Week 4 inventory fassam

Inventory Management
International Business
Liam Fassam

Inventory management
• It is a stock of materials (inventory) which is kept
in stock to combat variations in demand, which
can be regarded as a “safety stock”.
• Inventory held along the various nodes of a
supply chain is termed “work in process”.
• Inventories can cost 15-40% of their value in
handling, storage, insurance and slippage
(damage/theft)……therefore it is easy to
understand why inventory turn is so important.
International Business - 'Inventory
management' - Liam Fassam
2

Inventory location
Inventories usually comprise 3 elements:
1. Input stock (Raw materials/packaging)
2. Process stocks (semi finished goods)
3. Output stocks (Finished products)
So in the “farm to fork” example:
• Crops in transit from farmer to manufacturing plant are?
• The raw material being processed into cereal is?
• The finished product sitting in a distribution centre is?
• The finished product sitting in a retail store is?
3

Holding cost
Inventories can accumulate as a result of poor planning and
scheduling or as by design (purposeful stock holding).
Generally, inventory is viewed as a negative impact on
business as it incurs:
• Costs of capital (interest paid or interest fore gone)
• Storage space
• Handling
• Insurance
• Increased risk of damage and theft
• Obsolescence.
4

Holding cost - risk
• Fashion changes (style, colour and texture),
• Past ‘use-by-date’ for foods
• Deterioration
• Obsolescence due to new technology or to
model changes which make ‘old’
• Models out of date
• Damage
• Pilfering/theft
5

Holding cost - storage
• Building – the more inventory the larger the
premises
• Racking – larger quantities requires specialist
equipment to store
• Temperature controlled – food items often require
temp control, the larger the stock the greater the
energy demands to maintain good controls
• Handling cost – specialised equipment such as
forklifts and staff wages; each time a box is touched
it has a cost!
6

Holding cost - finance
• Interest on money invested in stocks of
materials, either the organization has had to
borrow money to pay for the stock held or the
money ‘invested’ in the stock could have been
used elsewhere in the organisation.
• Insurance – the greater the value of stock on
hand, the higher the insurance value will need
to be to cover loss and therefore increased
premiums.
7

Re-order point – “pull” systems
8
Stock drops
to the
agreed
level and
new order
is placed
The agreed
re-order QTY
is placed,
note the
stock used
after order
during the
lead time
Lead time
from order
to receipt
This is the “pull” process in action – sales happen, stock drops, order placed
The supply chain pulling product through – “value chain”
Safety
stock, to
prevent
against
stock
outs if
network
break
downs
occur

Re-order point – “Push” system
Reorder
point
Safety
stock
Time
Stockonhand
Lead time
Period 1 Period 2 Period 3
Output matches
demand
Demand out performs output
and we eat in to safety stock
As we need to replen safety stock
used in previous period our output
does not give us full stock on hand
requirements but low sales means
we have too much stock
This is the “push” process in action – output is premised on cost efficient
Manufacturing premised on the economic order quantity (EOQ)
9

Push versus Pull
10

Push versus Pull
In short…..
The pull system ensures inventory is made
available downstream based on demand…..
The push system feeds inventory through the
supply chain regardless of current demand…..
11

Economic order quantity (EOQ)
EOQ is a push system that can be used when there is
an advantage in bulk purchase/manufacture rather
than making several small purchases.
EOQ assumes:
• Demand is constant and known.
• Deliveries are to specification, the right quantity and
on time.
• There is no slippage of stock due to theft or
damage. This means that what the computer
shows as being in stock is correct.
12

Calculating the EOQ
The formula for EOQ is
Q = The square root of 2 x DO/PH
Q is the EOQ
D is the annual demand in units
O is the cost of raising an order
P is the price of a unit
H is the holding cost
13

EOQ model simplified!
Optimal
order
quantity
Order
set up
Order
quantity
Annualcost
Total
cost
Holding
cost
Where the costs
intercede is where our
most efficient cost
driver for EOQ resides
14

EOQ calculation example
Demand (D) 60,000 units per annum
Order cost (O)€100 per order raised
Price per unit (P) €75
Holding cost (H) 12% per annum
Therefore:
2 x 60,000 x 100 = 12,000,000
Divided by / 75 x 0.12 = 9
12,000,000 / 9 = 1,333,333
Square root of 1,333,333 = 1,154
15

