A Cat Statistical Analysis Report

Statistical Analysis Report for the A-CAT

A-CAT was one of the Indian leading producers of electrical appliance within the medium-scale industry. The A-CAT manufactured and distributed domestic appliance to the rural population India. Moreover, A-CAT had two medium-sized manufacturing units in a small town of Gondia located at the remote district in Vidarbha, a less develop area in India. The company primary flagship product was 500 kilovolt amps voltage regulator branded with VR-500 tag. Established in 1986, the company could boast of 40 employees. A-CAT had established a partnership alliance with Jupiter Inc. and Global Electricals for the production of cabinets and TV signal boosters respectively. Since 1986, the A-CAT had been in operation and the company budget between 2010 and 2011 provided the annual sales of Rs. 9,800,000 ($147,128). The functional company department are design department, manufacturing department, purchasing department, and sales and service department. Contrary to other companies that focus on the urban areas for the marketing operations, the A-CAT focuses on rural areas, and offers 100 different household electrical appliances that include FM radio kits, TV signal boosters, battery chargers, electronic ballasts, and voltage regulators.

However, the company has recorded a decline in the sale voltage regulators in the last few months. In reaction to a decline in sales, A-CAT deliberated to increase the inventory, however, some functional departments questioned the move of keeping the large number of transformers in stock. However, the management believed that an increase in stock of voltage regulators is necessary because these orders were categorized as rush orders. The other challenges that the A-CAT faced was that the suppliers were likely to increase the price if a continuity and uniformity for the transformers' order was not guaranteed. The company operations are also being affected by both the internal and external stakeholders. The important internal stakeholders are operation manager (Shirish Ratnaparkhi), Vice-president, store manager (Arun Mittra) and the company employees. The important external stakeholders are the suppliers, customers and the government.

On top of this, considering the economic outlook, and market scenario, the sales of voltage regulators have been volatile in the last few years despite an increase in the company revenue. Moreover, company faces the market problems, and the sales have been sluggish compared to the sales of the competitors. In response to the sluggish demand, the sale department has decided to forecast the demand for the voltage regulators in order to determine the amount of transformers to store in the inventory. Meanwhile the Vice President of the company called for the comprehensive data of the sales figures of the last several years. The usual method is to look into the sales figure within the last two years to estimate the number of transformers that would be needed for the voltage regulators. The essence of the data report is to meet the production levels, maintain the optimal stocking levels, and final productive levels. The data forecast will assist the company to plan the purchasing of the transformer better as well enhancing proposed sale projections.

II. Analysis Plan and Decision Making

A. Identification of the Quantifiable Factors Affecting performance of Operational Processes

The paper carries out the SWOT analysis to identify the quantifiable factors affecting performance of operational processes, which assists in enhancing the decision making of the A-CAT. Management.

Strength: The company financial records is one of the strengths of the A-CAT. The 2010 and 2011 budget reveals the annual sales of Rs 9,800,000. Since 2006, the A-CAT had enjoyed an increase in sales. For example, the company sold the average of 801.2 transformers voltage regulators in 2006, however, the company sales figure for the voltage regulators increased to 1,101.2 in 2010. The average sales figure that the company recorded during the past years contributed to the company strength. Moreover, the A-CAT recorded an increase in the sales of the refrigerators between 2006 and 2010. The company recorded sales of 16,102 refrigerators in 2006, and sales increased to 27,458 at the end of the 2010 fiscal year. The company strength also lies in its competent employees. The operation manager was one of the company competent employees who is responsible to forecast the effective production of goods using past data. Through the skill of the operation manager, the company is able to produce the goods tailored to the demand data.

Weakness: The A-CAT has not yet taken the advantages of the past data to forecast the appropriate number of product to manufacture and keep in the stock. For example, the company was unable to decide whether to keep the large stocks or small stocks in the inventory. Moreover, the company does not have enough resources to make suppliers to maintain same price for the product supplied. For example, the suppliers are likely to increase the price if the company has not been able to maintain the sales uniformity for the transformers.

Opportunities: The A-CAT can take opportunities of the healthy Indian economy and large population to achieve the market advantages. Dhoot, (2015) points the Indian economy has witnessed a substantial growth in the last few years. For example, the Indian economy has recovered from the turbulent economy and enjoyed a robust growth of 5% in the 2012 -2013 fiscal year. Moreover, the steady Indian economic growth will continue to provide the higher disposable income for consumers and assist people to upgrade their lifestyles. Thus, "a robust 400 million Indian middle class with growing disposable incomes has been instrumental in driving demand of various consumer electrical devices." "(Dhoot, 2015. p 2). Moreover, the number of nuclear families are increasing in India along with a rise in families with double digit income and having easy access to credit.

