Perfect Timing

A recent report from McKinsey discovered that too few telcos are managing the information available to them effectively in order to maximize profits. According to the survey of executives from telecom companies, nearly half of them say that their companies are considering investments in big data and analytics, while 30 percent of companies surveyed have actually made investments.

To decide whether these efforts improved overall performance, McKinsey estimated the contribution of big data to revenue by asking survey respondents their opinions outright, and by conducting a statistical analysis that correlated the profits of companies with their capital and labor investment and their use of big data.

Once plotted, the performance figures found that big data had a sizable impact on profits exceeding 10 percent. By co-innovating the Big Data Margin Assurance solution, SAP worked with Vodafone to ensure it wasn’t one of those telcos that are investing in big data without reaping any benefits.

Big Data Analysis in Action – Vodafone Case Study

For Vodafone, the value-add of implementing the solution was the ease of use and the increased agility. The solution’s advanced analytical capabilities enabled the transformation from reactive leakage fixing, to an assurance function that puts customer satisfaction and customer margin in clearer focus.

Prior to implementing SAP’s Big Data Margin Assurance solution, revenue leakage was being identified and managed by teams across the Vodafone footprint, guided by a Global Process Owner and five Global Process Leads based in Vodafone’s big markets. The teams suspected that there was actually more revenue leakage occurring, but their systems weren’t able to identify them.

At the beginning of the partnership Vodafone was looking for a system that would deliver:

• Fast iterative identification of leakage through visualization and interrogation of ALL data;
• Identification of more and new leakage patterns leveraging advanced analytics, learning and prediction;
• Ability over time to industrialize Use Cases and integrate with existing processes; and
• Actionable insight – granular insight for the identification of unprofitable customers or tariffs, enabling Vodafone to run detailed route cause analysis.

Analysis had to be timely to be efficient for some scenarios including:

• Customers misusing fixed rate tariffs (e.g. running SMS marketing campaigns), where costs outweigh revenues;
• Individual customers receiving multiple ‘stacked’ discounts (e.g. joining, loyalty, student, retention) driving lower and lower margins particularly when attached to already poor performing tariffs;
• Poor new offer performance where assumptions around usage or usage profiles were incorrectly estimated;
• Significant marketing campaigns and promotions linked to tariffs that are marginally profitable or unprofitable. Or tariffs that have become unprofitable through regulation or changing customer usage; and
• Incorrect network provisioning or rating where services are undercharged or can be misused by the customer.

London-based Vodafone is one of the world's largest telecommunications companies, operating in around 30 countries and partner with networks in over 50 additional countries providing mobile, fixed line and broadband services. As of September 2015, Vodafone had 446 million mobile customers, 12 million fixed broadband customers, and 9 million TV customers.

“The ability to understand granular customer profitability, specifically which customers are profitable or unprofitable and why, is a game changer for our industry,” said Thomas Holtmanns, Vodafone Director Finance Operations Central Europe and Global Margin Assurance. “SAP brings excellent capabilities to the table. SAP HANA Cloud Platform provides unprecedented levels of speed, massive processing and flexibility to query our significant data repositories. Its powerful analytics identify ways to increase margin and prevent leakage. This includes end-to-end client performance, outlier detection to uncover misuse or unreasonable behavior, new offer performance and what-if scenarios on proposed services changes.”