Silo Mentality in Organizations: A Mixed Methods Study

Introduction and Research Objectives

The guiding proposition of this study is that team dysfunction enables the creation of silos, which occur when teams do not share information with other teams within the same company. The primary objective of this research is to help leadership groups better understand subculture dysfunction in organizations that depend upon a collaborative communication model to achieve strategic results. A secondary objective is to help corporations understand why some leaders are unable or unwilling to implement silo-eradication solutions. To achieve these objectives, the following assumptions and research methods were employed.

Epistemic, Paradigmatic, and Theoretic Assumptions

The epistemic assumptions for this study include the notion that the lived experiences of individuals who have contributed to organizational silos or silo mindsets — as well as those who have sought to break them down — can be known through appropriate research methods. A further epistemic assumption is that people's views about the proprietary nature of "turf" in the workplace can change over time as they gain insight into their role and its importance to the larger organization. This assumption is congruent with the guidance provided by Hofer and Pintrich (2009), who advise that "people's epistemic assumptions change over time in a developmental fashion from early adolescence to adulthood" (p. 38).

The paradigmatic assumptions for this study include the view that people naturally resist change and will struggle to maintain the status quo as long as it serves their best interests. The theoretic assumptions applicable to this study include the perspective that people tend to act in their own best interests in ways that exacerbate the adverse effects of organizational silos, making them even more resistant to change.

Discussion of Methodology

Several research methodologies are available to social science researchers, broadly divided into qualitative and quantitative strategies. Although qualitative and quantitative methodologies share some commonalities with respect to overall objectives, there are fundamental differences that must be taken into account when determining which approach is best suited for a given research purpose, as shown in Table 1 below.

Similarities:

Both qualitative and quantitative approaches involve analysis through inference — that is, both reach conclusions based on evidence. Both involve a systematic process, both involve comparison (either internally or with related evidence from elsewhere), and both strive to avoid errors, false conclusions, and misleading inferences while seeking valid descriptions and explanations.

Differences:

Quantitative analysis is highly standardized and varies little between projects, whereas qualitative analysis encompasses many possible approaches. Quantitative analysis takes place at the end of data collection; qualitative analysis takes place throughout data collection. Quantitative analysis tends to test hypotheses through the manipulation of numbers representing facts, while qualitative analysis blends empirical evidence and abstract concepts in the form of words to explain or illustrate a theory or interpretation. Qualitative analysis is less abstract and does not assume that real life can be measured by numbers.

Source: Adapted from Neuman, 2009

Based on the respective attributes of each research strategy, it was determined that both qualitative and quantitative methods should be used to develop informed and timely answers to the study's guiding research questions. Accordingly, the study uses a mixed methods research design to inductively understand the issues examined. This design includes one-on-one and focus group narrative interviews; survey questionnaires using a Likert scale (1–5) to gather data on beliefs and values about team collaboration; and direct observation of focus group participant behaviors.

Although social science researchers have a number of different research methodologies available to them, a growing body of evidence confirms that the use of a mixed methods research design provides more comprehensive insights compared to the use of either qualitative or quantitative methods alone (Neuman, 2009). The selection of a mixed methods design was based on its ability to collect primary qualitative and quantitative data, thereby enhancing the robustness and trustworthiness of the findings that emerge from data analysis.

According to Creswell (2008), mixed methods research strategies are typically used when the researcher wants to:

· Compare results from quantitative and qualitative research;
· Use qualitative research to help explain quantitative findings;
· Explore using qualitative research and then generalize findings to a large population using quantitative research;
· Develop an instrument because none are available or useful; and
· Augment an experiment with qualitative data (p. 37).

Moreover, Creswell (2008) identifies several reasons for selecting a mixed methods design over a single-approach strategy:

· The insufficient argument — either quantitative or qualitative may be insufficient by itself;
· The multiple angles argument — quantitative and qualitative approaches provide different "pictures" of a phenomenon;
· The more-evidence-the-better argument — combined methods provide more evidence;
· The community of practice argument — mixed methods may be the preferred approach within a scholarly community;
· The eager-to-learn argument — it represents the latest methodology; and
· The "it's intuitive" argument — it mirrors "real life" (p. 38).

The procedures used in applying the mixed methods strategy will be administered in a concurrent fashion; that is, data emerging from both primary and secondary sources will be synthesized and interpreted simultaneously as the research process progresses (Creswell, 2008).