Methodology

  • Category:
    Management
  • Document type:
    Research Paper
  • Level:
    Masters
  • Page:
    3
  • Words:
    1910

5RESEARCH METHODOLOGY

Methodology Essay

Name of Institute

Qualitative Study on Data Analytics in organizations

Abstract

Data analytics in organizations entail the systematic computation of data in organizations for the sake of decision making. The determination of the outcome of data analytics in developed and developing nations is based on models of various sectors. Highly aggregated data is another factor that is a determinant of the results of data analytics. This paper offers the methodology used to obtain insights obtained from individual as well as group data around aggregate statistics.

Theoretical background

In the contemporary world, many companies have been organized and are governed around analytical competences and responsibilities. Since most multinational companies as well as national companies operate branches in different parts, the system of data at individual branches is linked to a central system from where decisions are made. Different companies have their own unique ways of administrating analytics. However, certain key elements are considered by all companies in developing their analytics. This include: people, data, tools and intent. Consequently, they give the scope of analytics in any organization. Key interests are embedded on the technological aspect rather that strategic aspects of individual organizations.

To diversify the central role of analytics in any organization, it is good to be objective. The in focus integrates the current situation and the data from the internal data sources. Governance and communication also has to be given so special a treatment as it is they form the major attributes to corporate performance. We had an international benchmark for American companies. Consequently, semi structured interview questions were used to make a qualitative study of data analytics of various organizations. The data obtained was primary, secondary or tertiary (Kumar 2014). Based on such data, conclusions can be drawn and recommendations made.

The questionnaire

The questionnaire used had semi- structured questions. It was categorized into six different parts so as to enhance the data collection process. Firstly, opening and background questions were administered. This was to aid in knowing at least some personal information about the interviewee. It aimed at finding out their role in the organization. It was also important to get a background on the cultural aspect of their company, their data engagement period and whether they had training regarding analytics or not.

Secondly, questions were structured about analytics in the company. This would assist in giving a general history about analytics in that company. It would illustrate about the value of analytics to the company employees. It would also assist in getting a supposedly true perception of the employees on the analytics of that company.

Thirdly, data about high level strategy had their own structured questions. It is very vital to know how the overall business strategies of a company are supplemented by their analytics strategy. Further, it is fundamental to learn if a business has a particular strategy regarding their analytics and its relevance to the business.

Next, it was vital to find out the view of the organization in establishing an internal analytics system or outsourcing. Again, does the organization have somebody who is in charge of analytics or not. It was also good to know how the organization allocates its resources towards analytics. This part majorly dealt with the organizational management of analytics.

Moreover, questions about a project on analytics were structured.in case one has a new data analytics project, how would they go about it. How can a successful data analysis project be managed, and what defines success in this case. It was also necessary to know if the employees have been involved in an unsuccessful data analytics project.

Finally, it was important to know about the organizational analytics improvement. How has analytics been improved in the organization over time? What are the suggested steps that can be taken to improve the current situation of analytics? These are some fundamental questions that would boost future improvements I organizational analytics.

The interviews

The interviews were semi structured. This is a data collection tool that is conducted I a fairly open framework that allows for a two- way communication (Kumar 2014). It is very important because it is less intrusive to the interviewees. Furthermore, it confirms what is already known even though it also establishes an opportunity for learning. More importantly, when individuals are interviewed in this manner, they are likely to be more open and frank to sensitive issues (Kumar 2014). Thereby, this was a good tool in performing the interviews. Some of the probing questions to which the respondents were subjected to included; ‘How do you perceive the importance of analytics in your company?’, ‘What role in analytics do you play in your department’ and ‘What do you think are the future trends with regards to analytics?’. These questions among others enhanced the understanding of the role of analytics in the various companies.

Eight different companies were interviewed. The interview time amounted to twenty hours. For the success of the interviews, five different industries were considered. This assisted in understanding the penetration, utilization and impact of the analytics in the organizations. After the interviews, a hundred pages of transcripts were obtained. They contained information relating to people’s skills, maturity of analytics, roles and competences, collection and usage of data, and the challenges that the analytics field encounter.

The methodology

This part describes the methodology used in the research to achieve the goals of research question in the context described earlier. The study originated from a need to describe and model the existing organisational structures around data analytics in multinational companies. The broad and novel subject caused many challenges in choosing the right methodology and the choices are described in this section.

