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The contemporary business environment has been occupied with different approaches and methods for solving problems. The technological boom has led to information explosion, and organizations are facing the challenge of ever-increasing volumes of data in their data stores. In the past, it has been difficult for executives to have information about the performance of their businesses and its environment gathered together, say in an open book (Bazerman, Loewenstein and Moore). However, the trend has changed with the invention of new methods of analyzing data. Through quantitative techniques, business statistics and the ever-increasing information can easily be analyzed and packaged together in forms easily accessible to the managers. The executives are thus in a position to have critical data compiled and scrutinized in a way that it can easily be understood for informed decision-making. Every organization should thus embrace the concept as it forms such a critical factor for continued growth and an assurance for success.

With the quantitative models for analyzing organizational data, business decision making has taken a new path. Executives are only provided with only what is most relevant for their execution of duties. They thus no longer rely on the traditional formats where they used to be provided with a series of filed data, which could cost them a fortune while analyzing. The importance of the quantitative approach, facilitated with the aid of technological facilities, is justifiable under such a scenario.

To improve the quality of services and products among organizations, as well as increasing the workplace efficiency and promote easy assessment of the organizational growth, quantitative reasoning is crucial. The reasoning is a product of quantitatively analyzing organizational data and information (Emperitas). As such, quantitative data can be argued as an asset in uncovering the predictable patterns leveraged in the business decision-making process.

Quantitative data reflects the most accurate information to be used for future extrapolations of business trends. As such, the data is very vital in organizational decisions that will aid in shaping businesses for future success. The accuracy with quantitative data envisages uniformity in questioning customers, standardization of responses, having typical customers, and analyzing business data statistically using innovative data analysis tools. The information attained from the analysis is thus vital for individuals planning to put up new ventures, building inventories that meet increasing demands, or those offering intuitive rewards to their customers while minimizing the costs. As such, the value of quantitative data in an organization cannot be neglected.

Finally, quantitative data can be an element of importance in addressing organizational accountability of members. It can been relied upon in uncovering cases of financial indignities within organizations and corporate entities. The signing into law of the Sarbanes-Oxley Act, which addressed corporate accountability, was an example of avenues where the value of quantitative data becomes resourceful (Etzioni). The Act represented federal enactments focusing on the culmination of financial scandals among accountants, thus promoting accountability and financial honesty in organizations. As such, the value of quantitative data in streamlining organizational management is portrayed.

Among other means through which quantitative data and methods can be used in solving organizational problems, the above highlighted facts form the basis. It is thus critical for any organization anticipating growth to embrace the use of quantitative data and methods to avoid throwing good money after bad.


Bazerman, MH, G Loewenstein, and DA Moore. ‘Why Good Accountants Do Bad Audits’. Harv Bus Rev. 80.11 (2002): 96-102. Print.

Emperitas, N. ‘Problem Solving – Quantitative Research – Emperitas’. N.p., 2015. Web. 25 Mar. 2015.

Etzioni, Amitai. ‘Humble Decision-Making Theory’. Public Management Review 16.5 (2014): 611-619. Web.




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