Business Operations Shuzworld Inc - Term Paper Example

Business Operations Shuzworld Inc Introduction Shuzworld faces a number of options in producing its Samba Sneakers and these options have to be properly analyzed. The company also needs to make estimates of its future sales in order to ensure that neither too much nor too little is produced. Additionally, the company needs to ensure that it has control over the processes of making eyelets and soles because some of the operators or hosts are out of control. This memorandum provides information that will assist the company in making decisions, forecasts and controlling production processes. Part A The three options that are available to Shuzworld are as follows: Buy new equipment for the Shanghai facility; Recondition the existing equipment at the Shanghai facility; or Outsource production to a vendor in China. The purchasing of the new equipment will definitely cost the companies a lot but that will have its own benefits in terms of its long term usage and reliability, which is the main concern of many of the companies. The second option to use reconditioned equipment is another source through which the companies can start their business in a new location or in their headquarters. The reconditioned equipment will be available from the market at a lower cost and will give the start-up companies or the emerging companies an opportunity to start work with the lesser amount of investment. The companies will be able to follow their cost effective measures that they have thought about and then will be able to work on the other tasks after the first task of cost management has been effectively done as the reconditioned equipment will be cheaper in rate. However there will be one issue of the reliability of the machines, as they might need repairs often. This may be a major problem for an emerging company who might not have a back up plan if the main machinery gets damaged. This may cause Shuzworld to cease the production process as well. The third option in terms of using the equipment is related to outsourcing the work and operations to another contractor company. This will ease the management in a way that they will need labor that will handle operations in the work field as that responsibility will now be solely of the contractor company. The main disadvantage of using this option is that the companies might pay more for the products that they could produce themselves at their own plants at lesser costs. In order to make a decision on which option to choose the current and forecast demand for Samba Sneakers is required. The buy and recondition options both have fixed cost but comparatively lower variable cost than the outsourcing option. The choice will depend on the number of Samba sneakers that Shuzworld expects to produce. Sensitivity analysis can be used to inform the decision. Sensitivity analysis is a technique that is used to determine ‘how the variation in output of a model can be apportioned to different sources of variation’ and how a given model will be influenced by information fed into it. The following table shows several production scenarios. Options Available for the Production of Samba Sneakers Production Volume     100,000 200,000 300,000 400,000 Recondition Existing Equipment   Per unit ($)         Fixed Cost 50,000   50,000 50,000 50,000 50,000 Variable cost/1,000 sneakers 1,000 1 100000 200000 300000 400000 Total Cost     150,000 250,000 350,000 450,000               Buying New Equipment             Fixed Cost 200,000   200,000 200,000 200,000 200,000 Variable cost/1,000 sneakers 500 0.5 50000 100000 150000 200000 Total Cost     250,000 300,000 350,000 400,000               Outsourcing             Fixed Cost 0   0 0 0 0 Variable cost/1,000 sneakers 3,000 3 300,000 600,000 900,000 1,200,000 Total Cost     300,000 600,000 900,000 1,200,000 The table indicates that if 300,000 or more units will be produced over time then the appropriate approach for the Shuzworld Inc. would be to buy the new equipment, which will be helpful for them in terms of its reliability and the long term use. The company might make a large investment in the beginning but then they will be better off in the long run as these machines have long term use and would not become defective very easily. The second option can also be adopted but there are risk factors involved as the damaged machine might make it inconvenient for the workers to produce the number of shoes in order to meet the daily requirements. Third option must never be used by the company as it will be far more costly for the company in short as well as long run. Sensitivity (what-if-analysis) was used because it provides several scenarios to inform decision. The calculations require simple arithmetic and can be done quickly with the use of Microsoft Excel. Part B According to Heizer and Render (2011) ‘forecasting is the art and science of predicting future events.’ The least squares method which is a precise statistical method can be used in trend projections (Heizer & Render 2011). The least squares method for finding the line of best fit uses the following equation: ŷ = a + bx where, a = y axis intercept; b is the slope of the regression line which indicates the rate of change in y the dependent variable which is sales in this case; and x is the independent variable which is time in this case. The formulas for a, b and x are as follows. The table below shows information which is required for use in the formula. Year Time Period (x) Sales (y) x2 xy 2Q 2007 1 90,000 1 90000 3Q 2007 2 95,000 4 190000 4Q 2007 3 98,000 9 294000 1Q 2008 4 96,000 16 384000 2Q 2008 5 102,000 25 510000 3Q 2008 6 99,000 36 594000 4Q 2008 7 118,000 49 826000 1Q 2009 8 109,000 64 872000 2Q 2009 9 124,000 81 1116000 Total Ʃx = 45 Ʃy =931,000 Ʃx2 = 285 Ʃxy= 4,876,000 If we substitute the figures use the figures in the table we arrive at the following results. x = Ʃx/n= 45/9 = 5 x2 = 25 ӯ = 931,000/9 = 103,444.44 b = (4,876,000 – 9*5*103,444.44)/ (285 – 45) = (4,876,000 – 4,655,000)/ (285 – 225) = 221,000/60 = 3683.33 a = 103,444.44 – 3683.33 * 5 = 103,444.44 – 18416.65 = 85027.79 ŷ = a + bx = 85,027.79 + 3683.33 * 10 = 85,027.79 + 36,833.30 = 121861.09 Therefore, estimated demand for the 3Q 2009 using the least squares method is 121,861. The exponential smoothing with trend adjustment model is another method that is used to analyze chronological observations in order to develop forecasts (Stevenson 2012). It is a very popular approach since it makes adjustments for trends which can lead to lags in the