The Sample

The companies and people interviewed were chosen by selecting companies to fit on following criteria: large multinational companies who have operations in Finland. In total 8 companies out of 10 contacted participated in to the study. One of the companies stated they do not have data analytics in any organised form and therefore they could not participate in study. From these 8 companies the interviews were planned to be from three different point-of-views: 1) one to two people executing the data analytic projects, 2) one to two people modelling the data analytic organisations, and 3) 1 – 2 decision-makers, who are using the insight gathered from data analytics. The sample is illustrated in the Table 1below.
Methodology

Overview of companies interviewed — 1Table

The Interviews

The semi-structured interviews

The interviews were semi-structured. This is a data collection tool that is conducted, a fairly open framework that allows for a two-way communication (Kumar, 2014). It is very important because it is less intrusive to the interviewees. This was achieved by asking probing questions to the interviewees. Examples of the questions asked included: ‘How do you perceive your maturity in analytics? What are your feelings about data analytics in your company?’ This was meant to confirm it what is already known to the employees. It also established an opportunity for learning. More importantly, when individuals are interviewed in this manner, they are likely to be more open and frank to sensitive issues (Kumar, 2014). Thereby, this was a good tool in performing the interviews.
Some of the probing questions to which the respondents were subjected to included; ‘How do you perceive the importance of analytics in your company?’, ‘What role in analytics do you play in your department’ and ‘What do you think are the future trends with regards to analytics?’. These questions among others enhanced the understanding of the role of analytics in the various companies.

Because the subject of research, internal data analytics, is understood in many different ways in different organisations, we wanted to ensure the right context by conducting semi-structured interviews with the participants in the study. There were also some unknown aspects under the chosen topics we wanted to find out, so the semi-structured method was used because we wanted to ensure all the implicit aspects of the subject, and ensure that all the point-of-views are covered.

The interviews were following a questionnaire, which had eight different parts: background information to put the context around the person and understand his or her point-of-view; company information to understand the company drivers affecting the analytics, including general history and the value of analytics to the company; high-level strategy to cover the strategy drivers, and to understand if the company has any analytics strategy and if it is included in the business strategy; the organisational part to help model the position of the analytics in the organisation: people in charge, the allocation and use of resources and the roles involved; people section to understand the knowledge spread and individuals working in analytics; communication section to cover the interactions between the different parties and how insights are delivered; a project part to find out successes and pain points; and an improvements part to find out further the possible challenges analytics are facing in the companies.

As a result, semi-structured interview questions were used to make a qualitative study of data analytics of various organizations. The data obtained was primary data, and no secondary or tertiary data was used (Kumar 2014). Based on such data, analysis can be made and conclusions drawn.

Data Analysis

Simultaneously with the interviews, the framework for analysis was constructed. The key findings were categorized in 24 different characteristics, further called dimensions. Of these dimensions, six had in total 25 sub-dimensions. The interviews were analysed then by putting the key findings into a Spreadsheet and looking at the big picture with the help of this structure. Nevertheless, the Spreadsheet revealed that no clear conclusions could be derived from the linkages between the dimensions and variables inside them, and therefore the case study method was chosen.

Case Study

Case study is regarded as a form of qualitative research methodology mostly used by researchers in various research fields. It is an approach that employs analysis of a desired phenomenon in its real context. Case study therefore has great importance with regards to integrity of the findings as well as quality of data obtained.

The case study method was employed because there were only seventeen individual interviews. From a statistics point of view, the sample size is too small to identify patterns of how companies organize around analytics. Secondly, the companies interviewed are from different industries and are thus regarding analytics in extremely different. This is attributed to the advantage of an existing benchmark for American companies. Therefore, a straight comparison between the companies is impossible. The case study method addresses those issues, by allowing for a comparison between and within the companies. It also allows for the measurement of one dimension at a time using several company examples.

Empirical study involves conducting research based on observations, case studies and some proven facts (Kumar 2014). In this case, empirical study was used since the topic covered was novel and complex, and there are no clear causalities, i.e. organisation to end up having a certain type of organizational structure might be because of many different dimensions.

Conclusion

It can be concluded that the methodology used was effective. It explains steps taken to study the qualitative aspect of data analytics in organizations. It uses large global companies for the study. It also examines roles at different levels. The results that come from the research can thereby be applied for decision making purposes.

Reference

Kumar, R., 2014. Research Methodology: A Step- by- step Guide for Beginners. California: SAGE Publications Ltd.