Mainframe Modernization ROI: A Cost-Focused Guide for Businesses

As businesses pursue operational efficiency and innovation, many are transitioning from legacy mainframe systems to distributed, open source environments. Once the cornerstone of enterprise IT, mainframes are now seen as costly and less flexible than modern computing platforms. This shift involves significant cost considerations, opportunities for savings and the potential for a positive return on investment (ROI).

For example, according to a survey by Kyndryl, mainframe modernization projects typically account for 3.9% of an organization's IT budget. These projects can lead to an average annualized cost savings of at least $23.3 million. Additionally, businesses report becoming 9% more profitable by modernizing on the mainframe, and 11% more profitable by integrating with other platforms or moving off the mainframe.

The Cost of Legacy & the Need for Modernization

Mainframes have long been reliable workhorses in sectors like banking, insurance and government, valued for their centralized control and transaction-processing capabilities. However, their limitations — high operational costs, inflexibility and difficulty integrating with modern technologies — have become barriers in a digital, fast-paced world. Transitioning to distributed systems powered by open source technologies offers a cost-effective, scalable and flexible alternative. Here are some of the key forces that necessitate modernization:

• Escalating Operational Costs: Mainframes rely on proprietary hardware and software, which are expensive and demand specialized skills.
• Talent Shortages: As COBOL and other mainframe-specific skills decline, organizations face increasing difficulty in maintaining their systems.
• Integration Limitations: Legacy systems were not designed for modern digital ecosystems, such as cloud, APIs and DevOps pipelines. This limits agility and innovation.

While the modernization process is complex, and upfront costs are high, it holds promise for long-term savings and improved business agility.

The following analysis breaks down the key factors influencing costs and the potential for ROI. The typical cost trends seen in mainframe modernization are summarized below.

The 3 Most Common Cost Patterns for Mainframe Modernization

Before diving into the specifics around cost analysis, we’ll review the three most common mainframe modernization approach cost patterns based on our experience, which are as follows:

Rehosting (“Lift and Shift”)

Move the mainframe applications to a lower-cost processor or to a cloud-hosted environment without modifying the architecture, code or data model.

Replatforming

Migrate mainframe applications to a new and modern runtime platform. Maintain the core application architecture and data model while making necessary code changes for the new OS, database and compiler(s).

Refactoring/Rearchitecting

Optimize the existing codebase, potentially the data model, and storage for the target on-prem or cloud environment without changing external behavior. Use modern languages and efficient cloud-native services.

Key Cost Trends During Modernization (Refactoring/Rearchitecting)

In this piece, we’ll be unpacking the cost trends for the refactoring/rearchitecting mainframe modernization approach. The overall business case for the cost-saving analysis and ROI can be derived from the various factors contributing to the cost and their trends analysis. 

1. Mainframe Infrastructure Costs (Decreasing)

Mainframe costs are often measured by a million instructions per second (MIPS), which quantifies the processing power of the system. Migration reduces these costs as infrastructure transitions to cloud or on-premises distributed systems. Cost models for mainframes include:

• Rolling 4-Hour Average Model: Charges based on the average CPU utilization during peak four-hour windows
• Sub-capacity Pricing: Fees tied to actual usage rather than total system capacity
• Full-Capacity Pricing: Based on total system capacity regardless of usage
• Performance-Based Pricing: Costs linked to workload throughput or transaction volume
• Subscription Models: Fixed fees for predictable cost structures

Post-migration, mainframe infrastructure costs decline as workloads shift to more cost-effective cloud platforms.

2. Cloud Infrastructure Costs (Increasing)

As workloads move to the cloud, costs for cloud services rise. However, cloud platforms like AWS, Azure, and GCP typically offer significant savings compared to mainframes. For example, in our experience:

• A mainframe with over 11,000 MIPS can cost ~$1,000-$2,000 per MIPS annually
• A comparable AWS infrastructure might cost $1.7M annually, with potential savings of 50–90%

Organizations can estimate cloud costs by benchmarking virtual CPU (vCPU) requirements against mainframe workloads.

3. Labor Costs (Increasing Initially)

Labor costs include skilled professionals for planning and executing migrations. These costs depend on factors like:

• Lines of Code (LOC): Larger codebases require more effort
• System Complexity: Complex dependencies, integrations and customizations demand expertise
• Legacy Languages: Specialized knowledge in COBOL or PL/I is often necessary
• Team Optimization: Labor costs can be controlled by assembling appropriately sized teams and leveraging automation tools; phased migrations help manage resource allocation effectively

4. Adoption Costs (Increasing Initially)

Training existing staff to work with modern platforms (e.g., Java, cloud technologies, microservices) is critical. Adoption costs include:

• Training duration, tools and external trainers
• Organizational change management and knowledge transfer

The Formula for Training Costs:

Total Training Cost = (Number of Employees × Training Duration × Cost per Employee per Hour) + Cost of External Trainers + Cost of Training Tools and Resources + Post-Training Support

5. Tools Costs (Increasing Initially)

Migrating requires tools for automation and code conversion. Costs vary based on:

• Licensing models (perpetual vs. subscription)
• Features like AI capabilities and cloud integration
• Customization and scalability requirements

Key considerations for tool selection include:

• Compatibility with legacy languages (COBOL, PL/I, Natural) and target platforms
• Automation capabilities to minimize manual intervention
• Vendor support and cost-effectiveness

6. Support Costs (Transitioning to Steady-State)

Post-migration, support costs focus on maintaining and optimizing the new system. Key components include:

• Managed services for monitoring and updates
• Maintenance for migrated applications
• Cloud platform support and scaling
• Skill retention and staff upskilling
• Investments in high-availability infrastructure and premium SLAs to minimize downtime

While initial support costs may rise, they stabilize as teams adapt to the new environment.

Cost Saving Opportunities Post-Migration

Mainframe modernization presents a compelling opportunity for organizations to achieve substantial cost savings and long-term benefits. Post-migration, businesses can significantly reduce mainframe infrastructure costs by decommissioning outdated systems, while labor costs decline as optimized processes and smaller teams improve efficiency. 

Over time, adoption costs fall as employees become skilled in modern systems, and tool costs decrease once migration phases are completed. Leveraging cloud infrastructure not only lowers operating costs but also provides enhanced scalability, while adopting open source solutions eliminates vendor lock-in and reduces licensing fees. 

Incorporating automation accelerates migration processes and minimizes errors, and taking a phased approach helps spread expenses and reduce financial risk. 

With these strategies, organizations can achieve 50–90% savings in annual operating expenses while gaining greater scalability and agility, based on our experience. To secure stakeholder buy-in, a comprehensive ROI analysis is essential, detailing cost reductions in infrastructure, labor and tools, alongside improved scalability through elastic cloud solutions and enhanced business agility. 

Next Step: Building the Business Case

Migrating from mainframes to distributed, open source systems is a strategic investment in an organization’s future. Despite the initial complexity and costs, the long-term benefits — cost savings, scalability and innovation — far outweigh the challenges.

Crafting a clear and data-backed business case ensures alignment, it supports informed decision-making, enabling organizations to unlock the full potential of modernization while staying competitive in a rapidly evolving market.

Businesses can achieve a smooth transition with a positive ROI by carefully evaluating cost drivers, optimizing resources and leveraging automation. Effective change management, stakeholder engagement and phased execution are essential for success in this digital transformation journey.