Decision-Making Effectiveness: Information Quality and Quantity

Executive Summary

In the past, managers were looking for any information that can support them in decision-making. However, today the volume of information that managers receive to utilize in decision-making is large, which creates an information overload. While data quality helps make the final decision, its quantity allows decision-makers to embrace the existing options and draw the possible outcomes of each strategy. In this paper, we will study two significant factors that influence the decision-making process which are the quantity and quality of information. We will compare these two factors to find out which one is more important in enhancing decision-making effectiveness than the other.

Introduction to the Issue

Not very long ago, information was very limited. People relied entirely on books and other resources in libraries for information. By contrast, in modern times, information is almost endless. Today we can easily surf the internet and find hundreds of websites and articles providing ample information to users. The only problem is finding quality information for use. With the abundance of information, quality of information has become an issue of concern nowadays. Quality information enhances decision-making effectiveness.

Decision-making is an important cognitive process in our personal and professional lives. Different decisions, whether small or major, have an important effect on the entire organization. Decision-making refers to the process of analyzing a range of alternatives before choosing the best one. To make a good decision, we must evaluate all the advantages and disadvantages of each choice, and consider all the available alternatives. In this regard, effective decision-making entails the selection of a choice that would help the company to reach its goals. Different factors can affect the decision making process, one of these important factors is the quantity and quality of information.

Decision-making relies on empirical information or data. In this view, a stronger information base would result in quality decisions. In the 21st Century information era, both quality and quantity of data are crucial for the company’s operations. By retrieving and analyzing data, a company can evaluate its chances of reaching its goals.

Moreover, by considering the rest of the information, which comes from less reliable sources, yet in much more plentiful amounts (quantity), a company can predict market conditions and develop strategies for a successful entry. In our technological era, we receive enormous amounts of data. This raises the question; is it the quality or quantity of information that is important in decision-making? In this research, we will define information quality, explain its five dimensions of qualitative data, and decide what is more important between the data quality and quantity in the decision-making process.

Objective of the Project

The main objective of this project is to analyze two main factors that affect the effectiveness of the decision-making process: the quantity and quality of information or data. It will evaluate the value and function of quantitative and qualitative data in the decision-making process. The success of company’s competitive strategies is largely dependent on the quality of information and organization relies on to make decisions. Information quality or quantity affect decision-making differently. Therefore, the other aim of this project is to rank these two factors in the order of their relative importance in decision-making.

Literature Review

The ongoing debate and the dilemma associated with the quality vs. quantity of information with regards to effective decision-making has inspired countless studies since the inception of managerial sciences (Anderson, Sweeney, and Williams, 2000). The objective has always been to assimilate the relativity of the two dimensions of information and to find the perfect mix of both factors that can help in decision-making.

It is clear that on a strategic level, the information provided has to have relativity of both the dimensions. The absolution of either one of the dimensions of reported information can induce an ineffective and bad decision-making process (Nooraie, 2012). The key, therefore, is to find a diversified and often customized mix of both dimensions of information provided to facilitate effective decision-making. It not only concerns the outcome of the decisions themselves, but also the decision-making process.

To interpret data, different approaches are used to transform the information into a meaningful form. The interpretation technique depends upon the nature of the information provided, whether it is focused more upon the qualitative dimension or the quantitative dimension (Ganswein, 2011). Thus, the approach taken to draw inferences from the data depends upon two variables, the qualitative and quantitative dimensions of the information provided, and the demands of the situation under whose influence the decision must be made.

To elaborate further, each situation would then need a certain mix of the qualitative or quantitative elements to the information given. Hence, there is no universal formula or rule to define the quantitative and qualitative aspects of the information that should be gathered for interpretation. The rational thing to do is to provide objective-driven mix of the dimensions of the information rather than the other way around.

The quantity against quality of information dilemma is not only related to methodology of information processing and subsequent decision-making. It also incorporates the psychological aspect, which is crucial when consumers are concerned. To elaborate more, qualitative information, if not transmitted with intensity or abundance in quantity, may lead to the perception of the information as non-vital and non-effective (Slone, 2007).

