Data is the new gold! Why data driven transformation puts you ahead of the game in Industry 4.0

Contributed by Lucky La Riccia, Head of Cloud Software & Services, Ericsson Middle East and Africa.

The ever-increasing pace of digital technology has transformed and created a new business climate that is moving faster than ever before. Unlike previous generations of the industrial revolution, Industry 4.0 is significantly transforming the way goods are produced and delivered and moving toward an industry that is fully connected and automated. The complexities of meeting customers’ needs have driven businesses to embrace the use of analytics to remain competitive and productive.

Data is the new gold in this technology-led era, and data-driven transformation places organizations ahead of the game. Adapting and implementing the best technology without pursuing data-driven transformation will still make an organization less competitive and in danger of going extinct.

 

Figure 1: Increasing complexity requires new technology for proactive & data-driven operations

 

Data-driven transformation is an organization’s ability to make better decisions leveraging data collected at various touchpoints from human-machine interactions using technologies like the Internet of Things (IoT). It is about leveraging insights into customer behavior, market trends, and operational efficiencies—a complete shift from the previous model based on a reactive approach to one that revolves around utilizing data for close to accurate predictions. Its benefits are enormous and include network stability, which is the foundation of a good user experience; reducing the volume of work orders and site visits, leading to a reduced cost of ownership; providing the best customer experience; reducing energy consumption; and ensuring the highest security standards.

Embarking on a data-driven transformation means leveraging a robust set of digital tools, which include automation, analytics, process mining, process discovery, machine learning (ML), and artificial intelligence (AI), to evolve the process execution from basic automation to awareness, adaptiveness, and eventually an autonomous state of orchestration. These lead to successful digital transformation for organizations of all sizes and create genuine business value and an outstanding competitive edge. These digital tools are essential to getting the most from data-driven operations.

The next evolution of data-driven operating models will need to support a wider variety of applications and use cases for consumers and businesses. Communications service providers will aim to provide configurable services with detailed agreements on functional and non-functional characteristics that require dynamic adaptation in real-time to deliver on these requirements. Concepts like “autonomous networks” and “intent” are needed to drive new propositions and automate networks to meet performance KPIs, SLAs, and business outcomes.

We see three main drivers for intent in building and operating new services. The first driver is the complexity and cost of operating 5G networks and beyond, which require a new level of automation—a level beyond even machine learning (ML) and artificial intelligence (AI). Secondly, the need to transform operations to better meet the needs of the business. Finally, the need for transparency and artificial intelligence (AI) explainability—so that we can trace back all decisions recommended and acted on by the system.

Today, Ericsson has 200 managed services contracts globally, out of which 25 have been transformed to Ericsson Operations Engine, which is a multi-vendor, multi-technology framework and the heart of our data-driven operations approach. It cuts across multiple dimensions, from processes through competence, organization, strategy, governance, data, automation, and artificial intelligence (AI).

This massive scale enables global feedback loops that we leverage to constantly evolve our processes and grow our closed-loop automation and artificial intelligence (AI) use case libraries, making it possible to handle 18.2 M work orders and 5b alarms every year with highly focused human intervention.

 

Figure 2: Quantitative benefits of the data-driven journey based on aggregated figures from 20 CPSs from Q1-2019 to Q4-2021.

 

This has a significant tangible impact on communications service providers’ operations and business outcomes. From a network performance perspective, data-driven operations reduce network unavailability by 34 percent while decreasing customer complaints by 21 percent. On the network efficiency side, the transformation led to a significant 12 percent reduction of work orders (WO) and 24 percent lesser truck rolls per node, and up to 8% reduction in energy consumption which has an important impact on CO2 emissions.

Leveraging our Managed Network Operations, we help operators transform their operations to successfully manage the increasing complexity of their networks. We achieve this by capitalizing on Ericsson’s global scale and telecom domain expertise; a proven data-driven transformation track record with outstanding results and award-winning customer references; committed service levels and predictable costs over the next 3-5 years; and the latest market artificial intelligence (AI), automation, and data insights as part of the Ericsson Operations Engine solution.

Adding people around legacy processes is not sufficient to deliver the volume and speed of change needed. A new look at data, processes, and automation is key to turning operations into data-driven ones. Transformation should not solely be focused on amending what is happening today. The real challenge lies in how to get there; it must be based on a clear vision of what the organization wants to achieve and deliver in the future. Defining this clear vision, anchored on tangible and measurable business outcomes and a solid investment plan, supported by executive sponsorship, must be the starting point.

The key to successful transformation is in the hearts and minds of the people affected. A new functional and organizational model is required to enable this digital transformation to service-centric and data-driven operations. If they embrace the vision and journey, the chances of success increase exponentially. On that basis, a smart change program is paramount and should be supported by strong and active communications and leadership involvement that engage people to propel the transformation forward.

Read more on our .com page: Data-driven operations. Does it pay off? – Ericsson

Blog originally posted on our .com page: Data is the new gold! Why data driven transformation puts you ahead of the game in Industry 4.0

Contributed by Lucky La Riccia, Head of Cloud Software & Services, Ericsson Middle East and Africa

Link to bio

Decoding a Bottom-up Operating Model for a Successful 5G Journey

Contributed by By Don Alusha, Senior Analyst, ABI Research.

To date, Communication Service Providers (CSPs) have pursued growth by selling and upselling telephony products in the consumer domain. With 3G and 4G, CSPs create value by mapping upward on their “sustaining” cellular trajectory toward consumers that are not satisfied with the functionality that each cellular generation offers. For example, as shown in Figure 1, 2G introduced Short Messaging Service (SMS), whereas 3G introduced browsing, video, and photo sharing. And 4G introduced speed, capacity, and Internet Protocol (IP) telephony. Branding power and, by extension, value creation migrate upward on the technology improvement trajectory. By contrast, with 5G, the industry has an opportunity to introduce something above and beyond Mobile Broadband (MBB).

For example, with 5G, CSPs have the potential to offer edge services, low-latency local data and compute processing, Application Programming Interfaces (APIs), and ecosystem development. 5G is expected to enable expansion of the existing consumer value chain. But importantly, 5G redefines CSPs’ service delivery and value capture models. In other words, there is an operating model disruption. CSPs’ existing operating model changes, both in terms of the nature of requirements and the sheer requirement scope that must be managed. With 5G and software platforms, a CSP’s operating model will need to propel a series of business outcomes supported by a thorough knowledge of customer circumstances. Enhancing the predominant top-down operating model is a transition journey for CSPs. But it is one that holds potential for new growth avenues.

