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Optimizing
Safety Stock levels by calculating the magical balance of minimal inventory
while meeting volatile customer demand is one of the biggest challenges of
inventory management. Many companies look at their own demand fluctuations and
assume that there is not enough consistency to predict future variability. Then they fall back on the trial-and-error
best guess weeks supply method or the over simplified 1/2 lead time usage
method to manage their safety stock.
Unfortunately, these methods prove to be less than effective in
determining optimal inventory levels for many operations. If the goal is to reduce inventory levels
while maintaining or increasing service level, one will need to investigate
more complex calculations.
One
of the most widely accepted methods of calculating safety stock uses the statistical
model of Standard Deviations of a Normal Distribution of numbers to determine
probability. This statistical tool has proven to be very effective in
determining optimal safety stock levels in a variety of environments. The basis for this calculation is standardized;
however, its successful implementation generally requires customization of the
formula and inputs to meet specific characteristics of operation [1, p.157].
Prioritization
of products plays key role in inventory management. Commonly used method is ABC
analysis. It helps to split assortment of the company into 3 groups: A-products
that make 80% of company income, B-products – 15% of company income, C-products
– 5% of company income. This classification enables clear comprehension about
what products are more important and what products are less important for a
company.
Based
on ABC analysis, management decides on desired service level for each group.
Parameter, which helps to express service level in safety stock, is called service factor. It is used as a
multiplier with the standard deviation of demand to calculate a specific
quantity to meet the specified service level. It could be calculated with use of
Excel function NORMSINV [4, p.1]. Table 1 presents a relevant example.
Service
Level
|
Service
Factor
|
Service
Level
|
Service
Factor
|
|
50,00%
|
0,00
|
90,00%
|
1,28
|
|
55,00%
|
0,13
|
91,00%
|
1,34
|
|
60,00%
|
0,25
|
92,00%
|
1,41
|
|
65,00%
|
0,39
|
93,00%
|
1,48
|
|
70,00%
|
0,52
|
94,00%
|
1,55
|
|
75,00%
|
0,67
|
95,00%
|
1,64
|
|
80,00%
|
0,84
|
96,00%
|
1,75
|
|
81,00%
|
0,88
|
97,00%
|
1,88
|
|
82,00%
|
0,92
|
98,00%
|
2,05
|
|
83,00%
|
0,95
|
99,00%
|
2,33
|
|
84,00%
|
0,99
|
99,50%
|
2,58
|
|
85,00%
|
1,04
|
99,60%
|
2,65
|
|
86,00%
|
1,08
|
99,70%
|
2,75
|
|
87,00%
|
1,13
|
99,80%
|
2,88
|
|
88,00%
|
1,17
|
99,90%
|
3,09
|
|
89,00%
|
1,23
|
99,99%
|
3,72
|
Table 1 Calculated Service Factor Based on Desired Service
Level
Now we can
assess efficiency of product prioritization using ABC analysis for the examples
given below. Common assumptions for the both cases are [2, p.54]:
1.
Lead time – 90 days (2,73 month)
2.
Order frequency – biweekly (0,5 month)
3.
Safety factor for A products – 99%, B – 98%, C – 90%.
First, we calculate
inventory level in USD in the 4 quarters with assumption that all of the
products have equal importance and need 99% service level (see Figure 1).
Fig. 1
You may find inventory level
calculation with ABC products classification based on their importance in Figure
2.
Fig. 2
Analysis
of the abovementioned examples shows that using ABC products classification gives
average 5% cost effectiveness compared to non-prioritized inventory management
(Figure
3).
Fig. 3
This abstract aimed to describe efficiency of usage of ABC analysis in
inventory management. It is worth noting that this method should be used as
volume and value segmentation on ABC groups. However, splitting products by
their volatility to maintain safety stocks stays the most powerful approach and
ABC segmentation makes extra saving by means of decreasing stock on hand.
Literature
1. Max Müller, Essentials of inventory
management, AMACOM Div American Mgmt Assn, 2003 – p. 243
2. David J. Piasecki, Inventory Accuracy:
People, Processes, & Technology, Ops Publishing, 2003, p.
352 ISBN: 0-9727631-0-4
3. Stephen C. Graves, Sean P. Willems, Optimizing
Strategic Safety Stock Placement in Supply Chain, Manufacturing & Service
Operations Management, Vol. 2, No. 1, Winter 2000, pp. 68–83
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