Decision Making: Quantity and Quality Information’ Effect

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Table of Contents

Executive Summary
Introduction: Information Management in the XXI Century
Literature Review: What Experts Have to Say
Information, Its Quantity and Quality and Decision Making Efficacy: Discussion
Conclusion: When Data Quality and Quantity Define Annual Profit Rate
Reference List

Executive Summary

Information management is important for companies in the era of information society. Entering the global market requires the ability to acquire and process a range of facts. While data quality helps make the final decision, its quantity allows embracing the existing options and draw the possible outcomes of each strategy.

Introduction: Information Management in the XXI Century

In the XXI-century information society, both quality and quantity of data are crucial for company’s operations. By retrieving verified facts, a company will be able to evaluate its chances in reaching its goals; by considering the rest of the information, which comes from less reliable sources yet in much more plentiful amounts, a company can define the current moods and the overall atmosphere of the market, as well as analyze a specific issue objectively, since even the so-called “verified” sources often provide rather one-sided assessments. The objective of the project is to define the value and function of qualitative and quantitative data in the decision making process.

Literature Review: What Experts Have to Say

The issue of data quantity and quality significance has been touched upon in a range of researches. More to the pint, a range of sources point at the fact that none of the information may contain 0% of uncertainty – no matter how verified the data may e, there will always be a threat of being mistaken (Kreye, Gohb, Newnes & Goodwinc, 2012, p. 683). Moreover, uncertainty can be split into qualitative and quantitative ones (Kreye, Gohb, Newnes & Goodwinc, 2012, p. 683). Hence, it will be more reasonable to talk about the ways that the aforementioned types of uncertainty affect businesses.

It is quite peculiar that a range of businessmen do the same mistake by ignoring the uncertainty stemming from qualitative and quantitative types of data, preferring to base their decision strictly on the information that has been confirmed. Thus, not only do they create the premises for a range of mistakes to be made in the process, but also miss a wonderful opportunity of embracing every single possibility and analyzing every possible scenario (Kreye, Gohb, Newnes & Goodwinc, 2012). Overconfident decision makers, however, often fall into another extreme (Kreye, Gohb, Newnes & Goodwinc, 2012). Hence, uncertainty in data is just as important as the verified facts, and it must be used to the benefit of the company, drawn from both qualitative and quantitative pieces of information and statistics.

Therefore, neither qualitative, nor quantitative information should be considered irrelevant in business, as the research carried out by Kreye, Gohb, Newnes and Goodwinc.has proven. Venkatraman & Huettel (2012), in their turn, develop the issue of uncertainty by considering information acquisition, processing and use from the perspective of complex economic decision making process. The significance of information and its management may not seem apparent enough until the mechanisms of the process are considered.

Therefore, it is necessary to take a closer look at the way in which a choice between several options, as well as the process of information processing in general, occurs. Seeing how the dorsomedial prefrontal cortex (dmPFC) has recently been proven to be the key support for the function of strategic control (Venkatraman & Huettel, 2012), it can be assumed that the decision making process is biologically based on considering the options that seem to be the most favorable in the long perspective: “a more parsimonious explanation for dmPFC function in complex decision-making could be that it supports aspects of decisions that are coded in relation to an underlying strategic tendency” (Venkatraman & Huettel, 2012, p. 1077). This consideration allows for assuming that people are biologically predetermined to considering the choices that seem strategically more efficient, i.e., qualitative data. Hence, quantitative information is often left overlooked, which means that a stronger emphasis should be put onto its acquisition and consideration.

Finally, the issue of information perception should be brought up. There is no need to stress the fact that the layout of the information predisposes the speed and efficiency of its acquisition. It is important to bear in mind that information comes in different forms, i.e., in visual, aural and tactile forms. As a rule, information visualization helps acquire the necessary data faster and process the information (Teets, Teegarden, & Russel, 2010).

Aimed at proving that information visualization affects its acceptance and processing, the research provides a range of peculiar results, which reveal the mechanisms of the human cognition process. Not only does visualization help avoid making mistakes in the process of passing a judgment and deciding to take a specific step, but aloes allows for defining the errors made in the previous decision making processes. With the help of the cognitive fit theory, it has been defined that the type of visualization of the data has a statistically significant effect (Teets, Teegarden, & Russel, 2010).

Information, Its Quantity and Quality and Decision Making Efficacy: Discussion

It is quite remarkable that each of the sources above provides a biological explanation of the decision making process. On the one hand, there are reasons to suggest that the steps, which people make, are predetermined by the use of their logical thinking; on the other hand, the three articles in question prove that the choices made in the course of a decision making process are triggered by a chain of chemical reactions in one’s brain.

With the obvious positive effects on the data perception in mind, one must admit that quantitative data is accepted much faster and digested considerably easier than the qualitative on. Indeed, it is comparatively hard to provide a visual interpretation of the results of a qualitative analysis, in contrast to the outcomes of the quantitative one (Teets, Teegarden, & Russel, 2010). Therefore, it can be assumed that quantitative information plays a pivotal role in the process of one’s decision making. In addition, the fact that the human brain is more apt to receiving numerical data than it is for using the qualitative information as the basis for making a particular choice is not to be ignored.

Still, it is worth mentioning that the qualitative information also contributes to the process of making a choice. While the quantitative data seems to affect one on a subconscious level, the availability of the qualitative one allows for making a conscious step and taking a well thought out step, with both the possible positive and negative outcomes in mind. Therefore, it can be concluded that the quantitative data and its visualization play the defining role in the decision making process, whereas the qualitative information allows for a logical justification of the stp to be taken.

Conclusion: When Data Quality and Quantity Define Annual Profit Rate

Though both types of information are equally important for the process of decision making and the choice of the right option, the significance of information quantity is often overlooked, whereas its quality is traditionally considered the top priority. However, medical research has demonstrated that the amount of data often predetermines the decision to be made.

Reference List

Kreye, M.E., Gohb, Y.M., Newnes, L.B., & Goodwinc, P. (2012). Approaches to displaying information to assist decisions under uncertainty. Omega, 40(6), 682–692.

Teets, J. M., Teegarden, D. P., & Russel, R. S. (2010). Using cognitive fit theory to evaluate the effectiveness of information visualizations: An example using quality assurance data. IEEE Transactions on Visualization and Computer Graphics, 16(5), 641–653.

Venkatraman, V. & Huettel, S. (2012). Strategic control in decision-making under uncertainty. European Journal of Neuroscience, 35(7), 1075–1082.

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