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Performance Management Roadmap

Solving the puzzle

Rapid maturation of OSBI technologies equals new opportunities for our clients. Some are new to investing in BI solutions, due to the high costs of owning proprietary BI software. Others have significantly invested over the past decade, but question if now is the time to consider OSBI. In either case, our Performance Management Roadmap is designed to meet these challenges.

Here’s how it works
The Performance Management Roadmap essentially tailors a pragmatic implementation plan for you. A performance management lens is applied to your business, and it defines and prioritizes BI projects that emphasize process improvement and evidence-based strategy development.

Through an intensive 4-6 week analysis, we confirm, challenge, and extend your BI program vision by recasting your business strategy into testable hypotheses. Then we deliver an implementation roadmap that includes an initial analysis of your business and source data requirements.

What we provide
The Performance Management Roadmap deliverables include:

BI Roadmap
  • Program Implementation Plan
    • Sequencing of projects for parallel and iterative implementation
    • Prioritized by business need
    • Mindful of project and data dependencies
  • Project Definitions
    • High-level functional purpose/scope
    • Expected source data requirements
    • Architectural build-out expectations and dependencies
    • Effort and timeline estimates
Business Requirements
  • Organized by performance related processes
    • Factors which are expected to have an impact on performance
    • Leading and lagging indicators which will be used to measure outcomes
    • Opportunities for embedded operational intelligence, higher analytics and process experimentation
    • Cross-reference to required source data
Governance Structure and Process
  • Define ongoing program management structure
  • Define program management processes
    • Project management and coordination procedures
    • Issue escalation process
    • Data quality management and data stewardship
Conceptual Architecture
  • Application, database and systems component identification and definition with software recommendations
  • Conceptual architecture diagram
    • Reporting (managed, standard and ad-hoc)
    • OLAP
    • Analytical/Statistical Modeling and Data Mining
    • Dashboards/Analytical Portals
    • Database technology
    • Servers and Storage
    • Meta-data management
    • ETL
Source Data Inventory
  • Identified by source
    • Content and Volumetrics
    • Platform and Accessibility
    • Life-cycle State (existing, planned, sunsetting)
    • High-level Complexity, Quality and Integration Assessment