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Research Project Case Solution & Answer

Research Project Case Solution 

Problem Statement

One of the major issues faced by the corporate world, is forecasting. Accurate forecasting techniques help the firms to be prepared for the future events. For example, forecasting for raw materials’ needs and demands, help the firms to reduce their holding cost and to maintain an optimal production level. Moreover, forecasting is used by the firms as well as the investors to forecast the market price for a stock.

Forecasting techniques not only estimate the future value for a dependent variable, i.e. sales, but it also states the relationship between the dependent variable as well as various independent variables. There is a number of forecasting methods that could be used by the firms to generate estimates for different values, including: regression analysis, time series and moving averages etc. The models for these forecasting methods could be generated through data analytics tools in excel, i.e. regression tool, linear programming tool, demand forecasting, demand analysis, uncertainty management and decision making etc.

Despite of the availability of these computer-generated models, there are numbers of cases available related to the problems being faced by the firms, which are related to forecasting.

Often companies have lack of knowledge about various methods of forecasting, hence they seek for external help. Example of these cases include: Caesars Palace hotel in Las Vegas, Nevada, which faced the problem of recruiting the staff for the front desk in the hotel, according to the future demand of the hotel check-ins (Sesia, 2014). Along with it, in India, A-Cat Corporation is looking for demand forecasting and the accurate method of demand forecasting (Sharma, 2013). Another example, includes: Europet, searching for the relationship between its sales and over-rising expense. (Lyle, 2007).

Background

A-cat Corporation

A-Cat Corporation is one of the leading mid-sized manufacturing organizations that specializes in manufacturing of domestic electrical appliances provided to price sensitive rural population in India. The company had recorded sales of 9800000 in the budget year 2010-2011. The external shareholders of the company includes owners of A-CAT Corp and suppliers of transformers whereas the internal stakeholders includes departmental employees, operations head Shirish Apparatchik, vice president Arun Mittra and president.

In addition to this, the voltage regulator is the main product of the company that was branded and sold under the tag of VR-500 that acts as a protective device for refrigerators & television against the voltage fluctuation and frequent power failures. The financial stability of the company have been strong on continuous basis because of increased demand for the reliable appliances at affordable price. However, the management of the company noticed various problems with the sales of the flagship product. Thus, the sales of the product became volatile as well as challenging for estimate causing some operational concerns for the company.

Since the sales of the product became volatile and unpredictable, determining the right inventory amount became challenging and difficult for the company. Furthermore, the production department complaints about the shortage of spares and components. Hence, the manager is highly concerned about the collection, analysis of pattern of data and must use some forecasting techniques as well as carrying out back testing & present valuable recommendation to deal with the problem.

Caesars Entertainment

Caesars Entertainment is one of the recognized US based casino and hotel companies that operates over 50 properties as well as 7 golf courses under many brands.It is based in Paradise, Nevada and founded in Reno, Nevada. In the fiscal year 2013, the company was known to be the fourth largest gaming organization of the world with the yearly revenue of 8.6 billion dollars. One of the greatest strengths of the company is comprehensive product and service portfolio. Additionally, the company has high level of customer satisfaction and a strong distribution network and it has strong presence in different locations.

Since customer experience is crucial to the success of the company and with the use of the analytical tools, the company could measure, understand and drive the customer experience. The case examines the introduction of the regression analysis model for forecasting the arrivals of guests to Caesars Palace hotel in Las Vegas, Nevada. The forecast would be used by company to change the levels of staffing on the short term basis. There are various methods that could be used to forecast the arrivals of guests including a multiple regression model and moving average techniques.

In addition to this, with the previous models used by Si-gala and Lee, they were unable to staff its properties within one FTE of what they need to process check-ins about 5 minutes. To successfully forecast check-ins, they both were concerned about considering more advanced models in order to improve the staffing accuracy because of the fact that with the unhappy hotel experience specifically at check-in, guests tended to spend 5 to 10 percent lower at the properties of Caesar and often takes their entertainment, meals and gambling to the nearby competitor, hence, reducing the profitability levels of the organization.

Fueling Sales at EuroPet

EuroPet S.A. is one of the valuable and leading multinational companies operating number of gas stations in many European countries. The core business of the company was selling fuel to the retail customers. Traditionally, the main competitors of the company includes PetroAmerica, InterOil, and Royal Scandia. The customers shown willingness to spend considerable markup for purchasing the convenience items while getting gas. The weighted average margin was 305 on the convenience store sales i.e. 100 euros of revenue yielded 30 euros of profit.  Despite preserving a low fuel price position in the market, the company had been unable to reverse this trend.

In many-countries of Europe, the growing propensity for the supermarkets to attach the stations of gas to their business operations posit greater risk to Euro Pet. As a result, the company has started to develop and brand its c-store which was co-situated with the gas stations. Despite spending enormous amount of money on advertisement of convenience store as compared to other market players did, the company’s management is highly concerned about the increase in sales related to the advertising-efforts justified the spending on advertisement by evaluating and assessing the market data from Marseilles, France – metropolitan area. The company is also concerned about the slumping sales of the c-stores.

