Once data has been collected, organizing and structuring it is essential to make it accessible, actionable, and meaningful for Application Portfolio Management (APM). Without proper organization, even well-collected data can become fragmented or overwhelming, making analysis and decision-making inefficient. This section explores how to organize and structure application data effectively for beginners in APM.
1. Defining Organizational Goals for Application Data
Before organizing the data, clarify its intended use to ensure the structure aligns with your goals. Common organizational goals include:
- Simplifying analysis for decision-making (e.g., rationalization, cost optimization).
- Ensuring transparency for stakeholders.
- Enabling efficient updates and ongoing data maintenance.
- Supporting future scalability as the APM practice matures.
Tip: Align the structure with APM goals, such as prioritizing applications by cost, criticality, or usage.
2. Grouping Data into Logical Categories
Organize application data into logical, easy-to-understand categories. These groupings can provide a clear structure for analysis and reporting. Common categories include:
- General Information: Application name, business owner, department, and primary purpose.
- Technical Details: Hosting environment, integrations, dependencies, lifecycle stage.
- Financial Data: Costs (CapEx, OpEx), licensing fees, and ROI.
- Usage Metrics: Number of users, frequency of usage, and geographic distribution.
- Business Alignment: Strategic importance, criticality, and business impact.
- Risk and Compliance: Security vulnerabilities, compliance requirements, and data sensitivity.
Tip: Use consistent labels and formatting for each category to simplify data entry and analysis.
3. Choosing the Right Format for Data Organization
The format in which you organize data can significantly affect its usability. Options include:
- Spreadsheets: Ideal for small portfolios or teams starting APM. Create tabs for different categories or types of applications.
- Relational Databases: Suitable for larger portfolios with complex data relationships, allowing for queries and analysis.
- APM Tools or CMDBs: Use dedicated software for real-time tracking and advanced features like visualization.
Tip: Select a format that matches your organization’s size and resource availability, ensuring it is scalable as your APM practice grows.
4. Prioritizing and Ranking Applications
Not all applications need the same level of detail initially. Prioritize applications based on their impact or strategic importance. Key prioritization methods include:
- High-Cost Applications: Focus on those with significant financial implications.
- Mission-Critical Systems: Applications essential to business continuity.
- Underutilized or Redundant Applications: Candidates for early rationalization.
Tip: Use a simple scoring model to assign priority levels (e.g., High, Medium, Low) to applications.
5. Leveraging Hierarchies and Relationships
Applications often have relationships with other systems, making it important to capture hierarchies and dependencies.
- Parent-Child Relationships: Group applications that depend on a core system (e.g., a CRM system with supporting plugins).
- Integration Mapping: Document how applications connect to each other and share data.
- Lifecycle Phases: Categorize applications by their lifecycle stage (development, maintenance, decommissioning).
Tip: Visualizing dependencies using diagrams or charts can make complex relationships easier to understand.
6. Standardizing Naming Conventions and Metadata
Establishing consistent naming conventions and metadata standards simplifies data organization and ensures clarity across teams.
- Naming Conventions: Use standardized formats (e.g., “Dept_Function_ApplicationName”) to reduce ambiguity.
- Metadata Tags: Include key attributes such as business unit, application type, and priority level.
- Version Control: Track changes to application data to maintain historical accuracy.
Tip: Document these standards and ensure all stakeholders adhere to them during data entry.
7. Creating Dashboards for Visualization
Structured data becomes more actionable when presented visually. Use dashboards to summarize key metrics and provide stakeholders with an overview of the portfolio. Key elements of a beginner-friendly dashboard include:
- Application Distribution: Grouped by department, usage, or cost.
- Financial Insights: Total cost by category or application type.
- Prioritization Status: Applications flagged for rationalization, investment, or retirement.
Tip: Simple tools like Microsoft Excel, Google Sheets, or Power BI can be used to create basic dashboards.
8. Building a Centralized Repository
A centralized repository ensures that application data is easily accessible and updatable. Key considerations for building this repository include:
- Access Control: Define who can view or modify the data.
- Data Backup: Ensure regular backups to prevent data loss.
- Version Management: Track changes to maintain an audit trail.
Tip: Use cloud-based solutions for easier collaboration and real-time updates across teams.
9. Maintaining Data Consistency
To keep the data useful over time, establish processes for regular updates and consistency checks.
- Periodic Reviews: Schedule quarterly or annual reviews of application data.
- Validation Processes: Cross-check data accuracy with stakeholders and source systems.
- Automation: Leverage tools to automatically update usage or cost data where possible.
Tip: Assign responsibility for maintaining data to specific roles (e.g., application owners or APM leads).
10. Preparing Data for Analysis and Reporting
Once organized, structure the data to support meaningful analysis and reporting.
- Filters: Set up filters to view data by department, cost category, or lifecycle stage.
- Summary Views: Create summaries of key metrics for quick insights.
- Export Options: Ensure data can be easily exported to reporting tools or dashboards.
Tip: Focus on simplifying complex data for non-technical stakeholders to drive better decision-making.
11. Documenting the Data Structure
To ensure consistency and scalability, document the data structure and guidelines for data organization. Include:
- Categories and attributes being tracked.
- Naming conventions and metadata standards.
- Processes for updating and validating data.
Tip: This documentation can also serve as a training tool for new team members.
12. Benefits of Organized Application Data
Organizing and structuring application data provides several benefits, including:
- Easier identification of redundancies and underperforming applications.
- Faster decision-making due to streamlined access to key metrics.
- Better stakeholder alignment through clear, visualized insights.
- A scalable foundation for advanced APM practices, such as automated analysis.
By organizing and structuring application data effectively, organizations can maximize the value of their data collection efforts, enabling clear insights and strategic decision-making. This foundational step ensures that application portfolios remain well-managed, adaptable, and aligned with business goals as APM efforts mature.
