Product, supplier, lifecycle, and quality signals become visible.
Manish Damarakonda · Engineering-led digital transformation
Smarter portfolios.
Stronger supply chains.
Supply chain portfolio strategy & product lifecycle optimization.
MedTech experience. PLM, SAP & AI-enabled operations.
Supply Chain
Product Lifecycle
PLM + SAP
Analytics
Automation
Applied AI
My Approach
A control-tower view of product operations.
Start with the product and the supply-chain decision. Connect lifecycle signals, enterprise data, and the people responsible for execution. Apply technology where it helps teams act with greater clarity.
PLM and SAP workflows align data, changes, and execution.
Analytics and applied AI support clearer operating decisions.
Expertise
Three capabilities, one operating model.
Supply chain remains the foundation. PLM, SAP, analytics, automation, and applied AI work as practical enablers for better lifecycle decisions.
Supply Chain & Lifecycle
- Product transitions
- Obsolescence strategy
- Supply continuity
- Cross-functional execution
PLM & SAP
- Connected lifecycle workflows
- Portfolio visibility
- Change and compliance execution
- Structured product data
AI, Analytics & Automation
- Operational decision support
- Workflow improvement
- Applied analytics
- AI-enabled process automation
Selected Impact
Connecting product decisions to operational execution.
Current work centers on lifecycle risk, supply-chain readiness, stakeholder alignment, and digital workflow improvement in complex product environments.
Lifecycle programs
Led product phase-out, forward-development, and obsolescence initiatives across complex MedTech portfolios.
Cross-functional alignment
Connected R&D, quality, supply chain, operations, and business stakeholders around structured decisions and executable roadmaps.
Digital workflows
Improved lifecycle visibility and operational decision-making through PLM/SAP-connected processes, analytics, automation, and applied AI.
Selected Work
Inside the work.
A public planning framework, followed by workstreams from my MedTech experience. Explore the artifacts behind the approach and the operational decisions each workstream supports.
Featured Project / Public Framework
MedTech Product Phase-Out
A reusable AI-assisted planning framework for product retirement, installed-base transition, and supply continuity. It translates a discontinuance scenario into a structured package of decisions, responsibilities, risks, and evidence.
Explore the public framework ↗Independent planning framework; not a claim of deployment or measured client outcomes.
What the framework structures
Scope & transition planning
Phase-out charter, installed-base impact summary, replacement paths, and a risk-ranked roadmap.
Ownership & execution controls
RACI, decision gates, transition tracking, supply and service assumptions, and approval evidence.
Risk & communication
Risk and control register, stakeholder communication matrix, and escalation criteria.
Evidence & closure
Evidence binder, open assumptions, closure records, and continuing obligations.
01 / Product lifecycle
Product phase-out & obsolescence
Managing the intersection of portfolio change, lifecycle risk, and supply continuity in complex MedTech environments.
- Contribution
- Leading phase-out and obsolescence initiatives and translating lifecycle risks into structured execution plans.
- Collaboration
- Engineering, quality, supply chain, operations, and business stakeholders.
- Decision focus
- What needs to transition, which dependencies matter, and how stakeholders align on next steps.
02 / Connected operations
PLM & SAP lifecycle workflows
Connecting product information and enterprise processes to support lifecycle visibility and coordinated execution.
- Contribution
- Supporting PLM/SAP-driven execution and improving lifecycle processes across regulated product workflows.
- Collaboration
- Product, engineering, quality, and operations teams working across enterprise systems.
- Decision focus
- How product data and change workflows support operational readiness and clearer handoffs.
03 / Decision support
Analytics & workflow improvement
Applying analytics, automation, and AI to practical lifecycle and supply-chain decisions.
- Contribution
- Leading AI-enabled analytics and lifecycle process improvements in medical-device workflows.
- Collaboration
- Engineering, quality, supply chain, and operations stakeholders.
- Decision focus
- Where better visibility and workflow support can help teams interpret operational signals and act.
