Comparing Small and Large Plant Investments for Card98
A. Decision tree
A decision tree is a non-parametric supervised learning algorithm that is utilized for both classification and regression tasks (Charbuty and Abdulazeez, 2021). However, it consists of the root note, branches, and internal node along with leaf nodes. The particular problem that can be determined is the low success rate of the product through the test marketing stage. There can be various challenges that can be faced by company R&D laboratories through developing the product Card98. The product can be rejected by the target market if the product is not well received by the target market during the test phase, it may indicate that there is little or no demand for the product. This can be a significant challenge for the company, as it will need to either make significant changes to the product or abandon it altogether.
Figure 1: Decision-tree
On the other hand, there can be limited market research; test markets may not accurately reflect the larger market. As a result, the product Card98 may not do well in the test market and cannot be successful in the larger market. Furthermore, if the product is not successful in the test market, the company may have to allocate additional resources to redesigning the product, which can drain the firm's resources. Apart from this, in case the product is unsuccessful, it may provide an opportunity for competitors to enter the market with similar products. This can be a challenge for the firm in gaining market share in the future (Jeong and Chung, 2023).
The NPV stands for a Net present value which is a formal financial metric used to determine the value of an investment or project. However, it takes into account the time value of money by discounting the expected value of future cash flows of the investment to their present value and then subtracting the initial investment cost. The Year 0 cost is £500000, year 1 can be by 100000, year 2 can be by 150000, year 3 by 200000, year 4 by 250000 and year 5 by 300000. However, the initial cash outflow is mentioned (Knoke et al. 2020). Thus through the calculation over the Excel function, the present value can be calculated as shown in the figure above. Thus, the sum of the total value will be -447871.538. On the other hand, the annual discount rate is 8.5%, the formulae of NPV is identified as "=NPV (8.5%, H8:H12)", the adequate result is 756,073.01 along with the initial value is estimated at 256,073.01. That, the value is positive and it means the investment is expected to generate a return that exceeds the cost of capital and is thus a desirable investment.
Grab The Best Academic Assistance In Just One Click
Through the specific context, in case there is a success rate in the test market there can be various pros and cons in building a small plant versus and large plant through potential gains and losses. However, gains in building a small plant can be, that a small plant requires less capital investment compared to a large plant (Bertram et al. 2019). This means that the firm can start production quickly and with less financial risk. On the other hand, a small plant can be more agile and flexible in adapting to changes in demand or market conditions. A small plant has lower operating costs that can lead to high profits for the firm. There can be losses in building a small plant, limited production capacity, and a small plant that has a limited production capacity, which can restrict the firm's ability to sell up its operations.
A small plant may not be able to achieve the same economies of scale as a large plant, which can increase the cost of production per unit. Apart from this the gains of building a large plant are, that a large plant can produce a high volume of products for CARD98 and it can help the firm to meet the demand in the market. Large plants can increase the firm’s competitiveness by enabling it to offer low prices and high-quality Card98 products. The losses of building a large plant are a large plant require a complex management structure that can increase administration and bureaucratic costs. A large plan can be less flexible in adapting to changes in market conditions or demand (Stewart and Shirvan, 2022).
D. Sensitivity analysis
Through the decision tree, there is a probability of various negative insights in the form of problems, including limitations in market research. It can be recommended that there be a better use of social media, it can be a valuable source of information about the customers and competitors, and it can be used over social media monitoring tools in tracking people's views about the product Card98 (Del Vecchio et al. 2020). Another problem that can be confronted will be limited resources, there can be an implementation of sustainable practices through the product, and this can help in reducing the use of finite resources by relying on renewable resources. The product negativity in the testing market can be the other probability of the issue; it can be resolved through promoting innovation, encouraging innovation by allowing new players to enter the market, and creating disruptive technologies.
The improvement in product quality, focusing on conducting quality control checkups and gathering relevant feedback from customers in identifying areas needed for improvement, will help in dealing with rejection by the target market. The problem of additional resources is the other probability problem that will be confronted; there can be smooth optimization of resource allocation, once identifying the resources that can be optimized effectively and implementing new processes (Gour and Winter, 2019).
