How to build your IT infrastructure for 5G-enabled edge computing

The global 5G-enabled edge computing market is growing rapidly, fueled by major technology changes that are disrupting the traditional networking industry. By 2025, this market is expected to exceed $50 billion.

5G has the potential to deliver a new generation of services, thanks to higher data rates and ultra-low latency. To take advantage of this potential, communications service providers are looking to move data processing and compute power closer to the end user — closer to the edge.

While the digital boom provides many opportunities for IT leaders, it comes with challenges: a growing number of smart devices, the need for faster processing and increased pressure on enterprise networks. To harness all this potential power, organizations need to modernize their networks to effectively consume these new services at the edge.

Some key trends are empowering this shift toward the 5G-enabled edge.

Shift to cloud-based virtualized networking

Ever-increasing amounts of data and video, mobile workload volatility, the rising number of connections and demand for lower latency are all driving organizations to develop transformative strategies. To embrace the 5G-enabled edge future, businesses must transition to networks with cloud-based virtualized networking.

Cloud-based networking allows for simplified management and expansion of network capabilities, which helps accelerate innovation, service fulfillment and operations.

Virtualization and cloudification are paving the way for an unprecedented level of cognitive automation, allowing networks to conduct intelligent, agile, responsive network and service operations.

The rise of NFV and SDN technologies

Network function virtualization (NFV) and software-defined networking technologies are expected to present the highest opportunities in the 5G infrastructure market. As a key enabler of 5G infrastructure, NFV is the next logical step in network evolution. NFV replaces single physical network appliances with virtualized network functions linked together across virtual machines.

Software-defined networking (SDN), on the other hand, is designed to make networks more flexible and agile. SDN redefines network architecture to support unique requirements of the 5G ecosystem. 5G SDN will play a crucial role in the design of 5G networks. In particular, it will provide an intelligent architecture for network programmability, as well as the creation of multiple network hierarchies.

AI and automation-enabled network management

The move toward virtualization and cloudification will require new levels of network automation, especially in a world where workloads are increasingly dynamic and many IoT applications require low latency. This would warrant a shift to AI-enabled network management platforms.

Network DevOps

The adoption of cloud-based virtualized networks has initiated a need for a continuous development and operations (DevOps) methodology. This is important in order to facilitate an automated, factory-based approach for end-to-end service lifecycle management.

Adopting a DevOps methodology for network operations is crucial to future network evolution because it provides an environment for continuously engineering (building, onboarding, testing and managing) new services — not to mention ongoing updates for existing services.

Network DevOps enables a lean, effective way to implement functionality and services that help improve customer experience and drive revenue by automating the services lifecycle and driving resiliency. As networks become increasingly software-based, this provides a straightforward way to create new services by assembling and chaining software components together. In fact, it allows for a DevOps-like model for network service development, network operations and end-to-end management.

There is no doubt that the explosion of the 5G-enabled edge market presents incredible opportunities for businesses to streamline IT operations and reap new value from existing resources. Implementing transformative network strategies and modernizing enterprise networks will help innovative business get the most from this opportunity and deliver new services at the edge.

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How healthcare payers can win in the world of the cognitive enterprise

new era of business reinvention is dawning that will accelerate disruption and reshape health insurance. With increasing pressure to improve customer experience, manage the explosion of data, and harness the potential of artificial intelligence (AI) and smart technologies to differentiate and drive growth, payer organizations must evolve to the next generation model for digital transformation — what we call the “Cognitive Enterprise.”

Shifting to a cognitive enterprise involves more than integrating cutting-edge technology. It requires a complete rethink of organizational culture, structures, and processes, powered by optimized use of data. Only then can a business move faster and smarter, enabling intelligent operations and continuous insights-led, customer-focused innovation.

The path to a cognitive enterprise is a transformation journey, but there are several elements for a winning strategy and concrete actions that can help you succeed.

So, what is the cognitive enterprise?

