Becoming a data-driven organization is a vision for several organizations. It has been frequently mentioned in the literature that data-driven organizations are likely to be more successful than organizations that mostly make decisions on gut feeling. However, few organizations make a successful shift to become data-driven, due to a number of different types of barriers. This article investigates, the initial journey to become a data-driven organization for 13 organizations. Data has been collected via documents and interviews, and then analyzed with respect to: i) how they scaled up the usage of analytics to become data-driven; ii) strategies developed; iii) barriers encountered; and iv) usage of an overall change process. The findings are that most organizations start their journey via a pilot project, take shortcuts when developing strategies, encounter previously reported top barriers, and do not use an overall change management process.

Conducting pilot projects are a common approach among organizations to test and evaluate new technology. A pilot project is often conducted to remove uncertainties from a large-scale project and should be limited in time and scope. Nowadays, several organizations are testing and evaluating artificial intelligence techniques and more advanced forms of analytics via pilot projects. Unfortunately, many organizations are experiencing problems in scaling-up the findings from pilot projects to the rest of the organization. Hence, results from pilot projects become siloed with limited business value. In this article, we present an overview of barriers for conducting and scaling-up data-driven pilot projects. Lack of senior management support is a frequently mentioned top barrier in the literature. In response to this, we present our recommendations on what type of activities can be performed, to increase the chances of getting a positive response from senior management regarding scaling-up the usage of artificial intelligence and advanced analytics within an organization.