Consumer & Entertainment Services, Internet of Things , Ente...
Our digital futures will be defined by how service providers, enterprises, and consumers drive and respond to major disruptions around artificial intelligence, data centricity, personalization, trust, privacy, OTT video, digital giants, and supersizing, according to speakers and delegates at Ovum's recent "Digital Futures 2018: Accelerating Growth in a Data-Driven World" event.
What emerged during the event is how critical it is for businesses to focus on introducing a data-centric strategy before progressing toward implementing an artificial intelligence (AI) strategy. In addition, giant strides will be made in digital assistant functionality in the future. Personalization, for example, is where AI can have the biggest effect on the consumer experience. AI will create reactive environments, so progress will be made in areas such as self-driving cars and emotion capture. Soon, though, innovation will no longer be just about "personalization" so much as "personification" – there is no point having a 360-degree view of customers if you cannot act on it and solve their problems. Companies are also beginning to see privacy and trust as bigger issues that are part of brand reputation.
In the global TV and video sector, OTT video presents the standout growth opportunity, and that will only cause further disruption for consumer telcos. A key way to exploit this opportunity is to gain strength via supersizing. In this sector, the threat posed by the digital giants of Facebook, Apple, Amazon, Netflix, and Google continues. In reaction to this, traditional fixed-line operators are looking to become data-centric businesses, and the media sector has seen greater merger activity to create scale across content creation and distribution.
An acceleration in the pace of technology change and a shift in market power between telcos and internet companies means that telcos will need to find new routes to revenue growth. Central to securing additional growth, the industry will need to respond to the following realities:
A new internet reality
A frictionless reality
An artificial intelligence reality
AI will ask new questions of us, some of them social. Two key questions arise:
A local reality
In today's data world, Telefónica is increasingly having to compete with data-centric businesses such as Google and Amazon. Chema Alonso, chief data officer at Telefónica, discussed the progression the traditional fixed-line company has made toward becoming a data-centric business that puts data front and center and takes data-driven decisions. For digital assistants to be effective, the right data needs to be accessed, so it has been critical for the business to focus on introducing a data-centric strategy before it can implement an AI strategy. This required a complete change in the way the company works, the aim being to create one platform that requires all data being generated by the business to speak the same language (i.e., be stored and processed in the same way all around the world). For this data to be properly understood, it must be normalized and the company must have access to it through the creation of tools that allow it to extrapolate insights.
Figure 1: How to gain insights from data
Source: Ovum, Telefónica
From this basis it is possible to build on top to create worldwide systems that are truly universal, Alonso said. All future apps and services can be built on this same platform and can also become universal, meaning they need to be built only once and then can be used worldwide. This creates great efficiencies for Telefónica and cuts costs. The company could now begin building a new interface and AI architecture to improve the customer experience, while increasing the customer's knowledge of Telefónica services and reducing the need to call the contact center. The ultimate goal has been to replace the wireline phone with something new that controls everything in a home – from turning on the lights to setting up a videoconferencing call and operating the TV. Alonso highlighted that traditional fixed-line providers are actually in a privileged position because landline phones tend to be in the living room. This creates a unique opportunity to make a device that replaces this phone with a product that can be easily integrated with and connected to all of Telefónica's services right in everyone's living room – Movistar Home.
AI is complex, is fast moving, and drives innovation, according to a panel of experts discussing the impact of AI on consumers. However, it faces many challenges and vulnerabilities and is shrouded in hype and misconceptions. Personalization is where AI can have the biggest effect on the consumer experience. Both Andres Alvargonzalez, marketing director at Nuance, and José Ramón Gómez Utrilla, senior product manager of AURA Telefónica, said they believe the focus needs to be on personalizing the user experience and using machine learning to suggest new products or services to customers so that companies can be proactive in creating new revenue streams. Patrice Slupowski, VP of digital innovation at Orange, described "AI as the new UI." The customer experience will be enhanced by reducing the number of clicks required by a user and replacing them with voice capabilities.
