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BioPharma Inc Supply Chain Network Analysis - Case Study Example

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The paper "BioPharma Inc Supply Chain Network Analysis" is a perfect example of a business case study. The pharmaceutical Industrial growth has been marked by massive development over the years. This is evidenced by the introduction of medical discoveries that are aimed at improving healthcare in the world…
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BIOPHARMA, INC.SUPPLY CHAIN NETWORK ANALYSIS By (Name) Code+ course name Professor’s name University name City, State Date Table of Content Page Executive Summary....................................................................... ..3 Background Information…………………………………………...4 Objectives ………………………………………………………… 5 As-Is Situation ………………………………………………..….. .6 Optimized Situation…………………………………………. …… 11 Recommendations ……………………………………………… …15 Conclusion ………………………………………………………… 15 Answers to the case ………………………………………………..16 Reference & Appendices Executive Summary The pharmaceutical Industrial growth has been marked by massive development over the years. This is evidenced by the introduction of medical discoveries which are aimed at improving healthcare in the world. The increasing number of health corporations over the past decades is owed to the global development in research and increasing market. Marketing strategies of the drugs have also advanced to higher levels as the industry grow as both small and large corporations comes with great initiatives for medical research. This may also be as a result of the increasing importance of medical needs that directly affects quality of life. The world has continuously realized the importance of research organizations and pharmaceutical companies like BioPharma, Inc. BioPharma, Inc. is one of the leading chemical bulk manufacturers in the world pharmaceutical industry. With its internal patents ownership of the two chemicals, Highcal and Relax, the company expects substantial growth in sales of these chemicals from its plants in all parts of the world. However, following decline in financial performance in 2009, the company has put considerable forecast on cutting costs and aims at having efficiency network. This paper analyses the company’s supply chain issues and the financial problems that have prompted the company to take some strategic financial decisions. Background Information The 2009 poor financial performance of the BioPharma, Inc. was owed to the high cost of production in its plants particularly in plants in Germany and Japan. As a result, the profitability of the company was affected massively making the management to adopt some cost cutting strategies within these plants without affecting the demand of its products. The Germany and the Japan plants have been manufacturing products under high costs according to evaluations. According to the nature of the products manufactured by pharmaceutical firms like BioPharma, Inc., there is high reliance on forecasting, an evaluation that informs the company of the financial gaps and performance. Forecasting also goes along helping them plan and determine their capital insights and resource investments as well as provision of updated recommendation of dealing with the emerging problems when they are detected. According to the evaluation, the Japanese plant has been the technology leader among the BioPharma networks and has been stable and able in handling the environmental and regulatory issues better than other plants. On the other hand, the plant at Germany has been a production leader with high margin of production ability compared to other plants worldwide. This plant has recorded high yield among other plants in various parts of the world. The other plants like in Mexico, Brazil, and India should be updated according to the company’s valuation and although BioPharma has forecast that sales of the two chemicals, Highcal and Relax, are likely to be stable with the exception of Asia, sales at Japanese plants is expected to have an annual growth of 10% for the next five years then stabilizes. The purpose of this study is to analyze BioPharma, Inc. plants costs and the company’s network options. It also analyzes different situations like the As-Is situations and the optimized situations of the company’s financial strategies and adopt a favorable recommendations thereafter. With a suitable conclusion, the study concentrates on the company’s supply chain system as well as its forecast for future performance of its sales and production. The company intends to maintain maximum production capacity in its plants. Conversely, it also needs to shutdown any plant which is productively inactive since it is assumed to continue incurring cost as well as the 20 percent fixed costs of production. Theses fixed costs that the company intends to reduce include depreciation costs, utilities costs, and salaries. The company also intends to reduce employees’ benefits in order to reduce costs of operations. The variable costs of production of each chemical includes raw materials and production