Multivariate statistics

Observations and Comparisons

Observations and comparisons of several variables are the focus of multivariate statistics. It uses three different techniques: factor analysis, multidimensional scaling, and cluster analysis. It serves several purposes and is an important part of every business. One of the uses is figuring out how much a particular product will sell for.

Using Several Variables

Change one variable and look for any differences in the results is what factor analysis, a multivariate statistical technique, entails. This strategy is one that many businesses have adopted. The two types of factor analysis are confirmatory and explanatory. While the confirmatory type verifies, the factors are determined by the data whereas the confirmatory type confirms the hypothesis in the structural models of equations. One variable is changed at a time and the results observed after changing the variable. For example, they can increase or decrease the variable one at a time and see the changes. For instance changing a brand name or the color appearance of a product and view how it affect the market demand or sales of the product(Sharma, 2008).

Real-life Examples: Wal-Mart

One of the real-life company that has used the factor analysis technique is Wal-Mart. Factor analysis has helped the company to determine the kind of market effort to put to increase sales. They are able to weigh the efforts and know what to eliminate and what to pursue. This is mostly done through surveying that is, several versions of a product are chosen then customers determine which version they would prefer most. Information on the most preferred version then helps the company to know the version that has more sales. Wal-mart had several issues in the year 2006 and used factor analysis to come up with a solution to the problems. The problems and allegations include using low prices and exporting thus destroying the local small businesses.

Preference and Attitude of Customers

Multidimensional scaling is a technique that a company uses to know the preference and attitude of customers toward similar products. The customers compare the products and give their preference based on the difference in characteristics of the products (Sharma, 2008). Therefore the company can know what features to include in their products to increase sales. The strength of this technique is that it has no biases or the views of the researcher. The researcher does not judge anything, but only the response of the customers is considered. Hence the decision of the features of the product is purely the preference of the customers and not the researcher. The perfect product that is preferred by consumers is then made increasing the sales of the product.

Real-life Examples: Sam's Club

Real life companies that use multidimensional scaling include Sam's Club. They used this technique to determine their green logo. Green represents a clean environment; therefore, customers would prefer their products because it is environmentally friendly and contains no contaminants. The club is up to the standards of the organizations that deals with environmental protection.

Cluster Analysis for Similarities

Cluster analysis as a multivariate statistical technique deals with similarities of observation from a population and then disintegrates into smaller sections basing on the minimal and maximal correlations. There are two divisions under cluster analysis that is nonhierarchical and hierarchical cluster analysis. Hierarchical arranges the data in the hierarchy that is a pyramid in the decreasing or increasing order. Nonhierarchical involves division of a large data set into smaller sets. The choice of the type to be implemented depends on the output desired. Cluster analysis has been used in cases for example of determining fraudulent transactions(Bennett, 2014).

Real-life Examples: SABMiller

The real life company that has applied this cluster analysis is the SABMiller. SABMiller is an international company that brews beer and produces Coca-Cola drinks. It has used cluster analysis to know fraudulent transactions, customer preference and also enlightening consumers on the difference between beers.

Importance of Statistics Software

There are many companies that provide statistics software websites that help in analyzing and interpretation of data. For example software like SPSS can predict patterns and give associations, therefore, guides in making of models.

The Advantages of Multidimensional Scaling

A multivariate technique that is most preferred and different from the others is the multidimensional scaling. It is more advantageous to use this method that cluster analysis and factor analysis. It is an easy way of increasing sales that is from just a simple survey the manufacturers are able to decide efforts to use so that they increase their sales(Warner, 2013). Variables such as change of the brand name and observing the sales can be used to determine the market demand and the response of the consumers towards the modification. Basing in mind that multidimensional scaling when used has no biases because the researcher does not give his views on the product, companies are able to make decisions that have the impact on the customers. That is, the product has the characteristics that the consumers prefer most, therefore, increasing the sales.

Detecting Customer Preferences

Multidimensional scaling is different in that it provides a mechanism of detecting, categorizing quantity and weighing the preference of consumers for an individual product. These characteristics make this technique outdo the other two in terms of choice. For a company to produce or modify their product, they should first know the response of the customer to avoid losing the market of the product. The other significant difference of multidimensional scaling to the other techniques is that it uses dimensions. Therefore many underlying variables can be discovered and be used to explain the variance of a dependent variable (Warner, 2013).

Real-life Examples: Microsoft Corporation

Several companies use the multidimensional scaling approach to problems in business. Another example of such a company that uses multidimensional scaling is the Microsoft Corporation. In Microsoft, the customer's response means a lot to them. They are able to correct their mistakes basing on the feedback of the consumer.

Using Multidimensional Scaling in Our Organization

In our organization, the issue at hand is to know more about the business that the other organization would like to sell to our organization. We can research and learn more about their business through multidimensional technique. We will be able to identify the strength and weaknesses of the product before purchasing instead of regretting at the end.

Comparison of Products

Through multidimensional scaling approach, the product to be purchased can be compared to other products before buying. That is we will be able to know the preference of consumers to our products versus the preference of the user to similar products from other companies. If the customer's attitude towards the product becomes negative, our organization will not buy. I can advise the upper management not to purchase based on my research. If the customer's preference for the product turns out to be positive, then I would encourage the management to accept the offer of purchasing the product. The purpose of the research is to recommend the organization either to buy or ignore the business. It would be wise to know the market demand and the sales of the business before purchasing it.

Unbiased Research

The research would not be biased on the business to be acquired. The customer's response would be used to make the decisions. The research would be without the favor of the company to be bought. Through the study of the business, we can make them make necessary modifications on their business before selling to our organization. The aim being, buying a competitive business that yields more profit and has high market demand.

Conclusion

These three multivariate statistics techniques are all useful depending on what you want to know more about the business. The preference of which method to apply depends on the issue at hand. They are very helpful techniques that almost all companies use in their day to day decision making. These decisions include when there is need of modification of a particular section of their product. They will have to first get the feedback from consumers of the product to get to know their response. Studying the three multivariate statistical methods that are, factor analysis, cluster analysis, and multidimensional scaling are important in all organizations. Therefore the management for all agencies should be familiar with each technique so that they become competent in the business market.

References

Bennett, S. (2014). Introduction to multivariate techniques for social and behavioral sciences (1st ed.). [Place of publication not identified]: Palgrave Macmillan.

Sharma, S. (2008). Applied multivariate techniques (1st ed.). New York, NY [u.a.]: Wiley.

Warner, R. (2013). Applied Statistics (1st ed.). Thousand Oaks, Calif.: SAGE Publications.