Simon Thompson, head of practice for big data and customer experience at BT Research, echoed the panel's view of the need for trust and control over personal data to improve the customer experience but also added rights and freedom as key ingredients. Systems need to be developed to give users choice. Data is crucial to enhancing the experience, and organizations need to use data as much as possible. However, Slupowski adds that they should not lose sight that privacy matters, and it is important to give ownership over personal data back to the user. Ultimately, digital assistants will need to become more human-like by being able to conduct small talk and use a degree of insight. If AI is not able to use insight to form conclusions or offer solutions, then it is likely that customers will be lost, Thomson said.
Ovum has recently completed the research for its 2018/19 ICT Enterprise Insights program. Based on interviews with senior IT executives in more than 6,500 enterprises worldwide, the program explores ICT investment plans and priorities for the coming year. For the last few programs, Ovum has focused on digital transformation, looking at how enterprises are using technology to change business models, processes, and platforms to deal with the demands of the digitally connected world.
Figure 2: ICT Enterprise Insights: Digital-enabling technologies usage plans
ICT Enterprise Insights explores the maturity in adoption of key enabling technologies for digital transformation. These include cloud-native architecture, APIs, IoT, blockchain, big data, AI, and Agile/DevOps. Strikingly, the survey suggests that big data is moving into mainstream adoption and AI is gaining considerable enterprise interest, seeing the strongest overall shift in focus in the survey this year. The survey also shows that adoption and interest in emerging technology varies significantly by industry; for example, big data sees high adoption in the financial services sector. Big data is the most advanced of these technologies, with 23% of enterprises having active operational deployments. While the proportion of enterprises with active interest in AI initiatives (i.e., planning, trialing, or deploying) shifted from 62% last year to 77% this year, actual deployment remains low at only 16%. There is still a considerable gap between interest and usage. However, the strong movement of big data is a leading indicator of how companies are thinking about AI, laying the groundwork that needs to be in place first before AI can be successfully implemented.
You can learn more about the ICT Enterprise Insights program here.
The Ovum-Amdocs AI maturity assessment model is an interactive tool that provides businesses with their AI strengths and weaknesses, according to Eden Zoller, principal analyst at Ovum, and Matthew Dowling, head of marketing for Western Europe at Amdocs. It is relevant to all service providers, particularly those struggling to navigate AI, looking to derive benefits from the technology in areas such as network optimization, sales and marketing, service innovation, customer support, and cybersecurity.
The tool consists of five pillars – strategy, organization, data, technology, and operations – and uses a scoring system to assess progress along an AI maturity path based on these pillars. AI maturity is assessed at four levels: AI novice (no proactive steps taken), AI ready (trialing AI), AI proficient (solid progress, some experience but mainly used internally), and AI advanced (good level of expertise, used internally as well as externally in the B2B and B2C markets).
The tool uses industry benchmarking to compare a company's results to others in the sector and can be used to understand where on the AI journey it is. The tool also suggests next steps, depending on how far along the maturity path a business is. By knowing the weaknesses and gaps, it is far easier for a business to move forward.
For David Snelling, program director for artificial intelligence at Fujitsu, the most exciting use of technology today is when AI is used to solve real business problems such as checking wind turbines for faults. Instead of being checked manually, images can now be checked much faster using AI, which creates only 16% of false positives that still need to be verified by experts.
Rob Scott, managing director, head of custody, collateral, and clearing at Commerzbank, highlighted that many processes in the banking sector are repetitive, with predictive outcomes making them ideal candidates for AI. Using automation to streamline processes has the potential to significantly enhance the client experience. However, companies will need to understand their data better, and this data needs to be structured in the right way in order to use AI effectively to tailor a richer client experience.
