THE DELTA PERSPECTIVE

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1 Can Edge computing enable international carriers to build a global cloud platform? Joao Sousa - Partner Sam Evans - Partner March 2019

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3 Can Edge computing enable international carriers to build a global cloud platform? Authors: Joao Sousa - Partner Sam Evans - Partner Introduction Edge computing is emerging as a new approach to network architecture that can offer enhanced performance versus traditional Cloud applications without needing to be purely onpremise and quickly becoming a core element of the Amazon Web Services (AWS), Azure and Google portfolios. In this paper, we assess the market drivers that have supported the emergence of Edge computing and the strategies undertaken by the global cloud providers. We then address how Edge computing, given its infrastructure requirements, could provide telecoms operators with a new opportunity, if they can successfully create scale through collaboration, to develop a new form of global platform and regain ground in the cloud space. 3

4 Understanding the emergence of Edge The proliferation and advancement of connected devices is driving the greater need for real time processing and storage closer to the customer, avoiding transit latency back to existing cloud platforms. The advancement of Edge is driven by three main forces addressing limitations of existing architectures, namely: 1) Appearance of advanced use-cases that require one or multiple enablers, including: a) Ultra-low latency; b) Ultra-high reliability; c) Extreme density of connected devices; d) Significant processing power at a reasonable cost; e) Storage and processing of data close to the origin. 2) Needs of global cloud providers, including: a) Extending cloud capabilities to device, controller and aggregator level, minimizing dependence on the key limiting factor connectivity; b) Improving QoS of existing cloud solutions to address new use-cases and secure market leadership. 3) Needs of telecom operators, including: a) Additional mechanisms to monetise assets through addressing emerging Edge computing use-cases; b) Optimising network economics, especially for 5G deployments; c) Significantly increasing density of radio access subsystem by moving network functions from existing mobile sites; d) Reducing the need to reach the core of a network by reducing the number of Single Exhibit 1: Edge computing landscape: addressing the needs of both global cloud providers and Telcos 4

5 Exhibit 2: Edge computing: enabling advanced 5G use-cases PAST PRESENT FUTURE Global computing In-country computing Edge Computing 2G/3G LPWAN (NR-IoT/LTEM) 4G/5G (R15) 5G (R16)/LEO Virtual things Data Platforms Expert based Predictive analytics Assisted intelligence Virtual representation Autonomous intelligence Digital twins Facilities Smart home / facility Autonomous facility / smart city Controlled things Robots / drones / vehicles / boats / airplanes Industrial automation Cobots Connected things Smart devices / equipment / grid Meters Trackers Source: Delta Partners analysis POS/ATM Remote Legacy access devices control Smart meters Fleet management Security tracking Machines / Grids Infrastructure Environment Goods/Parts Cattle Massive / pets IoT Humans Visual comms V2I Indoor tracking Indoor tracking V2V / V2M Mission critical equipment Fast moving objects Point of Failure (SPOF) and increasing density of connected devices; e) Ensuring real time access to the RAN, enabling context and location awareness; f) Enabling provisioning of advanced usecases through introducing radio QoS, security, multi-tenancy and low latency. These three drivers are rapidly changing the established architecture by increasing the role of devices and aggregation as well as simultaneously introducing a new layer of telco network Edge, an important part of Edge computing. Edge computing processes data in proximity to where it is produced instead of sending it back to be processed in the Cloud. By reducing the amount of data flowing to the Cloud, one can significantly reduce bandwidth costs, cloud computing service costs, and dependency on connectivity requirements. A further key benefit is the improved data security and compliance with data residency laws i.e. concerns regarding data storage in a country or region different to where the data owner resides. This is particularly important for specific enterprise verticals as well as government. Currently many countries, especially in emerging markets, have limited local data center infrastructure and so the Cloud is hosted outside the domestic market. Despite the many benefits of Edge computing, it will not fully replace the traditional Cloud. This is primarily due to the preferential economics and greater storage and processing capabilities of the Cloud versus Edge. As such, we expect that the future solution will be a mix of pure cloud, pure Edge and hybrid solutions which offer different combinations of cloud vs. Edge benefits optimizing the overall solution cost. 5