forecasts (Heizer & Render 2011; Stevenson 2012). It is one of the best methods, since other models do not address the problem of trends sufficiently (Stevenson 2012). In addition to a smoothing constant it also includes a trend adjustment factor. The formula for this model is: Forecast including trend (FITt) = exponentially smoothed forecast (Ft) + exponentially smoothed trend where, Ft = α (actual demand/sales last period) + (1 – α) (Forecast last period + Trend estimate last period) That is, Ft = α (At-1) + (1 – α) (Ft-1 + Tt-1) and Tt = β (Forecast this period – Forecast last period) + (1 – β) (Trend estimate last period) That is, Tt = β (Ft – Ft-1) + (1 – β)(Tt-1) The following table shows the results of a three month moving average forecast. Sales Volume Forecast Using Exponential Smoothing with Trend Adjustment Method Quarter Period Sales Unadjusted Forecast (Ft) Trend (Tt) Adjustment for Forecast (AFt) 2nd Qtr 2007 1 90,000       3rd Qtr 2007 2 95,000       4th Qtr 2007 3 98,000       1st Qtr 2008 4 96,000       2nd Qtr 2008 5 102,000 96,000 2,000 98,000 3rd Qtr 2008 6 99,000 99,200 2,480 101,680 4th Qtr 2008 7 118,000 100,876 2,158 103,034 1st Qtr 2009 8 109,000 107,524 3,954 111,478 2nd Qtr 2009 9 124,000 110,735 3,657 114,392 3rd Qtr 2009 10   117,274 4,810 122,084 The information in the table indicates that the expected/forecasted sales volume for the Quarter 3 2009 is 122,084 units. The least squares method and the exponentially smoothed with trend adjustment method of forecasting arrive at different results. The least squares method shows projected sales of 121,861 units while the exponentially smoothed with trend adjustment method 122,084 - a difference of 223 units. The results are close and the difference is not considered to be significant. Both methods take into account the trends in the figures. The difference may be explained by errors and the fact that the initial trend adjustment for the exponentially smoothed with trend adjustment method was based on finding the difference between sales in week 1 and 4 and dividing it by the number of periods between them – 3 periods. However, unlike the least squares method the exponentially smoothed with trend adjustment method has the ability to make adjustments in order to account for changes in trend (Stevenson 2012). The least squares method is a precise statistical method for finding a line that best fits a set of historical data (Heizer & Render 2011). Part C Control charts generally refer to displays made to represent a process in the form of run chart with statistical information with limits on the lower and upper side (Webber & Wallace 2007, p. 161). Basically control charts are designed to measure the degree of control of the process. The uppers and the lower limits of a control chart represent variation of data that commonly originates from the process to produce common-cause variation. Control charts are applied in projects with varied process so as to reduce the amount of such variation. To ensure that the process is in control, the management team performs two comparisons; compares the results of the process with the normal standard. Procedure of administering control charts entails various steps. The management team is first expected to define the standards of operating the project. The second step entails collection of data concerning the process to be investigated. The lastly stage of control chart quality control makes use of the data collected in step two to develop a control graph. Based on the type of graph obtained from monitored data, quality control team can then decide whether to adjust or change the process. For instance, the process will call for change or improvement if the monitored data fluctuates within the limits. This is because such causes are common causes originating from within the project. Secondly, special causes of project problems such as bad instruction, lack of training, inefficient process, or inadequate support system will be reflected by control charts by the presence of data falling outside the limits. In the presence of special causes of unsatisfactory results, the management will be forced to eliminate such causes before administering control chart. The charts which are copied below indicate the variations in performance by the operators or hosts of the eyeletting and shoe sole processes. Chart 1 Chart 2 The information in Chart 1 indicates that eyeletting fraction defective for operators 13 and 20 is ‘out of control or out of adjustments’ while the other operators are ‘in control with only natural variation present’ (Heizer & Render 2011). The information in Chart 2 indicates that shoe sole height samples for host 13 and 14 is out of control, while the other hosts are in control of what they are doing with lower levels of variation in their performance. The information suggests a small fraction of the operators’ or hosts’ performance is out of line and so it means that emphasis needs to be placed on further training and monitoring of them to ensure that their performance is brought up to standard. Quality is important to customers and so implementing total quality management (TQM) will enable the company to get it ‘right first time’. In accordance with the recommendations of Business Balls (n.d.) Shuzworld should also practice PDCA - Plan what is needed; Do it; Check that it works; Act to correct any problems or improve performance. Statistical process control (SPC) methods including control charts is a TQM tool that is useful for problem solving and continuous improvement (Chase et al. 1998, p. 201). This should be continued to ensure that deviations are within limits. Conclusion A lot of time was spent in analyzing the situations facing Shuzworld. If these recommendations, forecast methods and quality control measures are put in place Shuzworld problems will be much reduced. The company will then be able to concentrate on continuous improvement which is the basis for TQM. References Business Balls. (n.d.). The original quality Gurus. Retrieved on 17th Jan 2012 from: http://www.businessballs.com/dtiresources/quality_management_gurus_theories.pdf Chase, R.B., Aquilano, N.J., & Jacobs, F.R. (1998). Production and operations management: Manufacturing and services. 8th ed. USA: Irwin McGraw-Hill. Heizer, J. and Render, B. (2011). Principles of operations management. 8th ed. USA: Prentice Hall. Saltelli, A. and Chan, K. (2000). Sensitivity analysis. West Sussex: John Wiley & Sons. Stevenson, W.J. (2012). Operations management. 11th ed. NY, NY: McGraw Hill/Irwin. Read More