E. Analysis
Through the analysis, it can be determined that the large plant takes an extra 40% of the time than the small plant. However, the small plant can have less time as a small plant usually has fewer processes and fewer requirements of equipment and smaller production lines, this makes them quicker to set up and easier to manage. On the other hand, large plants, tend to have more complex production processes, requiring more equipment, longer lead times, and a large amount of workforce, which can lead to delays in completion time. Additionally, it can be determined that the formula for PERT is "(O + (4M) + P) / 6". It is determined that the completion time of a small plat building can be 7 days such that the large plant will take time of an extra 40% mentioned above, thus 10 days is for large plant completion. Apart from this, the required ratio through small plants versus large plants can be 86 and 121 (Al-Baldawi and Ali Hussein, 2021).
Table 2: Calculation of probability
The standard deviation measured is for the small plants at 22.86 and the large plants at 34.29. It can be visualized that a small plant in 8 weeks can be higher than the probability of building a large plant in 12 weeks such that it is analyzed in calculating standard normal distribution. This will give the result of 0.09107 for small plants and 0.13964 for large plants. Another justification can be determined; the actual probability of successfully constructing each plant within those periods will depend on a wide range of factors such as the skill level of the team and efficiency in improving the quality of materials.
F. Summarize findings
Through the previous question, it can be determined that the small plant building will benefit more to the firm more through producing the specific product of Card98. On the other hand, it can be determined that the small plant can be a more cost-effective preference, this is because the small plant has a requirement of few raw materials resulting in reduced capital with operating expenses (Charbuty and Abdulazeez, 2021). On the other hand, small plants require less time to build and can be operational sooner than larger facilities. It can help the company in meeting its demand and generate faster revenue. Small plants can have easier maintenance and repair, as they have fewer pieces of equipment and systems to manage. This can result in less downtime and increased efficiency. This can result in less downtime and increased efficiency. However, the PERT chart is used in determining the estimated timing of completion through the dual development of the plant.
The previous question also shows that the time variance is very important in ensuring the smooth establishment of the product Card98 in the market. It is visualized that the actual probability of value for the firm is better for a small plant. The firm can be new to the market and their investment can be low such that they need to analyze the various factors in reaching the target market. Apart from this, it can also be visualized that the firm can ensure its success and earn a relatively high amount of profits in achieving long-term goals (Gour and Winter, 2019).
References
Al-Baldawi, Z. and Ali Hussein, I., 2021. Estimating the Optimum Completion Time of Project Using Binomial Distribution and Probabilistic PERT Network. In Proceedings of First International Conference on Mathematical Modeling and Computational Science: ICMMCS 2020 (pp. 627-637). Springer Singapore. DOI: https://doi.org/10.1007/978-981-33-4389-4_57
Bertram, N., Fuchs, S., Mischke, J., Palter, R., Strube, G. and Woetzel, J., 2019. Modular construction: From projects to products. McKinsey & Company: Capital Projects & Infrastructure, pp.1-34. DOI: https://doi.org/10.1016/j.rser.2021.111880
Charbuty, B. and Abdulazeez, A., 2021. Classification based on decision tree algorithm for machine learning. Journal of Applied Science and Technology Trends, 2(01), pp.20-28. DOI: https://doi.org/10.1145/3429739
Del Vecchio, P., Mele, G., Passiante, G., Vrontis, D. and Fanuli, C., 2020. Detecting customer's knowledge from social media big data: toward an integrated methodological framework based on netnography and business analytics. Journal of Knowledge Management, 24(4), pp.799-821. DOI: https://doi.org/10.1108/JKM-11-2019-0637
Gour, G. and Winter, A., 2019. How to quantify a dynamical quantum resource. Physical review letters, 123(15), p.150401. DOI: https://doi.org/10.1103/PhysRevLett.123.150401
Jeong, S.W. and Chung, J.E., 2023. Enhancing competitive advantage and financial performance of consumer-goods SMEs in export markets: how do social capital and marketing innovation matter? Asia Pacific Journal of Marketing and Logistics, 35(1), pp.74-89. DOI: https://doi.org/10.1108/APJML-05-2021-0301
Knoke, T., Gosling, E. and Paul, C., 2020. Use and misuse of the net present value in environmental studies. Ecological Economics, 174, p.106664. DOI: https://doi.org/10.1016/j.ecolecon.2020.106664
Stewart, W.R. and Shirvan, K., 2022. Capital cost estimation for advanced nuclear power plants. Renewable and Sustainable Energy Reviews, 155, p.111880. DOI: https://doi.org/10.1007/s00122-019-03317-0
