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Stock refers to any resource that is used to satisfy current or future need of the firm (raw materials, work –in-process finished goods and others) (Evans and Olsen,1998). The level of stock that can firm wish to hold is dependant of the firm policy.  It can represent up to 50% of the invested capital or even as low as 10 % of its invested capital. Excessive stock levels can be very costly to the business.  Excessive stock can be caused by an inaccurate inventory system causing excessive purchases resulting in excess stock. However, business may purchase excess stock to protect against stock outs or inadequate inventory in order to meet customer demand. In case where a business deals with perishable products keeping low stock level is advisable. However, insufficient stock levels can lead to stock-outs. Therefore, developing and accurate inventory management system that helps in forecasting can help the organization purchase and store correct levels of inventory. This may cushion against possible stock outs that is not a desirable condition for the business.  Inventory planning and control will ensure that the firm maintains the correct balance between high and low inventory helping it minimize the cost.

Simulation Model

Managers in varied companies come across two forms of inventory choices: the first one is the number of added inventory to order or come up with, while the second one is the time to order or create it. Even though there is chance to apply these options distinctly, their connection is visible that a concurrent answer is normally vital. Taking into consideration the variables needed (though not certain), the demand in a 52-week period, this framework looks out for the maximum order size and reorder point that acquires the smallest amount in a year (Evans and Olsen,1998).

The primary focus is to limit the overall cost applied in the inventory. The overall price is composed of holding, ordering, shortage and purchasing costs. In a review system, managers consistently assess the inventory location. If the inventory goes below or becomes in line with the level R, which is the reorder point, the manager calls for Q units known as the order quantity. (The choice made by the manager is influenced by the location of the inventory, as well as the order that have not yet been acquired and not part of the level, as well as the inventory in possession. If the managers make use of the inventory level they would have to order constantly with the inventory going below R up to the time they get the order). The moment one gets the order after the lead-time, the level of inventory goes from zero to Q, and the sequence goes all over again.

In inventory systems, demand is not known and the lead time may range. So as to be safe from any drop in orders, the managers in most cases keep a safety stock. In this instance, it may not be vividly known that order sizes and reorder points will bring to a decline the probable total inventory cost. Simulation models have the ability to meet the needs of this question. In such an instance, demand is not known and is Poisson-distributed with an average of 70 units weekly. Therefore, the demand that will be probable is 3,640 units.

Taking into consideration that huge values are quite normal according to the Poisson distribution model.  Hence, this assumption has the same meaning when one says that the demand is normally distributed, averagely 70 and a standard deviation of 12. The Poisson is distinct enabling it to do away with approximation of values in the normally distributed random variables:

Other associations that meet the aspects of the inventory system comprise:

  • Every order is priced at £165 while the holding price of £2.50 for each unit
  • For all the demands not met there is a loss and the company loses £3 per item per week
  • The period in ordering and getting it is 4 weeks. Hence, the projected demand in the lead time is 280 units. Ordering is done at the closure of a week and acquisition is made at the start of another one.


The economic order quantity (EOQ) model gives the order quantity:  

For the EOQ model the reorder point should be equal to the lead-time demand. Therefore, if the lead time demand is 300 units, an order should be placed when the inventory falls to 300 units. Then, order will be delivered when the inventory level reaches zero. However, demand can fluctuate about the mean of 300 units, these results in shortages occurring approximately half the time (Evans and Olsen,1998). Due to high shortages cost, the firm should use a higher reorder point, a larger order quantity or both. Either the firm will incur more inventory than average. This will lower the total shortage cost but higher the total holding cost. Higher order quantity allows the firm to order less frequently, therefore lower ordering cost. However, an appropriate simulation will help us make clear choices. Simulation can test re order points and quantities to be ordered.

Warnsley Ltd

Warnsely places an order every 4 weeks and brings the stock levels to 100 items. Orders will be delivered the week following the placement the order with suppliers. Therefore, 

  • Reorder interval is 4 weeks
  • Desired stock 100 times

Lorrjon Ltd

Lorrjon Ltd places an order of 200 items at the start of the week after incoming deliveries have been received and items are below 150 items with no outstanding deliveries.  Therefore,

  • Reorder quantity is 200 items  
  • Reorder level is 150 items


Using the simulation model the following data was used as regards Warnsley Ltd. The initial stock was 60 items, order quantity 40 items, reorder level was unknown and the lead time was 1 week. Using the simulation model I was able to obtain the following total annual cost £ 727, 970 for Warnsley Ltd (Evans and Olsen, 1998). The same operation was done for Lorrjon Ltd re-order quantity was 200 items, reorder level was 150 items and average lead time was 4 weeks. Using the simulation model I was able to obtain the following total annual cost £ 500 285. For the results obtained it showed that Warnsley had poor inventory policy as compared with Lorrjon Ltd. Therefore, Warnsley needed to reorganize its inventory policy to ensure that it incurs the least amount in total cost. Wanrsley Ltd incurred high shortage cost due to fluctuating demand but low holding cost due to its least number of items and shortened lead time as compared with Lorrjon Ltd. Thus, Lorrjon had a better inventory of the two (Khan, 2004). However, it was important see if I could better parameters of re-order, lead time and re-order level that will ensure that the firms incur the least amount in term of cost. This will form the basis for our recommendation to the Head Stores Manager (Evans and Olsen, 1998).

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