Incedo Inc.

The current AI adoption levels coupled with improved machine learning techniques, is enabling companies to discover and operationalize business insights, previously hidden. Increased data availability and higher processing power is facilitating greater adoption, allowing enhanced methods with more data at lower cost.

Telcos world over are well positioned to make the most of this evolving situation by optimising their business and serving as AI platform enablers for other industries that are expected to spend upwards of $15bn annually on AI-led operations by 2021-22.

Three key trends that will define Telcos’ next decade are the reinvention of asset-light business models, resurgence of Telcos’ enterprise business, and liberation of network infrastructure that will accelerate and create a range of varied business models. Companies that embrace oncoming changes and those that make bold and quick investments will lead the pack and buck the trend.

Ovum’s findings reveal that the Telco market is perceived as second most at risk of disruption only after Healthcare. AI will play a large part in this change as Telcos look to implement technologies that reduce costs through greater automation, improved customer service, and optimized network and traffic management.

Significant improvements through AI will impact Customer Service, and Advertising/marketing operations, translating to improved cash flow for Telcos by 4x over the next 10 years.

Drivers of AI in Telco Ops

Artificial intelligence serves as an extension to a robust operational analytics system. However, whilst technology has been around for long, four powerful forces have accelerated greater adoption of AI.

  • Increased data availability: Available data on average is doubling every twelve months, attributed to increase in connected devices and much higher rate of data from connected devices. Evolved statistical models for decisioning are enabling new ways of managing and analysing very large data sets.
  • Data transformed towards a 360-degree view: Typically, Telco data is not integrated at a deep level, but instead scattered across functional and operational silos. The different data sets can vary widely in terms of quality and depth, rendering some data sets less actionable than the other. AI-powered solutions are helping integrate first & third-party data to maximize the ability of Telcos to achieve genuine 360-degree data view.
  • Increased processing power: Exponential growth of processing capacities is enabling AI solutions to be implemented on higher data volumes at lower cost. Additionally, distributed networks such as cluster computing on cloud have become exponentially more powerful.
  • Improved machine learning capabilities: Commercial interest in AI/ML has been growing strong with technology devoting significant capital to research. As a measure, Google doubled its AI research in the four years 2012-16.

Impact of AI on Telcos

There are opportunities aplenty for Telcos to leverage AI, as summarized below.  (Not exhaustive).

Customer Service & Contact Center Support

The advent of 5G in the telecommunications sector is driving multiple opportunities for organizations. 5G along with accelerated cloud adoption promises to deliver new digital services at a much lower latency through SaaS platforms, OTT services, and cloud based unified communication services, among others.

AI is a key enabler in improving quality of customer experience and quality of service. Telcos’ strategies to monetize data depend in large part on algorithmic intelligence and automation to handle exponential rise in traffic and onboarding new devices and users. Add to that, processing personalized customer service responses.

Key Opportunities

  • Assisted context-aware customer service: For customer service, the major reason why customers call is billing dispute. Using AI, Telcos can analyse user activity across engagement channels, and predict when a user calls in. Identifying intent and tailor their experience to get prompt resolution. Ex., when customer uses app or web to search billing pages, customer search data can flow into Telco Data Lake and finally when customer calls in, customer data from the Data Lake can be used to create context, which is plugged-in during agent call or chat.
  • Predictive maintenance of customer premise equipment: Analysis and insights of contact center notes to better the IVR system. With prior permission, analyse customer behaviour in terms of equipment used to signal a potential problem beforehand and pre-empt corrective action.
  • Conversational AI: Scaling and automating one-to-one conversations to drive down the cost and improve the efficiency of operations and customer service. Contact center first line virtual agent dealing with 90% of routine questions, with emotion sensing capability based on voice and video. Major use cases for implementation in the space of conversational AI are the regular ones that overwhelm contact centers. Ex.;. installation, set-up, troubleshooting and regular maintenance.

