Abhinav Yalamanchili

• Forecasted patient and prescription trends across 10+ therapeutic areas, contributing to accurate revenue projections and strategic planning.
• Collected and analyzed patient-level data from multiple databases, improving the precision of patient-based forecasts by 20%.

• Developed and tested user-friendly Excel dashboards to communicate key performance indicators (KPIs) and risk potential to brand managers and business leaders, reducing report preparation time by 30%.
• Created scenario-based models that helped portfolio managers and manufacturing controllers make data-driven decisions, increasing forecast adoption by 15%.

• Supported business development forecasting exercises, identifying potential revenue opportunities and assessing cost implications, resulting in a 25% improvement in early-stage financial assessments.
• Reconciled forecast assumptions with analyst and modeller reports, reducing data discrepancies by 10% and ensuring alignment with secondary data sources.

• Managed data analysis, transformations, and loading into forecasting solutions, streamlining data processing and improving reporting accuracy by 20%.
• Created PowerPoint presentations for client teams, tailored to specific business needs, enhancing client satisfaction scores by 10%.

• Supported solution testing and dashboard development, ensuring system reliability and reducing post-launch issues by 15%.
• Trained 30+ users on forecasting and reporting solutions, increasing system utilization across departments by 25%.

1. Requirements Gathering & Analysis:

• Facilitated requirements-gathering sessions with business stakeholders and clients, identifying process gaps that led to a 20% improvement in project delivery accuracy.
• Translated business requirements into functional specifications, reducing rework time by 15% and ensuring clearer communication across teams.

2. Data Analysis & Reporting:

• Analyzed customer usage data, providing actionable insights that contributed to a 10% increase in customer retention.
• Automated 30+ recurring reports, cutting manual reporting time by 50% and increasing report accuracy by 25%, driving more informed business decisions.

3. Process Improvement:

• Optimized end-to-end business processes, reducing cycle time by 30% through workflow automation and enhancing overall operational efficiency.
• Implemented process changes that decreased service ticket resolution time by 20%, resulting in a 15% improvement in customer satisfaction scores.

4. Project Management:

• Led cross-functional project teams to deliver projects on time and under budget, achieving a 95% on-time delivery rate.
• Utilized Harris's project management modules to track progress, reducing scope creep by 25% and aligning project outcomes with client expectations.

• Collected and analyzed over 500 data points weekly on COVID-19 trends and intelligence, identifying key drivers to support accurate pandemic forecasting.
• Conducted root-cause analysis on major forecast variances, reducing discrepancies by 25% through identification of trends and corrective actions.

• Developed and maintained sales and health forecasts with an accuracy rate of 90%+ by gathering, validating, and analyzing comprehensive data.
• Improved forecast accuracy by 15% through collaboration with cross-functional teams and building a centralized repository for forecasting and risk analysis.

• Collaborated with stakeholders to establish measures for forecast accuracy and bias, ensuring alignment on key forecasting metrics.
• Prepared and presented detailed forecast review reports to senior management, driving actionable changes based on forecast reviews.

• Identified and led opportunities to improve forecast accuracy, resulting in a 20% reduction in forecasting errors through the implementation of new methodologies.
• Developed and updated Standard Operating Procedures (SOPs) and system documentation, ensuring adherence to company standards.

• Trained 50+ users on COVID forecasting systems, enhancing system adoption and usage across departments.
• Collaborated with technical teams to integrate COVID intelligence into forecast models, streamlining the forecasting process for better decision-making.

1. Research & Development:

• Led a research project from inception, developing an automated solution to detect Noise-Induced Hearing Loss (NIHL) using audiogram data, delivering the final product within 6 months.
• Conducted comprehensive research on NIHL, identifying key patterns and trends that contributed to a 30% improvement in diagnostic accuracy.

2. Data Analysis & Automation:

• Developed data models and algorithms to automate the analysis of audiogram data, reducing manual analysis time by 40% and improving the overall efficiency of the process.
• Performed in-depth investigative analysis on audiometric datasets, ensuring accuracy and validity of results, which increased the precision of hearing loss detection by 20%.

3. Agile Project Management:

• Collaborated with cross-functional teams in a SCRUM environment, ensuring timely delivery of project milestones and maintaining a 95% on-time completion rate across sprints.
• Facilitated sprint planning and daily stand-ups, ensuring alignment of tasks with deadlines and mitigating any potential blockers that could hinder progress.

4. Stakeholder Collaboration:

• Worked closely with stakeholders to define project scope and expectations, integrating feedback into the research process to align with business goals.
• Delivered presentations and reports on the progress and outcomes of the research, enhancing stakeholder confidence in the project by 15%.

5. Innovation & Process Improvement:

• Identified opportunities for further automation in audiometric testing, leading to a proposal for a new solution that could reduce overall process time by 25%.
• Contributed innovative ideas that were later adopted into the company’s product roadmap, leading to increased interest in automated health solutions.