Consumer Operating Model

With 4G, CSPs’ operating model is both universal and uniform—integrate cellular networks to provide mass market, country- or region-specific subscriber static voice and data services. CSPs’ growth profiles revolve around technical excellence in cellular. Service logic resides within the network itself and is under CSPs’ control, producing positive feedback loops and outsize profits. A “build it and they will come” strategy is the starting point. What technology can be built is the foundation of a centrally governed approach. In that respect, CSPs capture profits from core to (subscriber) edge. It is an operating model where technology sets the (consumer) business agenda. It is an operating model where the buying party (subscriber) is a long way away from CSPs in terms of arm’s length. That is an all control, all top-down operating model that starts to be tested with 5G cloud networks and software.

Figure 1: Existing Consumer Value Chain (Source: ABI Research)

 

With network cloudification and 5G, the industry structure evolves toward decentralization. In contrast to 4G, 5G Network Functions (NFs) are spatially separated from one another. A case in point is local deployments of 5G User Plane Function (UPF), paving the way for CSPs to move into edge deployments and topologies. In other words, CSPs move out of the four walls of their virtual Data Center (DC) or physical DC to place networks and compute as close to their customers as they can. In a 5G era, CSPs’ cell sites, central offices, and DCs become infrastructure hubs. CSPs’ DCs grow from hundreds to potentially thousands, Virtual Machines (VMs) proliferate from hundreds to thousands, and networks increase from tens in central environments to hundreds at the “edges.” Consequently, CSPs shift from centrally hosted workloads in their DCs to a combination of central- and edge-hosted workloads in both partners’ and CSPs’ DCs.

Clearly, in a 5G era, the cellular ecosystem moves away from the “closed” and inflexible order of hierarchy toward openness and the fluidity of decentralization. And that, in turn, triggers structural changes not just in how next-generation 5G networks are designed, but also in the operating model required to commercialize those networks. These changes stand to be the pivotal axis for the emerging competitive landscape. For example, in software-centric 5G networks, there are constantly changing requirements, and there is customer- and/or service-specific connectivity. In this commercial setting, vectors like commercial focus, strategies, and operating models to execute start to be tested. Subsequently, a challenge that CSPs must contend with is on the operating model front. But the innovation potential that comes from modernizing existing cellular practices outweighs the transient challenges CSPs will have to face.

Strategize Bottom-up for a Successful 5G Journey

There is a growing demand for partners that understand customer requirements. For example, in the retail industry, for Sainsbury’s, the second largest chain of supermarkets in the United Kingdom, the requirement is not on the technology per se, but rather the business outcomes technology enables. Technology for Sainsbury’s is important as far as it enables the company to deliver on business goals. Sainsbury’s is interested in (any) technology supplier that can propel a whole series of business outcomes for it. For instance, speed of check out; how quickly they can get somebody through a register; how much shopping can Sainsbury’s digitally get inside a store; and how much data can Sainsbury’s deliver reliably to an end point (customer in store) are business outcomes it seeks to achieve. Ultimately, for Sainsbury’s, much like other enterprises and industrials, it comes back to what it wishes to achieve as a business. In other words, Sainsbury’s is on the lookout to buy solutions.

Clearly, enterprises define quality within the context of a “job to be done.” What enterprises need is the starting point. Their business outcomes set their partners’ technology agendas. In the emerging market landscape, there will be enterprise-specific, market-specific value-based engagements. Against that backdrop, CSPs will almost certainly need to learn to drive value bottom-up. In addition to continuing to excel in mass market MBB business, CSPs should adopt new business models. For example, CSPs should cater to a diverse set of application requirements, different services, and different connectivity needs. In other words, CSPs should build their growth profile starting from (enterprise) edge requirements and extending to (network and/or compute) core operations. This bottom-up, value-capture operating model equips CSPs and their peers with the readiness to intimately understand unmet individual customer requirements and respond in a targeted fashion.

5G cloud networks stand to unlock new transactions that supplement consumer volume-centered modus operandi with a bottom-up value play for discrete engagements. But the power of a bottom-up model is not enough. To monetize 5G-enabled digital services at scale, some of the existing top-down intelligence is needed, too. Learning how to operate in this hybrid top-down and the emerging bottom-up, horizontally stratified ecosystem is a journey for CSPs. Going forward, an effective and efficient operating model must contain both control and lack of control, both centralization and decentralization, and a hybrid of bottom-up plus some of the “standard” top-down intelligence. The idea is that CSPs’ operating models should flexibly fit and change in line with new and elastic market requirements as they continue their 5G journeys. Otherwise, new growth forays may hit a roadblock.

 

About the Author

Don Alusha is a Senior Analyst in the Telco Digitization practice at ABI Research where he provides research and analysis on service provider adoption of cloud technologies and their application in fixed and mobile networks. Pertinent research topics include Artificial Intelligence (AI) and Machine Learning (ML) technologies, Software-Defined Networking (SDN), Network Functions Virtualization (NFV), telco software, and applications.

 About ABI Research
ABI Research is a global technology intelligence firm delivering actionable research and strategic guidance to technology leaders, innovators, and decision makers around the world. Our research focuses on the transformative technologies that are dramatically reshaping industries, economies, and workforces today.

ABI Research是一家国际科技情报公司,为全球科技领袖、创新人士和决策者提供实用的市场研究和战略性指导。我们密切关注一切为各行各业、全球经济和劳动市场带来颠覆性变革的创新与技术。
For more information about ABI Research’s services, contact us at +1.516.624.2500 in the Americas, +44.203.326.0140 in Europe, +65.6592.0290 in Asia-Pacific, or visit www.abiresearch.com.

 

Wake up Neo…

Contributed by Sam Keys-Toyer, Head of Business and Portfolio Development, Managed Services Networks, Ericsson.

The industry has a successful history of managing networks by technology domain, with the basic ideal that if you maximize the availability of the network then you maximize the customer experience. This inside out philosophy has served the industry very well in the past decade, but it will not be enough to address the dramatic increase in service demand variability and the augmenting service outcome diversification CSPs are aiming to provide.

In 1999, I was about to enter my 30s when the Wachowskis released The Matrix, a science fiction-action film masterpiece about a massive simulated virtual reality world, created by Artificial Intelligence that blew my mind and maybe inspired the ideas behind the “Metaverse”. Twenty-four years later, not even the Wachowskis could have imagined the intensifying complexity at the Network Operations Centers (NOCs) behind today’s Matrix, inside Telecom Networks.

I took the red pill

After watching the film, there was only one question running through my head, how could anyone (human or machine) manage such a massive scale of data to keep the Matrix up and running? What was the operating model able to run such a big virtual reality simulation?