Digitally connected, cognitive organizations better understand customers and quickly pivot from insight to action. Championing change, they anticipate disruption, exploiting data and technologies to push into new directions, while enabling an agile workforce and improved market responsiveness.

Most organizations are just beginning to prepare for the monumental changes that will characterize the coming decade, fueled by unprecedented technology convergence. Cognitive enterprises are investing now to continue their journeys to the cloud and AI, experiment with new technologies, shift applications and infrastructures from legacy to new, and advance digital capabilities.

They’re also adapting organizational models and mind sets to optimize ways of working, enable new skills, and empower employees to innovate ideas and approaches that better meet customer needs.

Improving member experience

Cognitive technologies, such as AI and machine learning, enable healthcare payers to make sense of the massive amounts of data they collect and uncover meaningful insights at unprecedented speed. Designed to comprehend, reason and learn, AI automates real-time insights, revealing deep connections for a more nuanced understanding of individual customers and their health journeys.

Armed with this knowledge, payers can dissect how customers research, obtain and use health insurance, and they can tailor support to help consumers navigate decisions, meet wellness goals and effectively manage medical events, conditions and life stages.

Multidimensional intelligence also allows payers to personalize member experiences and drive proactive engagement, anticipating needs, shaping new products/services and solving issues or communication gaps, while predicting what customers are likely to want or need next. Creating a fuller picture of the customer experience, payers can improve trust, as well as satisfaction.

Empowering employees

Cognitive enterprises are embracing smart tools to drive new capabilities and streamline processes, to change how work is done. Combining technologies such as AI, multicloud, Internet of Things (IoT) and blockchain, organizations are building intelligent workflows that improve decision-making, as well as administration and delivery of care.

But digital transformation isn’t just about technology; it’s also about people. Cognitive organizations recognize they must build the workforce and culture needed to enable agile innovation and customer-centricity. They empower employees with more trust and autonomy, forming dynamic, collaborative teams that continually look for new ideas and approaches to better serve customers, enhance skills and improve work processes.

Optimizing interactions between smart machines and even smarter humans, cognitive organizations let employees move quickly from insights, to smart experimentation and consequent action, to rapidly respond to opportunities and market changes.

Advancing digital platforms

Design thinking, co-creation and agile approaches allow cognitive organizations to design integrated business platforms that deliver the perfect fusion of technology, powered by data to create more agile, intelligent services.

Developing a customer-centric, platform ecosystem that brings together cutting-edge technologies, underpinned by data, organizations can deliver successful customer, employee and partner experiences. The strategy for this modern platform architecture should:

◉ Redesign company workflows around AI: Designing business platforms that leverage the full power of data and AI to create smarter workflows, automate and digitize operations, and enable new capabilities, while ensuring deeper interoperability and connectivity with the ecosystems and networks that support customers.

◉ Support agile delivery: Optimizing AI-driven data, marketing, customer and CRM platforms, and linking these with other operational systems, can automate real-time data analysis, speed knowledge sharing and eliminate functional silos. This fuels agile collaboration and responsiveness, meeting customer needs in the moment.

◉ Connect customer touchpoints: Consumers expect companies to know them and provide individualized, on-demand, responsive services. AI-powered platforms enable organizations to connect in relevant ways, engaging members with personalized, timely interactions and delivering integrated experiences across touchpoints.

◉ Deliver trust and security: Trust in data is at the heart of cognitive workflows and decision-making, requiring organizations to ensure both the human and machine elements of key workflows and data sources are secure.

Transforming customer support

Imagine a cognitive assistant that can engage customers in real conversations, understanding what people say, as well as what they mean, and even detect sentiment and context to respond in meaningful ways. Sophisticated AI-driven speech recognition systems are using real-time data to enable conversational assistants to deliver on-target customer support, 24-7.

Offering consumers instantaneous answers, these cognitive assistants can help people connect to the right information, navigate choices and even complete health-related tasks. By removing the complexity of touchscreens and keyboards, they simplify interactions, expand self-service opportunities and can also entertain and educate members.