Maggie Buggie, SVP and global head of SAP Leonardo services at SAP, outlined that technology should no longer be seen as just business systems. Instead, the focus should be on the business outcome and how these systems can support it. Chris Gayner, director of labs at Symphony Ventures, agreed, noting that companies need to be aware that "sometimes AI isn't the answer," so they shouldn't merely be investing in these tools to feel they are being innovative. They are redundant if don't actually help solve a real business problem. As Jonathan Hewett, global CMO at Octo Telematics, said, automation should be used for problem solving, and then once the problem is clearly identified, intelligence can be applied to drive benefits.
Gayner highlighted the future need to prioritize what to do with the freed-up hours of the workforce disrupted by automation and to look to retrain staff. Adaptation is key to making the most of automation and AI. Snelling explained that humans are lucky in a sense, as most things need to evolve when a change occurs; however, people only have to adapt to the change. This will involve making changes to company culture and the skills of staff.
OTT video presents the standout growth opportunity in the global TV and video sector, accounting for two-thirds of growth in that segment over the next five years. A key way to exploit this opportunity is to gain strength via supersizing – a concept that revolves around the three C's:
Funds can be spent on technology, content, talent, etc.
Traditional media companies are merging.
Audiences will see subscale companies form joint ventures to compete.
This allows Apple, Amazon, Google, etc., to enter and disrupt markets.
A post-merger Time Warner spent $28.5bn on content in 2017 vs. $6.3bn at Netflix.
Traditional TV still very well-positioned.
The smart home market has evolved significantly over the past few years, but it will take many years to fully develop and reach mass market. In 2022, the smart home market will be the fastest growing segment, offering the biggest growth potential in the TMT sector.
Revenues, on the other hand, will increase at a slower pace as monetization remains a key challenge for technology vendors and service providers. The fast-growing appetite for smart speakers and AI assistants will transform the smart home. Also, new use cases will emerge as smart home tech penetration intensifies.
The recent M&A activity in the media sector is creating unprecedented scale across content creation and distribution. The move is a direct reaction to the potential existential threat posed by the ever-growing digital giants of Facebook, Apple, Amazon, Netflix, and Google, known collectively as FAANG.
The supersize strategy is an unproven one that depends upon successfully exploiting the larger audiences created by these expanded media entities. More data will be gathered about the supersized audiences, and it can be used for finer segmentation for advertising campaigns. The ability to deliver large-scale, consistent, targeted advertising across TV, digital, and mobile is an impressive tool for the supersized companies to wield.
Ovum predicts that there is only further disruption ahead for consumer telcos as OTT players continue to gather strength on both mobile devices and in the home. However, it is vital that telcos remain relevant to the consumer and to do so need to
optimize the customer experience by developing a best-in-class IP network
Evan Kirchheimer, research director for enterprise services at Ovum, asked if we are too obsessed with the technology, and if that might be why user adoption remains poor. Survey data shows that around 20% of firms have deployed tools like Slack. Usually, the same firms also have CRM and web-based conferencing. However, there is also a long tail, slow to adopt even basic applications like file sharing and instant messaging.
Julien Lesaicherre, director for EMEA, Workplace by Facebook, remarked that although enterprises have carried out impressive proof-of-concept projects with AR and VR, they invariably share the results via email. He suggested searching Facebook for groups with your company name – typically, a company of any size has dozens or hundreds, to say nothing of WhatsApp. This means the unofficial use of brands, data, and apps, an IT governance challenge.
The problem is engagement rather than apps as such. Some 70–80% of user time is spent on the top three applications, and any new project has to make the top three. This requires an understanding of users' motivations. Ovum's practice is based on understanding employees first, then business goals, and only then technology.
Ovum predicts that nearly 600 million connected devices will be deployed in smart cities by 2022. Smart lighting and smart parking are the most prevalent applications being deployed now. Demand drivers for smart cities include environmental, sustainability, security, and "citizen-satisfaction" factors. Supply-side drivers include new lower-cost technologies such as LPWA, public funding availability, and opportunities to leverage 5G rollouts. AI is already being used in the smart city for applications such as traffic management, digital facial recognition, and predictive policing.
