- It takes 1,000 hours of labor to complete one batch of sandals
- Production reaches a cost effective level of 283.83 hours per batch, this highlights the fact that the greater the number of units produced, the lower the overall production cost becomes
I used the excel spreadsheet module in POM for windows to calculate all the data for this particular product. I extended the production timeline by another four months to determine projected levels of revenue and profitability. Using this tool is highly credible since the accuracy of the method, as reflected in the calculations, show a coefficient of 80%.
- The Shanghai Factory
- Currently, the Shuzworld Shanghai factory produces 1,300 units per batch but is looking at increasing this volume to 2,800 units per batch. Managers at the factory are looking into finding a distribution patter than would produce the 2,800 units at the lowest costs. Using POM for Windows, we use 1,300 units instead of 2,800 to find the optimal monthly cost which is US$ 14,300. The solutions also state that:
- Warehouse 2 should receive 1,500 units
- Factory H should send 300 units to Warehouse 1
- Factory H should send 1,800 units to Warehouse 3
- Factory F should send 2,200 units to Warehouse 1
- Send other units to a dummy destination (Shanghai factory to send 1,300 and Shuzworld Factory H will send 200 to this destination) due to the excess supply over demand. The products are not shipped and therefore have no costs
- The company will have to determine if they have to find another warehouse for 1,500 units more of women’s shoes
In this scenario, Intuitive Lowest-Cost Method in POM for Windows was chosen because it chooses the allocations based on low-cost (Transportation Model, 2010).
A.1. For distribution patterns I used the shipping cost from various to the warehouses using three approaches: the Northwest-corner rule, the intuitive lowest cost and the Stepping Stone methods. Please note that these methods do not guarantee optimal costs and errors may be experienced from the calculations. With the use of computer-aided tools, managers can analyze the many different inputs that are required in determining their transportation needs. One notable tool is linear programming. In transport model analysis, linear programming found the lowest cost solution to the company’s shipping problems by looking at the various shipping points, destinations and the combination of these factors that produce an overall optimal (lowest) transport cost.
A.2. Three machines that work in sequence is used for the production of the casual deck shoe. Because of this set-up, if one machine fails the process cannot be completed. The machine should be repaired to make the process work again and as such can be mathematically described as Rs = R1 x R2 x R3 to determine the reliability of the entire process. Individually, the reliability measures are:
Machine 1 0.84
Machine 2 0.91 Total reliability of the process is 75.7%.
Machine 3 0.99
The machines are mutually independent of each other’s operations but the breaking down of one leads to a stoppage of the process. This is important because machine failure leads to costs. Simple maintenance scheduling will reduce production interruption in the future which will optimize production levels and keep costs down. Maintenance programs include inspections, servicing and repairs of factory machinery which should be performed at regular schedules to improve process efficiency and increase machinery life.
B.1. To increase the overall reliability of the production process for deck shoes, the company should move to invest in replacing machine 1 to increase the overall reliability of the process. Alternatively, the company may also invest in redundancy instead wherein the least reliable machine is backed-up by an identical machine. Providing a redundancy will mean that the process will continue even if the machines break down. If a backup machine #1 is available, it would raise reliability of machine #1 from 0.81 to 0.97 and increase the total reliability of the process from 75.7% to 87.8%.
B.2. The company is interested in finding out if the current system is reliable. It also wants to know if it can increase reliability by adding another machine. To work on this problem, we use the reliability general network tool to calculate product failure rate. This tool is used to calculate the current reliability of the process and the increase in reliability of the process after we inputted the redundant #1 machine into the equation. In addition, this tool determines the overall system reliability after the application of redundancy. What it does it that it calculates the production time lost due to the back-up machine coming up when breakdown ensues. The findings show that a parallel process is required based on having two working machines and the goal of increasing system reliability. The machines will work property and efficiently if there is preventive maintenance, which also helps reduce system failure and increase the life of the machines.
C. The economic order quantity was determined using the economic order quantity analysis tool. Based on this tool, the optimum number of shoelaces was found to be 27,387 pairs and holding costs of $2738.61. This volume of production minimizes the cost of ordering and inventory.
C.1. In this problem we are looking for the economic order quantity model (EOQ) amount. The EOQ is the inventory quantity that determines the optimum order quantity that a company should hold in its inventory with respect to demand, cost and production variations (Investopedia, 2013). The EOQ is helpful and is directly related to the company’s current business issue, that is, how to manage its inventory level efficiently so that it does not carry additional costs. The EOQ will lead to the right number of shoelaces to be ordered and is calculated by using the equation:
(Square Root of) 2*300,000*125/30,000=50
The calculations show that the optimal number of units to be ordered is fifty. The assumptions used in this calculation is constant demand. Currently the company requires 300 thousand pairs per year. This volume is ordered in advance and is received all at once. The EOQ model calculates that the actual required shoe lace pairs is less (27,387) and on average 13,693 pairs is needed as inventory. This means that the company is ordering too much and is holding the inventory too long. With the EOQ, the overall costs to the company should be minimized.