Because they offload routine inquiries, cognitive assistants also free up live agents to focus on more complex problem resolution. These tools can deliver convenient, personalized support, helping to strengthen brand connections and member satisfaction.

Building for the future

To make the shift to a cognitive enterprise, organizations will need to keep the human factors front and center, while considering how smart technologies can advance digital transformation to enhance both customer and employee experiences.

The winning formula will enable customer centricity, agile operations and smart workflows. It will also position the organization to differentiate their brands, better serve members and unlock growth. Now is the time to define the roadmap to deliver value in both the short and long term, capitalizing on the continual disruption that comes from being a cognitive enterprise driven to build the future of healthcare.

Source: ibm.com

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What if you could operate 10x faster at half the cost using cognitive RPA?

In a hugely competitive global industry, telecom operators must balance ongoing customer satisfaction against reducing operating costs. Too often, subscale technology investments are made for meager benefits, and automation is bolted on cumbersome processes supported by decade-old systems. Worse still, automation is often implemented without revisiting the underlying customer experience or evaluating what artificial intelligence (AI) could do to improve productivity.

The telecom industry runs rife with highly manual, voluminous, repetitive and complex rule-based transactions – things such as order validation, service fulfillment, service assurance, billing, revenue management and network management – and closely coupled with multiple legacy systems. With as result rigidity and lack of transaction visibility. In traditional lead-to-cash processes this has often led to poor service and customer dissatisfaction. Slowed by the process, customers are disincented to stay loyal, looking for a better offer elsewhere.

Reimagining the customer first

Companies are increasingly using robot process automation (RPA) to automate routine tasks. RPA’s potential benefits are manifold. They can include reducing costs, lowering error rates, reducing turnaround time, increasing the scalability of operations and improving compliance. By moving beyond basic robotics to intelligent interaction by combining RPA and cognitive technologies, telecom operators can replace tedious tasks and deliver costs savings and greater workforce productivity by:

◉ Striking a better balance between the front and the back office, while becoming faster and more reliable

◉ Enabling customers to self-serve so that sellers can focus more time on complex orders

◉ Cross-selling and up-selling through assisted sales and creating recommendations that all sellers know what the best sellers do.

The integration of cognitive technologies and RPA (see Figure 1) is extending automation to a new level, in this way helping telecom operators to become more efficient and agile and delivering more consistent services to the customer which is paramount in the current digital economy.

Figure 1. Moving beyond robotics to intelligent interactions

Entirely new user experiences can be achieved by taking an over-the-top (OTT) approach. The idea is to preserve the legacy system’s (also known as systems of record) capabilities to be the custodians of the business transactions. By interfacing with the “systems of record” through existing APIs or microservices, one can redefine the user experience more freely and use a combination of capabilities ranging from business rules engine, business process and management (BPM), AI, RPA and blockchain.

Using these tools in conjunction, and playing to the strengths of each of them, business benefits are amplified beyond what is achievable by overextending a single technology. This enables transparent and flexible automation of the business process in response to business needs. Technologies embedded with RPA can provide autonomous decision making, enable reasoning and remembering, and provide new insights and data discovery. For example, using AI and RPA technologies as part of a sales order management process can guide the seller to improve data accuracy by making recommendations that improve over time.

A process automation platform that sits “over the top” of existing IT interacts with IT but doesn’t require significant change. It lets telecom operators design the customer experience they want, then implement the transformed process to support that experience. Since intensive manual intervention isn’t required, the benefits of creating the process and experience supported by a process platform have positive impacts on productivity, cycle time, cost and customer satisfaction.

Massively reducing operational expenditure

Faster order fulfilment at half the cost, more self-serve options so sellers can pay more attention to complex orders and intelligent lead-to-cash processes that steers the back-office towards more areas of value are key to change telecom (see Figure 2, a tier 1 telco).