Network Optimization

AI is rooted in Telco virtualization of networks, namely, SDN and NFV. A fully NFV enabled network will be controlled by a single NFV orchestrator that dynamically determines critical network operations such as assignment of resources to a network function, provisioning new network nodes, or withdrawing network elements that go underutilized. Traffic will be controlled by a centralized SDN controller augmented by AI that allows for efficient and proactive routing of traffic enabling capacity to be managed effectively, network outages minimized, and faults bypassed. AI can optimize configuration of a Telco network according to dynamic network capacity demands, characteristics of traffic volumes, user behaviour, and other parameters. Network deployments may also be further improved by AI to predict traffic patterns and forecast user trends.

Key Opportunities

  • Telecom network capacity optimization and analytics: Transition to Network Function Virtualization (NFV), Software Defined Network (SDN), and Self-optimizing Network (SON). Self-optimizing network based on traffic information, detect anomalies beforehand and proactively optimize network performance.
  • AI for predictive network congestion and maintenance: Utilizing data, sophisticated algorithms and machine learning techniques based on past data. This helps in close monitoring of equipment, proactively anticipate failures and take corrective action before the customer raises the ticket.
  • Pre-emptive Vulnerability and fraud detection, cyber security helps defend critical network infrastructure from malicious attack.

Marketing Engagement

Understanding  user behaviour enables Telcos to create personalized customer engagements for its customers, creating offers and messages that are contextual and performed in real-time across a wide range of criteria, including personalized pricing plans, service bundles, and marketing messages. Personalized, real-time sales and marketing offers play a central role in Telcos’ data monetization strategies as well as enhance value of customers’ engagements and improve Customer Satisfaction (CSAT) and Net Promoter Score (NPS).

Key Opportunities

  • AI for faster response to personalized sales and marketing triggers, such as creating and tearing down offers. Product bundling recommendations.
  • AI-led customer engagements to replace manual intervention in select sales & marketing business processes.
  • New entries in product catalogues optimized by AI, such as price and size. Deep learning of competition and advertising data can be used to configure these entries.

AI Challenges for Telcos

Telcos face numerous challenges as they consider their next steps with AI, and they would need to keep a watch on the following factors, and they play out.

  • Threat from early movers: Telcos are not the only players looking to leverage AI to improve operations and services to gain competitive edge. Consumer tech. OTT and FANGs of the world are investing heavily in AI, and Telcos fear being left behind.
  • Data privacy: AI can leverage very granular consumer data insights and these capabilities will deepen going forward, to the point where they attract regulatory scrutiny. Telcos should ensure their AI solutions can safeguard data privacy.
  • Realign workforce for new employment opportunities and talent retention:  While the job market will evolve because of efficiencies and productivity introduced by AI-led automation, this will open up new possibilities for the workforce. Our workforce will steer AI initiatives, set goals, provide data and training, and monitor machine activities and performance. Fragmented AI skills in the organization, unclear AI organizational model results in difficulty while attracting and retaining AI talent.
  • Lack of end-to-end operational visibility: Numerous isolated POCs being undertaken by Telcos in the AI space make it difficult to present the comprehensive value and hence lead to insufficient leadership support for projects.
  • Lack of effective change management: Understanding of AI at different levels, unclear impact and value extraction and sporadic AI related training and adoption efforts makes it difficult in percolating changes to all levels uniformly.

How does all this shape the future of Telcos

In a decade from now, a new breed of asset-light carriers with more sustainable businesses will emerge as technology advances and evolving consumer demands reduce costs across operations.

There is more promise AI and digital technologies holds for Telcos, now more than ever before, which now enables asset-light carriers to operate customer-facing functions at drastically lower costs by substituting computer processing power for people. Both consumer and business customers are increasingly comfortable with digitally delivered self-service options, providing an advantage to carriers that build their businesses this way.

What is within the realm of possibility is that carriers could successfully operate with no stores, no call centers and significantly fewer field technicians.

