SELECTING THE BEST SOURCING OPTION FOR A COMPANY OFFERING BUSINESS INTELLIGENCE AS A SERVICE : Action Research in Procurement Analytics and IS Outsourcing - Gratschev, Saara (My University, 2021)
Data warehousing and extract-transform-load-analyze process are an integral part of the Business Intelligence as a Service organization’s service offering. However, poor quality of incoming data and client-specific customization coupled with high-growth pose scalability challenges to the case organization’s operating model. Moreover, data transformation tasks cannot be fully automated, leading the organization to need new data management resources continuously. When repetitive human involvement requiring data transformation tasks are conducted in high-cost countries, the production costs increase in relation to the new clients taken care of on a continuous basis. This dissertation focuses on understanding the optimal operating model for executing the repetitive data transformation tasks cost-efficiently without scarifying the organization's superior performance. This qualitative action research follows the IS outsourcing stage model framework and comprises several sub-steps to meet the research aims. The research results demonstrate the root cause for the scalability issues, define the evaluation criteria, and describe the project scope. Consequently, the results evaluate the potential benefits and risks related to current domestic in-house production, outsourcing, and in-sourcing scenarios. Finally, the research arrives at the operating model recommendation. The findings underline that the data transformation tasks are an essential part of procurement analytics BIaaS organization’s service provision, and therefore they should be kept in-house. Lower cost location allows additional investments in data management capabilities to strengthen the existing core competencies, improve the data transformation output quality, and enhance the overall service level. The results suggest that the case organization should transfer its repetitive data transformation tasks to nearshore or offshore subsidiary to minimize the operating costs and maximize the qualitative benefits.
Keywords: Data Management, Procurement Analytics, ETL, Data Transformation, BIaaS, IS Outsourcing, IS Insourcing