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Project Goals for a successful Business Intelligence Software Implementation
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Project Goals for a successful Business Intelligence Software Implementation

Business Intelligence Software gives business users the ability to track, understand, and manage information within an organization. Business Intelligence is taking on an increasingly strategic role as more organizations look for ways to tap into the valuable data stored in their operational systems. Even though a typical BI project has an average return on investment (ROI) of over 600%, but due to the way implementation is done, organizations are unable to fully benefit from a global, cross-functional analysis of information.

Business Intelligence Software gives an organizations employees, partners, and suppliers easy access to the information they need to effectively do their jobs, and the ability to analyze and easily share this information with others.

What are the Project Goals for a Business Intelligence Software Implementation?

  • Data Integrity
    • Everyone using the same integrated information
    • Common and shared master data and hierarchies
    • Integration and consolidation of various sources of data
    • Framework for cross-module reporting from ERP system
    • Maintain full granularity of high-volume, granular and non-granular transactions
  • Data Analysis
    • Transition from static to flexible online reports
    • Automation of complex calculations
    • Common definitions for complex calculations
    • Preconfigured formatting in Excel frontend (portal)
    • Centralized query development
    • De-centralized end-user reporting
    • Role-based data marts
  • Cost Reduction
    • Consolidation of infrastructure
    • Automated job scheduling
    • Reduction of manual reconciliation processes
    • Reduced need for customized programming
What are the Project Goals for a Business Intelligence Software Implementation

What are the Project Goals for a Business Intelligence Software Implementation

What are the Business intelligence strategies to use?

Business Intelligence strategies rarely fail because of technology more often than not, they fail for business and management reasons. Business Intelligence is by its very nature a cross-functional discipline, this strategy will only work successfully if there is an appropriate level of cooperation between departments.

What is a Top Down Data Modeling Strategy?

  • Perform an inventory of all reports
    • Function
    • Characteristics
    • Key figures/key performance indicators
    • Granularity
    • Source of data
  • Accept Duplication
    • Between ERP and Warehousing reporting
    • Among Warehousing structures
  • Advantages
    • User-specific
  • Disadvantages
    • May be difficult to incorporate new requirements
Top Down Data Modeling Strategy

Top Down Data Modeling Strategy

What is a Bottom-Up Data Modeling Strategy?

  • Extractor-based
  • Typically utilizes Data Warehousing standard content
  • Accept Duplication
    • Between ERP and Data Warehousing reporting
    • Among Data Warehousing structures
  • Advantages
    • Function-specific (e.g. Financial reporting)
    • Easier to handle changing requirements
  • Disadvantages
    • Not user-specific
Bottom-Up Data Modeling Strategy

Bottom-Up Data Modeling Strategy

What is a Hybrid Approach Data Modeling Strategy?

  • Most common approach
  • Assess required reports
  • Assess required fields
  • Perform ‘Gap’ analysis to match Business Warehouse delivered standard content

Business Intelligence is present in some shape or form in all of today’s large organizations. In most cases, Business Intelligence implementations are ad hoc and take place at a departmental level and without any overall Business Intelligence strategy.

What is the Data Integration Strategy for a Business Intelligence?

  • Logically segment data by summary vs. granularity
  • Ensure harmonization of characteristic values in order to enable the reporting of the merged data; many tools exist; e.g. Ascential, Master Data Management, and other tools
  • Create distinct key figures by source to enable summary reporting of each respective source of data
  • Use MultiProviders

What is the Query Development Strategy?

  • Query-based configuration is maintained centrally by the Data Warehousing Administrator
  • Selection and order of ‘Characteristics’ and ‘Key Figures’
  • Definition of ‘Restricted Key Figures’ (filtering key figure against one or more characteristics)
  • Definition of ‘Calculated Key Figures’ (formulas)
  • Definition of ‘Structures’
  • Definition of user-defined characteristic ‘Variable’ selection
  • Definition of user-defined ‘Time-Based Trending Variables’
  • Definition of ‘Conditional Formatting’
  • Formatting (e.g. subtotaling, decimal places, hierarchy levels, etc…)
  • Drilldown to other Data Warehousing queries (Report-to-Report Interface)

What is Business Intelligence Data Access Strategy?

  • Efficient data access
  • ‘Slicing and dicing’ data in an InfoCube should be relatively fast
  • Use the ‘Report-to-Report’ (RRI) functionality in Data Warehousing to drill from summary InfoCubes to granular objects
  • Avoid direct reporting against physical objects
  • Utilize user-defined time-based variables to apply different time periods to different columns of a report
What is Business Intelligence Data Access Strategy

What is Business Intelligence Data Access Strategy

What are the Critical Success Factors of Business Intelligence Projects?

No Business Intelligence deployment is completely without problems. In some cases, the problems may even be an essential part of getting the right resources and increasing focus on some aspect of the Business Intelligence project (for example with the data quality issues discussed earlier). It is important that you effectively manage expectations.

Implementation

  • Utilize Data Warehousing providers delivered Business Content
  • Prototype Business Warehouse content within 90 days
  • Establish clear scope
  • Implement Business Warehouse behind ERP; especially if ERP implementation is complex
  • Implement Business Warehouse within the context of a stable ERP environment
  • Minimize the usage of custom codes
  • Adhere to data modeling guidelines, system transport and performance
  • Strong technical team (data modeling and Basis)
  • Strong ERP teams

Staffing

  • Staff the appropriate mix of resources (experience)
  • Staff the appropriate roles of resources
  • Staff Business Warehouse team members that understand the business processes and their data

Organizational

  • The organization has a long-term, strategic commitment to Executive support
What are the Critical Success Factors of Business Intelligence Projects

What are the Critical Success Factors of Business Intelligence Projects

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