Continued user adoption of self-service data analytics tools : In software product management

Abstract

The amount of data has rapidly increased due to the evolution of big data. Data is utilized nowadays in many places on both strategic and operational levels as it can enable competitive advantage. The rapidly increasing data utilization creates a challenge with traditional data analytics solutions as the need for data analytics reports is several times the amount it used to be. Modern data analytics solutions are needed to widely utilize data analytics on both strategic and operational levels to gain the most competitive advantage from data analytics. Self-service type solutions for data analytics have been emerging to respond to the new needs for data analytics. The self-service type data analytics solutions include information technology-based data analytics tools. As with any other new information technology-based tool, user adoption is a critical success factor in the implementation of new data analytics tools. Especially, continued user adoption has a critical role in data analytics solution implementations to gain competitive advantage through data analytics over the long term. On the other hand, continued user adoption of information technology-based tools is a complex thing that might even lead to complete failure in the implementation of self-service data analytics solutions.

This research studies continued user adoption of a self-service data analytics solution from the end user-facing tool perspective. The goal of this research is to explain the critical success factors in continued user adoption of self-service data analytics tools. This research is limited to focusing only on the user adoption part of the information technology-based tool implementation, and the focus is on the continued user adoption. The research consists of two parts: literature review and empirical research. The problem is first approached on general-level information technology user adoption which is researched from existing literature. To better understand and explain user adoption in the context of self-service data analytics tools, empirical research is done in an organization where the user adoption process for self-service data analytics tools is ongoing. The empirical research is done as a case study with semi-structured interviews in the case organization. The case used in this research is the implementation of a new self-service data analytics solution in a software product management organization. The case company is a Finnish business-to-business growth software company that develops a knowledge work automation platform.

The findings of this research show that the user adoption of self-service data analytics tools follows a similar pattern to most information technology. Also, specific factors for self-service data analytics tools’ continued user adoption are identified. The identified key success factors for self-service data analytics tools are the availability of relevant data, user autonomy, and user’s context awareness. Availability of relevant data is identified as a prerequisite for continued user adoption of self-service data analytics tools as lack of it hinders users from confirming their expectations. User autonomy and user’s context awareness are identified to make self-service data analytics tools more useful, having a positive impact on continued user adoption. On the level of the case organization, the findings of this research are that the value potential of the new self-service data analytics tool has been identified by users, and the users have partially adopted the new tool due to that. On the other hand, the continued adoption is still ongoing as there are still unconfirmed expectations towards the self-service data analytics tool due to a lack of data for the actual role-related task usage.