6 Examples of Edge computing usecases Use-cases will evolve from simple enhanced cloud, i.e. default cloud services with improved QoS, to fully integrated hybrid and pure Edge computing solutions. With respect to Edge, global cloud providers and telecoms network operators are developing usecases with a focus on enabling services that cannot be served under existing network architecture. The service focus is on unlocking three enablers: 1) Low latency by bringing compute and storage infrastructure closer to the end-device and avoiding long-distance data transfers to major data centers the customer can experience low single digit latency (versus ms offered by global cloud providers today) via fixed (fiber) and mobile (5G) access networks; 2) Security and Compliance by increasing the number of Edge processing points, there will be fewer occurrences where sensitive data is sent abroad or to a different region, allowing for higher compliance with data localization laws and data security requirements; 3) Network utilization and reliability distributed nature of Edge will optimize backhaul and backbone use as well as reducing the number of points of failure, allowing for more robust service provisioning in all environments. This also reduces the global cloud providers dependences on connectivity offered by telecom providers. To demonstrate how telecoms network operators and global cloud providers are starting to address Edge opportunities, several examples can be highlighted. Telstra In 2018 Telstra decided to close c.2,500, around 50%, of its local exchanges and redeploy other facilities as local data centers. Telstra is also assessing multiple use-cases that can benefit from Edge computing such as in the mining and cloud gaming (Exhibit 3) sectors. They have investigated potential opportunities with hardware manufacturers and game developers to address consumer market needs. Cloud gaming consists in virtualize graphical processing in a cloud and replace expensive equipment (e.g. personal computers, consoles) required on the gamer side. Exhibit 3: How Edge use-cases leverage latency, security and network utilization benefits Latency 1 Localized AI 2 Cloud gaming 3 Enterprise private networks 4 5 Video streaming Hybrid storage 6 Cloud for limited connectivity 7 IoT Security & compliance Network utilization & reliability 6

7 By moving hardware to the telecom network Edge, gamers will have the potential to access highperforming computing power with low latency to enhance their gaming experience at a lower cost. Single digit latency of Edge computing is required to ensure the right customer experience. Telefonica Telefonica has developed a comprehensive Edge strategy, relying upon its OnLife program consisting in the upgrade of existing central offices to Edge data centers. It evaluated multiple Edge use cases, with a focus on use cases with potential short to medium-term impact, such as network storage or gaming. It is also working on evaluating potential partnership with AWS, where Telefonica s facilities could be leveraged by AWS Greengrass Edgecomputing service. Telefonica has launched an Enterprise Private Network solution (Exhibit 3) with Ericsson s technology that brings Telefonica s communications networks to end customers through an approximation process, called Ultra- Edge Computing, that consists in the UNICA-based network (Telefonica s cloud global platform) Core reaching the facilities of companies themselves. This approach increases bandwidth significantly, while simultaneously minimizing response times, thus achieving a significant improvement in the communication quality. Vodafone Vodafone s Edge computing trail spans multiple use-cases, revolving around Multi-access Edge Computing network architecture. For the consumer segment, cases include transportation, online entertainment, security; for enterprise, MEC-based communication and industrial solutions. Most cases were trialed as partnerships (together with vendors including Ericsson and Nokia). Focusing on mobile Edge computing for video streaming (Exhibit 3), Vodafone was able to prove substantial benefits to use MEC to enhance customer viewing online. This use-case was relevant as video is expected to contribute to 75% of data consumed on mobile by 2022 and 4 over 10 viewers drop out video viewing in case of buffering issues. Vodafone and its partners developed a laboratory environment recreating typical network congestion and latency experienced by mobile users. A MEC platform was in the backhaul aggregation layer of the radio access network, and a local cloudlet was used to operate virtual video server. This was compared to video stored on AWS servers. Results concluded that video on the Edge started quicker, with no stalls and lower waiting times due to rebuffering. Global Cloud providers: Amazon Web Services, Microsoft Azure and Google Cloud The leading global cloud providers have a clear understanding of the performance (latency, time for processing) and independence (lesser reliance on telco connectivity) benefits made possible by Edge computing for their cloud services. To reap these benefits, they are expanding their current cloud service portfolio to make them Edge ready, covering all network levels from device to global cloud. IoT and Edge storage are the first service areas to become Edge ready and are commercialized. Of the three, AWS and Microsoft Azure have the most comprehensive IOT offering including Edge, while Google, with less features on IOT, is focusing on building leadership on the entire AI vertical. AWS was the first global cloud provider to migrate to the Edge. First, AWS has developed a strong IoT Edge proposition consisting of AWS IOT Greengrass, which is a software that extends cloud capabilities to Edge devices. It also launched AWS Greengrass ML Inference which allows customers to deploy machine learning (ML) models on AWS Greengrass devices. It also launched AWS Snowball Edge (Exhibit 3), which is a data migration and Edge computing device, suited for local storage and large-scale data transfer. Snowball Edge Compute Optimized provides compute power for use cases such as advanced ML and full motion video analysis in disconnected environments. Customers can use these two options for data collection, ML and processing, and storage in environments with intermittent connectivity (such as manufacturing, industrial, and transportation) or in extremely remote locations (such as military or maritime operations) before shipping it back to AWS for data storage on the cloud. 7