C.2. We use the iventory analysis tool for EOQ because of its applicability to the business issue and the fact that it utilizes relevant information provided such as the demand, delivery, lead times, etc. The EOQ provides the best approach for determining optimum inventory levels.
D. The case shows that there will be two customers waiting to be served on the average. One customer will be served every time while another will be queuing based on a customer handling time of 5 minutes and a total transaction time of 10 minutes. Two cashiers will solve this proble because both will be served every time. There is a probability that there will be no customer waiting (50% when there is only one cashier and 75% when there are two). The customer wait-line analysis indicates that there will be 6 sale transactions per hour while there will be 12 register transactions per hour.
One Cashier System
D1. My recommendation is to have two cashiers. I believe that the time for a sale and the gap between is more important to be resolved since customer waiting time is effectively twice if they are waiting to be served. While employing another cashier will double the cost, getting the sale at half the time it would take with one cashier would outweigh that cost.
D.2. For this analysis, what is useful is the quantification analysis tool. This tool compares the costs of two applications, in this case one cashier and two cashiers. It provides the expected returns on both scenarios. Because of the probability that there will be more than two customers waiting to be served on the line at any one point, the solution of having two cashiers is intuitively correct. The use of the quantification analysis tool helps in the analysis and indicates that two cashiers will reduce cost while improving service levels.
III. The issue is outsourcing and the opportunity herein. If the company outsources, there will be no initial capital layout or fixed costs. The variable costs will only be $3 million. This variable cost will be two times the amount of the old equipment reconditioned but is only one fourth the cost of new equipment. The variable cost indicates that outsourcing is the way to go for the company.
A cross-over chart is presented below showing the financial advantages of each option. For this analysis, the break-even analysis tool (cost volume profit) is used to show the relationship between costs (variable and fixed), volume and profit. These parameters differ from scenario to scenario so it is very useful when comparing the variations in each possible option. Of the three options that are available (refurbishing old equipment, buying new equipment, outsourcing), the decision tool indicates that outsourcing is the most advantageous.
With refurbishing the old equipment option the results are buying of 350 units and a total cost of $350,000 and a breakeven of 25 units and a total cost of $75,000. With the option of buying new equipment, the breakeven volume is 80 units and a total cost of $240,000. If we compare refurbishing and buying new equipment, we calculate a profit at 350 units. The cross-over chart provides the visual representation of these options.
The best option to take will be dependent on demand. The graph also shows that the demand for Samba Sneakers is between zero and 25 units. In this case, outsourcing is the ideal option. When demand increases from 25-300 units, the refurbished equipment option is superior to the other two options but when demand is over 300 units buying new equipment is the way to go.
If Shuzworld has an indication of demand, then they will know which option to take. However, it is unlikely that demand will be less than 25 units (Samba is a new product) or that demand will exceed 300 units. Therefore the company should budget between 25 to 300 units and therefore should refurbish its old equipment. This also supports Alistair Wu’s comment that outsourcing is inferior to the other approaches. This comes from the fact that Shuzworld is sensitive about outside production and would rather keep everything in house or at least controlled. In addition, buying new equipment may not be wise at the moment since demand for the new product is still being tested.
Using the breakeven cost-volume-profit analysis in POM for Windows, we see that the tool supports this analysis. This tool is used because it related all the relevant parameters and comes up with an objective assessment of all the scenarios under examination.
Forecasting
Forecasting is the process of projecting future sales based of historical sales trend. The method that is normally used for forecasting is called the least squares method. Using the least squares method predicts the future sales through a straight line regression series model. Using intercept points (x and y) a slope is determined. Any change in that line made shows the forecasted sales.
The POM for Windows tool has a regression tool. Using this tool, we select time series as the X-variable and sales as the Y-variable. On the third quarter of 2009, the forecasted sale is $121,861.10, $169,744.40 in the next quarter (an increase of $47,883.30). We also use exponential smoothing by using a smoothing trend of 0.4 to manage the inflections in the data. The use of the ordinary least squares method for forecasting using the linear regression analysis tool is helpful because it shows the relationship of sales history and future performances based on statistical examination (Conttrell, 2011).
References
Cottrell, A. (2011). An Introduction to Regression Analysis: Basic Concepts. Retrieved from http://users.wfu.edu/cottrell/ecn215/regress.pdf
Investopedia (2013). Economic Order Quantity. Retrieved from http://www.investopedia.com/terms/e/economicorderquantity.asp
Transportation Model (2010). Retrieved from http://www.me.utexas.edu/~jensen/ORMM/computation/unit/mp_add/subunits/tran_add/