A report conducted by the Ernst & Young (2015) reveals that a domestic electrical appliance has recorded a substantial growth in the last few years due to the growth of the employment opportunities for the millions of Indians. Typically, the consumer electrical appliance has recorded growth rate of 28% . The factor responsible to the high growth rates is a significant increase in a local demand. Moreover, there is an increase in the demand for the electrical appliances in the rural areas. For example, 8% of the rural population own refrigerators, which the A-CAT has been able to explore in the last few decades. In essence, the demand for electrical home appliance in the rural areas has recorded a 30% growth rate. Dhoot, (2015) contributes to the argument by pointing out that A-CAT can take the advantages of the growth rate in refrigerators because India has been able to records sales of 14 million units of refrigerators in 2013."Key growth drivers are lower prices and rising demand for frost-free refrigerators. Fridges with a capacity range of 142-340 liters dominated fridge sales over the review period, representing 74% of total volume sales." (Dhoot, 2015 p 11). Thus, the A-CAT can exploit the aforementioned market opportunities of the electrical appliance in India.

Threat: A-CAT is facing a stiff competition from both internal and external manufacturers of the electrical appliance in India. Typically, the giant electrical manufacturers such as Samsung, and LG dominate the market of electrical appliance in India. Moreover, A-CAT is facing a market threat from electrical producers from China because of large imports from China is threating the growth rate of local producers of electrical appliances. For example, India imports 39% of its refrigerators from China in 2014. Heavy taxation on electrical alliance is another threat facing the A-CAT. The present total tax incidence is between 25% and 30% compared to tariffs levied by other Asian countries, which are between 7 and 17%.

B. Problem Statement Addressing Given Problem and Quantifiable Measures

The outcomes of the analysis reveal that A-CAT has faced challenges in penetrating the urban market despite the presence of the market opportunities among the urban population. Moreover, the company faces challenges to compete with the international manufacturers of electrical appliance in China. The threat of suppliers are the other problem facing the company. Typically, suppliers can increase its prices if the demand of transformers are not being maintained. Moreover, the A-CAT has not also been to take the advantages of past data to enhance market advantages. The vice-president believes that the current structure needs to be corrected because the company is required to implement effective production to meet the demand. The correct measure is to use the sale figures of the past two years to make a forecast to meet the normal production level of transformers. Despite the aforementioned sales forecast, the company faces challenges in increasing the production level of voltage regulator between 2009 and 2010 because the average production level of voltage regulator is likely to reach 1,101.2 in 2010. Moreover, the sale figures of the transformers were likely to reach 27,458 at the end of the 2010 fiscal year. Thus, the A-CAT is required to adjust its production capacity to meet the projected demand.

C. Strategy to Addresses the Problem and Method to improve Sustainable Operational Processes

A-CAT should devise the strategy to develop power over suppliers. The company should source for suppliers through the internet to HAVE power over the suppliers of the transformers. The A-CAT should not rely on local suppliers for the production of the appliances, rather, it should rely on multiple suppliers to enjoy a low cost of production. For example, sourcing the materials from China will make the A-CAT to enjoy the low cost of production. Moreover, A-CAT should employ more labor in the manufacturing department to assist the company to meet the rush order. The adjustment would assist the company to meet the forecasted demand of the transformer since the sales figures are likely to increase between 2009 and 2010.

III: Identification of the Statistical Tools to Collect Data

A. Identification of the Appropriate Family Statistical Tools for the Analysis

The study uses the descriptive statistics to summarize the data in a manageable form. The paper collects data on the company sale figures of the refrigerators and transformers between 2006 and 2010, and uses the descriptive statistics to summarize the data . The descriptive statistics provides the mean, standard deviation and median used for the summary of the whole data. From the data collected through descriptive statistics, the paper has been able to provide the visual graphical presentation of the mass data. The study also uses the ANOVA: Single Factor for data analysis. The essence of the ANOVA single factor is to test the null hypothesis. For example, the operations manager collects the sales data of the refrigerators, and used the data to perform the ANOVA analysis, and the results of the analysis reveal that the mean data of the transformer has increased between 2006 and 2008. Thus, the paper carries out the ANOVA analysis to determine whether the mean number of transformer are likely to change between 2006 and 2010. Additionally, the paper suggests using the regression analysis that assists in establishing the relationships between the dependent and independent variables. Moreover, the regression analysis can be used to forecast sales figures if the economy condition improves or not improve.