8 Exhibit 4: Comparison of global cloud provider Edge solutions Service areas Description Global Cloud / Core IoT services Cloud gateway Machine learning Kinesis Data Pipeline AWS IoT Machine learning Stream analytics Power BI Azure IoT Hub Machine learning Stream analytics Data warehouse Google Cloud IoT Provides a preconfigured solution for monitoring, maintaining, and deploying common IoT scenario A cloud gateway for managing bidirectional communication with billions of IoT devices, securely and at scale Telco Network Edge Bulk data transfer AWS Snowball Edge AWS Snowmobile Azure Databox N/A PB to EB-scale data transport solution that uses secure data storage devices to transfer large amounts of data in and out of Cloud, at lower cost Devices / Onpremise aggregation & processing Edge computing for IoT Real time data processing AWS Greengrass Kinesis Firehose Kinesis Stream Azure IoT Edge Event Hubs Cloud IoT Edge Edge TPU Cloud functions available for real-time processing Managed service that deploys cloud intelligence directly on IoT devices to run in on-premises scenarios Services that allow the mass ingestion of small data inputs, typically from devices and sensors, to process and route the data Source: Microsoft Azure, Amazon Web Services, Delta Partners analysis Microsoft Azure followed AWS into Edge with the launch of IoT Edge (Exhibit 3) that is made up of three components: 1) IoT Edge modules are containers that run Azure services, third-party services, or clients code. Modules are deployed to IoT Edge devices and execute locally on those devices; 2) The IoT Edge runtime runs on each IoT Edge device and manages the modules deployed to each device; 3) A cloud-based interface enables clients to remotely monitor and manage IoT Edge devices. Additionally, Azure announce Cognitive Service containers (Exhibit 3) that allow developers to easily add cognitive features such as object detection, vision recognition, and language understanding into their applications without having direct AI or data science skills or knowledge. By deploying Cognitive Services in containers, customers can analyze information close to the physical world where the data resides, to deliver real-time insights and immersive experiences that are highly responsive and contextually aware. Cognitive Services containers that customers deploy on their own. With the launch Cloud IoT Edge and Edge TPU by Google in 2018, all three major cloud players started providing ML service on the Edge. Google Edge positioning is especially focused on the development of the whole AI ecosystem (Exhibit 3:) which revolves around the Edge TPU and the Cloud IoT Edge. Google IoT offering is seen as less comprehensive than that of Azure and AWS, but their ML knowledge is perceived as very high, with a clear strategy of vertical integration. Specifically: the Edge TPU is an ASIC chip designed especially for running ML applications on the Edge, allowing customers to run compute intensive AI-related workloads. The Edge TPUs are the chip where algorithms carry out the task they have been trained to do. It makes Edge TPUs different from first Google TPUs, which were optimized to conduct the training part of the process. the Cloud IoT Edge is a software platform that powers Edge computing devices such as robots, turbines, oil rigs. 8

