Access Type

Open Access Dissertation

Date of Award

January 2023

Degree Type

Dissertation

Degree Name

Ph.D.

Department

Instructional Technology

First Advisor

Ingrid Guerra-Lopez

Abstract

Performance improvement (PI) is a field that employs diverse approaches and techniques across different disciplines. One crucial step in approaching any performance problem is conducting a needs analysis (NA). Studies have indicated that NAs are not conducted as frequently as they should be. With the advancements in technology, we now have access to a vast amount of organizational data that can be collected and generated with the help of business intelligence (BI) systems. These systems also provide quick analysis tools for processing the data. This study aimed to explore the impact of BI systems on the prevalence and effectiveness of NA processes in organizations. The study found that evolving technologies provide PI professionals with a wider range of data to assess learning and performance problems at a more systemic level. BI systems can be leveraged to improve the NA process by reducing the time required to collect and analyze data. The study used a survey method to understand NA practices and access to data from 734 participants. The research showed that data quality and accessibility are strongly correlated with the utility of data from BI systems. Additionally, data accessibility is positively associated with adherence to NA practices. The perceived success of the initiatives was found to have a positive relationship with the NA practices and data accessibility, thus highlighting their importance, as ineffective initiatives can result in increased costs for the company. This study informs organizations on how to reduce risks in decision-making and gain a competitive advantage by making data-informed decisions by sharing high-quality data with PI professionals. Effectively solving problems can be achieved by utilizing high-quality data, as well as applying the human touch and contextualization.

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