The Quantitative Techniques - Dragon Wool Limited - Case Study Example

THE QUANTITATIVE TECHNIQUES DRAGON WOOL LIMITED Name Course Code Professor’s Name Date The Quantitative Techniques Dragon Wool Limited Executive Summary Unforeseeable events often tend to affect a company’s core strategy. The impact of the events may be related to the company’s marketing plans, promotional techniques, and human resource procurement policies. Consequently, firms are forced to come up with plans that would help them to navigate through the tough times. For instance, Brexit brought several market uncertainties that could have been difficult to predict as the cross-national business environment in Europe was revolutionized. To keep afloat, firms had to find viable methods to support their operations in several European countries. Obtaining approvals and permits to operate in some countries became unpredictable for the British enterprises. To ascertain such viabilities, such companies were required to conduct rigorous market researches in several countries. This report attempts to analyze the several prospective strategies suggested for Dragon Wool Limited to determine the viability of each in the wake of Brexit. Background The Dragon Wool Limited company is a clothing manufacturer based in Wales. It specializes in woolen accessories such as scarves, hats, and gloves. At the start of each calendar year, the Chief Executive Officer (CEO) of the company organizes an annual meeting with the top management team to deliberate on the potential plan for the following twelve months. In 2017, the company was faced with market uncertainties heralded by Brexit. As such, the CEO instructed three members of the management to come up with potential strategies that the company could adopt. The plans were provided but they contained technical details and the CEO wanted them to be analyzed before a recommendation would be made. Discussion Task 1 Susan is the head of finance and, as such, she has unlimited access to the firm’s financial records. After examining the financial records, she suggested that the company should attempt improving its capacity to increase the volume of production. This could either be done by extending the current production plant in Wales or building a new one in Hungary. Extension in Wales. Susan projected that the company’s profitability would increase by £650,000. However, failure to acquire the planning permission would lead to a financial loss of £250,000 due to high production commitments. Using historical data, she found that there is an 85% chance that the Welsh government would approve the extension before 2018. An extra plant in Hungary. According to Susan, this option would be projected to increase the firm’s profitability by £750,000. Any delay in procuring planning permission before 2018 was expected to incur a financial loss due to production commitments that would amount to £350,000. According to research done by an overseas team, the Hungarian local government has reservations about the impact of foreign firms on the local community. As a result, only 10% of foreign firms get their planning permissions within a year. The team advises that, to speed up the process with an 80% chance, the company should promise to contribute to the development of the local community. Such a contribution has a present financial value of £20,000. Decision tree Probabilities Event 1 Event 2 Decision Payoffs Recommendations for maximizing expected monetary value. The various risks involved for the alternative directions have a risk associated with each (Gray and Larson, 2015). In some cases, the risks might be more than one. The CEO would be required to understand the nature of the risks so as to be able to make a viable final decision. By understanding the nature of the risks involved, the management will be able to prioritize the risks depending on the level of urgency. First, however, a qualitative analysis would be the best way of obtaining the information regarding the risks. Calculating the Expected Monetary Value (EMV) would be vital in this case. For the option of extending the production plant in Wales, the EMV may be calculated as; The probability of acquiring planning permission in a year multiplied by expected profitability = 85/100 * 650000 = 0.85 * 650000 = £552500 OR The probability of failing to obtain planning permission multiplied by the resultant monetary loss = 15/100 * –250000 = 0.15 * 250000 = 37500 EMV = 552500 – 37500 = £515000 This is a risk that the company would be willing to take since the potential financial advantage far outweighs the expected financial loss. On the other hand, the expansion in production into Hungary will have an EMV of; 80/100 * (750000 – 20000) = 0.8 * 730000 = 584000 in case the company is able to acquire a planning permission given that it also comes with an extra monetary commitment towards the development of the local community that amounts to £20,000. OR 20/100 *1 – 350000 = £70000 as the risk for not obtaining the permission. EMV = 584000 – 70000= £514000 In principle, expanding the existing production plant in Wales offers the chance to realize a higher monetary gain at a