Four goals for the data-driven telco

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Truly data-driven organisations excel at understanding their customers, driving new revenues, and evolving their business models. In order to achieve these benefits, telcos will need to create more useable data sets, accessible to all across the organisation – and to external partners in the future. What practical steps should they take to get there?


Format: PDF filePages: 30 pagesCharts: 10Author: Charlotte PatrickPublication Date: May 2022

Table of contents

  • Executive Summary
    • Capabilities telcos should develop over the medium term
    • What will telcos focus on in the mid-term?
    • Next steps
  • Becoming a data-driven telco
    • Short term drivers
    • Barriers in the short term
    • Long term drivers
    • Barriers in the long term
  • Availability of data
    • Use of data fabrics
    • Better data labelling
    • Rise of synthetic data
    • More intelligent data selection
    • Telco strategies for cloud usage
  • Equipping people
    • Augmented analytics and business intelligence
    • Decision intelligence
  • Work on governance
    • Governance across the telco
    • Agility in governance
    • Governance for AI and machine learning
    • Ethical governance
    • Improved measurement of governance
    • Governance in ecosystems
  • Index

Table of Figures

  • Figure 1: Timeline of telcos’ progression to being data-driven organisations
  • Figure 2: Capabilities for a data-driven telco
  • Figure 3: Drivers and barriers to becoming a data-driven telco
  • Figure 4: Key impacts on future telco markets
  • Figure 5: Components of a data fabric
  • Figure 6: Characteristics of telco workloads suitable for cloud vs on-prem
  • Figure 7: SAP Digital Boardroom augmented analytics solution
  • Figure 8: Emerging governance priorities for telcos
  • Figure 9: Telcos will use a combination of four governance styles
  • Figure 10: Examples and purposes of possible telecoms governance KPIs

Keywords: 5G, 6G, AI (artificial intelligence), AI and data analytics automation, algorithms, analytics, automation, big data, big data analytics, business models, Cloud, data, data centre, data ecosystem, data monetisation, decentralisation, Disruption, IoT, IoT analytics, legacy, Machine Learning, monetisation, natural language processing, telco data monetisation, telco data use cases, Use cases