cost. The variable cost is incurred as part of the cost of chemical produced, labor and scrap costs. As far as transportation costs are concerned, BioPharma transport its chemicals in containers by sea or trucks by land. According to Chopra and Meindl (2012), local production in each region is assumed to result in no import duty. Based on the assumption that sales represent demand for the period, production from Brazil, India and Germany may be sent to Latin America, Europe, and the rest of the Asia with the exception of Japan without incurring any import duty. Objectives The general objective of the study is to provide comprehensive information for the company on the best methods of cutting costs based on its efficient supply network. However, to effectively uncover the rooted supply chain analysis and the production factors of the company, the study seeks to pursue the following specific objectives; i. To analyze the current production costs of the company ii. To investigate the identified issues for the reason of the company’s profitability decline. iii. To determine whether the outdated production plants of the company in various parts of the world can affect it financial performance. Analysis As-Is situation The current situation is based on the result of the identification of the cost structure of each plant according to the 2009 forecasting group. According to the table shown below, production at some plants is not enough to meet demand in certain regions. Table 1 : Current Production and Demand of BioPharma, 2009. Plant Capacity Highcal (Production) Relax (production) Highcal (sales) Relax (sales) Highcal Relax Brazil 18 11 7 7 7 4 0 Germany 45 15 0 15 12 0 -12 India 18 10 8 5 3 5 5 Japan 10 2 0 7 8 -5 -8 Mexico 30 12 18 3 3 9 15 US 22 5 17 18 17 -13 0 Costs The summery of the total variable cost which include variable cost of production and transportation costs are as shown in the table below: Table 2: Current total variable costs for Highcal Production + Transportation Cost From/To Latin America Europe Asia w/o Japan Japan Mexico U.S. Brazil 8.9 9.15 9.2 9.2 9.1 9.15 Germany 11.35 11.1 11.25 11.3 11.2 11.2 India 8.6 8.45 8.3 8.4 8.6 8.55 Japan 11.9 11.8 11.7 11.5 11.85 11.85 Mexico 9 8.9 9.1 9.05 8.8 8.85 U.S. 9.05 8.9 9.05 9.05 8.85 8.8 Table 3: Current total variable costs for Relax Production + Transportation Costs From/To Latin America Europe Asia w/o Japan Japan Mexico U.S. Brazil 11.4 11.65 11.7 11.7 11.6 11.65 Germany 13.95 13.7 13.85 13.9 13.8 13.8 India 11 10.85 10.7 10.8 11 10.95 Japan 14.6 14.5 14.4 14.2 14.55 14.55 Mexico 11.5 11.4 11.6 11.55 11.3 11.35 U.S. 11.45 11.3 11.45 11.45 11.25 11.2 According to the two tables above (table 2&3), it is evidenced that the Germany and the Japanese plants has the highest variable costs of producing both thee highcal and relax chemicals. At this level, the main focus of this study is directed towards minimization of costs of the two plants. The transportation costs of the products are also affected by the import tariffs as shown in the tables below: Table 4: Import tariffs (percent of value of product imported, including transport) Latin America Europe Asia without Japan Japan Mexico U.S. 30% 3% 27% 6% 35% 4% The table above shows the regional duties and alliance. The duties on imports vary according to the origin of imports. The local production within each of the regions in the table above has no import duties. However, duties apply to raw materials, production, as well as the transportation cost components, not to the fixed cost component as shown in the table below. In this case therefore, a product passing through to Latin America incurs import duty of $3 and a transportation cost of $10. In order to get the actual production cost, this becomes $(10*0.3) = $13. Table 5 : Import Tariffs (Converted   Latin America Eur Asia w/o Japan Jap Mex U.S. Latin America Eur Asia w/o japan Jap Mexico U.S. Brazil 0 0.03 0.27 0.06 0.35 0.04 1 1.03 1.27 1.06 1.35 1.04 Germany 0.3 0 0.27 0.06 0.35 0.04 1.3 1 1.27 1.06 1.35 1.04 India 0.3 0.03 0 0.06 0.35 0.04 1.3 1.03 1 1.06 1.35 1.04 Japan 0.3 0.03 0.27 0 0.35 0.04 1.3 1.03 1.27 1 1.35 1.04 Mexico 0.3 0.03 0.27 0.06 0 0.04 1.3 1.03 1.27 1.06 1 1.04 U.S. 0.3 0.03 0.27 0.06 0.35 0 1.3 1.03 1.27 1.06 1.35 1 Table6: Plants Open/Shut, Lines On/Off Relax(1) /Off (0) HighCal(1)/off(0) Plant (1)/off(0) Capacity 1 1 1 18 1 1 1 45 1 1 1 18 1 1 1 10 1 1 1 30 1 1 1 22 When all the plants are fully operational, it has been determined that the German and Japanese plants require excess capacity. According to the table below, it is evidenced that the German plant required an excess capacity of 29 while 9 excess capacities were required for Japanese plant. Table 7: Constraints (Plants excess capacity) Supply region Excess Supply Brazil 0 Germany 29 India 0 Japan 9 Mexico 0 U.S. 0 In the process of analyzing the current (‘‘As-Is’’ ) situation, tools of analysis are used in finding the total cost. In this case, the fixed cost and the variable cost are added together and excel solver is used to aid the process of getting the total cost. The process begins by getting the objective function for the As-Is situation as