lower risk in the event of failure to acquire planning permission before 2018. The EMV is higher with this approach and this means that the option is better for cushioning the firm against the risk involved. If the promise to the Hungarian local government was lowered to £10,000, the optimal strategy would be affected since the probability of acquiring the planning permission within a year would be lower. In retrospect, it is plausible to assume that the monetary pledge to the local government in Hungary is the only factor affecting the chances of acquiring a planning permission in the country with £20,000 resulting into optimal chances. Lowering the value by half could also reduce the probability by half and this would lower the EMV of the opportunity to £29,200 (half of £58,400). In addition, the negative EMV of the threat would increase to £210,000 (60% of £350,000). As a result, the monetary viability of this potion would be compromised (King, 1968). Practically, this would make the option to be outright inferior to the alternative of extending production in Wales. The value of £20,000 should be the highest pledge that the company can give for its support in the development of the local Hungarian community. Any value higher than this would only increase the initial cost of the project without guaranteeing any merits given that the possibility of acquiring a planning permission does not increase accordingly. This value will be maximized at the optimal figure of 80%. Task 2 The marketing department conducted a market survey in 2016 to determine new consumer needs and preferences. From the survey, the team found that consumers were willing to purchase two new products from Dragon Wool Limited namely a shawl and a jumper. The prospective buyers of the shawl would be willing to pay £35 for it and were more concerned about the design. Those who expressed interest in a jumper from the company were willing to pay an average price of £30 and were more concerned about the quality. The marketing director liaised with the production and design departments to explore the feasibility of the two options. Constraints. The company would be faced with several limiting factors in case it starts the production of the two new products. First, the weekly supply of raw material (including both the natural and synthetic fibers) is fixed. This limits the production capacity for the products. Moreover, the production process and equipment is limited by the current production patterns. This is made worse by the fact that there is are limitations on the company’s human resource capacity. Weekly profit, cost, and net profit Profit = weekly sales from shawls and jumpers – cost of raw materials Assuming that x1 units of shawls and x2 units of jumpers are sold by the company in a week, P = (35x1 + 30 x2) – ((52000 * 0.02) + (62000 * 0.01)) = 35x1 + 30 x2 – 1660 This leads to a modification of the formulae for x and y. X ≤5 0, x2 ≤ 40 Cost = Weekly labor costs + Cost of power and other operational costs Net profit = Profit – Cost Linear programming. The objective function can be obtained from the expected revenue from the sale of the shawls and the jumpers. Z = 35x1 + 30 x2 The constraints require that the volume of production cannot be exceeded. The available raw materials can only allow for the production of 51 units of shawls in a week. A shawl will require 4 times more time in the knitting section where the production capacity is 50 units. In the drying section, a jumper takes 2.5 more time and the production capacity is 40 units. Thus; X1 + x2 ≤ 51, X1 +4x2 ≤ 50, 5x1 +2x2 ≤ 40, X1, x2 ≥ 0 From the model, x1 = 36 and x2 = 15. This means that the company should produce 36 units of shawls and 15 units of jumpers in a week. The expected revenue from this pattern of production can be obtained by using the values in the objective function. The result would be; Revenue = 35(36) + 30(15) = 1750 Profit = 1750 – 1660 = 90 Net profit = 90 – fixed labor cost and other operational costs With an expansion into Hungary, the firm would benefit from a new source of raw materials from the local suppliers. The new supply would increase the amount of natural fibers and synthetic fibers to 60,000 meters and 70,000 meters respectively. The new production capacity would be 58 units and the optimal capacity would produce 40 shawls and 18 jumpers per week. The expected revenue would increase to; 35(40) + 30(18) = 1940 (Nisse, 2015). Binding constraints tend to hamper the chances of a business enterprise venturing in new operations. The constraints could be geographical or design-related. When a business firm wishes to diversify its scope of operations in terms of the geographical reach or the pattern of production, it would need to contend with factors that limit its growth in the desired direction (Kendall and Kendall, 2014). The ease of procuring supplies is the commonest binding constraint. The firm would be compelled to customize its production capacity within its capacity to procure the requisite raw materials. The redundant or non-binding constraints do not influence the optimal performance of a firm. In the case of Dragon Wool Limited, the capacity of the