This research illustrates a successful hiring program that increased the number of individuals possessing varying levels of technical knowledge related to data science, business analytics or business intelligence; this was accomplished by examining six main areas of the recruitment process: structuring the recruitment process, sourcing candidates while developing an employer brand,  selecting candidates via various recruitment methods and assessments, using analytical tools throughout the recruitment process, aligning DATAP with company-wide strategic initiatives, and  evaluating DATAP’s effect on the organization through metrics. A descriptive research design method including a 5-point Likert scale was used to collect quantitative information from 108 employees. Statistical analysis methods including percentage calculations, weighted averages, Chi-Square tests, and Pearson’s Correlation were used to analyse the quantitative event data gathered. In aggregate, all six areas of the research show moderate to high effectiveness. The strongest indicators of the use of analytics tools and the candidate selection process were determined via statistical methods. Recommendations to further enhance overall effectiveness include a focus on using analytics tools, improving transparency within the recruiting process, and creating strategies that are sensitive in relation to age.

Key Words: Talent Acquisition, Data Analytics, HR Analytics, Recruitment Effectiveness, Employer Branding, Predictive Hiring.