We are seeing early experimentation with this among Telcos globally, where there are digital only wireless services from large incumbents, namely Verizon’s Visible plan in the US, and fixed wireless broadband Starry’s resource-light model in the US. Over the next decade, this shift toward digitalization and automation could set off a chain of similar events in the Telco market.

Proliferation of asset light carriers will deploy this strategy first, and their lower breakeven point will allow them to focus on targeted, smaller slices of the market. These carriers will be either standalone businesses or new arms of existing companies in other sectors that have strong branding and distribution that they can use to push a telecom offering.

Enhanced profitability of these new market entrants will put pressure on traditional Telcos’ price points and revenue, forcing them to respond with their own digital front ends. As per Ovum research, average Net Promoter Score for early adopters has risen by over 20% points, driving up revenue by up to 10%, while lowering customer-facing costs by over 30%.

Emerging technologies deployed in contact center operations cut down incoming customer calls and improve operations cost. As per BCG analysis, deflection rate of 20%-40% for customer calls can result in lowering the contact center cost by 10%-20%.

Taking a deeper look into this potential, AI implementation results in dual benefit for Telcos. On one hand it generates a potential of ~10% increase in revenue, while on the other hand also helps in cutting down the cost by ~15% across the value chain. Few areas gaining traction on the revenue side are lead generation and personalization, managing customer churn rate, upselling and cross selling offerings to customers. Similarly, on the cost side, network optimization, and workforce optimization.

Incedo’s solutions tailored to meet demands of the AI-led Telco world

Incedo has built a set of AI/ML pipelines that can be configured to solve a variety of operation optimization use cases. These pipelines can automate processes, tap into unstructured data sources for intelligence. Our solutions are driven by the following:

  1. Cross-industry techniques: Inspired by use cases across industries – eCommerce Recommendation Engines, Image Search by Google.
  2. Automated model training: Designed with AutoML features for automated learning across ensemble of techniques.
  3. Self-learning in production: Algorithm to identify model performance and run calibration in production. Like Google Maps suggest better routes when found.
  4. Modular design: Developed as Lego blocks for easy integration into existing infrastructures.

Incedo’s AI/ML Pipeline Tailored for Telco applications

AI/ML Pipeline Objective Techniques Telco Applications
NLP Pipeline To make sense of free form text data Topic Modeling – LSA, LDA, RNN
Classification – LDA2Vec, SGD, Random Forest
Sentiment – Stanford Symantec Libraries
  • Analysing Jeopardy Tickets
  • Automated test case generation
Optimization Pipeline To prioritize between actions based on predicted impact Markov Decision Processes – Markov Chains, Hidden Markov Models, Multi-Armed-Bandit, Reinforcement Learning
  • Emerging Hot-Spots
  • End-Point Placements
  • Personalizing Customer Interactions
Anomaly Detection Pipeline To identify or tag anomalies from a normal behavior AR Family of Models, Auto Encoders, LSTM, Isolation Trees, Neural Nets
  • Predictive Maintenance
Personalization Pipeline To personalize customer touch points – email, store, website, app, customer service Propensity Models to estimate intent
Reinforcement Learning to optimize content delivery in the real-time.
  • Web Personalization
  • Cross-Sell/Up-Sell
  • Customer Retention

Incedo is using its AI/ML pipelines to help a US based Tier 1 Telco to enhance its spectrum of network operations and customer service.

  1. Predicting optical network faults 48hrs. in advance to reduce trouble calls or expensive technician dispatches
  2. Automatic redirection of 5G build out issues to the right team for quick resolution.
  3. Automated ticket logging by extracting relevant information from emails, with the help of NLP based email tagging solution.
  4. Prioritize automation opportunities by identifying process gaps and bottlenecks using data mining algorithms.
  5. For customer service, a major reason why customers call is billing dispute. Using AI, Telcos can analyse user activity across engagement channels, and predict when a user calls in. Identifying intent and tailor customer experience to provide prompt resolution.

