The company analysis for BMW: quantitative analysis approach - Essay Example

? Quantitative analysis Quantitative analysis Introduction Quantitative analysis approach is a financial tool used to evaluate behavior of businesses. It uses complex statistical and mathematical measurement and models from research findings. The key aspect is the approach tries to explain reality mathematically by defining variable using numerical values. The approach is adopted for a number of reasons ranging from performance evaluation to valuation of financial instruments. It is also applied in predicting future financial events such as changes in share prices. A substantial qualitative analysis can also be used to report summary results of given situations in a specified degree of confidence. An example is a statement such as 46% of the residents in New York owns a pair of Nike shoes. In a quantitative approach, this may be enhanced by using a 95% confidence level for the true proportion and stating that the residents owning a pair of Nike shoes ranges from 41% to 48%. Quantitative analysis overview To come up with an effective and meaningful quantitative analysis report of a company, it requires one to follow a step by step procedure towards carrying out a research and obtaining the relevant data required. The first step is to develop a succinct and clear statement of the setback. The second step is developing a model which is a mathematical representation of the situation. After the model, the next step is to obtain the input data for the model. This data has to be accurate and relevant if otherwise it might lead to false results. Fourth step requires the manipulation of the model and data obtained to arrive at the best favorable solution to the stated setback. The solution has to be practical and implementable. The next step involves testing of the solution arrived at in the previous step. This step is aimed at ascertaining the accuracy and completeness of the input data used in the model. After the solution has been tested and proved to be practical, the next step requires an analysis of the results. The analysis first tests the implications resulting from the solution that is to be applied. Application and implementation of the solution to a business is bound to come with certain changes, therefore, it is necessary to find out and understand these changes before implementation. The final step is the implementation of the results. Here, the process involves incorporating the solution into the organization/firm. The solution should be able to help the company in the long by reducing its running costs and increase revenues. Developing a model In carrying out a quantitative analysis one requires to design a model that will be effective in coming up with a solution to the stated problem. There are various methods one can adopt to create a constructive model. The decision which approach and model relies entirely on the available data and the nature of the setback under study. Some of the methods used to arrive at a conclusive solution include regression models, forecasting and control models, inventory control models, inventory control models, network models, simulation modeling, waiting lines and queuing models, linear programming and probability. A brief Quantitative analysis on BMW Company The automotive industry is characterized by an exceedingly competitive market therefore, the actors in the market face a number of challenges such as the heightened cost of production, series of developments that need to be in check and, mature markets. This creates challenges to manufacturers in decision making towards ensuring constant operation and increase in profitability. BMW is among the leading producers of premium vehicles in the industry. The company has gained recognition from its distinctive design, luxurious and quality approach. Although the company has maintained a strong financial stand and maintained its market share, it still faces threats of low price substitutes from its competitors. The analysis is aimed at analyzing the financial records of BMW for the last financial year ended December 2011. The data from the stated period are to be used in creating a model that can be used to implement decisions aimed at increasing the company’s revenue. Inventory and control model In order for the company to increase its revenue first, it has to reduce on its costs. This requires the control of the inventory in the company. This can be assisted by use of the inventory control model that works on maintaining the appropriate balance between high and low inventory so as to reduce costs. The model follows a straightforward step by step process that requires: planning on the inventory to stock and efficient ways to acquire it, followed by forecasting the demand which leads to controlling the inventory levels. The key decisions involved in inventory control are to know when to order and by how much. For the case of BMW, the decisions have to be made so that the company when it comes to obtaining the inventory required in manufacturing, it does it at the time high demand and minimize during periods of low demand. The economic production quantity model, can be used by BMW to ensure maximum sales and demand are met which translates to increased revenue. The model takes shape as the figure below To determine the EPQ Parameters Q^* = Optimal production quantity (or EPQ) Cs = Setup cost D = annual demand d = daily demand rate p = daily production rate Ch = carrying cost Finding EPQ Q* = v(2DCs/Ch [1- d/p)] In year 2011, BMW produced a total of 275,979 units of vehicles to its market. Using this data we can create a model that allows BMW to produce an economic production quantity that will see it reduce costs and maximize on revenue. D = 275,979 units in 2011 d = 275,979 / 250 = ~1103 units per day p = 1300 units per day (when producing according to American market researcher Power, 2010) Ch = none Cs = $6000 per setup Q* = v(2?275,979 ?7500 ?1/((1-1103/1300))) = 175,954 units Use of probability Probability models can also be used by BMW; to gauge their future outcomes if certain decisions are to be made. We can use the probability method to verify that indeed it would be profitable for the company to produce 175,954 units annually instead of the 275,979 units. Using the standard normal table Z = (X-?)/? X = value of the random variable we want to measure ? = mean of the distribution ? = standard deviation of the distribution Z = number of standard deviations from X to the mean, ? Taking ? over a five year period to be 150,000 and ? to be 70,000 the probability that BMW will increase their revenue by producing 175,954 units only will be Z = (175,954-200,000)/70,000 = 0.37077 This represents a probability of 0.8734. This means that the probability of the company increasing its sales by setting the production level at 175,954 units is 0.8734. Conclusion After studying the company analysis for BMW, certain conclusions can be drawn out in a move to increase revenue and reduce company running costs. It is evident that qualitative analysis is a useful tool that should always be applied in company analysis. Reference: Conover, W.J. (1999). Practical non-parametric statistics 3rd Edition. New York: Wiley. Read More