Service providers are looking to smart cities for new revenue, and cities themselves need to find ways to save cost and drive new income. But the lack of technology standards, privacy concerns, siloed departments, funding and political uncertainties, and long procurement cycles all present challenges. To succeed, suppliers must develop creative business models, such as Deutsche Telekom's smart parking offering and Orange's integration and managed services offerings in the Middle East.
Maxine Holt, research director, information security, at Ovum, stated that 28% of companies are still not compliant with the EU's General Data Protection Regulation, and 37% are choosing to ignore GDPR. While 48.2% have a scalable data privacy program in place, 19.8% do not have a scalable program and are only GDPR compliant. Kevin Kiley, vice president of sales and partnership at OneTrust, explained that these statistics show that many companies are still getting their heads around GDPR, and privacy is still developing. The major challenge that needs to be overcome in some organizations is who deals with privacy and how they work with other departments. Additionally, awareness is crucial to compliance. It is the responsibility of everyone in an organization to ensure compliancy.
Kiley highlighted that some verticals have more exposure, but one thing is clear: the differences in compliance are not geographical because companies outside the EU have to be compliant too if they hold any EU customer data. In many cases, companies in the US, particularly those that were built on mining data such as Facebook and Google, have taken to GDPR sooner than even their EU counterparts as they were concerned they would be the first to be prosecuted and fined for noncompliance.
Aside from the regulation and the possibility of being fined for a data protection breach, companies see privacy and trust as a bigger issue that is part of brand reputation, Kiley said. Companies are beginning to move away from the idea that GDPR is just a tick-box exercise and now see it as an ongoing compliance requirement. Subsequently, the long-term trend will be toward building a global privacy program that not only focuses on GDPR but is more sustainable and efficient in the future. Making investments now in such a program should bring about savings in the future.
Figure 3: Evolution of a privacy program
Companies will begin to look for universal control points in their organizations regarding data protection and privacy because certain operational aspects are very similar in the various data protection laws. From there, it is easy to focus on the nuances and make adjustments to meet local requirements on consent and variations in the responses to a data breach. If companies adopt a strong, robust program and follow the privacy-by-design concept, then it is possible to meet the vast majority of data protection laws around the world.
Ovum Chief Research Officer Tim Jennings noted that many of the AI use cases in the ICT Enterprise Insights Survey were around the customer experience. Drew Crisp, executive partner, communications sector, and digital leader at IBM, pointed out the distinction between customer experience and engagement – one refers to the touchpoint with the customer, the other to the process behind it. The three business goals of efficiency, growth, and innovation are crucial here. AI could address the first by helping to go from "data to wisdom" in understanding and optimizing business processes.
Crisp also noted that improving the customer experience is no longer about "personalization" so much as "personification" – there is no point in having a 360-degree view of customers if you can't act on it and solve their problems. Action personifies the brand values presented to the customer. In trying to innovate and create new markets, it is crucial to understand the relationship between "predictability" and "malleability" – if customer behavior is predictable but not malleable, it is necessary to serve all the options through an omnichannel approach, where AI would excel, but if it is unpredictable but malleable, a design-led approach would be better.
Data quality and governance are vitally important, but perhaps more important is being sure AI projects would deliver fundamental value once all their potential costs are considered. Crisp remarked that there are plenty of proof-of-concept chatbot projects around, but the real challenge is scale.
Ovum sees four key mega-trends at the heart of future consumer experiences:
Sarah McBride, Analyst, Ovum
Adam Thomas, Lead Analyst, Global TV Markets
Alexander Harrowell, Senior Analyst, Enterprise Services
Richard Mahony, Global Director, Consulting
Mariana Zamoszczyk Senior Analyst, Consumer Services
Michael Philpott, Senior Practice Leader, Consumer Services
Carrie Pawsey, Senior Analyst, IoT Practice
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