It depends on the project size. The implementation of BI software can last from a few weeks to several months. Most of the companies, after the BI implementation, start to observe numerous benefits and decide to extend their system by adding new areas and functionality.

Business Intelligence systems should be implemented according to the priorities and importance of data sources. Starting from the implementation of the functions most important for company. The most popular is sales area and financial module.

High quality of data in Business Intelligence has significant impact on further successful implementation. A data warehouse (DWH) is a data management system that stores large amounts of data from multiple sources for later use in processing and analysis. In BI system DWH is the backbone of data storage. Building a DWH is a complex process. To do this experts use ETL/DQ processes. Most of the companies have their own DWH team that is preparing and standardizing the data for the BI team to analyze it afterwards.

Business Intelligence implementation should start simple by defining your objective, needs and data availability. The further key implementation steps are:

• Appoint team to be in charge of BI implementation
• Be aware of your data
• Take thought for BI KPIs you’d like to observe
• Select the right BI tool
• Build the infrastructure

Some of the key performance indicators of Business Intelligence implementation strategy are:

• Adoption – the number of BI users across the organization
• Quality – data quality and overall system reliability
• Speed – no excessive wait to load a report
• Ease of use – intuitive and agile BI solution
• Cost efficiency – the actual financial lift vs initial budget
• Satisfaction – BI implementation meets or not the users’ expectations

Typical threats coming with the implementation of Business Intelligence systems are:

• Low adoption of BI tools
• Data quality issues
• Lack of user training
• The Excel culture
• Bad cost estimation
• Bad implementation timeline estimation
• Chaotic BI development process