Observations from the market

The Covid-19 global pandemic has positioned Telcos at the forefront, in a mission critical mode as an essential services enabler, ensuring continuity in business operations during the pandemic. Advanced technology such as AI powered Digital Experiences, Automation & 5G connectivity are proving vital in delivering solutions to help fight the pandemic. While the adversity has opened up interesting opportunities, there are challenges aplenty.

In this rapidly evolving business environment, the new normal includes enforcement of physical distance and work from home that has created challenges in executing daily activities, work, supply chain and logistical delays, causing delayed initiatives and missed opportunities.

The Covid-19 pandemic has had a substantial impact on Telecoms and allied industries, though it fares slightly better than other sectors like manufacturing, and hospitality, and that no sector is immune to the pandemic, but some will suffer more than others.

Immediate Factors affecting Telco business

There are several reasons that will cause Telcos to revisit their 5G capex programs and deal with delayed timelines due to

  • Global supply chain disruptions,
  • Availability of 5G network devices,
  • Delays in formal standards definition,
  • Spectrum auction delays,
  • Delays in 5G infrastructure permits and inspections,
  • Closure of retail stores,
  • Availability of 5G supported mobile devices,

Immediate Business Impact on Telcos

  • Revenue Impact
    • Communication service revenues declined 3.4% YoY in mature markets.
    • International roaming revenues declined ~6% of billed revenue/year, especially in tourism heavy countries.
    • Freebies and waivers offered to retain retail subscribers.
    • Decline in global SME ICT spend on enterprise revenues.
  • Existing network optimization to deal with surge in network traffic Telcos are spending on improving existing capacities addressing overall network resilience which was positive over the past four months with an increased focus on traffic management, absorbing 10% – 70% spike in network traffic reported across Telcos.
  • Capex & Infrastructure Rollouts Supply side disruption slowed down 5G and fiber rollouts, with a reduction in capex. Potential upside in 2021 broadband demand anticipated to fast-track roll outs.
  • Supply chain Global smartphone shipment to decline 3.1% YoY in 2020. Production slow-down in Asian manufacturing hubs impacts global supply of panels, touch sensors and printed circuit boards.Trade wars notwithstanding, and aversion to Chinese 5G equipment vendors from deploying equipment indicated by several countries globally, including India; alternate suppliers better be prepared to step in to fill in the resultant demand-supply mismatch.

Economic recession slowing down device and service upgrades and suppressed 5G demand will defer Telco plans of aggressive deployment strategies.

As per Statista, the device segment, including PCs and phones could see the steepest fall, currently projected to decline 12.4% in 2020 compared with the previous year. Infrastructure will be the least affected segment according to the adjusted forecast with projected growth of 3.8% in 2020, as businesses keep utilizing cloud deployments. Thanks to the cloud and greater inclination towards “software defined”, technology infrastructure is the only segment in global IT to grow in 2020, while  other segments are projected to decline.

Imperatives for Telcos to emerge as winner in a Covid-19 hit world

In light of the new normal, leading Telcos are addressing three dimensions of managing a crisis; respond, recover, and thrive, which predominantly includes digital technologies.

 Experiences that are built on a foundation of customer-first

Calibrated strategy moving from digital-first to digital-throughout

  • Drive AI and automation programs broadly organization-wide and at far greater speed – network, customer, IT, front desk, and back office.
  • Enhance digital customer experience through self-service channels and support journeys. Intelligent BOTs to serve more than a bridge to the call center for complex queries and increase in AI-agent customer interactions.
  • Build and evolve capabilities to support new Telco value propositions, such as Software Defined Networks, Cloud networking, and Intelligence at the Edge.
  • Continuous testing of network reliability through intelligent automation.