shown below; Table 8: Objective function for the As-Is situation Fixed Cost 230.00 Variable Cost 1099.31 Total Cost 1329.31 Optimized situation for the BioPharma Based on the report and the current situation of the company, the analysis has varied options, one of which is to maintain the global network as at the current abilities and structure. The analysis can also opt for a complete shutdown of the some non-performing plants. In addition to that, it can also be possible to limit some plants o produce only one chemical. It has been established that shutting down non-performing plants would save the company 80% annual fixed and variable cost. On the other hand, limitation of a plant to production of one chemical would also save the plant 80% in terms of the cost which would have been incurred as a result of the other chemical. In more realistic terms, the Japanese plant is eminent for shutdown while the German plant may face limitation to only produce one chemical. Shutting down a plant at the optimal situation requires some aspects of the current or As-Is situation of the company. Using the exchange rate of 2009, the values of the current situation are critical in determining the shut down cost of a plant by adding to it the objective function. With the formula, 0.2*SUMPRODUCT (M61:O66, L41:N46), the full analysis is shown in the following tables: Table 9: Plants Open/Shut, Lines On/Off Table 10: Plant, HighCal and Relax fixed costs. Fixed Cost (million $) Plant HighCal Fixed Cost 20 5 45 13 18 4 17 6 30 6 21 5 In solver, the cells that represent table 8 are used and turned into binary. Once the solver is executed, there should be a new total cost and it is added to the shutdown cost which is now called the optimized cost. This is shown in table 11 below. Table 11: Objective function for optimized situations Objective Function Fixed Cost 182.00 Shutdown Cost 9.6 Variable Cost 26.16 Optimized Cost 217.76 Total Cost 208.16     According to the table above, it is very clear that the optimized cost is less than the total cost in the as-is situation. The original total cost which was 1329.31 has become 1293.38. The optimized solution has also caused the Japanese plant to shut down and has limited the German and US plants to only produce one chemical. The fixed cost has decreased but the variable cost has slightly increased which is understandable for limiting a plant into producing one chemical or shutting it down would result in a slight increase with the transportation cost, as demand would stay constant. Close examination however reveal that closing down the Japan plant should be carefully examined for the growth of the demand in the Asia without Japan region would increase by 10 percent for the next 5 years. It is also the technology leader within the BioPharma network and its developments are shared with other plants in the network. Closing it down could affect the performance of other plants that have an out-dated technology which could potentially affect a plant’s efficiency and effectiveness. On the other hand, the German plant still has excess capacity which is the result of limiting it to producing just one chemical as shown in table 12 below. Table 12: Excess capacity for optimized situation. Supply Region Excess Capacity Brazil 0 Germany 28 India 0 Japan 0 Mexico 0 U.S. 0 Restructure and Exchange rates: The company should strife to maintain the current distribution network because the exchange rate appears to be fairly stable. However in case there is change in currency of any country involved, then they should change the supply network. If there is hike in a currency of a market then the profits of the company will be lowered as well as increase the cost. In the event there is a reduction of the duties, the profitability of the company will increase due to decline in the production cost of the plants. 100% yield and modification In the analysis an assumption was made that production was to have 100% yields while maintaining quality. However a modification is necessary in order to understand the sensitivity of each constraint. The constraints to consider are the production capacity and shipping amount. Production should take into account a loss by incorporating loss percentage during production. This will adjust the objective function of linear programming. The same will apply to shipping amount. Recommendation The report adopted the following recommendations for effective financial and efficient performance of BioPharma, Inc.: Shutting down a plant would create labor disputes. Other than considering the effect of it brand out of these disputes, the company should also consider quantitative financial factors that would determine its profitability. The company should also consider its operational environment in terms of political environment and security. Most of its products are imported to different regions in the world making them vulnerable to terrorist attacks and other political misfortunes. These scenarios can affect its operations adversely. The technological database and background of some plants should be well considered before shutdown of the plant. Other plants with outdated