supply of raw material does not present an inevitable hurdle that would limit the firm’s pattern of production. As such, the firm can significantly shackle the restrictions placed on its capacity of production by the availability of raw materials by venturing into new regions where they can also be accessed (Hallaert and Munro, 2009). Task 3 Network diagram Critical path and normal completion hours. The path involving yarn inventory check-design-knitting -linking-inspection-mending-washing-packaging involves the longest time duration thats would take 22.5 hours. Total cost. A collective normal and crash cost of £209 would be incurred. If an additional cost of £10 per hour is also to be considered, the total cost for the process would be £434. Crashing activities. Some activities can be executed concurrently in an attempt to reduce the total completion time of the process (Baguley, 2008). Inventory check, design, and winding can be crashed to reduce the total cost. The resultant process would have a total completion time of 18 hours. The crash and normal cost would be £205 and the additional costs would be £180. As a result, the total cost of the process would be £385. This would lead to an 11% reduction in cost. According to Susan, the Head of Finance, the crashing should be approved since the resultant cost reduction is more than 10%. Upgrading the washing and drying machine. If the machine is upgraded, the total completion time would be 15 hours leading to total additional costs of £150. The total normal cost would be £190. The total cost of running the process would be £340. This leads to a 12% cost reduction and should, therefore, be approved. Recommendations and Conclusion Evidently, the company has several possible directions to take in an attempt to remain afloat in the wake of Brexit. However, the company might not have the capacity to implement all the viable options due to the presence of several binding and redundant constraints (Meredith, Mantel, and Shafer, 2016). The recommendations by the finance department about the expansion of production volume would lead to visible and significant financial advantages. Still, expanding the existing production plant in Wales should be followed by rigorous market research to ascertain the viability of new segments (Wouters 2012). In addition, the company should consider the restrictions brought about by the limitations in procuring necessary raw materials to cater for the additional production capacity costs. Extending production into Hungary will lead to a lower chance of financial merits at a slightly higher financial risk. Still, this might nevertheless be advantageous for the firm given that the new region will offer a new source of raw materials (Taven, Nilsen, and Nilsen, 2004). The new supply capacity will not only benefit the new plant but also the production of new products in the parent plant. In addition, the company will be compelled to contribute towards the development of the local community in Hungary. This initiative will be a beneficial marketing strategy and the company will essentially be fulfilling its expected societal responsibilities. With the good public image due to involvement in social activities, the company will get a bigger chance of extending production to more new regions. Launching new products will not lead to any substantial increase in the financial revenues of the firm. In addition, it is significantly dependent on the quality of marketing to be funded for the new products (Odiorne, 1969). This might even put a strain on the firm’s human resource capacity and the stock of raw materials. The expansion of the number of products is, as such, less beneficial when measured against the other available options. The most effective way to improve the financial performance of the firm would involve cutting its production costs by modifying the sequence of the processes. The cost reductions brought about by the crashing of activities and the upgrade of the drying and washing machine are more than 10%. In addition, the strategy can be adapted to all production plants including the new ones. References Baguley, P. (2008) Project management. London: Hodder Education. Gray, C., and Larson, E. (2015) Project management: The managerial process. New York: Mc Graw-Hill. Hallaert, J. and L. Munro (2009) ‘Binding Constraints to Trade Expansion: Aid for Trade Objectives and Diagnostics Tools’, OECD Trade Policy Working Papers, No. 94, OECD Publishing. Kendall, K. and Kendall, J. (2014) System analysis and design. Essex: Pearson Education. King, W. (1968) Probability for marketing decisions. New York: Wiley. Meredith, J., Mantel, S., and Shafer, S. (2016) Project management: a managerial approach. Hoboken, NJ: Wiley. Nisse, N. (2015) Graph theory and optimization: Introduction on linear programming. Sophia: University of Nice. Odiorne, G. (1969) Management decisions by objectives. Prentice-Hall. Taven, T., Nilsen, E., and Nilsen, T. (2004) ‘Expressing economic risk- Review and presentation of a unifying approach’, Risk Analysis, 24(4), pp. 989-1005. Wouters, M. (2012) Cost management: Strategies for business management. London: Mc Graw-Hill. Read More