Back in 2018 I leaped at the chance to lead a revolutionary project aimed at transforming Ericsson’s network operations model, a kind of the engine behind the film story that fascinated me 20 years before. We took a blank sheet of paper and started to define a new operational approach. One that moved Communication Service Providers (CSPs) away from reactive and incident driven operations to predictive and data-driven operations.

As part of their individual journeys toward that future, CSPs would need to transform in two essential dimensions, one technological and one organizational. The technological dimension entailed CSPs fundamentally moving toward an operations environment that was orchestrated end-to-end in an intent-driven fashion.

The organizational dimension, on the other hand, encompassed the cultural shift, re-engineered processes, ways of working and skills that CSPs would need to make internally to fully become a data-driven organization.

At that time, it was already clear that without addressing the organizational dimension and properly transform operations, CSPs could run the risk of simply adding complexity with new technology which in turn would drive cost.

While transforming operations is a constant state for most CSPs, the pace of change was new. Most CSPs were transforming too slowly, and continued effort was required to capture new opportunities, for example, at the network edge.

 

The Engine behind The Matrix

And the culmination of that project was the launch of the Ericsson Operations Engine (EOE) in 2019 – our multi-technology and multi-vendor data-driven approach to operate and optimize telecom networks. Ericsson Operations Engine is essentially a catalyst for CSPs to succeed in today’s “5G Matrix”, an agile and holistic solution intelligent enough to ensure a smooth operational transformation that capitalizes on people & domain expertise; data driven processes; modernized applications & platforms; automated and AI driven insights.

Today, I can proudly say we succeeded. The Wachowskis would have been able to see unparalleled scale enabled by global feedback loops that constantly evolve our processes and grow our closed-loop automation & AI use case libraries, making it possible to handle a Matrix of more than 710 thousand sites, 18.2 M work orders and 6.4 M RAN cells with highly focused human intervention. To illustrate, the aggregated level of close loop automation within our today’s network operations is above 88% and in 2022 we reached 36 M of AI recommendations annually.

This has a significant tangible impact on CSPs operations business outcomes. From a network performance perspective, data-driven operations reduced network unavailability by 34 percent while decreasing customer complaints by 21 percent. On the network efficiency side, the transformation led to a significant 12 percent reduction of work orders and 24 percent less truck rolls per node and up to 8% reduction in energy consumption which has an important impact on CO2 emissions.

Equally important is the benefit to cost and performance of running a network operations organization. The shift from people-based delivery to machine based delivery changes the cost and productivity profile significantly. Contrary to the Matrix, people are still required, but need to be skilled for different roles and the machines at this stage are most definitely not in charge. The Cloud has helped with 5x more efficient compute, than we had in the days of owning our own data centers. All of this means that you can achieve your goals of best network performance at much lower costs.

 

The intent-driven Matrix

Results speak for themselves, the so-called triple A (Analytics, Automation & Artificial Intelligence) has been and will continue to be a key element in this story. However, if we want to continue leading the CSPs transformation journey we- like Neo-, need to follow the white rabbit towards a scenario where telecom networks can rapidly respond to CSPs needs with little manual intervention by translating commands (Intents) into network-based actions.

Certainly, intent-based operations is an inevitable shift in the approach to monetize the 5G investments. The network will need to support a dramatic increase in service demand variability and adding more humans to cope with this demand will not scale. We see three main drivers for intent in building and operating new services:

  • The complexity and cost of operating 5G networks and beyond require a new level of automation – a level beyond even AI/ML today’s automation.
  • The need to transform operations to better meet the needs of the business.
  • The need for transparency and AI explainability – so that we can trace back all decisions recommended and actuated on by the system. Its about Trust!

Obviously, our EOE Operating model is evolving to support a self-optimizing network driven by intent and underpinned by hyper-automation. This involves transitioning from people managing the network to people managing the machines that manage the network. For this to work, data/knowledge, policy, automation, assurance, analytics, machine learning and reasoning, and security must be integrated into a true Intent-Based (Matrix)Network.

 

Industry must follow the white rabbit

The next evolution of the Data-driven operating models will need to support a wider variety of applications and use cases for consumers and businesses with CSPs aiming to provide configurable services with detailed agreements on functional and non-functional characteristics that require dynamic adaptation to the network. A sort of Hyper-automated Matrix reloaded, where telecom networks must be managed in real-time to deliver on these requirements. Concepts like “autonomous networks” and “intent” are needed to drive new propositions and automate the network’s state to meet performance KPIs, SLAs, and business outcomes.

During FutureNet World earlier this month, I had the chance to meet some industry analysts and customers and get a first-hand view from different sessions where I heard directly from CSPs how they are already anticipating a radically different future for their companies, particularly repositioning their business as solutions companies in line with what enterprises are demanding from telcos. This was really well encapsulated by the Enterprise Opportunity presentation by STL partners.

Lots of interesting discussions around Open Telco and Networks as a Service (NaaS), particularly the transformation challenges that a disaggregation strategy comes with. Having said that, it seemed clear that all the challenges ahead will require solid Data-driven operating models that, as shared during my presentation, are already paying off for CSPs.

By the way, I still prefer the original Matrix trilogy, but, I still don’t know Kung Fu.

 

Learn more about Ericsson’s Data-driven operations [https://www.ericsson.com/en/managed-services/data-driven-operations-does-it-really-pay-off]

Header image attributed to Marcu Spiske via Unsplash

 

Intelligent Operations Adapt & Thrive: Drive Operational Efficiencies Through Automation

Contributed by Alejandro Neme, Solutions Architect, Reailize, a B-Yond Company.

The Current Situation

In the 21st century, communications technology advancements have accelerated the pace of change for CSPs. In addition, the pandemic amplified the urgency of profound CSP reinvention by increasing societal reliance on physically distanced communication. The resultant increase in consumer demand further accelerated the necessity for CSP operations modernization. CSPs now need to adopt an IT-like operation paradigm to decrease operational costs, to improve time-to-market of new services, and ultimatelty to increase revenue. On the path to growth at scale, Cognitive AI will enable intelligent network operations to reduce OPEX, improve customer experience and decrease the adverse impact of network incidents on revenue by reducing the time to triage, troubleshoot and resolve customer impacting incidents. Likewise, migration to centralized and open OSS/BSS tools with open APIs will reduce licensing fees and CAPEX associated with individual domain-specific OSS tools by eliminating duplicated tasks and overlapping workflows.