production like India and Brazil may depend on the network of the plant, and any shutdown may limit the yields and production delays. When closing down a plant the system that is connecting all the plants in the breakdown thus it is necessary to consider the effects of the information system of the company. Conclusion Just like other global firms, financial and production performances are major threats to BioPharma, Inc,. The responsibility of the management in ensuring high productivity, profitability and efficiency rest on the strategic action that they make based on the evaluation and forecast reports. With the advancing technology, one decision may have catastrophic effects to the performance of the whole company. It is therefore important for BioPharma, Inc, to reconsider their production policies among all its plants worldwide to improve its global competitiveness and survival in the pharmaceutical industry. Answers to the Case Questions 1. How should BioPharma have used its production network in 2009? Should any of the plants have been idled? What is the annual cost of your proposal including import duties? Based on the current performance of BioPharma, the ompany should change their existing network structure and follow the optimized solution that was designed previously. The Japanese plant shutdown as recommended by the optimal solution and limitation of the German and US plants to producing only one chemical can be very effective to the company. This is based on the output that the ms solver produced for ‘as-is’ (1329.31) down to 1293.38 in the optimized solution. The decrease on the fixed cost is determined in the process proves that the original fixed cost was 230 and after using the optimization model, the value is now 182. The variable cost increased and that is because the German plant is only limited to producing only one chemical which could help increase transportation costs. 2. How should Landgraf structure his global production network? Assume that the past is a reasonable indicator of the future in terms of exchange rates. To find the optimal solution for each year starting 2004, the exchange rates should be taken into account and used as a basis in calculating the variable costs, transportation and production costs. Using the same basis as the original optimized table, the exchange rates from 2004-2008 are applied and the optimal costs are seen in table 13. Table 13: Optimal cost from 2004 – 2009 Year Optimal Cost 2009 1293.38 2008 1249.85 2007 1158.64 2006 1154.26 2005 1202.64 2004 1259.42 3. Is there any plant for which it may be worth adding a million kilograms of additional capacity at a fixed cost of $3 million per year? The total optimized cost for BioPharma without adding an extra capacity to any of its plants is 1293.38. To determine whether it is worth adding additional capacity, the solution needs to be redrafted by individually adding capacity to each location. There is also a need to add $3 million at the fixed cost of the plant where the extra capacity is added. Table 14: Original optimized cost versus Brazil +1 capacity. Brazil+1   Optimized Cost 1294.16 Optimized Cost (Original) 1293.38 Table 14 indicates that it is not worth adding 1 capacity to the Brazil plant with $3 million fixed cost for the original cost is still lower. Table 15: Original optimized cost versus Germany +1 capacity. Germany+1   Optimized Cost 1296.38 Optimized Cost (Original) 1293.38 Adding capacity at a fixed cost of $3 million to the German plant has increased the total cost by $3 millon which mean that it is not worth it as seen in table 16. Table 16: Original optimized cost versus India +1 capacity. India+1 Optimized Cost 1293.31 Optimized Cost (Original) 1293.38 In this situation, adding a capacity with a fixed cost of $3 million has decreased the optimal cost, which states that it is worth trying at the plan in India. This move will help BioPharma minimize cost. This is shown in table 17. Table 17: Original optimized cost versus Japan +1 capacity. Japan+1   Optimized Cost 1293.38 Optimized Cost (Original) 1293.38 For Japan, as seen on table 17, adding a capacity with a fixed cost of $3 million is not worth doing for the value has not decreased. The value obtained has stayed the same and it would be just a waste of time for BioPharma if they decide to add a capacity to the Japanese plant. Table 18: Original optimized cost versus Mexico +1 capacity. Mexico+1 Optimized Cost 1293.94 Optimized Cost (Original) 1293.38 Adding a capacity to the plant in Mexico with a fixed cost of $3 million has produced a slightly higher output and even though it is not much, it is still extra cost to the company so it is still not worth it. This is shown in table 19. Table 19: Original optimized cost versus US +1 capacity. US+1   Optimized Cost 1293.84 Optimized Cost (Original) 1293.38 Just like the plant in Mexico, the US plant shows that if a capacity is added to the plant with $3 million excess capacity, a slight increase is evident which states that it will not be worth the extra time and effort to do it as seen in table 20 as the original optimized cost versus optimized cost is pretty much similar. 