SAMEER TIKU

A result-oriented Digital manufacturing operations and Analytics Director with 22 years of combined domain experience in manufacturing and AI . I have spearheaded and optimized multibillion dollar asset base spanning across 4 continents and 21 global clients in business operations through digital transformation, product development and navigating through people , process , technology and governance landscape. Demonstrated track record in developing and implementing strategic initiatives that enhance operational efficiency, thrive goals of Sustainability set up by UN through implementation of analytics and orchestrating the footprint to drive revenue growth within the AI sector.

Professional Experience:

Principal Director Accenture , Pune — [May 2021 – till now]

• Led AI strategic initiatives, solution architectures, operating models business processes, implementations , product roadmaps of APM(Asset performance management) Predictive Analytics, Digital Twin in now, near and next horizons to achieve north Star for multiple organizations.
• Developed and implemented strategic plans for multiple organizations to align with company goals and objectives to AI lead initiatives through digital maturity assessment, cultural assessment, and industry and outcome based use cases.
• Product alignment with market trends, human centered design, competitive landscape, best of breed features resulted in operational efficiency of 10 -12% through unplanned downtime reduction, risk exposure mitigation, reduction in labor cost due to integration of disparate sources
• Up-skilling, staff augmentation , talent hiring and talent pool development . A growth of 5 folds in headcount and secured a budget of 15 million USD to enhance the product.
• Spearheaded creation of innovative product strategy for Analytic Industrial services with Microsoft Azure leading to a new revenue stream that meaningfully boosted the analytic COE revenue by over 10%.
• Developed KPIs to monitor AI performance, making data-driven adjustments to strategies as needed.
• Risk identification and risk assessment framework and workflow to mitigate consequences arising from non compliance.
• Product strategy creation focusing on Human impact, Transparency, GDPR, safety, cybersecurity, accountability.
• Establish a robust data strategy to ensure the availability, quality, and security of data for AI applications.
• Implement data governance frameworks to manage data lifecycle and compliance.
• MVP to test AI output in controlled environment. Evaluate pilot results and develop strategies to scale successful projects across the organization.

Creation of robust data strategy like data architecture, data governance framework for entire enterprise using best practices of ISO 14224 and CFHIOS.

• Lead and developed solutions for energy and mining clients on GE Predix platform to mitigate operational consequences.
• Institutionalizing of asset performance management workflows .
• Adoption and enhancement of GE Predix platform.
• Integration of disparate sources like APM, Historian, Alarm management, SAP PM, MES, APC and SCADA to provide holistic View.

Use cases Delivered:(High level view)

• Enterprise wise data integration and contextualization to host engineering, maintenance and operations data to enable a single source of truth and GEN AI based LLM models.
• Remote inspections to support connected worker initiative.
• Unified view of Safety critical elements and unification of HSE enabled use cases like isolation management in ePTW , dynamic barrier analysis and MOC resulted in reduction of 20% compliance cost.
• Anomaly detection based predictive analytics on critical assets implementation like Compressors, Control valves, Exchangers, coolers, Turbines, refrigeration , units to detect onset of failure and hosting on layer on 3D model. Financial risk reduction due to unplanned breakdown, proper optimization, reduction in energy consumption delivered significant improvements in EBIT(1 to 3% , ROCE (4- 6%).
• Orchestration ,fine tuning and retrieval of data on demand from multiple documents, manuals, and reports through RAG based retrieval techniques lead to reduction in 45000 Manhours of entire enterprise.