Hello I am Shanmugam
Chinna Lakshmanan

• Data Migration Factory in Safety and Pharmacovigilance
  • Implemented a data migration factory in the PV and regulatory spaces, utilized five important components: People, Process, Tools and accelerators, best practices, and an automated approach leveraging the Infosys Data Services Suite. Built the factory and conducted a few migrations to calibrate the components. The factory was run in four phases: evaluate, build, migrate, and validate, with continual improvement.
• Data Masking for HIPAA Compliance in Healthcare
  • I sold licenses for the Infosys Enterprise Data Privacy Suite data masking tool (worth 140K USD * 2) and data masking services (worth 400K USD, 350K USD) to Alameda and Molina Healthcare, two of my clients.
  • Used Delphix Tool for data masking with CareSource and LA Care clients. Coordinated with tool suppliers on a variety of features and services.
• Analytics Insights using multiple data sources
  • Adapted using four phased approaches: – Data foundation, building KPIs, insights, and using advanced analytics with AI or non-AI for the next best action. A subset of projects is provided, with each project’s TCV ranging from $150K to $300K USD.
  • Consumer reporting management system: This Project focuses on enhancing decision-making by developing and maintaining advanced Power BI dashboards that provide actionable insights into customer interactions across diverse channels (email, social media, websites, voice calls).Data is integrated from systems like CRMS, Salesforce, AWS, ERP (SAP), into Azure Data Lake and transformed through optimized pipelines into SQL Server to feed clean, reliable data into Power BI. This helps automate data processes, enabling business users to access real-time insights into customer behavior and trends,
  • Finance risk monitoring insights: Developed end-to-end analytical solutions for assessing, quantifying, and monitoring finance risk across a variety of business processes, including P2P, O2C, and R2R. The analytical solutions benefit GPO teams who implement finance controls such as P2P, O2C, R2R and FRMC team monitors finance risk.
  • Clinical Study Insights: Developed a dashboard to monitor clinical trial deadlines, usage of resources, and PM involvement. Automated proposal submissions, with accepted/rejected data consolidated into a centralized dashboard. Clinical project managers benefited from the dashboard by better study monitoring, resource planning, and task management, while leadership received faster, data-driven decision-making with centralized insights.
  • Market Competitiveness Insights: The project’s goal was to use financial data from Hyperion Financial Management (HFM) to drive strategic marketing and sales decisions, thereby expanding product reach from local to global. Decoded, modelled, processed, and constructed a data pipeline to Power BI, provided intelligent reporting. This provided senior management with real-time visibility into worldwide sales, market intelligence, and profitability, assisted in strategy formulation and improved market competitiveness.
• Data Quality Management:
  • Worked in the field of Data Quality Management entails proactively monitoring data quality across domains such as supply chain management, health, safety, and environmental sustainability, quality event management, and third-party management, generating DQ scorecards to track performance, and carrying out data migrations from legacy on-premises platforms to advanced AI-enabled cloud platforms while maintaining data integrity. The downstream data users, including unit EDOs leadership, benefit from greater data confidence by making more accurate and timely decisions.

• Consulting engagement in Data Management at enterprise
  • Data Management Strategy: Incorporated data management concepts into a company’s operational framework to make it a long-term activity and emphasize the significance of managing “data as a meaning” throughout the organization.
  • Data UCs identification for implementation and budgeting approval: Identify Data Capability & Maturity (DCAM) report, identify target state across Data Capability & Maturity domains, develop suggestions to attain necessary target state with high level Data Management Use Cases, and then build a plan for prioritized Data Management.
  • Data Quality Maturity: Defined the goals, approaches and plans of action to ensure that data content is of sufficient quality to support defined business and strategic.
  • Data Governance Maturity: Established the rules of engagement, prioritization and enforce compliance by definition of rules for data movement, established control guidelines and methods for evaluation of adherence to policies and procedures.
• Consulting engagement for Cataloged Pricing for Data Services
  • Facilitated Client Workshops and Interviews to map current business processes and performed an in-depth value scan to identify project needs and deliverables. Performed extensive primary and secondary research to examine the cost structures of over 60 IT services (data governance, security, mart, visualization, quality, and migration), mapping cost components to service delivery procedures and developing a price model for each service. Developed and implemented a dynamic pricing model utilizing automated process, simplifying the tracking and computation of cost components for complicated service offers, and streamlining business procedures to improve service costing.

• AI Democratization 
  • A foundational AI marketplace is established. It is used by all verticals in life sciences organizations, and the backend is supported by Veeva, SAP, SharePoint, Microsoft Dynamics, and ADL for retrieval. It allows business users to extract information about products, and sensitive and confidential data is restricted based on the business user profile. This solution is using Gen AI and software engineering for document retrieval, question answering, code generation, and text extraction.
• Gen AI in review of SDLC Documents submitted for CSV audit
  • Developed and deployed a web interface-based LLM application in SAP BTP using Claude models to undertake preliminary review of SDLC documents submitted for CSV (Computer System validation) review to improve processes and optimize the staff. Developed a performance evaluation metric to assess the correctness and consistency of output from the LLM model.
• AI Statbot for Biostatisticians
  • Until now, MA and ECPs relied solely on detailed trial reports or biostatisticians to analyze clinical data. The company aspires to pioneer AI-powered clinical intelligence ecosystems. AI Statbot can accurately convert English-language queries into statistical code for clinical outcomes, like GPT-4’s capabilities. Statistic execution and output interpretation are both automated. Demonstrated the technical possibility of knitting such components together.
• Pharmacovigilance anomaly detection
  • Pharmaceutical businesses manage massive amounts of data from various sources (e.g., call transcripts, audio, photos, emails, and social media, regulatory reporting). Anomalies such as unexpected adverse events, PII, and product quality compliance characteristics can have serious regulatory and safety consequences. This project detects anomalies, classifies product safety, extracts relevant attributes, and summarizes the content using Gen AI.
• Self Service Chatbot for Sales and Marketing associates
  • Developed a web-based chatbot application utilizing Azure Open-AI GPT to handle structured and unstructured information from ~1000 product manuals maintained in a centralized repository (client High Spot Backend Datastore). Managed complete training data preparation (targeting the medical sector) to enable high-quality, nuanced exchanges with the chatbot. Created a vector database capable of supporting extensive search capabilities within the chatbot framework. Ensure that the solution is accurate, reliable, and scalable (user and product manuals). Include extra customization and integration features with Microsoft Teams.