Engineering Research / Wichita State University / December 2021
Process Development for Porous Copper Wicks Using Resistance Spot Welding
Master’s project investigating a fabrication method for porous copper wick structures intended for heat-pipe applications.
- Evaluated powder size, welding duration, and equipment configuration using 120 V and 240 V spot welders.
- Used acetone-based porosity measurements and optical microscopy to characterize samples.
- Documented mass retention, mold leakage, oxidation, and equipment limitations.
Demonstrated laboratory fabrication feasibility; mechanical integrity, capillary performance, and thermal performance require further validation.
View research details on LinkedIn ↗Experience
Leadership at the intersection of product and operations.
HCLTech · Full-time · United States
Technical Lead
Leads AI-enabled analytics and lifecycle process improvements across regulated medical-device workflows, partnering with engineering, quality, supply chain, and operations while supporting PLM/SAP-driven execution.DePuy Synthes · Contract · Raynham, Massachusetts
Project Lead
Leads product lifecycle, obsolescence, and forward-development initiatives across complex MedTech portfolios, translating lifecycle risks and supply-chain inputs into structured decisions and execution plans.Ways to Work Together
Bring engineering context to your next transformation.
Connect with me about leadership opportunities or a focused conversation on lifecycle processes, supply-chain challenges, and digital transformation.
Supply Chain & Transformation Leadership
For organizations navigating product portfolios, supply-chain transformation, lifecycle risk, and digital operating change.
- Supply-chain transformation
- Product lifecycle programs
- PLM/SAP execution
- Cross-functional operating models
- Regulated or complex manufacturing
Advisory & Consulting
For teams that need a pragmatic roadmap from fragmented workflows to clearer operational execution.
- Transformation strategy and roadmaps
- PLM/SAP lifecycle process improvement
- Supply-chain analytics and decision support
- Workflow automation and applied AI implementation
About
Engineering discipline for transformation work.
I work at the intersection of supply chain portfolio strategy, product lifecycle optimization, and engineering execution. My MedTech experience spans product phase-out, obsolescence, forward development, and PLM/SAP-connected workflows.
My mechanical engineering foundation includes experimental manufacturing research at Wichita State University. Today, I connect that analytical approach with cross-functional coordination, analytics, automation, and applied AI.
Wichita State University
M.S., Mechanical Engineering | January 2020–December 2021
Jawaharlal Nehru Technological University
B.Tech., Mechanical Engineering | October 2010–April 2014
Selected Credentials
Learning aligned to product, supply chain, and AI-enabled operations.
Continuing education connects my mechanical engineering foundation with evolving supply-chain practices and digital tools.
Technical Product Management
LinkedIn · June 2026
Generative AI for Supply Chain Professional Certificate by CSCMP
CSCMP · May 2026
Digital Transformation in Supply Chains
LinkedIn · May 2026
SAP S/4HANA Essential Training
LinkedIn · May 2026
Orchestrate Multi-agent Workflows with Gemini Enterprise
Google · June 2026
Alteryx for Healthcare
LinkedIn · June 2026
Prompt Design in Vertex AI Skill Badge
Google · July 2026
Create Your First Gemini Enterprise Application
Google · June 2026
AI & Privacy
Responsible use of information on this website.
This personal website may discuss applied AI, analytics, automation, and supply-chain transformation, but it does not use visitor messages to train AI models.
When you use the contact form, the site prepares an email draft in your own email application. Your name, email address, message, and selected context are used only to help respond to your inquiry.
Any AI examples or capabilities described here are professional experience and service context. Information submitted through this website is not sold, rented, or intentionally shared for third-party AI training.
This static site is intended to collect minimal personal information. To request correction or deletion of information you previously sent, email damarakonda.manish@outlook.com.
Contact
Have a role, project, or transformation problem to discuss?
Use the form to prepare an email draft, or connect directly through LinkedIn or email.