4. How are your recommendations affected by the reduction of duties? Import duties play an important role in calculating the total cost for BioPharma. If the import tariff cost is reduced to 0%, the optimal solution displays a completely different result as opposed to the original solution with 100% import tariff, which is expected with reduced costs. The original optimal solution against the new optimal solution with 0% tariff is displayed in table 20. The same can be applied if the import tariff cost is reduced by 50% as seen in table 21. Import Tariff with 0% Optimized Cost 1267.20 Optimized Cost (Original) 1293.38 Table 20: Original optimal cost versus 0% tariff Import Tariff with 50% Optimized Cost 1283.57 Optimized Cost (Original) 1293.38 Table 21: Original optimal cost versus 50% tariff Both changes in the tariff cost still recommend shutting down the Japan plant and limiting the German plant to producing one chemical. Only this time at 0%, India, Mexico and US will produce only one chemical and at 50%, US joins Germany at only producing one chemical. This are displayed on both tables 22 and 23. Table 22: Plants open/shut, lines on/off with 0% tariff Relax (1=On) HighCal (1=On) Plant (1=Open) Brazil 1 1 1 Germany 0 1 1 India 1 0 1 Japan 0 0 0 Mexico 0 1 1 U.S. 1 0 1 Relax (1=On) HighCal (1=On) Plant (1=Open) Brazil 1 1 1 Germany 0 1 1 India 1 1 1 Japan 0 0 0 Mexico 1 1 1 U.S. 1 0 1 Table 23: Plants open/shut, lines on/off with 50% tariff The analysis has assumed that each plant has a 100% yield (percent output of acceptable quality). How would you modify your analysis to account for yield differences across plants? An example of random yield percentage can be applied to each plant, which is shown below: 94% --- Brazil 91% --- Germany 98% --- India 92% --- Japan 96% --- Mexico 95% --- U.S. Production + Transportation Cost From/To Latin America Europe Asia w/o Japan Japan Mexico U.S. Brazil 9.434 9.699 9.752 9.752 9.646 9.699 Germany 12.3715 12.099 12.2625 12.317 12.208 12.208 India 8.772 8.619 8.466 8.568 8.772 8.721 Japan 12.852 12.744 12.636 12.42 12.798 12.798 Mexico 9.36 9.256 9.464 9.412 9.152 9.204 U.S. 9.5025 9.345 9.5025 9.5025 9.2925 9.24 Table 24: Random yield % for HighCal Production + Transportation Cost From/To Latin America Europe Asia w/o Japan Japan Mexico U.S. Brazil 12.084 12.349 12.402 12.402 12.296 12.349 Germany 15.2055 14.933 15.0965 15.151 15.042 15.042 India 11.22 11.067 10.914 11.016 11.22 11.169 Japan 15.768 15.66 15.552 15.336 15.714 15.714 Mexico 11.96 11.856 12.064 12.012 11.752 11.804 U.S. 12.0225 11.865 12.0225 12.0225 11.8125 11.76 Table 25: Random yield % for Relax Optimized Cost 1349.41 Optimized Cost (Original) 1293.38 Table 26: Optimal cost with random yield % The obvious increase in total cost is apparent for when the random yield percentage is applied to the transportation costs, the increase in variable cost resulted in plants that are currently open to produce more to satisfy the demand and for the loss of production yields. These are demonstrated on tables 25, 26 and 27. 6. What other factors should be accounted for when making your recommendations? The main argument would be to continuously pursuit environmentally friendly. BioPharma needs to take into account the fact that there is a need to support green logistics to avoid paying extra tax. Other factors include a country’s social beliefs, culture and political guidelines. 7. What production network would you recommend for BioPharma, Inc. should use in 2015 when demand in Asia without Japan has also become stabilized? What is the approximate annual cost of your proposal, including import duties? Table 27: Plants open/shut, lines on/off 2015 Relax (1=On) HighCal (1=On) Plant (1=Open) Brazil 1 1 1 Germany 0 1 1 India 1 1 1 Japan 0 0 0 Mexico 1 1 1 U.S. 1 0 1 Table 28: Excess capacity for 2015 Constraints Supply Region Excess Capacity Brazil 0 Germany 21.827512 India 0 Japan 0 Mexico 0 U.S. 0 Optimized Cost 1376.60 Table 29: Optimal cost for 2015 Demand Forecast Asia w/o Japan Years HighCal Relax 2009 5 3 Increase 2010 5.5 3.3 10% 2011 6.05 3.63 10% 2012 6.655 3.993 10% 2013 7.3205 4.3923 10% 2014 8.05255 4.83153 10% 2015 8.857805 5.314683 10% Table 30: 10% increase in demand until 2015 Displayed in tables 27-30, the recommendation for BioPharma at 2015 would be to have Brazil, India and Mexico to be running at full capacity, limit Germany to only producing HighCal and US to only producing Relax. Japan is still recommended to shut down. Germany still has an excess capacity but it is evident that it has decreased over time. The optimal cost is expected to increase as the demand has increased Reference List Chopra, S and Meindl, P 2012, Supply Chain Management: Strategy, Planning and Operations, 5th Edition, Pearson Prentice-Hall, Boston, Pages 186-188 Appendices =0.2*SUMPRODUCT(M61:O66,L41:N46) (Optimized Cost Shut Down Cost) =SUMPRODUCT(K60:K65,H7:H12)+SUMPRODUCT(I29:I34,I60:I65)+SUMPRODUCT(I7:I12,J60:J65) (Fixed Cost Formula) =SUMPRODUCT(B60:G65,B40:G45,H50:M55)+SUMPRODUCT(B69:G74,B18:G23,H50:M55) (Variable Cost Formula) Read More
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