand, to manufacturing goods, to
transporting them, to supplying good to stores, inventory
impacts all areas of the supply chain.There are hundreds
of what-if questions to answer. If you adjust any part of the
supply chain, inventory will move as a result, and you need
to understand the relative impact of all of these variables on
cost, service, risk levels and sustainability.
Operation Complexity
Increases Challenge of Inventory Strategy
Development
Large supply chains are not the only ones that have complex
operations. For example, a company with a seemingly simple
network of three plants, three distribution centers and 9,000
finished goods may have a high level of shared raw materials
and components making their network very complex. With
so many options and combinations of how materials can go
into making each product, it is too much to figure out the
correct combination and optimal levels of inventory manually.
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Understanding Demand
Patterns/Variability
How well do you understand your demand patterns? Have
you taken the time to look at and analyze demand and
what signals it is sending into your supply chain? Do you
understand your demand in conjunction with stocking
locations where your inventory should be held?
Many classic techniques for how safety stock will be
determined assume a normal distribution of demand and
supply. This makes for some very simple and easy math,
but the truth is that most of demand is not normal. Most
demand has high levels of variability and is not consistent
from period to period. If you’re driving decisions for
inventory on the classic method, inventory will be either
overstocked or understocked depending on your actual
demand. You need the ability to classify your demand to
make high level segmented supply chain decisions to drive
stocking and overall inventory strategies.
Demand Propagation and Analysis
When making inventory decisions based on demand,
focusing on just one individual customer will give you a
false reading on what correct aggregate demand actually is.
You may have many customers that have erratic demand,
but considering the aggregate customer demand up to the
distribution level will create smooth demand that is easier
to analyze. A company can use this information to work
with manufacturing to better understand how changes in
production will effect inventory and service levels at each
distribution center.
“LLamasoft makes inventory optimization
modeling tremendously easier than with
our previous solution. We saw a big
improvement in process time, execution
time and quality of demand analysis.”
– Global Demand Manager
of a Chemical Company
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0
100,000
200,000
0 20 40 60 80 100
SSQty
Service Level
Historical Service Levels vs. Target Service Levels
Service vs Safety Stock Qty
0
50
100
150
Extremely
Variable
Slow Low Variable Lumpy Slow Highly
Variable
Erratic
AverageDOS
Demand Classification
Supply Chain Guru Recommends DOS by Demand Classification
90% Service Scenario
Challenge: A large retail company needed to improve their
overall service to customers.They had a large number of
SKUs in their network and multi-tier parent-child relationship
distribution center structure.They currently have a fixed DOS
year-round regardless of demand class but were interested in
understanding the cost of incremental service.
Solution: Spend the right amount of capital in the right
location by using demand classification and creating unique
inventory policies by SKU.They had a decision, either spend
25 percent less capital to achieve the same 80 percent
service level as today or spend five percent more in capital to
reach their target 90 percent service level.
Results: The large retail company was able to obtain service
levels of 90 percent with only five percent increase in
working capital, free up $8.4 M of capital held in unnecessary
safety stock and have the potential to apply the capital to the
right SKUs and locations to get back ~$75 M in lost sales.
Case Example
Balancing a Large Number of SKUs
with Customer Service Levels
By increasing capital investment by five percent this large retailer
was able to obtain 90 percent service levels in key demand classes.
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Unfortunately, many companies begin looking at their
inventory strategy development with a technology already
in mind. Technologies are wonderful and have the ability to
make a huge impact, but well before technology can be part
of the equation one needs to understand what business
problem(s) need to be solved. Understanding demand and
the root cause of inventory issues should be next, then
technology assessment and finally model development
and scenario analysis. Creating inventory strategy needs
to be thought of as a repeatable process and considered
a best practice. Supply chains are dynamic. With constant
changes, only analyzing inventory processes every three to
five years could be a huge competitive disadvantage and
may mean you are wasting millions of dollars every year.
Building an Inventory Strategy: Where to Begin
Strategy & Policy
Development
Repeatable
Process Defined
Model Development &
Scenario Analysis
Technology
Assessment
Inventory Drivers &
Root Cause Analysis
Data Collection &
Demand Classification
Specification & Scoping
of Business Challenge
10. 10
Supporting Technologies
There is a spectrum of technologies that help with
inventory and supply chain decisions. Technology can be
evaluated in terms of ability to influence decisions and what
competitive advantages they can provide. The graph to the
right maps out common supply chain technology areas on
this spectrum.
There is value in inventory reporting and querying and drill-
downs, but they are always looking in the review mirror—
great for telling you what impact your previous decisions
had on your business outcomes. LLamasoft technologies
have more forward-looking capability:
• Simulation
• Heuristics
• Optimization
Ability to Influence Decisions
Business Intelligence
(”Rearview Mirror”)
Decision Support
(”GPS”)
Standard Reports
Ad Hoc Reports
Query/Drill Down
Alerts
Statistical Analysis
Descriptive Formulas
Simulation (Discrete Event,
System Dynamics, Agent Based)
Predictive Modeling
Heuristics &
Genetic Algorithms
Optimization
CompetitiveAdvantage
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Tips for Choosing Technology Partners to
Support Your Inventory Strategy
• As stated earlier in this ebook, demand classification
is of utmost importance. Correct inventory decisions
cannot be made without first understanding demand.
