Once an application inventory has been created, the next critical step in the Application Portfolio Management (APM) process is preparing the collected data for analysis. Data analysis transforms raw inventory information into actionable insights, enabling informed decisions about rationalization, optimization, and alignment with organizational goals. This section outlines the steps necessary to transition from data collection to analysis, ensuring the inventory serves as a reliable foundation for APM activities.
1. Validate the Inventory Data
Before diving into analysis, it’s essential to ensure that the inventory data is accurate, complete, and consistent. Data validation helps avoid misinformed decisions that could stem from errors or gaps.
- Steps to Validate Data:
- Cross-Check Sources: Compare inventory data against procurement records, network discovery results, and stakeholder input.
- Engage Stakeholders: Involve application owners, business leaders, and IT teams to verify the accuracy of data fields, such as costs, ownership, and usage.
- Address Gaps: Identify and resolve missing or incomplete data, prioritizing critical fields such as application costs, lifecycle stage, and dependencies.
- Outcome: A clean, reliable dataset ready for meaningful analysis.
2. Organize and Standardize Data
Consistently formatted and well-organized data makes analysis more efficient and ensures accurate results.
- Steps to Organize Data:
- Group Applications: Categorize applications by business function, department, geographic location, or hosting environment.
- Standardize Formats: Ensure uniformity in naming conventions, cost structures (e.g., annual vs. monthly), and data types.
- Tag Key Attributes: Use tags or labels to mark critical attributes, such as mission-critical applications, legacy systems, or high-cost tools.
- Outcome: A structured inventory that supports easy sorting, filtering, and categorization during analysis.
3. Define Key Metrics and Indicators
Identify the metrics and indicators that will guide the analysis, ensuring alignment with organizational goals and priorities.
- Common Metrics for Analysis:
- Cost Metrics: Total cost of ownership (TCO), licensing costs, maintenance costs.
- Business Value: Application criticality, alignment with strategic objectives, usage levels.
- Risk Metrics: Security vulnerabilities, compliance gaps, end-of-life (EOL) status.
- Technical Metrics: Integration dependencies, hosting environment, performance metrics.
- Outcome: A clear set of metrics to evaluate applications and support decision-making.
4. Develop a Scoring Model
A scoring model provides a framework for evaluating applications based on multiple criteria, such as cost, risk, and business value. This model simplifies comparisons and prioritization.
- Steps to Build a Scoring Model:
- Define Criteria: Select evaluation criteria that reflect organizational priorities (e.g., cost-efficiency, business alignment).
- Assign Weights: Weight criteria based on their importance (e.g., business value = 50%, cost = 30%, risk = 20%).
- Score Applications: Assign scores to each application for each criterion, then calculate weighted totals.
- Outcome: A quantitative method for ranking applications and identifying candidates for rationalization or investment.
5. Identify Patterns and Trends
Analyzing the inventory data can reveal patterns and trends that inform APM strategies.
- What to Look For:
- Redundancy: Multiple applications performing similar functions.
- Underutilization: Applications with low usage relative to their cost.
- Legacy Systems: Applications nearing EOL or requiring high maintenance.
- High-Impact Areas: Critical applications driving significant business value.
- Outcome: Insights that highlight opportunities for rationalization, cost savings, or modernization.
6. Prepare Visualizations and Reports
Effective visualizations make complex data easier to interpret and share with stakeholders. They help communicate insights clearly and build support for APM initiatives.
- Recommended Visualizations:
- Cost Distribution: A breakdown of application costs by category, department, or geography.
- Usage Analysis: Graphs showing usage metrics across the portfolio.
- Risk Map: A matrix plotting applications based on risk and criticality.
- Rationalization Opportunities: Charts identifying redundant or underperforming applications.
- Outcome: Clear, actionable reports that facilitate stakeholder engagement and decision-making.
7. Engage Stakeholders for Collaborative Analysis
Involving key stakeholders in the analysis process ensures that decisions reflect both IT and business perspectives.
- Steps to Engage Stakeholders:
- Present Preliminary Insights: Share initial findings to gather feedback and refine analysis.
- Involve Business Leaders: Ensure applications’ business value is accurately assessed.
- Collaborate on Priorities: Align on key objectives, such as cost reduction or modernization efforts.
- Outcome: Stakeholder buy-in and alignment on next steps.
8. Prioritize Applications for Action
Use the analysis results to prioritize applications for immediate action, such as rationalization, investment, or modernization.
- Steps to Prioritize:
- Identify Quick Wins: Focus on redundant, underutilized, or low-value applications that can be retired or consolidated.
- Address High-Risk Applications: Mitigate risks by retiring or upgrading unsupported or non-compliant systems.
- Plan Strategic Investments: Allocate resources to high-value applications that align with business goals.
- Outcome: A prioritized action plan for optimizing the application portfolio.
9. Prepare for Continuous Improvement
Analysis is not a one-time activity; it is part of an ongoing process of refinement and improvement.
- Steps for Continuous Improvement:
- Establish Metrics: Track progress using KPIs such as cost savings, risk reduction, or application performance improvements.
- Iterate the Inventory: Regularly update the inventory to reflect changes in the IT landscape.
- Build Governance Processes: Formalize processes for maintaining and analyzing the inventory.
- Outcome: A sustainable framework for ongoing APM success.
10. Communicate Findings and Next Steps
Effectively communicating the results of the analysis builds momentum for APM initiatives and ensures alignment with organizational goals.
- How to Communicate:
- Create Executive Summaries: Highlight key insights, such as cost savings potential and risk mitigation opportunities.
- Host Stakeholder Meetings: Present findings to IT and business leaders, emphasizing how APM aligns with their priorities.
- Define Next Steps: Outline a clear roadmap for implementing changes based on the analysis.
- Outcome: Stakeholder support and a clear path forward for rationalization, optimization, and strategic planning.
Conclusion
Preparing for data analysis is a pivotal step in transforming the application inventory into a strategic tool for decision-making. By validating and organizing data, defining key metrics, developing a scoring model, and engaging stakeholders, organizations can unlock the full potential of their inventory. The insights gained through analysis enable targeted actions, such as cost optimization, risk mitigation, and portfolio alignment, setting the stage for long-term success in APM.
