1) Numerical methods were applied to improve supplies inventory management, increasing productivity by 1000%. Automating manual tasks like demand analysis freed up time for planning. 2) Accurate lead time and demand estimates are essential for balancing service level and inventory cost. Statistical analysis of past lead times and demand identified improvements over standard estimates. 3) Testing of new statistical lead time and demand estimates on sample items showed benefits to both service level and reduced inventory investment. Further testing across more items could provide more insights.

1. Supplies' Inventory Management Improvements
July 21, 2015
Gary B. Lauson, M.S., P.E.
1

2. Supplies' Inventory Management Improvements
Presentation Topics
• Numerical Methods Applied to Stochastic Inventory Management
• Increased Inventory Management Productivity by 1,000 Percent
• Lead Time accuracy is essential to the right balance between Service Level and Inventory Investment
• Demand accuracy is essential to the right balance between Service Level and Inventory Investment
• Future Improvements
• Numerical Methods can generally be defined as Computer Math
2

3. Supplies' Inventory Management Improvements
Numerical Methods Applied to Stochastic Inventory Management
• “The most important contribution management needs to make in the 21st century is . . . to increase the
productivity of KNOWLEDGE WORK and of the KNOWLEDGE WORKER” – Peter Drucker, Managing the
Challenges of the 21st Century
• Supplies’ planning work is mostly manual; therefore, the applied Numerical Methods are based on
automated simulation of manual planning methods.
• Manual planning evolved out of a need for reduced inventory and no existing method for computing the
basic MRP parameters: ReOrder Point and Economic Order Quantity.
• Today, Supplies has 550 C-Items on a rudimentary MRP system.
• Sophisticated Inventory Management models and software are available – these are not applied in the
Supplies Division.
3

4. Supplies' Inventory Management Improvements
Numerical Methods Applied to Stochastic Inventory Management
• Strategy / Approach to relieving a tool-limited condition through Innovation:
1. Minimize Inventory Management time requirements in order to have time to think about other
improvements.
2. Improve Lead Time estimates.
3. Improve Customer Demand estimates.
4. Move parts from manual planning to MRP, but subject them to the benefits of manual planning (e.g.,
summed warehouse inventories, planning exceptions, Award considerations).
4

5. Supplies' Inventory Management Improvements
Increased Inventory Management Productivity by 1,000 Percent
• Automated "Back Up" files that are used for inventory-buy documentation and for Purchase Order
creation.
• Created Passive Planning to identify items that appear to have low-inventory, but for multiple warehouses
actually have sufficient inventory (Fig. P-1).
• Automated Demand Graphs and Decision Support Values, both of which decreased the time required to
estimate Customer Demand (Fig. P-2).
• Created a Demand Planners' Screen that organizes inventory data for efficient decisions (Fig. P-3).
• Automated the human judgment that is used to improve Customer Demand estimates.
5

6. Supplies' Inventory Management Improvements
Increased Inventory Management Productivity by 1,000 Percent
• Automated buy order reviews that ensure order compliance with vendor Minimums and Multiples.
• Shifted demand data source from the Logility Software to a monthly "Sales By Vendor" Excel Pivot Table
report.
• Shifted time-consuming manual tasks to the computer, thereby freeing time for creative tasks with
productivity yield.
• Instituted the complete planning of all inventory items on a near-daily basis, thereby minimizing the
number of inventory-deficient items.
• Productivity Change Calculation (Fig. P-4).
6

7. Supplies' Inventory Management Improvements
Figure P-1: Passive Planning Results
When two warehouses carry the same item, Passive
Planning identifies items that appear to have low-
inventory, but actually have sufficient inventory. This
relieves an Inventory Planner of the need to evaluate
adequate-inventory conditions.
For the example at the left, Passive Planning reduced
the total number of items that required inventory
evaluation from 191 to 56 (a 70-percent decrease in
Planner workload).
Vendors with blue fill required planning, vendors
without blue fill did not require planning.
7

8. Supplies' Inventory Management Improvements
Figure P-2: Demand Graphs and Decision Support Values
Developed a computer
program that:
1. Captures inventory
sales data from a “Sales-
By-Vendor” Excel
workbook.
2. Groups sales data by
geographical region.
3. Reports award-
customer sales data.
4. Graphs inventory sales
data along with
associated regression
lines and centered
moving averages.
5. Replaced visual
inspection of number
matrices with a more
efficient (and simple)
graphical method.
8