• AI / Gen AI Strategy and Operating Model
  • Assessed the enterprise AI strategy and operating model in terms of people, process, tools, and technology in the Medical Technology Organization and submitted an assessment report on how to implement the AI risk framework, AI governance, AI development and deployment, and how to incorporate RAI principles into AI development.
• Innovation AI CoE
  • Client sought to use a push and pull strategy to ensure that their UCs were PoC-ed, while Infosys was asked to suggest novel AI UCs and have them approved by the central advisory board for PoC. R&D, Commercial, Pharmacovigilance, and Supply Chain are the primary focus areas for experimentation and proof-of-concept testing prior to production.

• AI SDLC Framework
  • Epic was used to generate the user story, which was then validated by humans in the loop for more coverage. User stories were used to create technical specs, functional specs, data specs, test cases, and risk assessment criteria for SAP and non-SAP projects. Piloted and found accuracy at 60%, with improvements and tuning underway to target 80% accuracy.
• Periodic Control Assessment: –
  • IT controls for computerized systems are assessed to see whether the system is fit for its intended usage. It will evaluate the facts and offer a concise report on control effectiveness or ineffectiveness, with impacted reasons.
• CSR Summarization
  • Summarized Clinical Study data into comprehensible prose to identify significant and insignificant measures. It focuses on adverse event summaries, mortality summaries, significant adverse events, clinical laboratory evaluations, and other safety assessments such as vital signs and electrocardiograms.
• Patient Support Program Chatbot
  • Demonstrated that GenAI can answer business-related inquiries and deliver graphical solutions using structured data. It eliminated a team of Power BI and Tableau dashboard developers, reducing the staff by 40%.
• SAP Training doc generation
  • Used open-source SAP S/4 HANA information to generate training materials based on project specific documents (BPD and test cases).

Big wins demonstrating domain or functional knowledge, ousted established vendors

• Patient Support Program
  • Patient Support Program domain capability demonstrated – HCP and patient journey in specialty pharmacy services, hub services, patient adherence support, on-demand clinical support, process transformation and optimization. Patient accessibility and affordability Payor Landscape Assessment
• Revenue Defender Leakage
  • Demonstrated the Value & Access landscape and identified early hypotheses across the end-to-end function to examine during the revenue defender program for eliminating major revenue leakage.
• RAI Enablement and Implementation
  • ResponsibleAI AI principles, policies, Acts, laws, NIST framework, and ISO 42001 capabilities have been shown in the healthcare and life sciences industries. Enablement in progress for AI Use cases Consolidation, AI Assessments, AI Governance, AI literacy, AI Tools implementation, AI Procurement, AI adoption, AI Sustainability, etc.

This Program was S4 HANA implementation for 72 countries.

• Developed business process flow charts and understood processes across several marketplaces, including orders to cash, accounts receivable, and procure to pay for pharmaceutical clients. The customer embraced a $2 million, multi-year effort to solve process automation gaps based on our roadmap and recommendations.
• Collaborated with SAP Basis team to implement Epi-Use Tool services across Dev, QA, UAT, and Dress Rehearsal environments for Organon. I was employed with SAP Masking for Non-Production and production environment.

In a multi-vendor environment, carried out two high-level transformation programs and reported progress to the SVP. Involved in the complete waterfall process, including program adoption and transition to BAU, which includes benefit sustainability.

• Implemented an incentive compensation management system for agents. The implemented program impacted the organization’s HR, Finance users, Finance Operations, and Legal divisions.
• The travel, costs, and invoice modules integrated with SAP Concur. An organization underwent a shift that impacted the teams in charge of travel, immigration, finance, accounting, auditors, and HR.

This generated new business and spurred expansion.

• Ataccama IDQ: Upskilled in Ataccama IDQ, an AI and ML data quality management solution. This training was intended for existing IDQ employees when the client transitioned from IDQ to Ataccama.  The implementation of rules, configuration migration in the pilot, and extended pilot demonstrated Infosys’ capabilities. We acquired the implementation businesses and increased our reach in a variety of areas, including R&D, Commercial, Supply Chain, Finance, ESG, and P&O.
• DCAM enablement: Trained in DCAM enablement in six phases – assess, collect, score, actionize, define and review in each component; data management strategy and business case, data management program and funding model, data quality management, data control environment, business data architecture, data governance, data technology and architecture. This proved the capabilities and performed DCAM assessment for each business unit every six months and presenting the report to the VP of data analytics.
• IAPP AIGP (AI Governance Professional): With the advancement of AI technology, professionals across all industries must understand and implement acceptable AI governance practices. The AIGP accreditation helps us maintain the uptrends in the industry, AI acts, and laws in managing the AI products.