Rapid scalability and resilience of network operations in a hyper-connected 5G internet of everything world Network operations

Overall network resilience was positive over the past four months with increased Telco focus on traffic management, absorbing 10% – 70% spike in network traffic reported across Telcos.
As an instance, leading US Telco Verizon is projected to spend $18.5 billion this year on improving its network resilience, a $500 million increase over its planned spend triggered by demand surge during the pandemic.

Increased spend in building network resilience will be channeled towards modernization of legacy systems that need to scale up to demand.

Telcos and broadband providers are working overtime to cope with demand spikes and maintain reliable connectivity through capex spends, augmenting and optimizing their current wireless and broadband networks. However, the inability to monetize this investment in the short term, and deal with challenges from declining sales and roaming revenue, retail chain closures, relaxing limits and out of bundle charges are hurting the earnings.

Reduced cycle time in innovation and change deployment

The power of AI-based technology combined with 5G when blended with distributed edge computing, cloud and IT functionalities will drive the next wave of innovation. The pace of change will compel innovation cycle times to reduce drastically to make solutions relevant to the current times.

Promise of 5G technology & innovation in a pandemic

5G tech. can address prevailing connectivity and network performance challenges, more so during a pandemic, as it enables the transformation of public health and offers possibilities of new treatment methods. Leveraging advantages of speed, latency, number of connection points and range, apply to the following 5G enabled use cases.

  • Real-time thermal imaging of people in motion in public spaces,
  • Smart robot in Tele-medicine, remote diagnosis, consulting, and emergency treatment
  • AR/VR in Tele-education and Tele-conferencing
  • Smart transportation, unmanned vehicle solution

Cost optimization & efficiencies to gain prominence by moving from fixed cost to variable cost model

  • Transition likely from fixed cost to variable cost model to reduce operating leverage, translating to following shifts:
    • Pay-per-use for O&M, and AMC,
    • Network utilization and consumer demand based site rentals,
    • Retail store redundancies,
      • Automation of business processes for corporate efficiencies such as finance, tax, billing and operations,
      • Consolidation, mergers, and fundamental shift in market structures with formation of Netcos.

Incedo’s service offerings to engage with Telcos

Post pandemic, the economic recovery will happen at a very fast pace that will spur consumer and business confidence starting Q3-Q4. It’s a fact of life that there will be an immediate set back on the supply chain, investments, operation and delivery due to Covid-19. It is unlikely to have a lasting effect in the direction emerging for Telecoms since the middle of the last decade, which is characterized largely by high speed, low latency 5G experiences, digital transformation, AI, virtualization, automation, and accelerated transition from traditional voice to unified communications.

Overall Consulting and Technology Services like ours will need a re-calibrated strategy of delivering solutions focused on immediate needs through digital & automation that will help tide over the current situation.

We help clients unlock the full potential of 5G as it promises to transform the industry. We leverage the client’s digital and data infrastructure to deliver world class customer experience and in optimizing their networks & biz operations.

Incedo solutions for Telco to help tide over the pandemic crisis

  • Legacy Systems Modernization
    • Platform re-engineering
    • Application modernization
    • Cloud engineering & migration services
  • Digital Transformation and Analytics

Combining design thinking, data-informed decisions, iterative experimentation backed by our integrated data science, UX and innovative engineering capabilities provide clients a full-stack solution.

  • Next wave of innovation & engineering will be driven by the power of AI combined with 5G, blended with distributed edge computing, cloud and IT functionalities. Incedo is at the intersection of the blend to deliver innovative engineering solutions.
  • Security takes on an even larger stage with high reliance on economic activity on Telco networks. Incedo’s cyber security solutions address growing vulnerabilities in networks going by the numbers of phishing and malware attacks targeted at remote working.

Why do companies need to reimagine their customer service? And why do they need to learn from Digital Natives like Google, Amazon, etc.?  That is because these digital natives are setting the standard for customer expectations – In a recent survey, when customers were asked which company would they want to take Telecom services from, 60% people responded Google or Amazon!
So what are the key differences in the way Digital Natives approach Customer Service?

