TM Forum helps Axiata harmonize its big data approach

Who: Axiata Group Berhad

What: Streamlined its approach to big data across the group

How: Created Axiata Analytics and used TM Forum’s Big Data Analytics Maturity Model

Results:

• An average 40% increase in data maturity assessment scores for the operating companies, which translates into better customer satisfaction scores (a 16X improvement in some cases) and churn reduction
• Creation of a group-wide data governance policy
• Definition of a minimum baseline to evaluate analytics use cases
• Launch of financial KPIs to measure the impact of analytics on the business

Consider this staggering statistic: A mobile operator serving 8 million prepaid subscribers generates about 30 million call detail records (CDRs) a day, or 11 billion a year. If you add CDRs for postpaid and wireline subscribers, the volume and variety of data increase substantially – and this estimate is for just one type of metadata. Add to this all the other types of data generated in a communications service provider’s (CSP’s) business, and the dilemma becomes crystal clear.

Indeed, most CSPs are struggling with the massive amount of data they collect from customers, networks and services. Malaysian operator Axiata Group Berhad is no exception, but the company does have an exceptional approach to managing all its data. In 2017 it opened Axiata Analytics to streamline data analytics across its operating companies, a process that necessarily must begin with assessing the status quo.

Axiata at a glance

Axiata is one of the leading telecommunications groups in Asia in pursuit of a vision to be “the New Generation Digital Company by 2022”. The company has transformed from a holding entity with a portfolio of pure-play mobile assets into a business with a “Triple Core Strategy” focusing on digital telco, digital businesses and infrastructure. Today Axiata's operations, which span 11 countries, include enterprise business solutions, digital financial services, digital advertising and a global digital platform that connects services and content providers to 3.5 billion consumers.

Meeting the challenge

In 2016 Axiata realized it needed to address a significant gap that had resulted from having separate data analytics teams for each of its operating companies. The teams were made up primarily of staff who had deep technical knowledge but lacked business understanding, and the few data scientists employed in Axiata’s operating companies were undertrained and underutilized. At the same time, business leaders were not leveraging data to help with business decisions. The company established Axiata Analytics in 2017 and appointed Pedro Uria-Recio Vice President and Head of the division. The team now employs 180 data professionals who facilitate sharing of best practices in analytics across the operating companies.

Axiata Analytics is cross-functional and includes marketing specialists, consultants, data scientists and engineers, full-stack developers, and designers (140 people are permanently assigned to specific operating companies, while 40 work across the group). The intent of Axiata Analytics is to implement global best practices for big data analytics in all the operating companies. To do this, Axiata turned to the TM Forum Big Data Analytics Solutions Suite, which includes a data maturity assessment methodology called the Big Data Analytics (BDA) Maturity Model.

“We used this to baseline not only the operating companies, but also Axiata’s digital companies, providing a comprehensive cross-business assessment,” Uria-Recio explains. “An additional advantage was that we could understand where we stood against other global CSPs that had previously undertaken the BDA maturity assessment.”

Assessing data maturity

To start, internal data science and marketing groups within each operating company used the maturity model to conduct self-assessments. These were followed by TM Forum-led assessments. In each case, participants answered questions in 10 operational areas, each of which contains several sub-dimensions. In all, there are 35 sub-dimensions and more than 130 questions to be evaluated and categorized. The 10 operational areas are listed below with examples of questions asked: Answers to the questions are evaluated and weighted so that maturity can be assessed at a level between 1 and 5, where 1 is indicative of a basic, initial or ad hoc implementation and 5 is market leading. The tool follows the standard five-level maturity methodology based on the Carnegie Mellon Capability Maturity Model Integration (CMMI) standard. The idea is to use the tool to assess the “present state” of big data analytics against the TM Forum global benchmarks and identify gaps and opportunities to improve across the entire business domain from strategy to governance.

• Business strategy – Is there a vision and are there goals for analytics? Are all units in the organization aligned to the BDA strategy?
• Business and functional capabilities – To what extent are BDA deliverables used in business decisions?
• Technology platform and system – Do you have the tools for handling various types of data and analytical processes?
• Architecture – How are the BDA components integrated into the Enterprise architecture? Are they scalable to meet future business needs?
• Data management – Do you have policies and processes in place for all aspects of data management such as data storage and retention, metadata management, data security and access?
• Processes – Do you have all the necessary processes and capabilities from data sourcing all the way to data presentation and feedback?
• Budget and financial tracking – Do you have a budget for BDA activities and a framework to track the ROI of BDA activities?
• Governance – Do you have a data governance policy in place?
• Organizational readiness and management – How aware and open is your organization to BDA and its benefits? Do you have sufficient talent for analytics projects?
• Key performance indicators (KPIs) and business metrics – Do you maintain a catalog of KPIs and to what extent is it being derived using analytics?

“For each one of the 130+ questions, we identified what the future state should be in six months, 12 months and 18 months,” Uria-Recio explains. “This allowed the participating operating companies and digital companies to not only compare themselves with their peer companies in the group, but also measure themselves against global best practices/benchmarks and strive towards a higher excellence score.”

He adds: “Not surprisingly, the self-assessments produced a higher score than the guided assessments, as TM Forum probed into deeper business areas and cross-functional dependencies. However, all parties were happy with the result, and an ongoing assessment environment has been created so that progressive maturity can be monitored and documented.”

Getting buy-in at the top

Importantly, Axiata required C-level executives to participate in the assessments and take responsibility for KPIs as a result.

“In any maturity assessments of this sort, the participation and support of C-level executives in the organization is critical not only from a sponsorship point of view, but also to highlight the importance of areas like data governance and data ethics within the organization, which are often overlooked at the operational level,” Uria-Recio says.

The KPIs from this exercise are measured on a C-level dashboard visible to Axiata Group and operating company chief executives, which indicates the importance of the exercise within the whole organization. In addition, the company put in place a Data Governance Council, where executives in charge of analytics and artificial intelligence (AI) meet every quarter to review the most critical aspects of data governance, most of which were identified during the TM Forum assessment.

Impressive results

Axiata has committed to undertake its data assessment over a three-year period to understand and monitor progress, but the company is already achieving promising results.

“To date, the maturity of all the operating companies and digital businesses have improved significantly, with an average of about a 40% increase in the maturity score,” Uria-Recio says. “This has manifest itself in numerous areas, ranging from increases in customer satisfaction – in some cases, by more than 16 times – to churn reduction and increased innovation capabilities. Moreover, we created a data governance policy as a result of the assessment with TM Forum.”

The policy is based on the framework from Data Management Association International – Data Management Body of Knowledge (DAMA-DMBOK), which defines standards and processes for 11 areas of data governance, including data security, data quality, data architecture, data modeling and design, and metadata management. The company also has launched financial KPIs to measure the impact that analytics have on the business.

“For each use case in the blueprint, we clearly defined how the impact should be measured in terms of incremental revenue or cost reduction,” Uria-Recio explains. “For example, if it was a monetization use case, we measured revenue uplift across all subscribers touched by any monetization campaigns versus global control groups within the same time frame. We then defined an impact index which sums the incremental revenue and cost reduction across all use cases, normalized to EBITDA. This score is called Economic Impact (EI).” Now Axiata is moving on to assess its AI maturity using TM Forum’s new AI Maturity Model & Readiness Check. This will enhance the company’s big data analytics assessment and complement its corporate governance, security and ethics domains.

“Assessing our AI maturity is not only about gaining clarity on our current status, but more importantly it is about strategically charting our path to becoming market leaders in AI implementation,” says Uria-Recio.