Are You Using These Key Benchmarks in Your Application Modernization Decisions?

As an Architect we all use certain Architecture characteristics decision matrix while taking a decision around application modernization.
Recently I was having mentoring session on Open Architecture Community and one of the participants has asked me a question saying how we would qualify or is there a Benchmark figure which every Architect could use to take a decision while qualifying an application to be modernized.
For example – How would we qualify an application is business critical? How would we know an application Functional Fit hence to be retained? How would we know the TCO of an application is high or less hence decision of Retire Vs Retain can be taken?
Establishing benchmark figures for application modernization can be challenging because they are often industry-specific, vary by organization size, and depend on the unique needs and context of the enterprise. However, I am providing some general benchmark figures and guidelines for each parameter. These figures can serve as a starting point, primarily to the newcomers to Architecture domain. It's essential to adjust them based on our organization's context and industry benchmarks.

1.     Functional Parameters:

·        Business Criticality: If an application supports >80% of core business processes, it's deemed highly critical.

·        Redundancy: Applications with >70% overlap in functionality with others might be candidates for consolidation.

·        Functional Fit: Applications meeting <60% of current and future business needs might be considered for replacement.

·        User Satisfaction: Applications with a user satisfaction score <70% (on a scale of 100) might need improvement or replacement.

2.      Technical Parameters:

·        Architecture & Technology Stack: Applications built on technologies older than 10 years might need modernization.

·        Integration Capabilities: If >3 custom integrations are required for an app, consider its suitability.

·        Performance: Response time >3 seconds for critical operations might be a concern.

·        Scalability: If an application cannot handle a 50% increase in load, it might be non-scalable.

·        Security: Any application failing standard security tests or with >5 critical vulnerabilities should be addressed immediately.

3.      Operational Parameters:

·        Maintenance Cost: If maintenance costs exceed 25% of the application's initial development cost annually, it might be too high.

·        Support: If >15% of total IT staff is dedicated to one application, consider its efficiency.

·        Downtime & Outages: More than 2 unplanned outages a month might be a red flag.

·        Compliance: Any non-compliance should be addressed immediately.

4.      Financial Parameters:

·        TCO: If the 5-year TCO is >150% of the application's initial implementation cost, reconsider its value.

·        ROI: Applications with an ROI of <10% over 3 years might be underperforming.

·        Depreciation: If an application's value depreciates >20% annually, it might be a concern.

5.      Strategic Parameters:

·        Alignment with Business Strategy: Applications aligning with <50% of strategic goals might need reevaluation.

·        Vendor Relationship: Poor vendor performance in 2 out of 3 reviews might be a sign to reconsider the partnership.

·        Future Roadmap: Applications without a clear 3-year roadmap might be at risk.

6.      Lifecycle Parameters:

·        Application Age: Applications >10 years old might be considered legacy and need reevaluation.

·        Lifecycle Stage: Applications in the decline phase for >2 years should be considered for sunset.

·        End of Life: Any application nearing its end of life should have a transition plan.

7.      Data Parameters:

·        Data Quality: If >15% of an application's data is deemed inaccurate or outdated, it's a concern.

·        Data Volume: Applications with <50% utilized data storage might be over-provisioned.

·        Data Sensitivity: Any breach of sensitive data should be addressed immediately.

8.      Adoption and Utilization:

·        User Count: If <40% of licensed users actively use an application, its adoption might be low.

·        Frequency of Use: Applications used <50% of expected frequency might be underutilized.

·        Training Needs: If >20% of users require extensive training, usability might be a concern.

9.      Flexibility and Customization:

·        Configurability: If >20% of business needs require custom coding, consider the application's flexibility.

·        Customization: Applications with >50% custom code might be hard to maintain.

10.  Migration & Transition Parameters:

·        Data Migration Capabilities: If migrating data takes >6 months, it might be too long.

·        Transition Costs: If transition costs exceed 70% of a new application implementation, reconsider the move.

Comments

Post a Comment

Popular posts from this blog

Image
  Composable Gen AI: The Smart Way to Build AI Systems (With Real Examples) After 20+ years in tech, I've seen every architecture trend come and go. When Gartner started pushing "composable architecture" a few years back, I'll admit—I rolled my eyes. "Great, another buzzword," I thought. But after seeing how AI is actually being used in the real world? This time, it's different. Composable Gen AI isn't just theory—it's the only sane way to keep up with AI's breakneck evolution. Let me explain why (with real examples you can steal). What is Composable Gen AI Architecture? (No Jargon) Imagine building with AI Lego blocks : Instead of using one giant, expensive model (like GPT-4) for everything... You snap together smaller, specialized models for each task.  Why This Beats the "Monolithic AI" Approach                                                   ...
Read more

Is Model Context Protocol Replacing Enterprise Service Bus?

Image
An Airport Conversation That Completely Changed My Thinking Last week, I had one of those unexpected moments of insight that hits you outside work, outside meetings, outside architecture thinking— in an airport lounge of all places. I was sipping a cold coffee, waiting for my flight, when I overheard a Sales Head from a tier-1 consulting firm seated next to me. He wasn’t speaking — he was shouting into his phone. And this is what he said: “Forget ESB and middleware… we should be selling Model Context Protocol –based AI solutions. This is the future. Push MCP hard.” He said it with the conviction of someone giving orders to conquer a territory. At first, I laughed internally. You can’t just shout away 20 years of enterprise integration patterns . But the line stuck in my head. And the more I thought about it, the more I realized: he’s wrong in conclusion, but right in direction. This blog is the result of that airport moment — and everything it triggered i...
Read more
When “Hello World” Needed Kubernetes (…and Azure Functions, and GPT-5) When “Hello World” Needed Kubernetes (…and Azure Functions, and GPT-5) A light, sarcastic read for anyone who has watched a tiny task blossom into a full-blown cloud transformation project. #sarcasm #cloud #devlife #overengineering Quick jumps Step 1 — The Wrong Prompt, The Wrong Rabbit Hole Step 2 — The Permission Drama Step 3 — Enter the Cloud Circus Step 4 — GPT-5 to the Rescue (or Not) Step 5 — The Buzzword Buffet Step 6 — Hydra Problems Multiply Step 7 — The Grand Confusion Final Thought There’s a new kind of developer on the loose—let’s call them the new-gen dev . Brilliant? Yes. Ambitious? Absolutely. But allergic to the word simple . Give them the tiniest task and suddenly you’re not watching coding; you’re watching an over-engine...
Read more