On the other hand, the information may be perceived as important while it may have no qualitative importance and substance when it is present on a quantitative abundance. Therefore, the psychological aspect makes things complex regarding the direct understanding of the dilemma and debate associated with the qualitative versus quantitative dimensions of the information to be processed. Organizations base their strategies on empirical data that encompass both qualitative and quantitative aspects of information.

The effectiveness of an organization’s strategy defines its success or failure in its industry. According to Slone (2007), “the reason why firms succeed or fail is perhaps the central question in strategy”. The direction of an organization can be the result of the collective effect of the decisions made by its management over time. In other words, the decisions’ quality is mirrored toward the organization’s bottom line.

For that reason, people, over the past few years, have sought to understand the relationship between information and decision-making. This empirical study proves that “quality of information has a systematically quantifiable relationship to the quality of decisions as reflected in organizational outcomes” (Slone, 2007).

Gorla, Somers, and Wong (2010) attribute the “informational deficiency of managers” to the availability of large amounts of “irrelevant information”, which makes objective decision-making problematic. In strategy formulation, making a right or wrong decision can be the line between life and death. In organizations, decision-making is a crucial task, especially when the decisions involve new changes or strategies. Decisions are often pegged on the empirical data or information provided.

However, in our time, people are bombarded with a huge amount of information that might be relevant or not. Even with valid information, huge amount of information can present too much ‘noise’ in the decision-making process (Sasaki, Becker, Janssen, and Neel, 2011). In other words, information quality directly or indirectly affects decision-making. For example, incorrect information generated by a faulty program or miscalculated data, will most likely affect the quality of the decision and ultimately lead to undesired results (Gorla, Somers, and Wong 2010)

Gorla, Somers, and Wong (2010) define information quality as the superiority of outputs generated from particular data or information, which can be presented in different forms such as a paper report, a computer generated result or a human decision. Information quality has five dimensions: currency, completeness, consistency, accuracy, and format. For currency, it means that the information is provided in its most recent version.

On the other hand, completeness describes the property of information to cover all the relevant aspects of the issue at hand. With regard to consistency, the different facts or information groups should have a logical coherence such that there is no conflict between them. Accuracy refers to the correctness and exactness of the information corresponding to the issue at hand. Finally, format describes the presentation of such information to the users (Gorla, Somers, andWong 2010).

Depending on each situation, quality could be more important than quantity, vice versa, or both equally important. For example, Canefhem and Campenhout in their 2010 study, found a positive relationship between financial institutions’ loan rates and the information provided by small and mid-size enterprises (SMEs) when they are applying for leverage. The study states that enterprises that give high quality and large quantity information stand a better chance of receiving ‘leverage’ at a cheaper rate than those that give provide less amounts of inferior data.

The issue of data quantity and quality and its significance has been examined in a wide range of researches. More specifically, a range of sources point at the fact that none of the information may contain 0% uncertainty, i.e., “no matter how verified the data may be, there will always be a threat of being mistaken” (Kreye, Gohb, Newnes, and Goodwinc, 2012, p. 683). Moreover, uncertainty can be divided into qualitative and quantitative dimensions (Kreye, Gohb, Newnes and 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 many business executives make the same mistake by ignoring the uncertainty stemming from qualitative and quantitative types of data, preferring to base their decision solely on the information that has been confirmed. Thus, not only do they create the premises for committing a range of mistakes during the decision-making process, but also miss a wonderful opportunity of embracing every single possibility and analyzing all possible scenarios (Kreye, Gohb, Newnes and Goodwinc, 2012).

Overconfident decision makers, however, often fall into another extreme (Kreye, Gohb, Newnes and Goodwinc, 2012). Hence, uncertainty in data is just as important as the verified facts and thus, the information drawn from both qualitative and quantitative sources and inferential statistics must be used for the benefit of the company.

Therefore, as the research by Kreye, Gohb, Newnes, and Goodwinc (2012) has proven, neither qualitative nor quantitative information should be considered irrelevant in business. On their part, Venkatraman and Huettel (2012) develop the issue of uncertainty by considering information acquisition, processing, and use from the perspective of complex economic decision-making situations. 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 the choice between several options as well as how 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 and Huettel, 2012), it can be assumed that the decision making process is biological. It is based on the assessment of the option that seems to be the most favorable in the long perspective.