 

The Resolution Path

In addition to reducing OPEX and CAPEX expenditure, new revenue opportunities are driving CSPs to embrace digital transformation. For example, new revenue streams are emerging thanks to modern technologies like mMTC, URLLC, eMBB. Services such as industrial & vehicular automation, mission-critical broadband, augmented reality and smart city cameras require guaranteed SLAs & OLAs. Best effort Quality of Service (QoS) is no longer an option. In addition, to beat the competition, CSPs must expedite time-to-market for new services and products. To be successful, CSPs must also be agile in service fulfillment and close the loop with the service assurance processes.

The characteristics of traditional, unintelligent CSP operations include:

  • Siloed incident management caused by inefficient and overlapping workflows overlaps leading to longer issue resolution times
  • Domain-specific OSS tools increase licensing and support costs
  • NOC and SOC are flooded with alarms, simply too many to effectively manage, leading to delayed reactions or completely missed incidents
  • No way to determine the customer impact of network incidents in real-time, resulting in investing time and effort into fixing problems that have limited or no impact on customers. In parallel, actual customer impacting issues are going unnoticed and unresolved
  • A break-fix approach which is completely reactive, often customers have already been impacted by the time the issue is discovered

 

The adoption of Intelligent Operations will help CSPs overcome many of these challenges.

This blog describes Intelligent Operations from a 3-dimensional perspective, namely, People, Processes and Technology. The progression of the technology dimension will be addressed through the design and enablement of centralized cloud native end-to-end automated and Continuous Assurance. Key objectives that need to be achieved include:

  1. Understanding customers’ real experience and real perspective of using services, monitoring that continuously and raising anomalies when there are service quality degradations
  2. Correlation of service degradations against network alarms, performance counters, configuration management and other relevant sources of information to rapidly understand where the problem is occurring
  3. Learning the patterns from past incidents and apply those learnings to predict future incidents
  4. Understanding of actual and predicted customer impact of network problems and using that to prioritize those problems based on customer, service and revenues impact
  5. Automation of the root cause analysis of customer impacting issues, using AI to provide recommendations on how those issues can be resolved and where possible, automation of the resolution of those issues back into the network before customers even realize they have an issue
  6. Leveraging AI and ML to predict issues before they occur based on the learnings from past events. This enables a CSP to become truly proactive.

 

On the People pillar, the goal is to populate operational organizations with DevOps-skilled collaborators who can take E2E ownership of service incidents. The biggest hurdle here is to convert the mindset of people from siloed operations organizations to a collaborative, customer-centric way of working. The intended outcome is automated network operation that allows high-skilled Engineers to focus on QoS / QoE by gradually enabling ML/AI to manage manual tasks related to monitoring, detection, alerting, remediation and service fulfillment.

On the Process pillar, intelligent operations will assess and evolve legacy processes. The Legacy approach to network assurance was siloed, inefficient, and riddled with duplication of effort. As the pace of change in the CSP industry continues to accelerate, goals have transitioned towards establishing processes focused on service assurance/fulfillment through a closed-loop approach. The CSP processes of the future must eliminate manual, repetitive tasks and workflow overlap.

The business outcomes from following this approach are:

  • Improved customer experience means happier customers, which leads to higher retention rates and increased revenues
  • Improved operational efficiency means improved service reliability and results in a CSP being able to do more with less
  • Lower operating expenses through automation of issue resolution through integration of recommended actions to 3rd party systems

Reailize supports CSPs on their evolutionary journeys to Intelligent Operations. Our solutions, including ML-based automated anomaly detection, anomaly prediction and root cause analysis, provide our customers globally with solutions that have been field tested at some of the largest CSPs in the world.  Our solutions are designed around a cloud-native, open and modular architecture providing flexibility to resolve many of our customers more critical operational challenges.

In addition, our solutions include SME consultancy to assess, plan, and implement the progression of the People and Process dimensions. We offer tailored assessment, implementation, and operating services to align our clients’ processes with the three pillars of Intelligent Operations. Our transformation approach reviews each client’s specific business drivers and leverages GNOC resources, SOC Expertise, and Cognitive NOC capabilities to implement Intelligent Operations in compliance with TM Forum standards and recommendations.

Reach out to demo@reailize.com to learn more about how Reailize can guide your transition to public/hybrid cloud solutions.

The Future of Telco Networks in the Cloud: A Discussion Between Matt and Marco

Contributed by Matthew Twomey, Head of Product Marketing & Marketing, Anritsu Service Assurance & Marco Gatti, 5G Product and Solution Manager Anritsu Service Assurance

(This started, as nearly all good conversations are, on a friendly argument with my good friend Marco while in the pub eating tapas in Barcelona)

Matt: Marco, monitoring telco networks is inherently more difficult due to their unique challenges, such as subscriber mobility, diverse services, and stringent regulatory requirements. While cloud providers have made great strides in recent years, I think they are not yet ready to handle this complexity. However, they will eventually get there with the help of network software providers and monitoring and service assurance vendors like ourselves in Anritsu.

Marco: Matt, I understand your concerns, but I’d argue that telco networks are not fundamentally different from other IT services; they just have specific requirements related to the Telco industry, like defined networking capabilities. The complexity and challenges you mentioned can be solved by the cloud provider and made available as industrialized cloud service for on-demand consumption, and we’ll see IT cloud ultimately consuming Telco Cloud. The business cases will differentiate the adoption among private, public, and hybrid cloud approaches.

Matt: While I agree that cloud technology has made significant advancements, we can’t ignore the additional unique aspects of telco networks, such as mobility and diverse services. These complexities require specialized cloud-aware monitoring solutions, and cloud providers must invest in dedicated resources and technology partnerships to handle them effectively.

Marco: That’s true, but cloud providers like AWS, GCP, and Azure have already begun deploying network functions in the cloud, as well as implementing edge computing to address latency and availability concerns. They are partnering with many suppliers, like ourselves, to help address these issues. Moreover, they are continuously improving their infrastructure to meet the evolving needs of their customers, including telcos.

Matt: I agree that cloud providers are making progress but must also comply with the stringent regulatory requirements for telco networks. Ensuring their infrastructure and services meet these standards can be challenging and resource-intensive. Who can tell who is responsible when a regulatory requirement fails on a cloud?

Marco: While compliance is challenging, cloud providers are no strangers to regulatory requirements. They already cater to industries with unique regulations, such as healthcare and finance. Cloud providers will adapt to the telco industry’s requirements as they gain more experience and develop specialized solutions. This will clarify contractually who’s accountable and responsible, the CSP, the cloud provider, or the network vendor when events happen.