B. Determination of the Category of Provided Data, and Justification the Data fits into the Category Type. Relationship between the data and tools

The category of the data for the analysis is the sales figures of the refrigerators between 2006 and 2010. The data consist of the sales figures for the Quarter I, II, III, and IV of the refrigerators. Moreover, the sales data of the transformer between 2006 and 2110 are used for the analysis. The major reason for using the data for the analysis is to forecast the sales figure so that the company can produce the optima production of the transformers and refrigerators that will meet the market demand so that the suppliers will not increase the price of materials, which may consequently increase the cost of operations.

C. Most Appropriate tool to Analyze Data from the Family of Statistical Tools

The descriptive statistics and ANOVA tests are the appropriate statistical tools to analyze the data in the case study. The tools will be able to assist the company to determine whether the sale figures are increasing. Typically, the paper will be able to use the mean value in the descriptive statistics to determine the appropriate production level to meet the projected demand. Moreover, ANOVA will assist the company to test the average sales production of the transformers that will meet the market demand.

D. Justification of tool for the Data Analysis

The chosen tools will assist in making effective decision on the number of transformers that the company will produce in a given year. It is essential to realize that some functional departments in the company were questioning the policy of keeping a big stock of transformer in the inventory since the transformers are part of the principal components of the voltage regulators. Thus, the descriptive statistics will assist in comparing the mean data of the transformers and voltage regulators. The data collected will assist in making a decision about the number of transformer to produce for the 2009 and 2010. The ANOVA statistical will also help the company to understand whether the sales of the transformer and voltage regulators are increasing or decreasing. The ANOVA will also assist the operations manager to test the hypothesis, which will assist in making an effective decision about the number of transformer and voltage regulators to produce in the forthcoming years.

E. The Best Quantitative method Informing Data-driven Decisions

The quantitative method is a method of using of the statistical tool to make an effective decision. The Mean is the best form of the quantitative method used to develop the average value of the data, and the Mean is the best tool to make an effective decision. Moreover, the study will use statistical technique using the graphical illustration to make decision. For example, the histogram allows the company to develop a big picture about the overall data. The visual presentation of the data will assist in evaluating the sales performance in the past years, and the historical data will help the company to forecast the sales for the 2009 and 2010.

IV. Data Analysis to determine the Appropriate Decision

A. process needed for the Statistical Analysis

The process needed for the data analysis is to collect the historical data of the transformer to test the following hypothesis:

Hypothesis:

Ha: "The mean number of the transformers required exceeds 1000 transformers." "

The study collects the historical data for the period of 2006- 2010 to test the hypothesis, and the data are presented below:

Transformers Dataset

ta

2006

2007

2008

2009

2010

January

February

March

April

May

June

July

August

September

October

November

December

Average

801,1667

898,6667

990,3333

1083,667

1101,167

Afterwards, the paper carries out the descriptive statistics of the transformer dataset, and the table below provides the outcome of the descriptive statistics. The 2010 Mean value has made the study to reject the null hypothesis because the Mean of transformers for the 2010 exceed 1000 (Mean=1101.16)

Descriptive Statistics

Transformer Voltage Regulators

2006

2007

2008

2009

2010

Mean

801,1667

898,6667

990,3333

1083,5

1101,167

Standard Error

24,18766

39,52853

41,95025

44,64651

39,649

Median

1045,5

1140,5

Mode

#N/A

#N/A

#N/A

#N/A

Standard Deviation

83,78851

136,9309

145,3199

154,66

137,3482

Sample Variance

7020,515

18750,06

21117,88

23919,73

18864,52

Kurtosis

-1,62662

-0,60905

-0,85282

-0,83045

-1,10512

Skewness

0,122258

0,77195

0,649615

0,561198

-0,34583

Range

Minimum

Maximum

Sum

10784

11884

13002

13214

Count

12

12

12

12

12

Confidence Level (95,0%)

53,23668

87,00172

92,33187

98,2663

87,26685

The output of the ANOVA single factor makes this study to also reject the null hypothesis because F> F crit where the F=10.71 and F crit =2.54.

Anova: Single Factor

SUMMARY

Groups