model of business intelligence maturity levels for mobile operators

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?

The objective: Better decisions!

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

The model

• Basic idea:

The model (2)

Improvement needed!

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