Venkatraman and Huettel (2012) state that “a more parsimonious explanation for the dmPFC function in complex decision-making could be that it supports certain aspects of decisions that are coded in relation to an underlying strategic tendency” (p. 1077). This consideration allows for the assumption that people are biologically predetermined to consider the choices that seem more efficient strategically, i.e., qualitative data. Hence, quantitative information is often left overlooked, which means that a stronger emphasis should be put on its acquisition and consideration.

Finally, the issue of information perception by decision-makers should be examined. It is worthwhile stressing the fact that the layout of the information predisposes the speed and efficiency of its acquisition. Aural, visual, and tactile are the three types of information that a person can receive. As a rule, information visualization helps acquire and process the necessary data or information in a much faster way (Teets, Teegarden, and Russel, 2010).

The aim of the research by Teets, Teegarden and Russel (2010) was to prove that information visualization affects its acceptance and processing. The study yielded a range of peculiar results that revealed the actual mechanisms of the human cognition process. Not only does visualization help people avoid making mistakes in the process of passing a judgment and deciding to take a specific step, but it also allows them to define 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 on decision-making (Teets, Teegarden, and Russel, 2010).

Personal Stance and Discussion

We believe that quality is preferred over quantity in all cases. For a decision to be effective, it is crucial that the right type of information is made available for the decision-making process to be effective. The effectiveness of a decision depends on the quality of information, not its quantity. There is no doubt that informational quality is necessary for a decision to be effective. But then again, some people are more comfortable with the quantity of data, as it puts them on a safer side; the abundance of information enhances the managers’ understanding of the situation.

If you make a decision based on quality information, you will be seen as someone who is thought provoking and a great leader. That is what most of us desire when making a decision. We actually want our decision to be effective so that everyone not only considers our decision, but also acknowledges us for our hard work and persistence. The only drawback when you focus on quality is that your frequency of decision-making will be low as finding quality information is time-consuming and analyzing it is draining. Nevertheless, we believe that if the focus is on quality information, the probability of the decision being effective is much higher than when the focus is on quantity.

In our view, effective decision-making is an important role played by the management. To have effective decision-making that has positive impact on the organization, the benefits of the decision should be evaluated versus its damages. The quantity and quality of information can be used as factors to support the decision. In the past, information was a scarce resource and finding data was so difficult.

However, today with technology and development, too much information can be found, which raises concerns over information quality. Therefore, we should look for quality of information over the amount of information or quantity. For effective decisions, it is vital to consider the value of information or quality rather than its quantity. It requires more efforts to check the quality of information because our decision will be based on available data or evidence.

Relevance, specificity, accuracy, reliability, and timeliness information are important things in evaluating the quality of information. Often, decisions that are based on quality information help organizations achieve its objectives much faster compared to those founded on quantity. The only concern with information quality is the required time to find valuable data to use in making a decision.

Therefore, in some cases, managers make decisions based on the available amount of information due to time limitations. In this regard, we can put the analysis in two dimensions: the quantity contributes to correct decision-making and quality of information enhances the effectiveness of the decision. But then again, as a personal stance and for the sake of time (time management being crucial in higher-level managerial jobs), we would prefer quality focused information.

As already stated, quality and quantity are the two key attributes of information or data. The amount of information that a decision needs should be determined, as it is important in finding a solution that meets the objective of the decision. The value of data is another major factor to support decision-making because information is a limited resource that takes much effort to get.

The quality of information can contribute to making the right choice and help a person understand the real-world relationships. The content of information can also help in decision-making. There are two ways of defining the information content: (1) the gaining method of scanning and (2) focused search (Ganswein, 2011). The gaining method of scanning is oriented towards problem recognition, whereas the focused search aims at resolving the issue at hand.