9 A good example of implementation is provided by the company LG, which used both Edge TPU and Cloud IoT Edge to run algorithms in smart manufacturing LCD panel inspection processes, which increased to 99.9% accuracy of processes AWS, Azure and Google employ similar principles in their Cloud-to-Edge expansion. They strive to develop an end-to-end technology stack across cloud and Edge to simplify app development and allow for efficient cloud and Edge management. In Exhibit 6 below, it is demonstrated how AWS IoT product portfolio fits along the network stack. As more cloud services become Edge-ready, the diversity at the Edge will grow. To accommodate this diversity, AWS and Azure will continue to invest and grow their ecosystem of software vendors, system integrators and solution providers. The larger this ecosystem, the more likely they will have the right Edge solution, and the more likely they will win over the market. From the analysis of use-cases and strategies by telecoms network operators and global cloud providers we identify three key points for consideration: 1) Defining the Edge Global cloud providers and telecom operators use different definitions of Edge. For Cloud providers Edge extends up to end-user device levels (smartphone, IoT sensor, laptop, etc.), while for telecom operators, the line is drawn at existing access locations (e.g. central offices, BSC/RNC, etc.) or corporate client premises. Currently, the main challenge faced by global cloud providers is the availability of connectivity infrastructure. Moving Edge/hybrid solutions towards the end-user device level will help them to become less dependent on Telcos. 2) Cloud providers adding Edge to the existing portfolio Global cloud providers are actively adding Edge components to their existing product portfolio. They are leveraging their dominating position in the application market to offer new Edge services or improving and complimenting existing services with Edge/hybrid benefits. This allows them to better position for the future retail market of Edge. 3) Telcos 5G focus Telecom operators are mostly focused on 5G implications of Edge and seem to be in an earlier stage of retail product development. Telcos are in the best position to become leaders in the development of enablers for 5G Edge use-cases. Exhibit 5:Overview of AWS Snowball Edge network architecture Console / CLI / SDK Data flow Control flow DMS, IAM, Snowball, S3 APIs AWS Scheme Conversion Tool SCT DMS Client DMS Engine adapter Snowball Edge appliance DMS local replication Instance Existing data (Full load) Shipping DMS replication Instance Customer "Local" tasks S3 Bucket "Remote" tasks AWS Source DB S DMS Engine F On-going replication data F DMS Engine T Target DB 9

10 Exhibit 6: Overview of AWS IoT stack Network slicing Edge computing Example for AWS Per type of traffic and type of customer IoT device Device is connected to AWS cloud via IoT SDK or FreeRTOS IoT SDK IoT FreeRTOS AWS Greengrass Edge computing platform, which can operate without connection to the cloud Cloud solutions Enterprise AWS solutions AWS Lambda Amazon S3 physical integrated into operator network Amazon EMR AWS cloud AWS IoT Core AWS IoT Device Management AWS IoT Device Defender AWS IoT Analytics Devices IoT Device Operator HetNet Operator CO / Network buildings SDN functions Operator NFVi AWS PaaS AWS IaaS Operator OTN AWS Edge DC / Main DC AWS platforms AWS IaaS MPLS capability to mobile E2E service in partnership between operator and cloud provider Creating value at the Edge Edge computing solutions utilize components across the entire network technology stack, from global cloud to end-user devices and sensors. There is a significant difference in terms of accessibility of different Edge components for global cloud providers and telecoms operators due to the nature of their business models and legacy investments. While global cloud providers dominate at the beginning (global platforms) and end (devices) of the service provisioning path, telecoms operators have a strong position in network infrastructure at national and access levels particularly important for Edge computing is access network connectivity and Edge (e.g. central offices and aggregation points). Global cloud providers ownership of network infrastructure is limited and considered as a key bottleneck for expansion from cloud to the Edge, as mobile and fixed access networks require significant investments of money and time to be built. This situation creates challenges and opportunities for both global cloud providers and telecom operators. On one hand, global cloud providers are more advanced in terms of product readiness and access to end-users. On the other hand, they lack two critical components for a full-stack Edge Computing service: access connectivity and access network Edge (aggregation points). The value chain of Edge computing has many similarities with traditional clouds. The main difference is the number of additional network levels involved: devices; on premises aggregation/ compute; and telco network Edge. The value of Edge Computing generated for service, infrastructure, hardware and software providers are shown at three technology layers: 1) Applications. Comprehensive consumer, business and telecom solutions addressing end-user needs. This layer includes pure Edge and hybrid (combining four components: device Edge; customer premises Edge; telecom network eege; and global/national platforms) services that are based on other layers of the value chain; 2) Enablers. Edge and hybrid (Edge + global) IaaS and PaaS solutions, Edge NFV (mostly for 10

