copyright © 2011 syspro all rights reserved. inventory optimization user group 17 th august 2011
TRANSCRIPT
Copyright © 2011 SYSPRO All rights reserved.www.syspro.com
Inventory Optimization
User Group 17th August 2011
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What we’ll cover
Why Optimize Inventory?
The Four Steps to Inventory Optimization
Measurement of Inventory Performance
The IO Suite in Relation to other SYSPRO Modules
Looking at the Four Steps in more detail
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Why Optimize Inventory?
Inventory costs a lot to acquireInventory often in top two assets
Inventory costs a lot to keepStorage costs 20% - 40% of its cost valuePoor stock turns a low return
Inventory affects service levelsCustomer satisfactionWithout customers you don’t have a business
Supply chains don’t work without inventory
Cost
Cost
Inventory represents an opportunity for big gains
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Benefits of Inventory Optimization
Improved forecast accuracyA better estimate of the demandLower safety stock
Reduces investment in inventoryTypical reductions of 20% - 30%Improved stock turns
Improves achieved service levelsTypical increases of 3% - 30%Improved sales turnoverImproved ROI
Identifies waste in the supply chain
Focuses on where value is delivered
Cost Cost
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Forecast Error
Why Inventory Optimization?
Time
Level of
Inven
tor
y
Forecast
Lead Time
Lead Time Error
Inventory Optimization
Actual Demand
The primary drivers of Inventory Optimization are uncertainties in Supply and Demand
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Causes of inventory
Uncertainties in demand
Uncertainties in supply
Lead time greater than service time
Demand & supply quantities not equal
Limitations on order frequency
Higher service levels DemandSupply
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There are three kinds of inventory
Time
Lev
el o
f In
ven
tory
Safety or buffer stockLowers risk of stock outsBalance between cost and service
Cycle stockTo meet demand levelsConstrained by batch size, EBQ, MOQ, or shipping constraints
Excess stock Result of poor forecasts, policy settings or management
Minimum
Maximum
Average Stock
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The Four Steps to Inventory Optimization
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The 4 Steps to Inventory Optimization
Understand the importance and behaviour of the stock codes in each location
Get the best possible estimate of Demand (Forecast)
Set the appropriate stock levels to meet this demand (Stock Policy and Modelling)
Replenish Timeously to Plan
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The inventory variables
Actual Demand
Demand Forecast
Forecast Accuracy
Order frequency
Lead time
Order or lot size
Delivery reliability
Target service level
Time-phased Target Inventory
Stock PolicySupply side Demand side
Modeling
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Graphic illustration of the 4 Steps
Let’s take a look at what the IO Suite does
Inventory Forecasting (and Families & Groupings)
Inventory Optimization
Remember the 4 Steps?
After this we will delve into a more detailed view
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Step1: Identifying key items through Pareto analysis – importance and behaviour
0%10%20%30%40%50%60%70%80%90%100%
0% 20% 40% 60% 80% 100%
D 46%of itemsC
16% of items
80%
A17% of items
95%100%
Sales value ranking of items
Per
cent
age
sale
s va
lue
Percentage active stock codes
98%
B21% of items
1. Importance and Behaviour
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Step 2: Get the best possible Forecast
April
May
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
April
May
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
April
May
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Now
Actual DemandBest Fit AlgorithmDemand Forecast
1. Input Historical Data (in this Example We Have 2 Years)
2. Use Inventory Forecasting or Families & Groupings to Find the Best Suited Algorithm 3. Use the Algorithm to Forecast into the Future
2. Best estimate of
Demand52 000.00
48 000.00
44 000.00
40 000.00
36 000.00
32 000.00
28 000.00
24 000.00
20 000.00
16 000.00
12 000.00
8 000.00
4 000.00
0.00
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Step3: What is the right stock level for this Demand?
April
May
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
April
May
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
April
May
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Now
Actual DemandBest Fit AlgorithmDemand Forecast
52 000.00
48 000.00
44 000.00
40 000.00
36 000.00
32 000.00
28 000.00
24 000.00
20 000.00
16 000.00
12 000.00
8 000.00
4 000.00
0.00
2. How Much Stock For This
Demand?
