Redesigned Data Ops for a Telecom Major to Achieve Operational Excellence

About the client

Leading telecom provider

Challenges

• The client lacked data-driven insights, hindering service operation optimization.
• The existing data warehouse lacked capabilities for analyzing unstructured customer data.
• Data needed normalization for analysis due to format and source variations.
• Extracting insights from unstructured data required tools their infrastructure lacked.

Approach

• The approach included identifying KPIs, implementing data collection mechanisms, and utilizing analytics tools for analysis.
• Select processing tools, develop algorithms for organization, and integrate analysis capabilities into existing infrastructure.
• Normalize data by assessing formats, developing pipelines for standardization, and implementing quality checks for consistency and accuracy.
• Extract insights from unstructured data by selecting NLP tools, integrating them into pipelines, and training analysts on their effective use.
• Leverage Databricks by evaluating, deploying, developing workflows, and training personnel for optimizing service operations.

Solution

Innover designed and developed a transformative data solution that helped unlock insights from unstructured customer data, empowering optimization of service operations through comprehensive analysis of technician and customer behavior KPIs.

• Utilized 26 data sources to create a nested loop data model.
• Employed an iterative approach for model development to tackle business challenges.
• Addressed unproductive truck roll optimization.
• Performed customer sentiment analysis and churn prediction.
• Conducted chronic caller analysis.
• Implemented field force capacity planning and optimization.
• Worked on repeat ticket reduction.
• Developed an interactive PowerBI dashboard featuring key KPIs related to technician and service performance.