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Model of business intelligence maturity levels for mobile operators. Mikael Ojala Thesis Seminar on Networking Technology Helsinki University of Technology April 5 th , 2005. Agenda. Background Objectives of the thesis Methodology What is Business Intelligence? BI maturity The model - PowerPoint PPT Presentation
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Model of business intelligence maturity levels for mobile operators
Mikael Ojala
Thesis Seminar on Networking Technology
Helsinki University of Technology
April 5th, 2005
Agenda
• Background• Objectives of the thesis• Methodology• What is Business Intelligence?• BI maturity• The model• Results and conclusions
Background
• Thesis written at AffectoGenimap• Supervisor: prof. Heikki Hämmäinen• Instructor: M.Sc. Mikko Mattila• Started in September 2004
Objectives of the thesis
• What is mobile operators’ Business Intelligence like?– Does operators’ BI vary from other fields?
• Create a model for measuring mobile operators’ maturity on Business Intelligence– Is the model different for different kind of operators?
Methodology
Two main phases of the thesis:
1. Theoretical framework and building of the model
2. Validation of the generated model
Used methods: literature survey and qualitative interviews
Used methods: qualitative vs. quantitative interview results
What is Business Intelligence? (2)
• A process that refines and shares knowledge that is needed by the decision-makers
• BI is a continuous process
BI has a cyclic behaviour
Different cycles for different levels of decision-making
Business Intelligence maturity
• Definition: Business Intelligence consists of cycles
• That means that...
BI maturity = The efficiency of the cycles!
• Two aspects to BI maturity:
1. The maturity of technology
2. The maturity of organisation’s policies
Results
• The validation resulted the final model• Model is rather general:
Mobile operators’ BI does not differ from other fields!
• Two models: – A model for service operator– A model for network operator
Conclusions
• The maturity of the operator’s business affects to the maturity of its BI
• Large organisation size sets more demands for organisation’s BI
• Feedback for the model:+ quantitative
+ information on many levels
- answers are always qualitative
• Usage:– Quality checking, benchmarking, etc.
Thank you!
Questions? Comments?
mikael.ojala@affectogenimap.fi
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