Scaling‐Up Data‐Driven Pilot Projects

Abstract

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.

Understanding data culture/s: Influences, activities, and initiatives: An Annual Review of Information Science and Technology (ARIST) paper.

“…A review of critical success factors in data governance by Al‐Ruithe et al (2019) identifies organizational culture change as a critical success factor for data governance—in other words, changes in organizational culture may be necessary to align organizational culture to these data governance objectives. Others see strong data governance as a prerequisite for a so‐called “data‐driven culture” that is based around performing data analytics to gain strategic insight and drive innovation (e.g., Berndtsson et al, 2018). A data‐driven culture is defined as a culture that is “characterized by a decision process that emphasise[s] testing and experimentation, where data outweighs opinions, and where failure is accepted—as long as something is learnt from it” (Berndtsson et al, 2018).…”

“…Others see strong data governance as a prerequisite for a so‐called “data‐driven culture” that is based around performing data analytics to gain strategic insight and drive innovation (e.g., Berndtsson et al, 2018). A data‐driven culture is defined as a culture that is “characterized by a decision process that emphasise[s] testing and experimentation, where data outweighs opinions, and where failure is accepted—as long as something is learnt from it” (Berndtsson et al, 2018). A 2018 survey of business executives (Davenport & Bean, 2018) suggests that while start‐ups may have data‐driven cultures from the outset, established firms make slow progress transforming towards data‐driven cultures, despite significant concerns about the potential for disruption from start‐ups.…”

Project management: openings for disruption from AI and advanced analytics

“…Note that although many organizations may be inclined to pilot a few initial projects, a rationalized approach to a set of projects with an overriding goal and long-term plan may actually use resources more efficiently and result in outcomes more supportive of overall strategy. Berndtsson et al (2020) provide a more detailed exposition of strategies to increase the probability that pilot projects will scale for organizational use.…”

Data-Driven Organizations: Review, Conceptual Framework, and Empirical Illustration

“…Australasian Journal of Information Systems Fischer et al 2023, Vol 27, Selected Papers from ACIS 2022 Data-Driven Organizations competitors (Berndtsson et al, 2018;Constantiou & Kallinikos, 2015). Among other things, this is because organizations that are driven by data have been found to operate with improved processes and innovative data-enabled products and business models (Sivarajah et al, 2017), and to make better decisions in general (McAfee & Brynjolfsson, 2012;Svensson et al, 2019).…”