11 5G), SDN / SD-WAN, Devices / On premises equipment. This layer includes hardware and software that will significantly decrease time-to-market and required investments for deploying Edge Applications; 3) Basic infrastructure. Includes basic access network Edge hosting services (such as access to premises, power, a/c, security, etc.) and multiple levels of connectivity from international backbone to last-mile mobile and fixed access. Wholesale Edge: an opportunity or carrier dilemma? For telecoms network operators there are opportunities to both retail and wholesale Edge computing. From a retail perspective, based on the likely use-cases there will be demand from specific enterprise verticals, while from a wholesale perspective demand is likely to come primarily from the global cloud providers, who wish to leverage the local telecoms infrastructure to offer Edge solutions to their customer bases. The key question for telecom operators is whether to focus purely on a retail offering, or also to open their Edge capabilities to the global cloud providers, which in turn can lead to greater competition for their enterprise segment. Given the scale of global cloud platform developer bases (e.g. AWS, Azure), it is likely that developers will wish to develop on their existing stacks as they move into the Edge computing environment rather than develop on new technology stacks, especially at a localized level, for Edge services. As such, at a retail level, telecom operators will likely to be able to identify specific Edge opportunities, a significant share of the retail market will be served by global cloud providers. Telecom operators can play a major role in establishing Edge Computing environment and creating value by serving the global cloud providers also. They have the ideal network footprint in place to provide basic infrastructure services located at telecom network Edge. Exhibit 7: Infrastructure landscape of Edge Telcos strongholds Global Cloud strongholds Access connectivity National backbone International backbone Devices On premises aggregation Access network Edge Country level platforms Global platforms Edge computing services 11

12 Exhibit 8: Existing infrastructure challenges and opportunities Global Cloud Providers Challenges Dependence on connectivity provided by 3rd parties, especially on the last mile, increases time to market and puts pressure on CAPEX requirements Economical and time-to-market challenges to densify DCs in developed markets and expand to emerging markets Opportunities Improvements in mobile processing power create an opportunity to move selected cloud functions directly to devices bypassing connectivity barrier Existing infrastructure (global platforms) and customer base can be additionally monetized through introducing edge and hybrid services Telecoms Limited access to end-user devices and lost battle on global clouds impacts the ability to quickly deploy and monetize retail applications Network Edge is a critical enabler for many Edge computing applications global cloud providers require it to offer a full stack of services Geographical presence of telcos is much wider comparing to global cloud providers telcos can enable not only edge / hybrid but pure cloud solutions in new markets Exhibit 9: Layers of Edge value chain 1 Applications B2C solutions B2B solutions Solutions for telecoms 2 Enablers Edge IaaS / PaaS Hybrid IaaS / PaaS Edge NFV SDN / SD-WAN Devices 3 Basic Infrastructure Connectivity: access, aggregation, backbone Edge hosting 12

13 Global cloud providers are actively expanding their data centers and reducing the gap with telecom operator s network Edge infrastructure this is largely true in developed markets. A good proxy for understanding the number of telco network Edge data centers required for global coverage will be the number of existing telecom central offices thousands of locations across the globe. In comparison, the Amazon, the market s leading cloud provider has 116 Edge DCs globally. The addition of Edge will make the landscape of available cloud services and application even more complex. Another potential revenue stream for telecom operators lies in existing ICT space they can offer tailored Edge and hybrid solutions by leveraging own and global cloud providers infrastructure and platforms. There is an opportunity for telecoms operators to enable global cloud providers expansion from the cloud to the Edge by offering telecom network Edge services such as Edge and Hybrid IaaS/PaaS, Edge NFV and SDN/SD-WAN. Telcos can also self-provision solutions for 5G enablement and unlock value by sharing these solutions with other operators. This approach is more challenging with the ongoing competition from global cloud providers but will allow telecom operators to benefit from cloud provider s established client relationships and promote a sustainable economic model of Edge computing. Exhibit 10: AWS global Edge data center footprint The number of Edge DC (#, end of each year) Edge locations Multiple edge locations Regional edge caches Notes: Taiwan is counted as China; Source: Companies websites, Delta Partners analysis 13

