Business Intelligence in Telecom & VAS | business intelligence in telecom industry

Value-Added Services

Value-added services are a part of telecommunication industry which includes all the services apart from voice calls and fax transmission. Their main motive is to enhance the actual/standard value of the product/service. If we talk about mobile phones: SMS, MMS and data access are the value-added services.

Value chain of VAS

  • Content Providers- They are the originators of the content
  • Content Aggregation- They wrap all the applications & content from the developers and distribute them in order to sync with the customer’s need
  • Software Developers- They are the developers of the VAS applications
  • Technology Enablers- They provide the platform to access these services
  • Handset Manufacturer- They have various roles that comprises of embedding software links in their handsets, allowing direct access to content portals, creating services customized to the need of certain regions,
  • Mobile Operators- They provide transport and support mechanism for the mobile services to be delivered
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Benefits of Business Intelligence in telecom industry and VAS

  • Revenue Assurance has always been a critical area for the VAS providers. It helps in determining the financial performance of the business. But due to revenue leakages, the VAS providers are facing issues. Hence BI tool/model is designed to analyse/ identify these loopholes.
  • BI tool/software helps the decision support system to evolve which helps in extraction of data more quickly from different sources. Based on the BI approach DSS system is further categorized as

 

  • Model driven DSS
  • Data driven DSS
  • Knowledge driven DSS
  • Document driven DSS

 

Key-Performance Indicators

How can the businesses measure the effectiveness of the services provided by them? Answer is Key performance Indicators (KPI).

KPIs are used as a tool that enables the tracking of the performance of the services. It also helps in identifying the risks that are associated and the mitigation steps that should be implemented to avoid them. It helps in improving the effectiveness of the services. The organization is able to understand that how well they are performing with respect to their strategic goals and objectives.

Following are the KPIs for VAS:

  • Cost-Benefit Analysis
  • New account wins for VAS
  • VAS sold in a specific time period (such as during a promotional event)
  • Usage rates for various specified VAS (for e.g. number of accounts utilizing tele-voting)
  • New ways on improving customer experiences
  • Monitor workforce expenses on customer services and call centres
  • Customer Trends and Segmentation
  • Quality and Usage Analysis
  • Trend and Segment Analysis
  • Account Balances
  • Agent Efficiency
  • Customer Satisfaction
  • Average Revenue
  • Fraud Analysis
  • Network Planning and Utilization
  • Call Routing
  • Revenue Analysis
  • Service Call Monitoring
  • Compliance Analysis

 

 

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Case study

Company Profile: Aircel is a fifth largest Mobile service provider based in India. It has a subscriber base of about 83.05 million subscribers with revenue of $1.159 billion USD.

Problem: The amount of data generated from continuously growing customers was beyond the capabilities of normal spreadsheets to process. The biggest challenge was to get the granular data i.e. to get a view of single customer. Even though group of customers might have similar products and services, they might have different usage behaviour or patterns based on their segments, geographies and devices used. Getting such insights was a challenge for Aircel.

Solution: Aircel decided to use BI technology to tackle this problem. For that, they evaluated different BI tools and found one. BI facilitated customer profiling. The subscriber usage, payment and VAS behaviour helped in designing specific plans for different types of subscribers. Having a standard business intelligence platform has helped Aircel standardize definitions of major KPIs and ensure consistent availability of data with agreed logic. This reduced data revalidation efforts and the need for offline spreadmarts to support local logic.

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