How GenAI-Powered Self-Service BI Helps Telecom Teams and Execs Gain Competitive Advantage 

11 Dec, 2023 •

GenAI-Powered Self-Service BI Helps Telecom Teams and Execs Gain Competitive Advantage

Telecommunication teams and execs have pressing questions, and the answers are locked away in their operational systems. DvSum empowers telecommunications teams to tap that locked away data quickly and easily to unleash data insights and maximize business outcomes.  This is how GenAI powered self-service BI helps telecom teams.

By leveraging the power of Generative AI (GenAI), DvSum enables self-service Business Intelligence (BI) via natural language interactions with all your operational data.  

The DvSum Data Insights platform makes it effortless to discover, understand, and trust the data with self-service BI for everyone. With quick, secure setup and no IT hassles, it is a game-changer for operational efficiency and strategic advantage. 

This blog explores common challenges faced by telecommunication organizations to access data quickly and securely to make better-informed decisions based upon reliable insights. 

Example Telecom Use Cases 

Data consumers, staff and executives regularly struggle deriving actionable insights from data sources that tend to be hosted in different formats and systems. With luck, data might be centralized in a data warehouse such as Snowflake or a data lake such as Databricks. They might have access to operational reports or dashboards built with business intelligence tools such as Salesforce Tableau, Google Looker, and so on. Even with mature BI tooling, in the best-case scenario: Ad hoc questions requiring interactive analysis are simply not possible except when performed by analytics team members who often don’t understand the data, the nature of the questions being asked, or are not available instantly to help. 

Some specific use cases follow. 

Use Case #1:  Improve Operational Efficiency 

Maintaining a Hybrid fiber-coaxial (HFC) network is costly, tedious, and time-consuming work. Each truck roll (i.e., sending out a technician) can easily cost $US300 and can take hours to resolve. 

The more information that can be quickly and easily retrieved from a support agent and on-site technicians, the faster issues can be resolved, thus driving both operational efficiencies, and improving service level availability metrics such as time to repair (TTR) and limiting repeat or unnecessary truck rolls. 

Use Case #2:  Improve Customer Satisfaction 

Customers often contact the support team with urgent issues and a vague description such as “my internet is not working.”  

The agent thus needs to uncover information as to whether it’s a network issue, a poorly performing on-site cable modem, or other issue.  

The technician scrutinizes performance statistics such as latency, uptime, throughput, and so on. The data helps form a hypothesis as to the root cause, identify potential solutions and drive improved Customer Satisfaction. 

Use Case #3: Strategy Analysis for Executives 

Executives want fast answers to simple questions. For example: “What is my worst performing node and why.” The reasons for poor performance may not be readily apparent. While utilization could be problematic, so too could a degraded hardware element resulting in dropped packets. An out of policy over-subscribed CMTS node could also be the culprit. Perhaps a customer cable modem running outdated firmware is at fault. Executives want to know where chronic performance issues exist, the actual root cause of the problem, and the correct remediation. Missing the mark on root cause is costly, inefficient, and negatively impacts customer satisfaction. 

The challenge: self-service BI with “in-the-moment, iterative analysis” 

To say the challenge is simply self-service BI with “ad hoc analysis” understates the problem.  

Data is hard to access 

Data is in multiple systems. Often, companies build data warehouses or data lakes to federate the data into one location. This approach is costly, time-consuming, and does not cover 100% of the data needed to solve known and unknown business challenges.  

  1. Structured data is located across systems and databases 
  1. Unstructured data is found in documents like operational manuals or wiki pages 

Questions are ad hoc and iterative but technical staff are backlogged 

The ad hoc nature of analysis is also both “in-the-moment” and iterative. It is compounded by the traditional approach requiring both in-depth business intelligence and data skills. Often this means waiting for days for a report that may not have all the right information.  

Default reports and dashboards can provide a reasonable starting point, and it is possible BI assets are sometimes developed by data analysis experts who understand how to access and navigate the data model behind the scenes. Often those efforts can solidly address the more common reporting requirements; however, in most scenarios, network planners need to go much deeper and pivot to many other related questions – all very quickly, iteratively, and in-the-moment.  

Telecom professionals need to be able to hypothesize and analyze on-the-fly. However, the company usually cannot offer real-time access to centralized BI teams. Typically, staff do not have the deep BI skills needed to get answers within the minutes or seconds for a question “in-the-moment.”  

The solution: AI-powered chat interface that understands your data  

DvSum CADDI (“Conversational Analytics for Data Driven Insights”) allows support agents, technicians, and executives to find data and insights themselves with self-service BI by simply chatting with data in natural language.  

DvSum securely combines OpenAI’s GPT-4 with a powerful underlying data infrastructure – including data catalog, data governance, and data quality. Therefore, any authorized user can query data quickly, easily, and iteratively. 

With out-of-box connectors and trained on the Telecommunications domain, it is set up and running with your live data in two weeks or less. 

DvSum’s patented architecture allows you to securely work with your existing data sources and systems. Data never leaves your network. 

Built on a strong data-foundation, the DvSum Data Insights platform also includes a data quality module that can help standardize and harmonize data to drive more accurate reporting and insights. 

image 1

DvSum CADDI understands the data landscape and automatically accesses multiple databases and systems to quickly provide an answer and the sources cited to confirm the reasoning behind the answers.  

Conclusion  

DvSum CADDI empowers the telecommunications professionals to become more autonomous and productive with self-service BI to achieve “in-the-moment” analysis. Contact us today to see how DvSum CADDI can help you.  

Share this post:

You may also like