Overview
This case study illustrates how a mid-sized organization successfully implemented an early-stage data collection process to kickstart its Application Portfolio Management (APM) practice. The organization faced challenges common to beginners, such as incomplete inventories, stakeholder resistance, and limited resources. By adopting a structured approach, they were able to achieve quick wins, establish foundational practices, and demonstrate the value of APM.
Background
- Organization: A mid-sized retail company with 250+ applications supporting operations, sales, marketing, and logistics.
- Challenge: Rising IT costs, overlapping functionalities in the application portfolio, and growing technical debt prompted leadership to initiate APM efforts.
- Objective: Conduct a basic data collection exercise to create an application inventory and identify initial opportunities for cost savings and rationalization.
1. Challenges Faced
The organization encountered several obstacles during its early APM efforts:
- Fragmented Data: Application information was scattered across departments, with no centralized repository.
- Limited Stakeholder Buy-In: Business units were hesitant to share data, fearing increased scrutiny or budget cuts.
- Resource Constraints: The IT team had limited time and budget to dedicate to APM efforts.
- Low Data Quality: Existing records were outdated, incomplete, or inconsistent.
2. Approach Taken
The organization developed a phased approach to overcome these challenges and successfully implement data collection:
Phase 1: Gaining Stakeholder Support
- Communication: IT leadership hosted informational sessions to explain the purpose of APM and its benefits, emphasizing cost savings and better resource allocation.
- Quick Wins: Highlighted redundant applications (e.g., multiple project management tools) to show immediate potential for savings.
- Incentives: Assured business units that their input would lead to better IT services and reduced downtime.
Phase 2: Creating a Data Collection Framework
- Templates: Developed a simple spreadsheet template to capture key data points, including:
- Application name, owner, and business unit.
- Licensing costs and maintenance expenses.
- Usage metrics (e.g., number of active users).
- Dependencies and integrations.
- Ownership: Assigned each business unit responsibility for providing accurate data about their applications.
Phase 3: Using Tools to Support Data Collection
- Manual Inputs: Collected business and financial data through interviews and surveys with application owners.
- Automated Discovery: Used a lightweight tool (SolarWinds AppOptics) to gather technical data, such as performance metrics and hosting environments.
- Validation: Cross-checked collected data against existing ITSM records to ensure accuracy.
Phase 4: Prioritizing Applications
- High-Cost Applications: Focused initial efforts on the top 20% of applications based on cost.
- Mission-Critical Systems: Included applications critical to operations, such as the ERP and CRM platforms.
- Quick-Win Opportunities: Targeted redundant or underutilized applications for immediate review.
3. Results Achieved
Inventory Creation
- Developed a centralized inventory covering 80% of the application portfolio within 60 days.
- Identified 15 redundant applications, accounting for $120,000 in annual savings through consolidation.
Stakeholder Engagement
- Business units began to see the value of APM, leading to increased collaboration and improved data quality in subsequent updates.
Improved Decision-Making
- The data enabled the IT team to classify applications into categories (keep, invest, retire), laying the groundwork for a rationalization strategy.
Efficiency Gains
- Automated data collection tools reduced manual effort by 40%, enabling the team to focus on analysis rather than data entry.
4. Lessons Learned
- Start Small and Focused
- Prioritizing high-cost and mission-critical applications made the project manageable and impactful.
- Communicate Benefits Clearly
- Transparent communication helped gain stakeholder support and address resistance early in the process.
- Combine Manual and Automated Approaches
- Manual inputs from stakeholders provided context, while automated tools ensured technical accuracy.
- Iterate on Data Quality
- Initial data quality was imperfect, but iterative validation improved accuracy over time.
- Demonstrate Value Quickly
- Early successes, such as identifying redundant applications, built momentum and confidence in APM.
5. Next Steps
Based on the success of the early-stage data collection process, the organization planned to:
- Expand Inventory: Capture data for the remaining 20% of the portfolio.
- Formalize Governance: Create an APM governance framework to ensure ongoing maintenance and updates.
- Introduce Scoring Models: Develop a scoring system to prioritize applications for future rationalization efforts.
- Invest in Advanced Tools: Upgrade to a more comprehensive APM platform to support scaling and deeper analysis.
Conclusion
This case study highlights how a mid-sized organization overcame common challenges to establish a foundational APM practice. By starting small, leveraging simple tools, and focusing on immediate value, the company demonstrated the feasibility and benefits of APM. The success of this early-stage initiative not only addressed pressing issues but also created a foundation for long-term continuous improvement and strategic alignment. This approach serves as a practical blueprint for other organizations embarking on their APM journey.
