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Identification of KPIs, dashboard creation and data analysis to improve Amazon’s Talent Acquisition Strategy

Luciano Camilli

Identification of KPIs, dashboard creation and data analysis to improve Amazon’s Talent Acquisition Strategy.

Rel. Domenico Augusto Francesco Maisano. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Della Produzione Industriale E Dell'Innovazione Tecnologica, 2023

Abstract:

The thesis is based on an internship experience at Amazon Luxembourg, where I worked as a direct report to the Head of the Project Management Office and supported the WorldWide Bar Raiser Program for project performance activities. The Bar Raiser Program is the core of Amazon’s talent acquisition strategy to hire candidates who “raise the bar”. Bar Raisers are skilled interviewers who act as neutral third parties in recruiting a candidate. First, a theoretical section on project management and its centrality in goal definition to meet the company's strategic objectives is presented. The paper then outlines the methodologies and tools developed during the internship to improve performance. The main goals included the automation of reporting, allowing more visibility to internal stakeholders, and a risk assessment of key activities with contingency measures. The overall objective of the Bar Raiser Program was disaggregated into its components. Every component was mapped, the ownership assessed, and sub-objectives redefined. On an operational level, the benefits of my work included an efficiency of 50% monthly time savings for internal reporting operations, an improvement of stakeholder engagement levels of 200%, and a 100% reduction of reporting defects. At a more strategic level, I revisited the key performance indicators and created a supply and demand model to assess program sustainability in the long term.

Relatori: Domenico Augusto Francesco Maisano
Anno accademico: 2022/23
Tipo di pubblicazione: Elettronica
Numero di pagine: 97
Informazioni aggiuntive: Tesi secretata. Fulltext non presente
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Della Produzione Industriale E Dell'Innovazione Tecnologica
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-33 - INGEGNERIA MECCANICA
Aziende collaboratrici: NON SPECIFICATO
URI: http://webthesis.biblio.polito.it/id/eprint/27484
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