Using a tool that can help you to track and predict
demand is essential.
• A tool that optimizes inventory across all tiers of the
supply chain or end to end optimization is critical for
success.
• For time-phased seasonality considerations, a tool to
help make decisions on when to prebuild inventory,
where to hold inventory, and whether building more
capacity instead of prebuilding is necessary.
• What are your inventory management techniques to
manage the inventory you have and make decisions on
inventory in the future? If you don’t know the answer to
these questions you’ll need a tool to help you develop
inventory policy.
• Service level optimization and stratification to help you
decide what the best levels of service are for all of your
product SKUs.
• Simulation will help you take the results of the above
optimization solutions and model what these changes
will do to the supply chain.
Technologies
Demand
Classification
Inventory
Policy
Development
Time Phased
Approach for
Seasonality
Multi Echelon
Inventory
Optimization
Simulation
Service Level
Optimization
& Stratification
12. 12
Instead of being wary of the optimal levels of inventory
proposed by supply chain technologies, simulation helps
support the validation of operational feasibility of inventory
strategy in a locked down environment instead of having
to test the strategy in real world situations. Simulation also
provides detailed visibility of supply chain performance on a
detailed daily/weekly/monthly view.
Benefit ofTesting
Optimization
Results with Simulation
Fill Rate: 96%
Safety Stock: 870
Fill Rate: 100%
Safety Stock: 1250
Assuming
Normality
Target Fill Rate: 95%
Optimal Safety
Stock: 834
UsingThe
Right Demand
Classification
Modeling non-normal demand provides a 30% inventory
savings (in blue) over the ‘traditional’ solution (in orange)
13. 13
Challenge: The large healthcare company’s hip
reconstruction products had an exceedingly complex
inventory problem. For every patient surgery that is
scheduled each operating room requests the full set of
products be ready in the surgery.This generates significant
excess inventory that will either sit in hospitals unused
or need to be sent back to the manufacturer adding
additional costs to both the hospital and the manufacturer.
Another aspect of the challenge is very high service level
requirements for surgeries raising the question of how they
can free up working capital and run a simulation to verify that
service is not being compromised with the new strategy.
Solution:To reduce inventory in the field the company
developed two inventory reducing strategies. The first
would require surgeons to use patient-specific implant sizing
based on digital templates to request more accurate hip
sizing. The second would be to work with hospitals to share
surgery schedule data three to four weeks in advance for
better inventory forecasting. A baseline model of the existing
network was created and they conducted scenario analysis
on alternative processes and network configurations using
network optimization, safety stock optimization and simulation.
Results: Each inventory strategy recommendation was
determined and validated in simulation showing that a
combination of safety stock and providing one backup size
would result in the highest percentage of correct sizing
fulfillments and reduce costs by 16 percent resulting in
millions of dollars saved by hospitals and the manufacturer.
Case Example
Health Care Company Addresses
Patient-Specific Inventory Challenges
Value
Baseline
Optimized
Network
16% Cost Reduction
15% Inventory
Reduction
Total Inventory Holding Cost
Return Transportation Cost
Outbound Transportation Cost
14. 14
The LLamasoft®
Supply Chain Guru®
supply chain modeling
platform enables companies to model their supply chain
operations then run inventory policy experiments and
optimization scenarios to find actionable solutions.
• Demand Segmentation: Identify SKU-level demand behaviors
at each echelon of the supply chain, then categorize them
based on their unique attributes
• Inventory Policy Prescription: Prescribes the appropriate
inventory policy for each demand category to help yield optimal
service levels at the lowest total cost
• Multi-Echelon Inventory Optimization: Identify the best
possible inventory stocking levels for each product-site
combination throughout the supply chain
• Simulation: Simulate each individual order, shipment, and
replenishment action to track the overall performance of the
supply chain under real-world conditions
This rigorous approach to inventory modeling that spans
demand segmentation to inventory policy prescription to multi-
echelon inventory optimization to simulation provides:
• The most accurate and robust inventory strategy
• A strategy that can be feasibly deployed in the real world
• The best balance between service and cost (working capital)
Putting it AllTogether
15. 15
Case Example
Integrating Multi-Echelon Inventory Optimization into
a Monthly Planning Process
Challenge: A global manufacturer of latches, screws and
hinges had a manual inventory planning process of reviewing
demand to set safety stock levels based on variability of the
SKU.This process lacked the ability to analyze the impact of
stocking decisions across sites and evaluate the impact of
variability and customer service policies on inventory levels.
Solution: The company adopted multi-echelon inventory
optimization (MEIO) to simultaneously optimize inventory
targets across all items, echelons and locations to meet
global service level targets.The first step was to build
a Supply Chain Guru model of the company’s products,
from raw materials to finished goods. Next, 15-20 different
scenarios were modeled to the impact of key drivers
(e.g. service level, service time, lead time, lot size and
replenishment frequency) on safety stock and cycle stock.
Results: The project demonstrated a significant opportunity
to reduce inventory levels of stocked items while improving
service levels:
• The MEIO solution sent to SAP provided a powerful tool
for monthly inventory planning
• Safety stock reductions could provide an inventory value
reduction of 16 percent
Total inventory value reductions of 20-25 percent can
be achieved with reductions in minimum order size,
replenishment frequency and reduction in lead times.