Anritsu are sponsoring FutureNet World, 3 & 4 May, London

Matt: Another concern is the seamless integration of telco-specific monitoring solutions with cloud infrastructure. In short, monitoring is vital to understand what is happening on the network. Still, it will be even more important as an input into zero-touch networks orchestrating not only the telco network but also the cloud. This may require cloud providers to think of customizations and novel solutions, as well as work with telco operators and monitoring solution vendors in a more in-depth way.

Marco: Seamless integration between CSPs, Network vendors, monitoring solutions, and potentially multiple cloud types and providers is a crucial requirement for cloud adoption success. Integration is challenging, but cloud providers have a track record of working with various partners and vendors to develop integrations and customized solutions. As more telco operators embrace the cloud, we can expect cloud providers to invest in and prioritize seamless integration with telco monitoring solutions.

Matt: That’s a valid point, Marco, but we should also consider that monitoring on public cloud is compute and storage intensive. Cloud providers might hesitate to allocate resources for these tasks due to the associated costs. Monitoring, however, is not optional, as it is essential for ensuring service quality and customer experience.

Marco: You’re right, Matt. Monitoring in the cloud can be resource-intensive, but I believe that cloud providers will find ways to optimize their resource usage and costs enabling effective monitoring solutions. Moreover, as the market evolves and competition increases, cloud providers will be incentivized to address the needs of the telco industry more efficiently.

Matt: I agree, and deploying clever AI closer to the edge and within the monitoring solutions themselves will be vital to ensuring efficiency and keeping cloud costs down. By analyzing data in real time and making intelligent decisions at the edge, we can reduce the amount of data that needs to be processed and stored in the cloud, ultimately lowering costs and optimizing resource usage.

Marco: That’s an excellent point, Matt. Combining edge computing and AI-driven monitoring solutions can alleviate some of the resource-intensive aspects of telco network monitoring in the cloud. As cloud providers and telco operators continue collaborating and innovating, we expect to see more efficient and cost-effective solutions.

 

Embracing a next-generation network management approach

Contributed by João Miguel Antunes, Head of Autonomous Networks Offer, Celfocus.

From connectivity to connected experiences

Most Communication Service Providers (CSPs) have their digital transformation in action, having typically started from the customer touchpoints and business support systems and slowly made their way to operational support systems and the network itself.

By now, it is clear to the Telco industry that how CSPs drive their network digital transformation will guide them to different business opportunities in the future.

Moving from providing connectivity to connected experiences, CSPs can again be seen as innovators by transforming how society moves, works, plays, and cares for its citizens. This is where the most value for operators lies – whether it is on providing an immersive entertainment experience at a stadium, an efficient work experience at a next-gen factory, or even a life-saving experience on a connected ambulance.

The Future Digital Society

 

Next-gen network management

For these connected experiences to be sustainable, CSPs need to approach the transformation of network management processes holistically, meaning:

  • Think about processes from an E2E perspective covering the entire services lifecycle.
  • Adopt a solution-first approach, not a product, technology, or vendor-first approach.
  • Promote synergies of processes and tools between engineering and operations.
  • Simplify solutions, having fewer pieces to run, upgrade, etc.
  • Promote automation and data-driven decisions as the path to the autonomy of processes.
  • Spark an agile network mindset with responsiveness to business needs.

    Celfocus is a Sponsor of FutureNet World, 3 & 4 May, London

CSPs aim to provide a fully digital network experience to customers, and this can be achieved through a unified network management platform with foundational agile capabilities that can leverage AI/ML & automation to boost CSPs teams’ efficiency and TTM (Time To Market) while delivering autonomy of network management processes.

This foundation responds to the needs of leveraging the substantial amounts of data produced by CSPs, combining advanced analytics and orchestration & automation on top to enable operators to automate planning, readiness, fulfilment, and assurance with minimum human intervention and with the simplest solution possible to operate.

Also fundamental is the use of standardisation to achieve network-as-a-service that, together with the intrinsic agile network responsiveness, can increase network value capture with both CSPs’ business units and partners.

 

Simplified Vision of a Unified E2E Network Management

 

Moving towards autonomy

There is an increased demand for flexible, cost-effective, self-owned and self-kept solutions. Based on our deep experience in CSP domains, we believe that a solution composed of data-driven, agile, modular, and scalable platform components leveraging a healthy mix of both open-source and solid commercial products can respond efficiently to the automation of most needs and can evolve alongside CSPs with a mindset of think big, start small, and move fast towards autonomy.

Top 5 Use Cases for IT Automation in the Telco Industry to Be Future-Ready Today

Contributed by Brent Hunter, Sales Engineer,  Resolve Systems.

Navigating the fast-paced, highly competitive telecommunications industry calls for a proactive approach to stay ahead of the curve. As customer expectations soar and technological advancements continue to shape the sector, telcos must embrace IT automation to remain relevant. Delving into 5 top use cases for IT automation in the telco industry, let’s uncover the key drivers that empower businesses to thrive in today’s market and be well-prepared for the demands of the future.

 

  1. Network Automation

Network automation involves automating the management, deployment, and monitoring of network devices and services. This can significantly improve the efficiency of network operations, reduce human errors, and minimize downtime. For telcos, network automation is essential in ensuring reliable and high-quality service delivery.

Key benefits of network automation for telcos:

  • Faster deployment of network services
  • Improved network performance and reliability
  • Enhanced security through real-time monitoring and automated threat response
  • Reduced operational costs

Example use cases include device onboarding, network device inventory and backups, and software upgrades.

  1. Incident Management

Efficient incident management is crucial for maintaining service quality and customer satisfaction. IT automation can streamline incident management processes by

automatically detecting, categorizing, and prioritizing incidents. Automated workflows can also help in the swift resolution of issues, minimizing the impact on customers.

Key benefits of automated incident management for telcos:

  • Faster issue detection and resolution
  • Enhanced customer satisfaction and loyalty
  • Reduced need for manual intervention
  • Improved service level agreement (SLA) compliance

Example use cases include link down issues, health-check of passive intermodulation devices, and VPN connectivity issues.

  1. Provisioning and Decommissioning of Services

IT automation can significantly speed up the provisioning and decommissioning of services, such as setting up new connections or decommissioning unused resources. By automating these processes, telcos can ensure that customers receive services promptly, and resources are utilized efficiently.

Key benefits of automated provisioning and decommissioning for telcos:

  • Improved customer experience
  • Faster time-to-market for new services
  • Optimized resource utilization
  • Reduced operational costs

Example use cases include new device service configuration, re-homing configurations, and remote device calibrations.

  1. Performance Analytics

With the increasing volume of data from a multitude of sources within network and IT systems, turning the data into actionable insights can help telcos harness the value of data. These analytics can play a vital role in improving the quality of services offered by telcos.

