Chapter 5: Conclusion
5.3 Limitation and Future Research
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financial companies, and validated the key factors which were summarized by this research did have an impact on value creation-chain of Big Data. For companies who are going to invest in Big Data technologies, especially for financial companies, they could expect and estimate the possible benefits more specifically. Besides,
understanding the key success factors in Big Data implementation of the selected cases will be helpful in introducing Big Data technologies, and is expected to decrease the failure chance of the investment on Big Data technologies.
5.3 Limitation and Future Research
Although this study provides many insights of Big Data implementation, there are still many limitations due to resource restraints. First, the multiple case study in this paper is conducted across only four companies; thus, there is no guarantee that the research results of this study can be apply to all companies in financial industry.
Second, the study targets of this research are all big companies, small companies may not be suitable of the findings of this study. Third, rather than interviewing the whole related employees in the targeted companies or personally participating in the real cases, the result of interviewing only one or few senior IT managers of each company may not be very complete. Fourth, this study only focuses on the financial companies in Taiwan, the research results of this study may differ from other countries. Last, this study only focuses on the financial industry, the research results of this study may differ while applying in other industries.
This research provides a general understanding about the benefits generated from Big Data and the critical factors that affect the value creation of Big Data. To verify the findings of this study, future researches could be conducted in other companies, other industries, other countries, or other methodologies.
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Appendix A: Semi-Structured Questionnaire
Interviewee: Company: Job Title:
Department: Date: Time:
Part A. Process of implementing Big Data
1. How many years has your company implemented Big Data? years 2. What kind of data is analyzed in Big Data?
3. How big is the data?
4. What fields does Big Data applied in? □CRM
□Others 5. What technology or tools are imported or used?
6. Please describe the Big Data application process.
Part B. Impact after implementing Big Data
5-strongly agree; 4-agree; 3-neutral; 2-disagree; 1-strongly disagree
1 2 3 4 5
1. Informational Benefits
1-1. Big Data enabled a faster or easier access to information for decision-making.
Example:
1-2. Big Data improved the information quality or accuracy for decision-making.
Example:
1-3. Big Data provided information in more useable formats.
Example:
1-4. Others
Example:
2. Transactional Benefits 2-1. Big Data reduced cost.
Example:
2-2. Big Data increased financial returns.
Example:
2-3. Big Data enhanced productivity or efficiency.
Example:
2-4. Big Data grew the business.
Example:
2-5. Others
Example:
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3. Strategic Benefits
3-1. Big Data improved partnerships or relationships with other companies.
Example:
3-2. Big Data enabled a faster response to changes.
Example:
3-3. Big Data improved customer relations and segmentation.
Example:
3-4. Big Data helped providing better or innovative products, services, or business models.
Example:
3-5. Big Data helped aligning analytics with business strategy.
Example:
3-6. Big Data helped creating competitive advantages.
Example:
3-7. Others
Example:
Part C. Critical Factors Are the following options an important factor in Big Data implementing process? (5-strongly agree; 4-agree; 3-neutral; 2-disagree; 1-strongly disagree)
1 2 3 4 5
1-1. Data accessibility
Example:
1-2. Data timeliness
Example:
1-3. Data quality
Example:
2. Data policy
Example:
3-1. Staff capacity
Example:
3-2. External support
Example:
4. Tools and technology
Example:
5-1. Organizational culture
Example:
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5-2. Leadership
Example:
6. Others
Example: