Week 4 inventory fassam

Inventory Management

International Business

Liam Fassam

International Business - 'Inventory management' - Liam Fassam

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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.


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Inventory locationInventories 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?


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Holding costInventories 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.


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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model changes which make ‘old’• Models out of date• Damage• Pilfering/theft


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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!


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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.


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Re-order point – “pull” systemsStock 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 placedThe supply chain pulling product through – “value chain”

Safety stock, to prevent against stock outs if network break downs occur


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Re-order point – “Push” system

Reorder point

Safety stock

Time

Stoc

k on

han

d

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 stockused 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)


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Push versus Pull


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Push versus PullIn 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…..


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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.


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Calculating the EOQ

The formula for EOQ is

Q = The square root of 2 x DO/PH

Q is the EOQD is the annual demand in unitsO is the cost of raising an orderP is the price of a unitH is the holding cost


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EOQ model simplified!

Optimal order

quantity

Order set up

Order quantity

Annu

al c

ost

Total cost

Holding cost

Where the costs intercede is where our

most efficient cost driver for EOQ resides


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EOQ calculation example

Demand (D) 60,000 units per annumOrder cost (O)€100 per order raisedPrice per unit (P) €75Holding cost (H) 12% per annum

Therefore:2 x 60,000 x 100 = 12,000,000Divided by / 75 x 0.12 = 912,000,000 / 9 = 1,333,333Square root of 1,333,333 = 1,154


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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.


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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.


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Calculating the safety stockWhen 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:


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Calculating the demand deviation

Forecast demand Actual usage Deviation

1 50 60 10

2 76 80 4

3 80 70 -10

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.


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Calculating the lead-time deviation

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.


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Total safety stock deviationIf 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)


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Calculating the service level deviationDeviation 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.


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Lets work through the following two examples in

your own time and evaluate outcomes:


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Example 1Forecast demand Actual usage Deviation

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 we ignore period 3 as it does not have detrimental effect on order fulfilment

(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)


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Example 2Forecast demand Actual usage Deviation

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 we ignore period 1 as it does not have detrimental effect on order fulfilment

(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

Education

Transcript of Week 4 inventory fassam