With IT automation, data from multi-vendor sources can be collected, analyzed, and visualized in real-time, enabling telcos to make data-driven decisions and proactively address potential issues.

Key benefits of automated performance analytics for telcos:

  • Real-time insights into network and service performance
  • Proactive identification and resolution of performance bottlenecks
  • Enhanced service quality and customer satisfaction
  • Better-informed decision-making

Example use cases include Netcool alarm diagnostics, log file audit, and IT ticket analysis/enrichment.

  1. 5G Network Deployment and Management

5G is revolutionizing the telecommunications industry with faster data speeds, lower latency, and improved network capacity. IT automation can help telcos efficiently deploy and manage their 5G networks, ensuring optimal performance, resource allocation, and service delivery.

Key benefits of automated 5G network deployment and management for telcos:

  • Accelerated 5G network rollout
  • Enhanced network performance and capacity
  • Improved resource allocation and utilization
  • Reduced operational costs and complexity

Example use cases include RAN test connectivity, network auto-remediation, and customer case update emails.

 

Embracing Automation for a Future-Ready Telecommunications Landscape

As the future of the telecommunications industry unfolds, embracing IT automation is imperative for telcos to remain competitive and agile. By automating essential processes such as network automation, incident management, provisioning and decommissioning of services, performance monitoring and analysis, and 5G network deployment and management, telcos can stay at the forefront of innovation, meet the increasing demands of customers, and adapt to emerging technological trends.

With the rise of technologies like 5G, the Internet of Things (IoT), and edge computing, the telecommunications landscape is set to become even more complex and interconnected. IT automation will play a crucial role in enabling telcos to harness these innovations, delivering next-generation services and experiences to customers while maintaining operational efficiency.

By implementing these IT automations, telcos will not only secure their position in the current competitive landscape but also be well-prepared to shape and lead the future of the industry. The adoption of IT automation will undoubtedly drive the telecommunications sector towards new heights of performance, customer satisfaction, and technological breakthroughs.

 

About Resolve Systems, a Silver Sponsor of FutureNet World

Resolve Systems helps enterprise technology teams worldwide achieve agile operations with an industry-leading intelligent IT automation and orchestration platform. With more than a decade of automation expertise, Resolve’s solutions are purpose-built to address challenges posed by increasing IT complexity. Join Gabby Nizri, Chief Strategy Officer at Resolve Systems, on May 4 at 11:40am, at his panel discussion, “Transforming the Way We Run Our Businesses Through Automation.” You can also find Resolve at Stand #3. Schedule time now to get your demo virtually or onsite.

Transforming the Telecom Landscape: Embracing Autonomous Operations enabled by AI

Contributed by S.Chandrasekar, Head of Digital Transformation Office, Tata Communications Transformation Services.

 

The telecommunications industry is undergoing a significant transformation, driven by the emergence of new technologies such as 5G, ORAN, SDN and Cloud computing. These technologies offer new opportunities for telcos to enhance their customer experience, launch new products and optimise operations. However, the legacy technologies are still relevant and generating revenues though in a complex, and siloed landscape which are largely manual and reactive. To overcome these challenges, Telcos need to move from reactive to predictive to autonomous operations.

Let’s explore how Machine Learning and Generative AI models can play a significant role in addressing the concerns of Telcos, challenges in adoption and how to mitigate them.

 

Legacy telecom landscape: a Multi-Tech Multi-Vendor Ecosystem

The legacy Telecom landscape is complex owing to its multi-technology, multi-vendor heterogenous nature, with proprietary hardware centric technology resulting in Telecom Operations being siloed which results in

  • Multiple/Heterogenous Management Panes
  • Lack of End-to-end Network Visibility
  • Highly Manual
  • Slow to Change / Provision

In this landscape, the Telecom Operations are largely manual. The number of rule-based alarms are huge, with equally huge false positives, leading to delays and significant amount of manual effort to assess the impact to the network. Ineffective cross-domain correlation leads to delays and consequently affects the customer experience. Traditional rule-based automation investments by the Telcos are not yielding the desired ROI.

 

Heroes of the Future: Data Analytics & AI based Automation

While Telecom technology matures to a fully Digital Native phenomenon, Telcos need to progressively adopt Data Analytics and AI based Automation, an approach which is technology, domain, and vendor agnostic. AI/ML techniques are used to correlate root causes based on historical and real-time Data from heterogenous sources. Self-learning models, round-trip/close-loop automations can take the Telecom operations from largely manual and reactive to predictive to Autonomous Operations.

Generative AI models can play a significant role in addressing the challenges faced by telcos. By analysing large amounts of data in real-time, identifying patterns, and providing insights, AI can be used to proactively prevent issues before they arise. In addition it can enable :

  • An intelligent chatbot for customer service
  • Train employees on new technologies
  • Assist with network planning and optimization
  • Autonomous troubleshooting
  • Self-healing networks

In our own experience of working with Telcos globally, we have seen significant benefits in introducing AI based solutions. For e.g., we were able to achieve following benefits for a Telco in Enterprise NOC operations:

–              ~700-man-hours saved per month

–              60% – reduction in handling time

–              100% – accuracy of reporting

–              80% – efficiency enhancement

Another example is where improvement in the service assurance processes was achieved for Tier1 Operator by implementing AI/ML based operations. It helped them enhance operational efficiency, service quality, and scalability and thus achieved:

  • 15%-19%improvement in SLA performance
  • 15% reduction in early life failures
  • 10%-15% OPEX improvement

We strongly believe with the adoption of AI/ML based operations, telcos can gain valuable insights into their processes, identify areas for optimization, and make more relevant decisions to deliver enhanced customer experience and business goals. In addition they can identify new market opportunities, predict customer behavior, and optimize marketing campaigns.

 

Risks, Challenges and mitigation while adopting Autonomous Operations

However, there are also potential risks and challenges associated with autonomous operations that need to be addressed. One of the main concerns is the potential for AI Hallucination where AI-based systems make errors or unintended decisions. Proper training and testing of the AI systems, as well as the use of human oversight and intervention, when necessary, can mitigate this risk.

Another challenge is the need for a skilled workforce to manage and maintain the autonomous operations. Telcos need to invest in training their employees on new technologies and processes to ensure that they are equipped with the necessary skills to manage and maintain the autonomous systems.

 

Conclusion

The telecommunications industry is going through a significant transformation towards autonomous operations, and telcos need to embrace intelligent automation, data analytics, and AI-based automation to remain competitive. While there are potential risks and challenges associated with autonomous operations, they can be mitigated through proper training and testing of AI systems and the use of human oversight and intervention when necessary. The benefits of autonomous operations far outweigh the potential risks, and telcos that adopt this transformation will be better positioned to provide faster, more efficient service to their customers while reducing costs and improving service quality.

What ways do you think AI and Automation can impact your telecom operations. Do share your inputs and thoughts at  tcts.marketing@tatacommunications.com

 

 

IP network automation: Realizing the benefits and overcoming challenges

Contributed by Sasa Nijemcevic, Vice President and General Manager, IP Network Automation business unit, Nokia.

Network automation has become a crucial topic for network operators looking for ways to streamline their operations, achieve cost savings and drive operational excellence in a rapidly evolving industry. At Nokia, we have been at the forefront in supporting operators on their journey to IP transport network automation.

Quantified benefits of automation

Looking back at projects we have deployed with our operator customers, we can see the benefits that IP network automation has brought them. Analysys Mason conducted in-depth interviews and analysis with some of them to quantify these benefits.

One of the most compelling findings is that operators can reduce network operations cost by up to 65 percent by using automation at the IP layer. Automation cuts the labor time required for repetitive manual processes by 68 percent, resulting in substantial cost avoidance. It also reduces the frequency of human errors and time to process errors by an impressive 85 percent, leading to increased network reliability and performance.

Another significant advantage of network automation is that it helps operators react faster to customer demand, leading to an 88 percent reduction in time to revenue. Automation also allows operators to resolve network issues and faults more quickly, reducing mean time to repair by 71 percent. These benefits translate into improved customer satisfaction and increased competitiveness in the market.

Threefold skill set

Realizing the full potential of network automation is not without its challenges. One key obstacle I have observed is the need for skilled personnel. Network engineers now require a diverse skill set that includes:

  • Proficiency in programming: Engineers need to know how to write and test code.
  • Familiarity with cloud environments: Engineers need IT expertise, with Kubernetes orchestration in particular.
  • Deep network knowledge: Engineers need expertise in their network domain and its associated standards and protocols. Increasingly, they require expertise across multiple domains.

Many operators lack these skills in-house, and acquiring them can be costly and time-consuming. At Nokia, we have a global team of experts who are well versed in these areas and can provide training and consultancy services to help operators overcome this challenge.

Prioritization of network automation

Prioritization is another network automation challenge. Not all processes can be automated at once, and we’re seeing operators prioritizing based on their specific business objectives.

For example, some operators are focusing on revenue generation and prioritizing the automaton of service provisioning and modification processes. Others are prioritizing assurance activities to ensure the best quality of services for their customers.

Cost reduction can also be a driving factor, so operators are applying automation to tasks such as provisioning of network equipment, as well as upgrades and backups of their software releases. Operators can also reduce cost by using automation to optimize traffic and make the best use of network resources.

A use case-based approach

My team at Nokia is taking a pragmatic approach to network automation, focusing on specific use cases that address business problems or opportunities and deliver tangible outcomes for our customers. We have developed a comprehensive catalog of use cases that cover network lifecycle management, service fulfillment, assurance and analytics. The catalog also includes use cases that deal with IP network optimization through path placement, whereby a better understanding of traffic leads to better efficiency, higher availability and lower latency in the network.

In addition, we provide a whole set of cross-domain IP–optical coordination use cases. These use cases include topology discovery, true path diversity, coordinated maintenance and troubleshooting. They ensure that operators have a holistic and integrated approach to network management across the IP and optical layers.

A key characteristic of our catalog is that it provides use cases that are predictable and fast to deploy, so our customers can save time and money.

Conclusion

Network automation offers significant benefits to operators, including cost savings, improved network reliability, faster time to revenue and enhanced customer satisfaction. However, it requires careful consideration of skills, prioritization and a pragmatic approach to use cases. At Nokia, we are committed to supporting operators in their automation journey, providing expertise, tools and solutions to help them unlock the full potential of network automation and drive operational excellence.

 

Dynamic Inventory: The Foundation of Your Successful 5G Journey

Contributed by Kailem Anderson, Vice President, Portfolio & Engineering, Blue Planet, a Division of Ciena.

For Communications Service Providers (CSPs), the first step in turning their 5G vision into reality is a modern inventory system that provides an accurate, current, and networkwide inventory of all physical and cloud-based resources and services.

5G is a game changer

Before network operators can fully monetize 5G investments and achieve their business goals, they need to automate network operations. And, before they can automate these operations, they need a current and complete view of their network and services inventory, end to end across the RAN, transport, 5G core, and cloud domains. In fact, accurate near real-time inventory data is the foundation for every step of the 5G journey—from planning the deployment of cell sites and fiber nodes and determining the optimal placement of virtual resources to delivering high performance network slices to online gamers on demand, and everything in between.

Unfortunately, CSPs often build their 5G networks on top of legacy inventory systems that are limited to a single domain or vendor. This approach forces highly skilled engineering and operations teams to manually gather and correlate network inventory data from multiple systems to manage networkwide capacity and to design end-to-end services, which add cost and delay to a myriad of routine tasks, like new service activation, and prevents the delivery of dynamic slice-based services.

Blue Planet, a division of Ciena, are the exclusive Diamond Sponsor of FutureNet World, 3 & 4 May, London

CSPs attempting to operate advanced 5G networks with legacy inventory systems have several paths forward.  They can assign precious technical resources to develop a homegrown inventory solution, or they can engage a vendor or system integrator to build a new, use-case specific inventory system.

But most CSPs don’t have the resource availability or expertise to build their own inventory solution, and none want another closed inventory system that requires expensive customization and imposes vendor lock-in. Instead, operators need a partner with open, modular, vendor-agnostic solutions that can evolve with their changing needs.

Overcoming 5G challenge with dynamic inventory

Blue Planet’s Dynamic Inventory lays the foundation for 5G. It uses open APIs and other robust technology to federate data from legacy inventory systems, network management systems (NMS), and Software-Defined Networking (SDN) controllers—and uses this data to dynamically create and maintain an accurate, current, end-to-end network resource inventory and to visualize the service topology.

By automating the collection and federation of network and service inventory data from multiple sources, Blue Planet provides a networkwide ‘single source of truth’ and a unified end-to-end service view. This approach not only simplifies key operations, but it also lets CSPs replace their legacy inventory systems at their own pace, without the risks and costs associated with ‘rip-and-replace’ upgrades.

“Blue Planet is a key component of our 5G platform, allowing us to dynamically manage all our network inventory and service orders in real time. With Blue Planet’s open, agile, and programmable approach, DISH can rapidly deploy services and allocate resources to wholesale and enterprise customers, enabling them to provision network slices based on SLAs.”

Marc Rouanne, VP and Chief Network Officer at DISH Wireless

Beyond dynamic inventory

Of course, the complexity, scale, and ‘newness’ of 5G challenge more than just legacy inventory systems. 5G introduces new service and technology demands, new levels of complexity, and requires new skills for engineers and technicians. In response, Blue Planet offers two additional modular state-of-the-art automation solutions that help CSPs manage this complexity, keep OPEX down, and profitably realize their 5G-related business goals.

Our Network Lifecycle automation solution streamlines operations and reduces the burden on already strained IT teams by automating the:

  • ‘Day 0’ deployment of virtual resources in the RAN and 5G Core, including centralized and distributed units (CU/DU), an essential first step toward accelerating your 5G deployments
  • ‘Day 1’ configuration and activation of virtual resources such as the Next Generation Node B (gNB) as well as the transport interfaces that interconnect the gNB with the 5G core
  • ’Day 2+’ monitoring of all network resources and services, which supports ongoing operational tasks such as optimization and troubleshooting activities, with a roadmap that includes configuration and change control

Our Network Slicing Automation solution helps CSPs monetize their 5G investments with highly differentiated on-demand services. The solution provides zero-touch slice lifecycle management, automating the creation, assurance, and deactivation/deletion of dynamic network slices in mere moments without manual intervention.

All Blue Planet 5G solutions are modular and standards-based and can be deployed together or in conjunction with third-party inventory, orchestration, and assurance systems— giving CSPs the ability to protect their existing investments and build best-of-breed IT/operations environments.

Pulling it all together

Today, CSPs are looking to automation to overcome the complexity of 5G—manually activating and troubleshooting pre-defined static services must be replaced with open and cloud-native automation solutions to provide high-value on-demand services that drive customer satisfaction and profitability.  But automation starts with—and is dependent on—an accurate network and service inventory.

We have a mantra at Blue Planet: ‘You can’t automate what you can’t see.’  By automating the discovery, federation, and reconciliation of inventory data from multiple legacy OSS and other sources, we create a ‘single source of network truth’—a dynamic inventory that accurately shows the current state of the RAN, transport, and packet core network domains. This accurate, real-time view of network resources and the service topology is the essential foundation for 5G automation—and monetization.

Accelerate your 5G journey with Blue Planet.

Effective NaaS Solution Development & Why Its Critical to Look Internally First

Contributed By: Morgan Stern, VP Automation Strategy, Itential.

Service providers find themselves in an increasingly competitive and challenging environment. The good news is, traffic on their networks continues to grow year over year. The bad news is, they’re challenged with scaling their infrastructure to stay ahead of that growing demand in the fastest, most cost-effective way. And even though traffic is growing, service provider revenue is not growing at anywhere near the same rate. On top of all that, hyperscalers have entered the market and are using their own cloud-centric operating model to introduce new competing services and generate their own revenue streams. In many cases, service providers are losing out on the most profitable services to the over-the-top (OTT) players.

To stay competitive and profitable in this new environment, many providers are looking at Networking-as-a-Service (NaaS) to innovate faster and further monetize their networks. NaaS can offer new revenue opportunities, provide a faster return on network investment, simplify the consumption of network services, and lower the cost of implementing those services. What many providers are discovering, however, is that delivering NaaS is vastly different from their current operating models. Beyond that, many providers simply don’t have the basic capabilities to expose their network capabilities as NaaS services.

Despite those challenges, NaaS – when implemented the right way – can offer service providers a compelling way to offer new solutions and use cases.

 

Build an Internal Sandbox

For service providers looking to explore a NaaS solution, there are a number of questions to ask and things to consider.

First, is defining what NaaS actually entails and how a service provider can implement it. One operator’s NaaS requirements may be different from those of another operator.

Along with that, what type of NaaS service will customers be willing to pay for? What would make it a commercially viable solution?

Also, what type of NaaS consumption model does the operator want to explore? Will they offer an external solution, an internal solution, or a combination of the two?

Other considerations are:

  • How do users discover services?
  • How do we charge for services? Is it a usage model?
  • How do we enable users to track their consumption?
  • How do users order and change services?
  • How do we track deployed services and manage service quality?
  • How do users test and resolve issues?

 

It can become very complicated very quickly.

Many providers, wisely, are taking a very methodical and deliberate approach to exploring NaaS and gaining the expertise necessary to eventually offer a commercial service. Jumping right into offering an external NaaS to customers can be a very complicated process, especially if the operator doesn’t have any orchestration or automation infrastructure. And the investment involved can make an operator think twice about taking that plunge.

Meet the Itential team at FutureNet World 2023

A better alternative for operators considering embarking on a large-scale NaaS initiative would be to look internally first – to use an internal offering and their own internal customers as the proving ground for their proposed NaaS model.

Using an internal solution as a provider’s “sandbox” provides a great deal of flexibility as they game plan their NaaS approach, put together the service composition, and gain the technical and operational experience they need to prove out their model in a less commercially risky way. A service provider’s internal offerings, systems and customer base – while just as important as their external opportunities – are an easily accessible laboratory to define what a NaaS offering could look like, how users will consume it, how to make it operational, and all the other pieces that need to be worked out to make a NaaS offering consumable and commercial externally.

Keeping the process in-house can also be less of a financial risk compared to developing an external offering. Internal cost allocation and control – while far from haphazard – tend to be more flexible and easier to absorb as you develop your NaaS solution.

In addition, starting with an internal NaaS solution can also give the provider insights into some commercial opportunities they may not have already thought about.

 

Look Inside to Look Ahead

Developing a NaaS solution and deploying it to customers can also be expensive. And while there are many good theories in the marketplace about ways to do it, the reality is, many operators lack the expertise and functionality to actually make it happen.

Taking the industry’s old monolithic model for product development and applying it to NaaS development probably won’t be successful. But by looking inward first, an operator can gain the expertise and develop the necessary functionality to offer a NaaS solution in a way that doesn’t require a massive investment of time or money, and that can minimize some of the risks involved in focusing on an external solution first.

Working with an experienced partner like Itential that can provide a flexible framework for designing and deploying NaaS services is critical too. Itential has worked with multiple service providers to enable NaaS services by utilizing the Itential Automation Platform’s rapid integration capabilities, no-code design environment, and robust API exposure model. With Itential, teams have been able to transform existing manually-configured services into production NaaS API-driven services in as little as three months.

At the end of that day, the knowledge and experience an operator can gain by building an internal NaaS solution first, can pave the way for more commercially viable and cost-effective external offerings in the future.