Senior Manager, Process Operations & Product Management
Takeda · Bengaluru
Job Description
Objective / Purpose:
Support the Head of Process Optimization & Enablement in applying operational excellence and human-centered design to evaluate, redesign, and continuously improve the processes underpinning GPT (Global Program Team) ways of working and the broader R&D Operational Excellence function. This role combines process design expertise with technical acumen to translate business needs into scalable, technology-enabled solutions — automations, dashboards, and digital products — that improve insight generation, data usability, and operational efficiency. Working closely with Data, Digital & Technology (DD&T) and business stakeholders, the role stewards a practical, Lean-based optimization framework and moves teams beyond static documentation toward integrated, user-centric, digitally enabled solutions that balance enterprise standards with business flexibility.
Accountabilities:
1) Process Design & Improvement
Evaluate current processes and ways of working for GPTs and R&D Operational Excellence functions, and partner with the Head of Process Optimization & Enablement and function owners to redesign prioritized processes against strategic needs.
Identify possible opportunities where AI, automation, or digital tooling can reduce manual effort, accelerate cycle time, or improve quality — recommending what to automate versus keep human-in-the-loop, and the expected value.
Incorporate automation, analytics, and emerging AI capabilities to support self-service and system-generated insights that improve decision-making and operational effectiveness.
Reimagine static outputs (e.g., fixed dashboards) as flexible solutions that support both standardized reporting and user-driven data exploration.
2) Technology & Data Enablement
Collaborate with business owners, DD&T, and data teams to translate business requirements into scalable technical solutions for redesigned processes.
Embed and optimize data within process implementations for structured, reusable inputs, ensuring alignment with enterprise data standards and governance.
Identify and evaluate data sources critical to process improvement initiatives, assessing availability, accessibility, and usability.
Hands-on development and delivery of technical prototypes and demos to validate process improvements, demonstrate new capabilities, and drive adoption.
Partner with DD&T and data quality SMEs to uncover barriers to data access and establish frameworks that balance end-user flexibility with a single source of truth.
Maintain accessible, well-governed process documentation — interconnected with related resources and structured for long-term version control — so functional leads can apply Process Optimization & Enablement methods independently.
3) Continuous Improvement & Adoption
Lead follow-up on prototypes to capture lessons learned and refine solutions before broader rollout, keeping a clear line of sight from design intent to adoption and outcomes.
Support and ensure post-implementation assessments are completed to capture value, ROI, and opportunities for continuous improvement.
Represent process design work in working groups and governance forums on behalf of the Head of Process Optimization & Enablement.
4) Cross-Functional Enablement & Relationships
Provide process design support and technical reference guides across R&D Operational Excellence functions, in alignment with the framework set by the Head of Process Optimization & Enablement.
Partner with the Operations & Digital Enablement Lead to train peers and line function teams, building an internal process design capability that isn't dependent on any one individual.
Define simple leading and lagging indicators (e.g., cycle time, rework, adoption, quality) that support periodic process health reviews, and recommend the next round of improvements.
Build effective working relationships with GPT Enablement, CAPTIVATE process leads, R&D line function leaders, transformation program leads, and DD&T partners to ensure designs reflect real operating constraints and surface upstream/downstream dependencies.
Education & Competencies (Technical and Behavioral):
Bachelor's degree required; advanced degree preferred, with 4-6+ years of experience in process design, business operations, data/analytics, or digital transformation.
Strong, hands-on command of operational excellence and process improvement methodologies (e.g., value-stream mapping, metric development, root-cause analysis, RACI design, and Kaizen-style improvement events).
Demonstrated experience supporting end-to-end process redesign in matrixed organizations — from current-state diagnosis through future-state design, pilot, rollout, and sustainment.
Systems-thinking orientation, with the ability to see how a process sits inside a wider operating model and design processes that coherently accommodate upstream and downstream impacts.
Experience with data platforms, analytics tools, or reporting environments (e.g., Power BI, data models), including a working understanding of how AI and automation can be applied to enterprise processes.
Understanding of data governance, data standards, and data quality principles.
Strong analytical orientation — comfortable defining simple process KPIs and using data to diagnose issues and quantify improvement.
Able to operate across functions without direct authority and bring senior stakeholders along.
Preferred: familiarity with cross-functional drug development execution, GPT ways of working, and portfolio/project/resource management processes within R&D.