9. Supplies' Inventory Management Improvements
Figure P-3: Demand Planners’ Screen
The Planners’ Screen at left organizes inventory
data for efficient management decisions.
Features include:
1. Months-On-Hand (MOH) inventory summary
values for two warehouses (Cary and Ontario).
2. Summed Purchase Order (PO) values for each
warehouse, for comparison with the vendor’s
PO $ Minimum.
3. Keystroke-saving recurring comments (see
“Comment Type” on right side of figure).
4. Back Order Ratios for determining potentially
excessive customer orders.
5. A calculated Transfer (Txfr) Balance that tells
the planner the inventory transfer that will
balance inventory levels between two
warehouses.
6. Order Increment/Decrement buttons.
7. Kit-Item decision-support data.
9

10. Supplies' Inventory Management Improvements
Figure P-4: Productivity Change Calculation
The net result of the instituted productivity improvements is a conservative 1,032-
percent increase in productivity, with no loss of inventory management decision
accuracy.
The 71-item reduction that’s reflected in the above calculation is due, in part , to an
early company decision to shift C Items to the Material Requirements Planning (MRP)
system.
The instituting of complete planning of all assigned inventory items on a near-daily basis
further multiplies the 1,032-percent figure.
10

11. Supplies' Inventory Management Improvements
Lead Time accuracy is essential to the right balance between Service Level and Inventory Investment
• Supplies' vendor Lead Times have not been updated in eight years. Statistical Lead Times provide that
update and other information.
• There can be a significant Lead Time difference between East- and West-Coast Warehouses (Fig. LT-1 and
LT-2).
• There can be a significant difference between Statistical Lead Time and Standard Lead Time (Fig. LT-2 and
LT-3).
• About 25% of Lead Times are close to the vendor's Standard Lead Time (Fig. LT-4).
• Statistical Lead Times are computed for parts with sufficient Lead Time data and are applied to 383 Non-
MRP parts.
• A Numerical Method identifies and removes statistical outliers (Fig. LT-1 shows an example outlier).
11

12. Supplies' Inventory Management Improvements
Lead Time accuracy is essential to the right balance between Service Level and Inventory Investment
• 95%-probable Lead Times are computed on outlier-free data and an assumed Normal Distribution.
• Statistical Lead Time data identifies vendors whose Lead Times are systematically above Standard.
• Program identifies computed Lead Times that have potentially excessive change.
• Items with potentially excessive change have their Lead Time v. Time graphs visually inspected. Lead Time
is adjusted, if necessary.
• Testing of Statistical Lead Times on four items revealed benefits to Service Level and to Inventory
Investment; Test Period: 4/15-7/31/2014 (Figs. LT-5-8). Testing on more items would probably provide
additional insight.
• Statistical Lead Times will play an important role in transitioning remaining B- and C-Items to MRP.
12

13. Supplies' Inventory Management Improvements
Figure LT-1
0
20
40
60
80
100
120
6/10/2014
7/30/2014
9/18/2014
11/7/2014
12/27/2014
2/15/2015
4/6/2015
5/26/2015
7/15/2015
131512 (Cary)
95% LT = 32 days; Std LT = 28 days
There can be significant differences in Lead Time
between East- and West-Coast Warehouses. Cary
Warehouse 95% Lead Time = 32 days (Fig. LT-1);
Ontario Warehouse 95% Lead Time = 58 days (Fig. LT-
2).
Incorporated into the program a Numerical Method
that identifies and removes statistical outliers (note
outlier example (in red): extreme point at 116 vertical
units).
95% LT = 32 days
13

14. Supplies' Inventory Management Improvements
Figure LT-2
0
10
20
30
40
50
60
70
80
7/30/2014
9/18/2014
11/7/2014
12/27/2014
2/15/2015
4/6/2015
5/26/2015
7/15/2015
131512 (Ontario)
95% LT = 58 days; Std LT = 28 days
95% LT = 58 days
There can be significant differences in Lead Time
between East- and West-Coast Warehouses. Cary
Warehouse 95% Lead Time = 32 days (Fig. LT-1);
Ontario Warehouse 95% Lead Time = 58 days (Fig. LT-
2).
14