.Description of Methodology

Methodological approach

The research intends to use case study research methods in exploratory research. The use of the various case studies help in understanding the implications of the different forecasting methods in different contexts of issue. The case study analysis help in generating new ideas and they are of high significance because they are an significant way of illustrating theories and are used to generate a multi-faceted and in-depth understanding of the complex issue in the real life context. Thus, various case studies are used with different problems of forecasting because the case study research method offer more accurate data as compared to interviews and surveys. Additionally, the case studies offer rich insights and perspective that could lead to in-depth understanding and knowledge of problem, issue and variables.

Data collection

The data is collected from the different case studies in order to examine the different problems related to demand forecasting as well as apply the findings of the case to the problem. Each case study discussed in the report have itself gathered the data which is used to apply different forecasting techniques to present the valuable solution to the problems.

Methods of analysis/ testing

Simple moving average forecast

The simple moving average method can be the best data analytic tool for any kind of application. One of the widely forecasting tools is the simple moving average method which provides strong idea of the trends in the data set. It is highly useful technique for forecasting the long term trends. The simple moving average method also offers a smoothed line, less prone to whipsawing down and up in response to temporary as well as slight price swings back and forth. Furthermore, the simple moving average method can be used for forecasting product or commodity with the constant demand where there is seasonality or slight trend. Moreover, the method is helpful and useful in separating the random variations(Nau, 2014).

Under the case of A-Cat Corporation, the use of the simplest forecasting methods provides strong foundation of forecasting the future demand of the products in the market.  By using the simple moving average method, the demand of transformers is predicted for the near future based on historical demand patterns.

Descriptive analysis

The descriptiveness highly used for describing the basic features of the data within a study. The descriptive statistics tends to provide the summaries related to the measures and samples. The descriptive-analysis is of high importance on the ground that the raw data makes it challenging for the company to visualize what the data is showing whereas the descriptive analysis helps to present data in comprehensive as well as meaningful manner, which in turn allows simple and accurate interpretation of the data. Furthermore, the descriptive analysis are fundamentally used for presenting quantitative descriptive in the manageable form and help in simplifying the large and raw data in the sensible way (Trochim, 2015).

In order to convey impression of the data, the descriptive analysis is used to quantify the data and analyse whether the average demand for transformers increased or decreased over the period of time. The data of descriptive analysis could be used by the quality control department of A-Cat Corporation in order to efficiently improve the operational performance.

Exponential smoothing method

The exponential smoothing forecasting method uses historical data to estimate the demand of the inventory in the near future. This method takes most obvious observation into consideration & weighs them accordingly.The exponential smoothing provides more accurate picture of the estimation because of the fact that it takes into account the forecast for most recent period of time and actual value of that time. Additionally, the exponential smoothing forecasting method help managers plan inventory in more efficient manner on more relevant basis of the most recent data. In addition to this, the exponential smoothing method also produces accurate forecast in a way that it accounts difference between actual projections & what actually occurred.Furthermore, in the exponential smoothing method, the weight is put on each observation which tends to be decreased exponentially over time which is often better as compared to naïve or moving average methods where the similar weight is given to all the relevant historical months(Vandeput, 2019).

Under the case of A-Cat Corporation, the use of the exponential smoothing model helped in estimating the demand of the transformers in the year 2011, which in turn lower the risk as well as help in in making better financial decisions that improves resource allocation, cash flows, profit margin and create more opportunities for growth.

One-way ANOVA

One of the widely used statistical tools – one-way ANOVA aims to assess and evaluate the various mutually exclusive theories related to the data. It is used to test the statistical different among the means of more than one groups. It tends to provide the overall equality test of group means

Regression analysis

Regression analysis is the most powerful predictive modelling statistical tool that helps to examine the relationship between more than two variables of interest. The regression analysis helps investigate the correlation as well as causal effect relationship between dependent and independent variable. The broad spectrum of the regression analysis model includes description, forecasting, estimation and prognostication. The methods tends to lead to more accurate and correct errors&smarter decisions.It most likely provides a new perspective and assess the cumulative effect of the multiple factors.

Test of hypothesis

The test of hypothesis allows to test the claim related to the pupation as well as find out how likely it is to be true. By assessing the plausibility of the hypothesis with the use of the sample data, the organization become able to assess which mutually exclusive statement is best supported by the sample data.

Statistical Analysis

A-Cat Corporation

Recently, A-Cat’s financial performance has been negatively impacted by transformer fleet efficiency technology. Using inefficient stock forecasting methods will underestimate and overestimate stocks. In order to better estimate the required stocks in the near future, several statistical or quantitative methods and models need to be used, such as:

Simple Moving Average (SMA):

This is one of the simplest forecasting methods. To calculate it, we add the demand for transformers from 2006 to 2008 and divide by 3 to forecast the data for 2009 to 2013. The analysis shows that the demand for transformers was 865 in 2009 and 899 in 2013. This method can be faster, simpler, and simpler to determine if the demand for a transformer decreases or increases depending on the mode. It is recorded by the moving average…………………..

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