Tesi etd-06302013-192513 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
TRIENBACHER, THOMAS
URN
etd-06302013-192513
Titolo
Analysis and Optimization of Business Processes based on Key Performance Indicators
Dipartimento
INFORMATICA
Corso di studi
INFORMATICA PER L'ECONOMIA E PER L'AZIENDA (BUSINESS INFORMATICS)
Relatori
relatore Prof. Bruni, Roberto
tutor Jung, Thomas
tutor Jung, Thomas
Parole chiave
- BPM
- Business Process Analysis
- Business Process Management
- Business Process Optimization
- Key Performance Indicators
- KPI
- Master Data Management
- MDM
- Measurement
Data inizio appello
19/07/2013
Consultabilità
Non consultabile
Data di rilascio
19/07/2053
Riassunto
Business Process Management (BPM) aims to improve a company's performance by the application of various methods and tools in order to manage and optimize business processes. The optimization by means of Key Performance Indicators (KPIs) starts with the definition of the objectives of the process. Based thereon, the corresponding critical success factors can be derived which then are used to define appropriate KPIs. Therefore, the kind of information required depends on the context and the objectives of the business process. Business processes in Master Data Management (MDM) deal with master data, which represent the core business objects of an organization. The main objective of MDM is to provide master data with high quality. Therefore, the processes are characterized by automatic and manual verifications and a high dependence on the human resource. To approve the elaborated theoretical concepts, a case study, which investigates an inter-organizational MDM process of a leading producer of chemical products, has been conducted. Considering the specific characteristics of a MDM process, the following KPI-categories has been identified as the most relevant ones: Cycle Time, Productivity, Quality, Timeliness and Resource Utilization. The case study has been conducted within the SAP environment, which enables the implementation of the whole procedure, from the collection of the information to the analysis and optimization of the process.
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