How can telcos apply the latest practices in AI and analytics? And how are they doing?
Deployment of digital twins by telcos runs significantly behind some verticals as they have less compelling use cases. However, they are now going live in multiple network-related areas. What are the key drivers and barriers of digital twin adoption in telecoms?
Telcos have been creating data related products and services to support their enterprise customers for the last 10 years. As this market expands into a wider range of more complex customer needs, we explore where the best opportunities are for telcos to support enterprises in their transformation into data-driven organisations.
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?
Analysis of the edge computing market highlights video analytics as a short-term opportunity with a large edge-addressable market. We examine the video analytics market today, the role of edge in stimulating growth, and the actions telcos can take to achieve success in this space.
This research defines and considers the topic “Future of work” – exploring the impact of emerging technologies and economic and social changes on telcos, and identifying how A3 (analytics, AI and automation) can help solve new challenges.
In this report we update our initial model of the potential financial value of adding analytics, AI and automation (A3) into a telco’s processes. Our bottom up assessment of 150+ processes across networks and operations, customer channels, sales and marketing shows telcos can achieve financial benefits amounting to more than 8% of annual revenues.
The forces of divergence and convergence have shifted in favour of the latter, with the move to cloud native and software-defined networking. We evaluate how operators can take advantage of convergence to drive greater efficiencies, scale economies and service innovation.
Improving customer experience has been a focus for telcos for almost 20 years, but there is still some way to go. This research looks at how A3 is helping telcos today and how it can address key challenges in future.
We spoke to Telefónica about its 10 year experience of building a data monetisation business (previously called LUCA). This deep dive into its strategy, organisational structure and the products developed highlights what it takes to succeed in this challenging market.
As analytics, AI and automation (A3) technologies mature, we explore nine potential A3 capabilities telcos could offer to their enterprise customers. We identify the sweet spots for telcos by assessing the importance of each of the nine capabilities across 14 industry verticals and mapping them against telcos’ existing levels of expertise.
Mobile operators have many of the assets and capabilities required to become a major force in financial services, but they will also need to tap expertise in data analytics/machine learning.
Adopting automation, AI and data analytics is a key pillar of telco strategies. This report aggregates the surveyed opinions of more than 100 telecoms execs and provides recommendations on the practical roadmap for achieving this.
Our latest research covers industry perceptions of likely changes regarding telco investment priorities and activities in 2021. It looks at the relative importance of different technologies (e.g. 5G, automation), propositions in enterprise and consumer markets, networks, strategy and leadership.
Will many other digital commerce and content companies follow Reliance and Rakuten into the consumer connectivity market?
Over the next 10 years, advances in A3 are going to drastically change the way telcos manage their core businesses, how their businesses are organised, and the demands of their customers. We outline the core capabilities A3 capabilities telcos will need to remain competitive in their core business and to be effective ecosystem players over the next ten years.
Singtel’s data analytics business, DataSpark, has achieved some impressive results, but scaling is hard. Its path highlights lessons on dealing with the challenges facing all telcos building new businesses, e.g. how to govern and manage relationships with the broader organisation, measuring success, and finding the right skills and partners.
AI, coupled with a data-centric approach and automation, looks like it is starting to pay back the operators who have led in this field. Where can industry leaders go next, and what are the key lessons for others on how to ‘jump the curve’?
Assuring networks, services and devices in the world of 5G, edge and IoT demands new capabilities in automation, AI and analytics (A3) at the edge of networks. This report sets out a roadmap for telco decision making around assurance tool creation, deployment and possible monetisation.
It has been six years since telcos began introducing data and analytics products into their portfolio of enterprise services. This report assesses the potential value of data monetisation across 13 verticals, and by type of data analytics product.
True E2E automation has not yet been achieved, but network automation is a reality now, and one which telcos must master to survive. What steps are telcos taking to implement network automation, what challenges must be overcome and what benefits can be expected?
We consider the potential financial value of adding analytics, AI and automation (A3) into a telco’s processes. Our modelling assesses the value of A3 in more than 150 processes across core network operations, customer care channels, and sales and marketing.
This report maps the application of analytics, automation and AI (A3) across the telco organisation, identifying where each technology is most effective, and providing a foundation for understanding and planning the use of A3 to improve core business performance. Part 2 will estimate the potential value of applications.
Finnish telco, Elisa, repeatedly achieves surprising wins with innovative new propositions. For example, it now sells Elisa Automate, its fully automated Network Operations Centre (NOC), to other telcos. Most telcos buy their NOCs from vendors. How does this relatively small telco punch so much above its weight? At the heart of the answer is a Finnish word which cannot directly be translated to English: sisu.
Our latest research shows that only one in five telco AI projects has made the leap from proof of concept (PoC) to live deployment. How can telcos improve the hit rate and achieve real performance improvements?
Although nearly all operators aspire to deploy autonomous networks and personalised customer services, few have actually implemented advanced analytics at scale across their organisations. Almost universally, telcos are hampered by incomplete and siloed data sets and cultural resistance. What have the industry’s leaders done to overcome these challenges?
Autonomous networks are still many years away, but AI-supported automation is a reality now, which all telcos must master to survive. What steps must telcos take to implement AI in network maintenance, optimisation and planning, and what is it worth?
Telefónica’s systematic and sustained push into personal data management holds valuable lessons for other telcos about building trust and credibility. The report also covers personal cloud / data plays by NTT DOCOMO and financial services company Mint.
There’s no doubt that AI is a transformative technology, and chatbots are a focus for many telcos looking to benefit from it. We look at case studies from Telenor, Deutsche Telekom and AT&T to find telcos’ best path toward employing AI. Despite the hype, chatbots may not be the best first step.
Big data analytics could help telcos improve performance, rebuild revenues and regain relevance with consumers, but it is not a quick fix. This report looks at what telcos have done in this area so far and what they need to do next.
Artificial intelligence (AI) is more powerful and affordable than ever, and the leading consumer-facing AI platforms – Google, Apple, Facebook and Amazon – are in an arms race to bring the technology to smartphones. AI will radically change the way people use smartphones, but what are the implications for data traffic and consumer expectations, and what role should telcos play in this evolution?
Artificial intelligence (AI) is improving rapidly thanks to the growing use of deep neural networks to teach computers how to interpret the real world (deep learning). These networks use vast amounts of detailed data to enable machines to learn. What are the potential benefits for telcos, and what do they need to do to make this happen?
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