EOQ calculation example cont.
• If we assume the supplier manufactures units in
batches of 100, each order would be 1,154 opposed
to 1,200.
• As the total annual demand is 60,000 our resultant
EOQ gives us a delivery schedule of 52 per year.
• Therefore it is important in a push system to have
constant periodic reviews to ensure output matches
demand.
16

Safety stock calculation
• Quite often it is purported that safety stock is simply
calculated as:
Demand / 50% Lead time = X days reserve (safety stock)
• Where organisations have fairly stable supply lines and
little variation, this simplistic over deployed method will
result in too much inventory being carried.
• For organisations that have severe demand fluctuations
this will entail constant stock outs.
This is all too simplified, does not allow for world class SCM
practices such as constant review through S&OP practices.
17

Calculating the safety stock
When calculating the safety stock we need to understand the
demand and lead time deviation, on a constant review basis (once a
year at budget time does not suffice!)
Therefore first stage of safety stock calculation equates to:
Demand variation + lead time variation = safety stock
The final step is ratifying the above against an expected service level
(The level of service to your customers – remember in value chains
this has effects up/down stream and therefore ratifies the need to
understand the auspices of supply chain theoretical capacity)
Lets walks through the following example:
18

Calculating the demand deviation
Forecast demand Actual usage Deviation
1 50 60 10
2 76 80 4
3 80 70 -10
19
Demand in period 1 and 2 gives a deviation (10+4)/2=7
We do not include the deviation for period 3, as our forecast was
higher than usage, therefore by including this figure would only
increase the amount of safety stock on hand…….so we only look at
the areas of historical or live data that can have a detrimental
effect in satisfying the customer needs, thus avoiding stock outs.

Calculating the lead-time deviation
20
Expected lead time Actual lead time Deviation
1 10 days 17 days 7 days
3 8 days 6 days -2 days
Demand in period 1 and 2 gives a deviation (7+5)/2=6
We do not include the deviation for period 3, as with the quantity
deviation, the lead time in period 3 was sooner than expected and
therefore will not have a detrimental effect on satisfying customer
demand.

Total safety stock deviation
If our demand is 90 pieces per period and each period consists
of 18 work days the daily demand is:
90/18 = 5 pieces per day demand
Given our lead time deviation is 6 days we need to multiply
this by the daily demand:
6 * 5 = 30 pieces
To appreciate the full safety stock we also need to include the
deviation in sales we ascertained early of 7 pieces over 2
periods:
30 + 7 = 37 pieces of safety stock for 3 periods (QTR1)
21

Calculating the service level deviation
22
Deviation multiple Customer service level
2 95%
3 97%
4 99%
The standard deviations used by organisations to achieve a certain service level are
highlighted above
In our example if we chose to attain a 95% service level for meeting demand:
Our safety stock relating to standard deviation (demand/lead time) is 37 pieces.
Therefore:
37 * 2 = 74 pieces
So our safety stock for 3 periods based on deviation in lead time,
Demand and expected service level is 74 pieces.

Lets work through the
following two examples in
your own time and evaluate
outcomes:
23

Example 1
24
1 100 110 10
2 110 120 10
3 120 80 -40
(10 + 10) / 2 = 10
we ignore period 3 as it does not have detrimental effect on order fulfilment
(5 + 6) / 2 = 5.5 days
(Lead time * daily demand) + forecast deviation = (5.5 * 5) + 10 = 37.5 pieces
Service level deviation (95%) = 2 * 37.5 = 75 pieces (97% service level = 112.5 pieces)

Example 2
25
1 1,000 2,000 1,000
2 2,200 2,400 200
3 2,500 2,600 100
(1,000 + 200+100) / 3 = 433.33
(2 + 30) / 2 = 16 days
(Lead time * daily demand) + forecast deviation = (16 * 5) + 433.33 = 513.33 pieces
Service level deviation (95%) = 2 * 513.33 = 1026.66 (97% service level = 1539.99
pieces)

Week 4 inventory fassam

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