Figure 2. Example of operator transformation business case

Dramatic cost reductions can be realized in incremental sprints, with significant meaningful change possible in just months. It requires focus on the following areas:

◉ Build a business case with the line of business or shared services that will see the greatest gains and align incentives to make collaboration happen. Start with relieving pain points and improving the user experience.

◉ Decouple legacy from a new user experience. Don’t rebuild IT but breathe new life into interactions with older, legacy applications to provide the much-needed budget relief.

◉ Create a center of competence that includes design thinking approaches and build AI and robotic content libraries and extensive industry-specific process flows and business rules. Consider AI process platforms to automate perceptual and judgment-based tasks through the integration of capabilities such as natural language processing, machine learning and speech recognition.

We’re at a key inflection point, moving from a world of processes run by humans supported by technology, to processes run by technology supported by humans. Where are you in seizing the opportunities that cognitive RPA offers?

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How to transform customer experiences with cognitive call centers

Customer data and insights can help steer companies to new levels of innovation, engagement and profit. And, most organizations are sitting on a gold mine of customer data. But, it’s how customer data is used that matters. How is your organization collecting and using customer insights? Are you using it to create the most engaging customer interactions? And, are you creating a cognitive conversation with your customers? These are critical questions that not all companies are yet considering, but should.

Understanding the importance of cognitive conversations

A cognitive conversation takes advantage of data from external, internal, structured and unstructured voice and multichannel sources to deliver a customer response that is more conversational, relevant and personal. Organizations can meet changing customer preferences and behaviors by learning from every interaction. All parts of the organization can take advantage of data collected from different areas of the company to improve customer loyalty.

Businesses are recognizing that while customer interactions often begin on one channel, valuable insight and feedback is also being gathered from customers on other channels across the business. Unifying customer information across channels gives businesses a more complete context to resolve customer issues more fully and more quickly.

With the speed to which customer expectations are changing, it is conceivable that customers will prefer to manage their relationship with businesses without interacting with a live agent. Customers are using more channels to interact with businesses and are doing more research through websites and referrals before ever engaging.

A more conversational, personal, seamless and device-independent approach to customer engagement is critical. Customers are likely to commit to a brand or product after a satisfactory experience, so it is time the whole company focused on adopting capabilities to enable a more cognitive experience for clients and potentially surpass competitors.

Taking full advantage of the gold mine of customer data

Every department in your organization, from marketing to sales to customer service, has data on customer behavior. That collective data can be used to meet and even exceed the demands of customers. An organization’s brand, website, notifications and certain self-service channels, whether voice or chat, demonstrate commitment to the customer.

It may seem overwhelming to gather all this information across your organization at every entry point of interaction and also deliver a seamless, consistent and cognitive experience. But, it doesn’t need to be.

If you can tap into cognitive capabilities, they will turbocharge interactions across channels. This combination can transform traditional self-service brand engagement into a more relevant and relational experience for customers. Customers can use both traditional interactive voice response (IVR) features with cognitive capabilities, which can be integrated with an existing contact center environment, as well as other third-party applications such as computer-telephone integration (CTI). Combining these capabilities is a unique approach that transforms the customer experience to a more conversational and cognitive interaction. As a result, resolutions can be achieved more quickly than interactions handled by traditional IVR systems alone.

Transforming the customer experience

Changes in the customer experience journey are happening fast. There is no slowing down or stopping the convergence of technology and increasing demand for quick, relevant and personalized customer interactions. The stakes are high when it comes to the customer experience, and it’s not just the contact center that needs to take notice. The customer experience is a whole-company issue.

Customer experience is at a crossroads of change and transformation, adding a new level of engagement across the organization. Taking advantage of the forces pressuring organizations to evaluate their strategy, technology and general understanding of customer behavior will set the pace for the cognitive revolution.

Four key factors are making transforming the customer experience a hot topic:

1. Increased value of customer experience as a market differentiator
2. Speed of changing customer demands
3. Cognitive capabilities make collecting, learning and understanding data in near real time a reality
4. Market leaders figuring out how to combine knowledge with technology to magnify the customer experience

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