CSPs need to leverage data across the entire organization
The value of data to communications service providers is not in question. What is unclear, however, is whether they are capable of leveraging it across the entire organization. Indeed, lack of a cohesive big data strategy is arguably the biggest obstacle to them becoming digital service providers.
16 Dec 2019
CSPs need to leverage data across the entire organization
The value of data to communications service providers (CSPs) is not in question. What is unclear, however, is whether they are capable of leveraging it across the entire organization. Indeed, operators have been trying to come to grips with big data and data analytics for the last decade, and lack of a cohesive strategy is arguably the biggest obstacle to them becoming digital service providers (DSPs).
For this report we conducted a tightly focused survey of people working in data analytics roles within CSPs. Perhaps unsurprisingly, 88% of respondents said they consider the effective use of data across the entire organization essential for their businesses (see graphic opposite).
The percentage almost certainly would have been lower had we included different job roles in the survey. Many senior executives, for example, don’t know how data is used in their organizations. They may see the results of using data in a customer loyalty program or an initiative to reduce operating costs, but they don’t necessarily connect results to the collection and analysis of data about customers and network performance.
The reality is that a very small proportion of telco board members have a background in digital technologies or capabilities. As such they may lack insight into how data analytics underpin and shape successful 21st century organizations.
In this report we explore how CSPs are collecting, storing and using data, and we offer guidance to help operators leverage data to improve customer experience and optimize networks. But first it helps to understand the kinds of data CSPs generate and what they want to do with it.
For this report we conducted a tightly focused survey of people working in data analytics roles within CSPs. Perhaps unsurprisingly, 88% of respondents said they consider the effective use of data across the entire organization essential for their businesses (see graphic opposite).
The percentage almost certainly would have been lower had we included different job roles in the survey. Many senior executives, for example, don’t know how data is used in their organizations. They may see the results of using data in a customer loyalty program or an initiative to reduce operating costs, but they don’t necessarily connect results to the collection and analysis of data about customers and network performance.
The reality is that a very small proportion of telco board members have a background in digital technologies or capabilities. As such they may lack insight into how data analytics underpin and shape successful 21st century organizations.
In this report we explore how CSPs are collecting, storing and using data, and we offer guidance to help operators leverage data to improve customer experience and optimize networks. But first it helps to understand the kinds of data CSPs generate and what they want to do with it.
What is data?
CSPs use two main types of data in their businesses:
Data created by customers – which tends to fall into three categories: traditional customer relationship management (CRM) data collected from billing records and interactions with contact centers and retail stores; data collected from digital touchpoints including websites, mobile apps, chatbots and posts on social media; and performance data (traditionally the focus here has been on dropped calls and location but increasingly is on throughput, congestion and visibility of the packets flowing across the network)
Data generated internally by employees and systems – which includes information in IT systems, which contain lots of different types of data relating to the business and customers, and network data about how the network is performing and customers’ usage of the network CSPs are transitioning from focusing on simple business intelligence to big data analytics. Big data has resulted from an explosion in real-time usage data and deployment of cloud-based systems and technologies. Now operators are working to develop cohesive strategies to leverage it by applying artificial intelligence (AI) and machine learning across all parts of their businesses.
Part of transformation
The benefits of successfully leveraging data across the entire organization are the same as for digital transformation more broadly:
Improving customer experience – without leveraging data from and about their customers, CSPs cannot hope to match the experience that DSPs like Amazon, Facebook and Google deliver. However, telcos are at a significant disadvantage. Whereas the whole customer lifecycle is digital for DSPs, most CSPs interact with their customers through a wide variety of channels including retail shops and contact centers as well as digital interaction. Furthermore, IT systems supporting customer touchpoints are often poorly aligned.
Improving operational efficiency – this is a broad category that includes converting all interaction with customers to digital channels in order to reduce the size of call centers, and better managing network alarms and adopting self-healing technologies. CSPs are also looking to reduce costs by improving capacity planning and introducing proactive fault management.
Increasing revenue from new and existing services – when it comes to upselling and cross-selling services to customers, the effective use of data plays an extremely important role.
Most operators are transitioning to bundled-service strategies (for example, triple-play or quad-play services or bundling over-the-top services like Netflix and Hulu with mobile subscriptions). But their ability to target customers effectively is compromised because of their inability to leverage usage data.
AI & machine learning
The promise of AI and machine learning is breathing new life and urgency into CSPs’ efforts to leverage the vast amounts of data they have. For example, network automation has emerged as a key requirement for 5G and will require the effective use of AI.
AI and machine learning also provide a focus for strategies to effectively leverage data. Operators and industry organizations such as TM Forum are compiling use cases for AI across departments and developing a data model to help operators use data more effectively, which we’ll explore in the report.