15. Supplies' Inventory Management Improvements
Figure LT-3
0
10
20
30
40
50
60
70
80
90
6/10/2014
7/30/2014
9/18/2014
11/7/2014
12/27/2014
2/15/2015
4/6/2015
5/26/2015
7/15/2015
210905 (Ontario)
95% LT = 76 days; Std LT = 21 days
95% LT = 76 days
There can be significant differences between the
Standard Lead Time and the Statistical Lead Time. The
Standard Lead Time is 21 days; the 95-Percent
Statistical Lead Time is 76 days.
15

16. Supplies' Inventory Management Improvements
Figure LT-4
0
2
4
6
8
10
12
14
16
18
6/10/2014
7/30/2014
9/18/2014
11/7/2014
12/27/2014
2/15/2015
4/6/2015
5/26/2015
7/15/2015
9/3/2015
604820 (Cary)
95% LT = 14 days; Std LT = 14 days
About 25% of Lead Times are close to the vendor's
estimate (i.e., close to the Standard Lead Time).
This is what the data looks like when a 95-percent-
probability Lead Time = Standard Lead Time. Note
that both the Standard and the Statistical Lead Times =
14 days.
95% LT = 14 days
16

17. Supplies' Inventory Management Improvements
Figure LT-5
0
5
10
15
20
25
30
35
40
45
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
20140102
20140107
20140110
20140115
20140121
20140124
20140129
20140203
20140206
20140211
20140214
20140219
20140224
20140227
20140304
20140307
20140312
20140317
20140320
20140325
20140328
20140402
20140407
20140410
20140415
20140418
20140423
20140428
20140501
20140506
20140509
20140514
20140519
20140522
20140528
20140602
20140605
20140610
20140613
20140618
20140623
20140626
20140701
20140707
20140710
20140715
20140718
20140723
20140728
20140731
006418 Both Sites
3M Usage 006418 Both Sites True Available True Buy
006418 Both Sites Std LT 006418 Both Sites Mod LT Linear (006418 Both Sites True Available)
Statistical Lead Times Testing: The Red Line shows
decreasing True Available Inventory (w/ no Stock Outs)
and increasing Demand (Blue Line).
17

18. Supplies' Inventory Management Improvements
Figure LT-6
0
10
20
30
40
50
60
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
20140102
20140107
20140110
20140115
20140121
20140124
20140129
20140203
20140206
20140211
20140214
20140219
20140224
20140227
20140304
20140307
20140312
20140317
20140320
20140325
20140328
20140402
20140407
20140410
20140415
20140418
20140423
20140428
20140501
20140506
20140509
20140514
20140519
20140522
20140528
20140602
20140605
20140610
20140613
20140618
20140623
20140626
20140701
20140707
20140710
20140715
20140718
20140723
20140728
20140731
146457 Both Sites
3M Usage 146457 Both Sites True Available True Buy
146457 Both Sites Std LT 146457 Both Sites Mod LT Linear (146457 Both Sites True Available)
Statistical Lead Times Testing: The Red Line shows
decreasing True Available Inventory (w/ no Stock Outs)
and decreasing Demand (Blue Line).
18

19. Supplies' Inventory Management Improvements
Figure LT-7
0
5
10
15
20
25
30
0
20
40
60
80
100
120
140
160
180
20140102
20140107
20140110
20140115
20140121
20140124
20140129
20140203
20140206
20140211
20140214
20140219
20140224
20140227
20140304
20140307
20140312
20140317
20140320
20140325
20140328
20140402
20140407
20140410
20140415
20140418
20140423
20140428
20140501
20140506
20140509
20140514
20140519
20140522
20140528
20140602
20140605
20140610
20140613
20140618
20140623
20140626
20140701
20140707
20140710
20140715
20140718
20140723
20140728
20140731
207228 Both Sites (KIT)
3M Usage 207228 Both Sites (KIT) True Available True Buy
207228 Both Sites (KIT) Std LT 207228 Both Sites (KIT) Mod LT Linear (207228 Both Sites (KIT) True Available)
Statistical Lead Times Testing: The Red Line shows
increasing True Available Inventory (w/ no Stock Outs)
and increasing Demand (Blue Line).
19

