BYOD Debate: The Scientific Method

Scientific Method: The BYOD Debate

The Scientific Method

The scientific method is a recipe for constructing non-arbitrary, consistent, and reliable representations of natural phenomena by collecting and analyzing relevant data in a systematic and organized manner. It forms the basis of theory-development, and generally comprises of five major steps -- i) formulation of a question about the phenomenon of interest; ii) development of hypotheses based on knowledge obtained from existing theories and literature; iii) conduction of independent experimental tests to test the formulated hypotheses; and iv) recording of data or primary observations from the experiment; v) comparison of the gathered data and hypotheses (Rochester University, n.d,.). Experimental data will either rule out or confirm the hypotheses for which the test was conducted. In case the data does not support the hypotheses, the researcher is required to repeat the experiment for confirmation; and if the two are repeatedly incompatible, they are supposed to modify the hypotheses so that they are a valid representation of nature (Rochester University, n.d.).

The scientific Method in Information Systems and Communication

In business information technology, the scientific method provides an effective framework for IT managers to make crucial decisions on, for instance, the computer model that would best suit the nature of the organization, the IT infrastructure that would help the organization realize its goals effectively, the most effective data networks for the organization, and so on. The scientific method helps managers to avoid being guided by bias and intuition in the making of crucial decisions (Zikmund, Babin, Carr & Griffin, 2012). It provides a basis for them to test their intuitions scientifically through systematically-collected data so that they are able to make choices and decisions that serve the best interests of the organization and its owners (Zikmund, Babin, Carr & Griffin, 2012). We can imagine, for instance, a situation where an IT manager has to make a choice between investing in hardware components from a large, established manufacturer such as Apple, and a smaller manufacturer such as Acer Inc. Intuition would automatically drive him/her to prefer the large manufacturer; but the scientific method would require him to put this intuition in the form of a testable hypothesis, say 'components manufactured by Apple are better than those manufactured by Acer', conduct research to identify the features inherent in both and the suitability of these features to the organizational functions, and then use the information obtained from the research to make a decision, either confirming or rejecting the hypothesis.

Based on this background, the subsequent sections of this text aim at demonstrating how the scientific method could be used in making the decision of whether or not to invest in the 'bring your own device' (BYOD) program at the workplace.

The Problem: Does the BYOD Program Increase Worker Output?

Organizations are increasingly adopting the BYOD program, where employees are allowed to use their own smartphones, tablets, and laptops for work purposes, which essentially enables them to work virtually and connect with clients from anywhere (Privacy Rights Clearinghouse, 2013). Some organizations extend company-owned devices to their employees to facilitate their virtual operations (Privacy Rights Clearinghouse, 2013). Word has it that the BYOD programs increase organizational efficiency, saving the organization the need to invest in high-cost company devices and plans, and making it possible for employees to conveniently access company files and contacts, and also respond to client needs from anywhere (Privacy Rights Clearinghouse, 2013).

However, there is concern that BYOD programs, especially in those companies that do not provide company-owned devices, would pave way for the development of the 'mine is better than yours' syndrome, and this would bring about inequality among employees, making some feel inferior and less motivated. Moreover, there is a high likelihood that the program would distract employees from their functions at the workplace and make them more preoccupied with social networking apps, games, and other forms of business-unrelated content that would now be easily accessible.

Based on this background, the author is interested in establishing whether the BYOD program is a worthy investment. In spite of the shortcomings identified earlier on, he hypothesizes that:

Hypothesis: The BYOD program increases worker output and organizational performance, and is towards that end, an investment worth considering

Hypothesis-Testing

There are two major ways through which the stated hypothesis could be measured.

Pilot Experiment: the IT manager could implement the program in a small section/part of the organization - for instance, the IT department alone, and take note of the effect. If the program yields positive outcomes, that is, if it increases worker productivity and overall departmental performance, then it could be replicated in other departments. Otherwise, the IT manager would have to adjust the hypothesis to indicate that the BYOD program was after all not a worthy investment.

Financial Report Reviews and Expert Advice: the IT manager could review the financial documents of organizations that have already undertaken the program to determine if it had any effect on performance. Similarly, he could seek out the advice of experts, who in this case could be managers whose organizations have already implemented the program. Information obtained in this way could either bear out or falsify the hypothesis being tested.

Evaluating Program Success

Trend analysis, where performance indices prior to the implementation of the program are compared with the figures reported after implementation, can be used to assess the success or failure of the program. There are three open possibilities in this case; i) that there was improved organizational performance as suggested by the hypothesis; ii) that the program had no noticeable effect on organizational performance; and iii) that the program decreased organizational performance. The specific measures that would be undertaken in this case include:

Margin Comparisons: profitability margins measure the cents per dollar gained by the organization from a single dollar spent in investment (Whittington & Delaney, 2007). Consistently rising profitability margins following the implementation of the project could be taken to symbolize the program's success. Similarly, a streak of falling profitability margins following the implementation of the project could be a sign that the project is costing a lot more than it is bringing in.

Growth: revenue is the most commonly-used index for measuring an organization's degree of growth (Whittington & Delaney, 2007). A higher growth in revenue than is usually reported is a symbol that the program was successful, yielding higher benefits than costs. Similarly, shrinking revenue figures would be interpreted as a sign of failure as they would mean that the project could be taking up more resources than it is bringing in.