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Step3: Set the Appropriate Stock Levels
April May June July Aug Sept Oct Nov Dec Jan Feb Mar
Now
Demand Forecast
MinMax
Resulting Stock (Average)
52 000.00
48 000.00
44 000.00
40 000.00
36 000.00
32 000.00
28 000.00
24 000.00
20 000.00
16 000.00
12 000.00
8 000.00
4 000.00
0.00
1. Depending on Your Stock Policy IO Calculates Min/Max Levels for the Forecast
2. Let’s say we decide the Min/Max Levels were not ideal so we try different policy options
3. Set Appropriate Stock Levels
Cost
Stock policy
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Step 4: Replenish Timeously to the Plan
April May June July Aug Sept Oct Nov Dec Jan Feb Mar
Now
4. MRP Calculates How Much
Replenishment & By When
Demand Forecast
MinMax
Resulting Stock (Average)52 000.00
48 000.00
44 000.00
40 000.00
36 000.00
32 000.00
28 000.00
24 000.00
20 000.00
16 000.00
12 000.00
8 000.00
4 000.00
0.00
1. Once we are satisfied with the Min/Max Levels – this becomes input to MRP
2. MRP Takes Calculated Min/Max Levels, the Opening Stock, Orders In Process and Lead Time, and Suggests Replenishment To Comply With The Stock Policy
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Measurement of Inventory Performance
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Determining Inventory Performance
Try to find a balance between Service and the investment in inventory to provide it
Measure the Service delivered to the customer
Measure the quality of the Forecast (Forecast Error or Accuracy)
Measure how fast the inventory “turns over”Stock Turns = Annual Cost of Sales / Cost of Stock
An alternate view of this is the “stock cover”Months Cover = 12 / Stock Turns
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The IO Suite and Other SYSPRO Modules
Inventory Forecastin
gSales Orders
Families and
Groupings
Inventory Optimizati
on
Requirements PlanningInventory
Forecast
Master Data, Setup, Stock
on Hand
Min / Max levels
Work in Progress
Purchase Orders
Open Purchase Orders
Open Jobs
Historic Deman
d
Forecast
Master Data, Setup, Stock
on Hand
Open Jobs
Open Purchase Orders
2. Best estimate of
Demand
3. Set Appropriate Stock Levels
4. Replenish Timeously to
Plan
1. Importance and Behaviour
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Behaviour and Importance of Stock Codes
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Analyse for Importance and Behaviour
Example from a SYSPRO customer
Over 3 000 SKUs
Many of these have erratic demand
Use a Pareto (ABC) based on sales value or gross profit to analyse importance
Use a Pareto based on hits (demands) as a simple indicator of forecastability
Combine these to manage in like groups
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Use a combination of Hits and Sales Value
Hits (Demands):
A > 36 p.a.
B 13 to 35 p.a.
C 7 to 12 p.a.
D 1 to 6 p.a.
Sales Value:
A 80% (> R275 000 p.a.)
B 95% (R34 000 to R275 000 p.a.)
C 98% (R11 800 to R34 000 p.a.)
D 100% (R1 to R11 800 p.a)
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Examples of the Combined Ranking
Item Hits Qty Sales ValueHits ABC
Sales ABC Both
RF12 3 107 16 460 7 035 336 A A AA
VH72 2 079 19 540 4 511 775 A A AA
H7F3 6 6 3 970 154 D A DA
F114 2 720 9 005 32 871 A C AC
P99 11 12 100 3 342 089 C A CA
RF81 1 013 7 306 8 449 A D AD
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Getting the Best Possible Forecast
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Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0
50
100
150
200
250
Forecast = Mean 100
Max Demand 200
Min Demand 50
Half the Average Demand
Double the Average Demand
Forecast without Seasonality
Demand Forecasting Based on Average Demand Leads to Poor Forecast Accuracy
Average Demand = 100 unitsDemand Varies from 50 - 200 units
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Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0
50
100
150
200
250
Average Demand 100
Min Demand 50
Max Demand 200
Actual (+)
Actual (-)Revised Forecast
Forecast with Seasonality
Demand Forecasting Based on Accurate Seasonal or Other Trends Leads to Better Forecast
Accuracy
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A more complex demand pattern
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Looking at 3 Years of Demand
Average for forecastAverage stock 2.5 monthsStock Turns 4.8Service level < 85%Forecast Accuracy < 60%
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Using a more suitable Algorithm
Holt-Winters MultiplicativeAverage stock 2 monthsStock Turns 6Service level 90%Forecast Accuracy > 90%
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Forecast Accuracy
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Set Policy and Model Stock
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Setting Dynamic Min / Max Levels
Average stock 1.2 monthsStock Turns 10.2Target Service level 95%Forecast Accuracy > 90%
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Safety Stock vs Service Level
Investment
70 %
75 %
80 %
85 %
90 %
95 %
100 %
Ser
vice
Lev
el
2 weeks 4 weeks 6 weeks
10 %
3 %
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Achieved Service Levels
Achieved Service Level for a Selection Set
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Achieved Service Levels
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Sort on Actual Shortfall Descending
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Manage the Plan through MRP
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IO Levels in Requirements Planning
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