  • Fix at Source – While traditional organizations look to call deflection to save costs, digital natives believe that customer service indicates a customer pain point that should be fixed “at source”.
  • Use Product Thinking and Tech to solve issues – Too many processes and policies at legacy organizations are driven by risk, legal and finance making them high friction. Digital natives, start with the voice of the customer to design the right customer experiences and use technology to manage risks
  • Put AI and Technology at heart of everything – Not as siloed solutions to micro-problems but for driving end-to-end orchestration of customer experiences

To build next gen customer service capabilities, Incedo recommends 5 key initiatives:

  1. Use Voice of Customer to drive business priorities
  2. Fix root cause at source using Product Design Thinking
  3. Personalise Service Channel Mix
  4. Leverage AI to increase machine and self-serve digital channels
  5. Use Cloud based architecture to enable AI driven Customer Service at scale

Voice of Customer to drive business priorities

KPIs to optimize: NPS

Customers talk about products and service through multiple medium – they leave reviews on product pages, social media, App Store, etc., call care, write emails or escalate to senior management. Often, the focus of customer service teams is on “managing” these inputs – douse the fire if the review is negative. However, there is a wealth of information available in these customer inputs on what is working and what is not – the challenge is that there is a lot of noise and traditional approaches have been inadequate. Advanced NLP + AI techniques can help organizations extract very actionable insights from these VOC channels

Voice of Customer to drive business priorities
Fix root cause at source using Product Design Thinking

KPIs to optimize: Calls/Incidents per Unit/Order

Most customer service issues require cross-functional approach and product design thinking to resolve at the root cause. For example, when faced with fraud most organization end up putting strong checks and balances in place that also add a lot of friction to genuine customer journeys. Digital natives, on the other hand approach it differently:

  • They build robust tech and AI based preventive and corrective mechanisms and continuously refine them
  • They take a ROI based approach – compensating customers for small ticket breaches rather than adding friction

Personalize Service Channel Mix

KPIs to optimize: NPS, CSAT

A recent study showed that digital channel leads to highest customer satisfaction for service. However, all customers are not equal and so are the issues they face. Personalization of service channel based on following key parameters is recommended:

  • Customer lifetime value – High LTV customers expect white glove treatment best provided by high-quality agents
  • Digital affinity – Forcing low digital affinity customers towards digital channels and vice-versa can lead to dissatisfaction
  • Anxiety Levels – Some issues cause high anxiety, channels with best resolution rates if the customer is reaching out for these issues

Fix root cause at source using Product Design Thinking
Leverage AI to increase machine and self-serve digital channels

KPIs to optimize: Resolution Rate, MTTR (Mean Time To Resolution), Operating Cost

What should you automate or move to self-service? The choice should be driven by volume and resolution complexity of issues. High volume, low complexity issues lend themselves well to self-serve channel whereas high complexity issues will require human touch. Design of chatbot and self-serve solutions should begin with design thinking of customer journeys
Leverage AI to increase machine and self-serve digital channels

Use Cloud based architecture to enable AI driven Customer Service at scale

KPIs to optimize: Time to Market

The solutions and approaches outlined in the previous 4 initiatives require building real-time AI/ML models that evolve continuously. Traditional data and technology architectures cannot keep up with the velocity of change and volume of data. Cloud based architectures are key to solving this problem given inherent scalability and vast & growing libraries of reusable components.
However, transforming existing legacy architectures to cloud based is a daunting task. Organizations can follow a 2-speed approach to this transformation:

  • Speed 1: End to End Cloud transformation use case by use case
  • Speed 2: Building out the cloud architecture that can support multiple use cases and future needs

In conclusion, customer service as most organizations know it is transforming and Digital natives are at the forefront. Leaders of traditional organizations can drive this transformation by undertaking 5 key initiatives that put the customer at the heart of the service – to begin this journey a cross-functional empowered team that can own and drive these initiatives is recommended. It is either that or slow death as customers abandon sub-par experiences for better ones.