14 Carrier Edge: the global platform opportunity Can leading telecoms carriers compete with global cloud providers on Edge computing market? We believe that a globally distributed platform of Edge IaaS/PaaS deployed on existing infrastructure of telecom operators can help leading carriers regain ground in the market. As mentioned above, carriers have widespread network infrastructure for its existing operations, while global cloud providers mostly rely on major data centers with limited densification in key markets. By creating a single unified platform, telecoms network operators can develop a global enabler for applications and services of cloud providers. A much denser data-center footprint will be required for Amazon/Microsoft/Google/Facebook to dominate Edge computing in the same way as they are dominating the global cloud environment. Telecom operators have the great advantage of having key physical infrastructure already financed and built, especially significant in semi-developed and emerging markets. Collaboration between international telecoms carriers is the key to successfully develop and deploy this globally distributed platform. Apart from individual approaches on exploring Edge computing opportunities, we have identified three priority directions for Telcos depending on the extent of collaboration: Exhibit 11: Three waves of potential Edge opportunities Wave 3: Long-term opportunities Wave 1: 5G platform Leading development of a single standard for 5G Edge covering hardware, platform and cyber security Wave 2: Edge IaaS/PaaS Pre-provisioning of a unified Edge IaaS/PaaS for enabling cloud provider in emerging markets using existing deployed infrastructure Providing the service capability to other market players (e.g. developers) Other advanced services (e.g. own applications) 1) Global network of Edge IaaS/PaaS suitable of providing NFV/SDN for 5G a single standard covering hardware ecosystem, Edge computing platform, cyber security for the Edge. True 5G is not possible without having Edge infrastructure in place. Standalone deployments are putting significant pressure on operators financials. International carriers can jointly deploy the required infrastructure in their preferred countries and reap benefits by sharing it. This can be done through assigning geographical markets to different OpCos and then exchanging infrastructure access. Given the nature of IaaS/PaaS and NFV/SDN/ SD-WAN, multiple complexities of sharing the infrastructure will be solved automatically. These deployments will naturally lead to the next opportunity; 2) Enabling global cloud providers in semi-developed and emerging markets by offering Edge IaaS / PaaS Main battlefields for global cloud providers are developed markets, this is reflected by the fact that many countries still do not have a single data center. Pre-provisioning of Edge IaaS/ PaaS by telecoms operators will drive global cloud providers to consider partnerships over building its own infrastructure. In the most underdeveloped markets, availability of Edge 14

15 data centers will have major implications on global cloud providers decision on entering the market. While in countries where Amazon/Microsoft/Google already have a major data center, enabling Edge applications will significantly improve their time-to-market, allowing telecoms operators to benefit from the extensive retail footprint of global cloud providers; 3) Long-term opportunities on advanced use of Edge - Constructing unified cloud computing infrastructure and providing service capability with key features of computing, storage, network and security are inevitable choices of telecom operators looking to migrate away from the dumb pipe position in the tide of ICT convergence. As IT and CT converge, Multi-access Edge Computing will be critical for the digital transformation for operators, as this helps operators to quickly build cooperation with OTT or application developers. Telecom operators can open the storage and computing capabilities of the MEC platform to application developers and content providers, providing them with a brand-new service development environment and user experience. In addition, the information at the wireless side can be encapsulated into various services (for example, RNIS, location-based service, and bandwidth management service) running on the MEC platform and available to enterprises and vertical industry. There is already at least one good example of the platform development approach. Deutsche Telekom founded MobiledgeX a company that is creating a marketplace of Edge resources and services that will connect developers with the world s largest mobile networks to power the next generation of applications and devices. MobiledgeX is building a developer-friendly, multi-tenant, on-demand set of Edge services to enable the deployment of applications, application components and services much nearer to connected users and devices than is possible with today s centralized cloud services. From a developer perspective, the goal of MobiledgeX and the Edge ecosystem is to make sure any Edge services offered seamlessly integrate into existing ways of developing and do not add any additional operational burden than already existing in best practice cloud-based design workflows. (source: MobiledgeX website) Exhibit 12: Overview of MobiledgeX architecture 15

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17 Joao is a Partner with almost 20 years of management consulting experience advising a multitude of clients in the TMD space in Western Europe and Latin America. Joao holds an MBA from INSEAD (France) and a Bachelor s degree in Civil Engineering from the Instituto Superior Tecnico in Lisbon. Sam is a Partner at Delta Partners, a leading specialist global TMT Advisory, Corporate Finance and Investment firm. Sam has advised mobile operators, content distributors, network infrastructure providers, device vendors and payments networks across North America, Europe, Africa, Middle East and Asia. He has a degree in Philosophy, Politics and Economics from Oxford University. If you would like to contact the author to further discuss this topic, you can to: js@deltapartnersgroup.com Delta Partners is the leading Advisory and Investment firm specialised in Telecoms, Media and Digital with offices in the Middle East, Africa, Europe, Asia, Latin America and the United States of America. We partner with global and regional telecom providers, digital players, other TMT clients and our investors to help them address their most challenging strategic issues. Our unique combination of Management Consulting, Corporate Finance 1 and Investments 2 creates unparalleled value for our clients, investors and business partners. For more information, please visit and follow us on 1 Delta Partners Corporate Finance Limited and 2 Delta Partners Capital Limited are members of the Delta Partners Group of companies and are authorised and regulated by the DFSA.