20. Supplies' Inventory Management Improvements
Figure LT-8
0
5
10
15
20
25
30
35
0
20
40
60
80
100
120
140
20140102
20140107
20140110
20140115
20140121
20140124
20140129
20140203
20140206
20140211
20140214
20140219
20140224
20140227
20140304
20140307
20140312
20140317
20140320
20140325
20140328
20140402
20140407
20140410
20140415
20140418
20140423
20140428
20140501
20140506
20140509
20140514
20140519
20140522
20140528
20140602
20140605
20140610
20140613
20140618
20140623
20140626
20140701
20140707
20140710
20140715
20140718
20140723
20140728
20140731
723418 Both Sites (KIT)
3M Usage 723418 Both Sites (KIT) True Available True Buy
723418 Both Sites (KIT) Std LT 723418 Both Sites (KIT) Mod LT Linear (723418 Both Sites (KIT) True Available)
Statistical Lead Times Testing: The Red Line shows
increasing True Available Inventory (w/ no Stock Outs)
and increasing Demand (Blue Line).
20

21. Supplies' Inventory Management Improvements
Demand accuracy is essential to the right balance between Service Level and Inventory Investment
• Many methods exist to estimate logistical Demand – from simple Statistics to sophisticated Numerical
Methods.
• Developed a new method: A computer program that simulates the human judgment involved in estimating
Stochastic Demand from monthly historical data.
• Program applies Numerical Methods to the task of Demand Estimation: Polynomial Regression, Numerical
Integration, and Root Location.
• Program suppresses short-term Demand Spikes and Demand Surges, thereby preventing high-probability
over-buying (Fig. D-1).
• Program factors Demand Trend and Change in Demand Trend into the Demand estimate (Fig. D-2).
21

22. Supplies' Inventory Management Improvements
Demand accuracy is essential to the right balance between Service Level and Inventory Investment
• So far, 150 / 150 automated Demand estimates have been confirmed by visual inspection.
• Program eliminates the time-consuming need to manually estimate Demand. Approximate Time Savings:
15 hours / month.
• Program operates on 12 months’ data and better optimizes inventory than a pure statistical approach
because it applies human judgment in: (1) suppressing Transient conditions, and (2) capitalizing on Trend.
• A 12-month pure statistical approach produces an estimated 19.5 percent increase in inventory compared
with the 12-month Numerical Method approach (Fig. D-3).
• Automated demand estimates will play an important role in transitioning all remaining Supplies' B- and C-
Items to MRP.
22

23. Supplies' Inventory Management Improvements
Figure D-1Program suppresses short-term Demand spikes.
Red dot at right side of chart is the Numerical Demand Estimate.
Numerical Demand
Estimate
0
100
200
300
400
500
600
700
800
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Q(t)
t
23

24. Supplies' Inventory Management Improvements
Figure D-2Program factors in Demand Trend and Change in Demand Trend.
Red dot at right side of chart is the Numerical Demand Estimate.
Numerical Demand Estimate
0
100
200
300
400
500
600
700
800
900
1000
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Q(t)
t
24

25. Supplies' Inventory Management Improvements
Figure D-3: Estimated Inventory Increase with Statistical Method
A 12-month method was
selected in order to:
Accommodate long-lead time
items (e.g., 100- to 200-days).
Force consideration of Demand
seasonality.
25

26. Supplies' Inventory Management Improvements
Future Improvements
• Place into service the newly-developed MRP parameters (i.e., ReOrder Points and Economic Order
Quantities).
• Develop a computer program that facilitates efficient visual inspection of Statistical Lead Times and
Demand estimates.
• Develop a report that identifies significant Trend in Lead Times and Demands.
• Develop a part-specific time-series report of Service Level and Inventory Investment.
• Develop a program that numerically determines the optimum combination of Lead Time, Demand,
and Safety Stock parameters for part-specific Service Level and Inventory Investment.
26

27. Supplies' Inventory Management Improvements
Numerical Methods can generally be defined as Computer Math
• I have been developing Numerical Methods software since 2002 in the following areas: Engineering,
Physics, Roots of Equations, Linear Algebraic Equations, Optimization, Curve Fitting, Calculus, and
Business / Inventory Management.
• Due to Supplies‘ dependence on Excel, all programming was done in Visual BASIC for Applications/Excel.
• Learned Numerical Methods development from the Chapra/Canale text: Numerical Methods for Engineers,
4th Edition. Adhering to their requirements for high-quality software development:
1. Top-Down Design: Systematic development; i.e., general objectives w/ division into specific segments.
2. Modular Programming: Use of functions / subroutines within an organized and coherent scheme.
3. Structured Programming: Well-structured code IAW the three Control Structures: Sequence, Selection,
Repetition.
4. Program Testing.
27