The quality of information is considered more significant in making strategic decisions than its quantity. The concept of quality can be identified as the level to which organizations’ decisions reflect precise understanding of the fundamental relationships that relate strategic choices with its outcomes (Forbes, 2007). The availability and quality characteristics of information sources are vital qualities of the information used in decision-making. Sometimes, decision makers cannot control the information sources, including quantity and quality of data or even its availability and thus, have to use what is available to them (Ganswein, 2011).

The quality of data sources is related to the information they provide. Quality sources must exhibit relevance, specificity, accuracy, reliability, and timeliness of information provided. Information is considered effective if it supports the formulation of good decisions. Personal information from the management board, subordinate managers, employees, customers, or related business organizations vary in terms of quality depending on its relevance and reliability. Impersonal internal reports, studies, and memos are considered high quality information sources. In contrast, all external impersonal sources such as newspapers, journals, or government publications are categorized as low quality sources due to their limited reliability and timeliness.

Moreover, the information richness has a major impact on the way data sources are classified. For example, personal sources usually provide information with a higher richness than impersonal sources. There are two modules dealing with information, the provider, and the user. It is important to distinguish between the information provider’s ability to provide the correct data from the user’s ability to use it effectively. There are different designs of effective information use, which depend on the relationship between the data received and the thinking approach of the user (Hodgkinson and Starbuck, 2008).

Although the quality of data depends on trusted sources, it also relies on the period the gathering the information is gathered. Nooraie (2012) observed that when there is time pressure, the decision made does not always meet its objectives. The researcher further found that the presence of time pressure is negatively related to the quality of decision-making (Nooraie, 2012).

With the obvious positive effects on the data perception in the mind, one must admit that quantitative data is easier to understand than the qualitative one. Indeed, it is comparatively hard to provide a visual interpretation of qualitative analysis results compared to the outcomes of the quantitative one (Teets, Teegarden, and 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.

Nevertheless, it is worth mentioning that 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. 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 step to be taken.

Conclusion

To conclude, both the quantity and quality of information affect decision-making effectiveness. Both types of information are equally important for the process of decision-making. In our view, effective decisions depend on the quality of information, not its quantity. Therefore, managers and leaders should consider quality of information over its quantity in making decisions.

References

Anderson, David R, Sweeney, Dennis J., and Williams, Thomas A., “An introduction to management science”, 13th Edition, 2000, Cincinnati, Ohio: South-Western College Pub.

Caneghem, T., and Campenhout, G., “Quantity and quality of information and SME financial structure”, Small Business Economics, 2012, Vol. 3, Iss. 1, 341-358.

Forbes, D. P., “Reconsidering the Strategic Implications of Decision Comprehensiveness”, Academy of Management Review, 2007, Vol. 32, Iss. 2, pp. 361-376.

Ganswein, Wolfgang., “Effectiveness of Information Use for Strategic Decision Making”, 11th Edition, 2011, New York: Wiesbaden, Gabler.

Gorla, N., Somers, T., and Wong, B., “Organizational impact of system quality, information quality, and service quality”, Journal of Strategic Information Systems, 2010, Vol. 12, Iss. 2, 207-228.

Hodgkinson, Gerard P., and Starbuck, William H., “Organizational Decision Making: Mapping Terrains on Different Planets”, 2nd Edition, 2008, London: Oxford Press.

Kreye, M.E., Gohb, Y.M., Newnes, L.B., and Goodwinc, P., “Approaches to displaying information to assist decisions under uncertainty”, Omega, 2012, Vol. 40, Iss. 6, 682–692.

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Sasaki, T., Becker, V., Janssen, M., and Neel, R., “Does greater product information actually inform consumer decisions? The relationship between product information quantity and diversity of consumer decisions”, Journal of Economic Psychology, 2011, Vol. 4, Iss. 6, 391-398.

Slone, John P., “Information Quality Strategy: an Empirical Investigation of the Relationship between Information Quality Improvements and Organizational outcomes”, 1st Edition, 2007, New York: Capella University.

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

Venkatraman, V., and Huettel, S., “Strategic control in decision-making under uncertainty”, European Journal of Neuroscience, 2012, Vol. 35, Iss. 7, 1075–1082.