Assistant Vice President at Taggd
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Business Consultant - Analytics & Digital - QMS - IIT/NIT/IIM/ISB (7-12 yrs)
Role: Business Consultant - Analytics and Digital (QMS)
Reporting to: Principal-Quality Solutions
Education and Experience: B.Tech and MBA with 7-10 yrs of experience (Premier Institutes only)
This role enables the business team (manufacturing operations) on taking data driven decisions on productivity improvement, cost improvement and compliance. Capability of identifying opportunities for effective utilization of data generated from digitized core processes which will result in better business outcomes. Capability of bringing Industry 4.0 technologies to solve the business needs and process challenges.
This major ask from this role is to bring in leading digital and analytics initiatives manufacturing operations of Pharmaceutical Industry, utilizing data from Quality Management System, Manufacturing Processes, Testing Processes, People data etc.
1. Stakeholder Management
- Identification of all stakeholders
- Accurately assesses the level of stakeholder involvement and level of support
- Effectively builds credibility and trust with stakeholders
- Ability to adjust behaviour, communications style based on stakeholder needs
- Ability to keep stakeholders engaged, responsive, proactive and invested
- Ability to manage third party vendor performance by developing KPIs
- Ability to manage conflict and maintain consensus among stakeholders
2. Business Knowledge
- Industry Knowledge - Ability to identify key trends shaping the industry
- Knowledge of major competitors, customers and regulatory environment
- Knowledge of different marketing and sales models
- Displays understanding of key business processes and domain
- Knowledge of Key business metrics and their use cases
- Ability to present a viable business value proposition
3. Need Identification
- Ability to use a variety of techniques to gather requirements like brainstorming, reading SOPs, Asking probing questions etc.
- Ability to uncover additional information that is unimportant to the stakeholder but critical for the solution
- Accurately captures information in a manner that stakeholders understand and can review and validate
- Ability to translate the needs to technology requirements
- Ability to ensure that requirements link to the business goal
- Confirms that stakeholders have a shared understanding of requirements
- Ability to Benchmark processes and metrics
- Ability to identify unmet business needs / opportunities for improvement
- Consistently identifies requirement change and manages change.
4. Change Management
- Accurately assess stakeholder attitude and willingness to adopt the new solution
- Effectively use organizational network / authority structures to influence solution support
- Ability to identify stakeholder training needs and capability development plan
- Ability to foresee adoption problems and resolve the same
- Develops acceptance criteria and a plan to evaluate solution
- Ability to track solution against metrics and do course corrections to meet the same
- Ability to develop and execute a communication plan for adoption
5. Data Value
- Ability to explain the importance of data and what data represents
- Ability to demonstrate how data can be used to reduce uncertainty and risk related to business decisions and embedded decisions
- Ability to identify problems that can be addressed with data
- Ability to demonstrate importance and uses of metadata and indexing for data discovery, description, reusability, and information retrieval
6. Data Acquisition
- Ability to conduct data acquisition from relational databases and flat files.
- Ability to describe how data is organized and captured for different data types and their use cases for organization
- Ability to establish the key required internal and external data sources as well as data availability and accessibility.
7. Data Cleaning
- Ability to design, review and monitor optimal approach for data quality assessment
- Knowledge of potential data issues such as missing values, duplicates and inconsistent formats, and the implications for the data science/analytics process
- Ability to perform data audit using data summarization, sanity checks and validation
- Knowledge of a variety of exploratory data analysis methods and techniques, such as box plots, histograms, scatter plots and Pareto charts, suitable for various data types.
8. Analytic Planning
- Ability to Develop sound research questions around identified issues
- Ability to assess data in terms of reliability and appropriateness to the possible solutions
- Ability to evaluate the challenges and usefulness of multisource analytics
- Ability to Design experiments which include hypothesis-testing and problem-solving with data
- Ability to demonstrate importance of design thinking in planning data analytics solutions for human consumption
- Ability to demonstrate operationalization of fuzzy concepts to enable measurement and explain potential challenges to the validity of the analysis
- Ability to Explain how differences in data and desired outcomes impact the appropriateness of data analysis techniques (e.g., descriptive vs. diagnostic vs. predictive vs. statistical)
9. Data Modelling
- Knowledge of Statistics
- Ability to source additional information, ideas and solutions through a variety of sources such as research and relevant libraries
- Ability to build a user interface and support use of model through collaboration with key stakeholders and understanding of the problem and organizational context.
10. Data Visualization and Results Presentation
- Ability to interpret results and draw insights from analysis in the context of the original problem
- Ability to explain the role of data visualization in discovery, communication, and decision-making
- Ability to Use standard APIs and tools to create visual displays of data, including graphs, charts, tables, and histograms.
- Ability to propose a suitable visualization design for a particular combination of data characteristics and application tasks.
- Ability to describe issues related to scaling data visualization from small to large data sets.
11. Business Insights
- Ability to assess opportunities through Use case creation by identifying KPIs and ROI estimation
- Ability to build the business case for performing a BIA
- Ability to present insights to stakeholders
- Ability to identify the best visualisation tool based on detailed knowledge of the data, organisational context and data analytics capability
12. Awareness about Quality Management Systems
- Understanding of Organisational Quality Management Systems and processes
- Awareness about Manufacturing Processes, Engineering Processes, Laboratory Processes, Technology Transfer Processes and Computerized System Management Processes
- Ability to Apply tools for monitoring processes to ensure high quality