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Tag: Network Asset Management

  • Software License Management: The 8 key ingredients for managing software licenses for the telecom industry

    Software License Management: The 8 key ingredients for managing software licenses for the telecom industry

    In today’s telecom world, organizations are heavily reliant on software solutions for numerous functions, including task-critical ones. As a result, software licensing can be a significant budget entity for many organizations. Effective license management is essential to preventing inaccurate tracking of software licenses and usage measurement issues that can cause budget discrepancies.

    In almost all cases, the software is sold by licensing, whether it be a perpetual license to use the software or a subscription settled monthly or yearly that must be renewed continually. To ensure that you are utilizing every penny spent out of your software assets, the first thing to do is to understand the types of licensing agreements and plan the license management accordingly.

    This is where Software license management (SLM) comes in. Software license management refers to all organizational aspects of deploying and maintaining your organization’s software assets. It is a part of the broader software asset management category.

    Given the large share spent on software licenses, an exceptional benefit of SLM is the revenue it can save you by identifying unnecessary or unused/underused software. Paying for such software can stack up to a sizable sum for each user or device covered by an unused solution. SLM enables you to track all software purchases and audit their usage, or lack thereof, in the case of unused paid subscriptions.

    Another benefit of SLM that can help in even more significant financial savings is that it enables enforcing compliance with End-User License Agreements (EULA). Any device running unlicensed software reveals you to potential financial penalties and legal issues in most circumstances.

    When following your software licenses, it is vital to know how the latest technology impacts software usage and policies. With 5G and, thereby, artificial intelligence (AI), augmented reality (AR), machine learning (ML), and the Internet of Things (IoT) picking up pace in recent years, software licensing has had to adjust to the advancements introduced by these developments.

    The extensive use of automation powered by AI and ML has impacted SLM by enabling the automatic functioning of many of the processes. This includes overlooking what programs are being used, how they are being used, and setting up control protocols to limit their usage to authorized individuals and roles. These tools can also be used in the maintenance of software to make it easier to detect violations of EULA.

    IoT devices are now present at all business and consumer levels and functions, including telecom. Observably, the SLM implications of these devices can be tricky, and the software underlying them can be challenging to manage using traditional SLM tools and procedures. It’s important to track new processes for applying SLM techniques to IoT devices to optimize your ability to utilize them. Proactive SLM allows the improvement of your IT efforts. It provides the possibility to lower costs and boost your ability to react to changing business conditions by drawing the maximum advantage of the capabilities of your software rapidly.

    As we have seen, managing your software licenses is essential to avoid the negative results associated with non-compliance. The following are points to help your telecom business to manage software licenses:

    Document software management policies

    SLM records and stores your software management policies to manage and serve when required to avoid costly surprises come audit time.

    Usage governance procedures

    Establishing controls for managing software usage across the organization and groups of workspaces is a breeze with SLM. It also ensures that only authorized users can download and use the software they are authorized to use. These management controls are critical in an era where users can effortlessly access the software at work or home on various devices. The procedures of usage of software policies in all telecom spaces should be tied to your usage governance utility to effectively onboard and offboard employees via provisioning automation.

    Software lifecycle management

    Special care must be undertaken to manage all aspects of the software lifecycle, including renewing licenses, updating information, and communicating usage parameters to employees. With SLM, it can be done efficiently.

    Usage monitoring

    It is necessary to constantly monitor which programs are present on your network, how they are being used, and who is using them to ensure that your authorization policies are working as planned and that the correct solutions are being applied for desired purposes. With SLM integrated, it is still possible to use automated and manual auditing when needed.

    Automated updating checks

    Automated discovery of software versions is available with SLM, enabling you to operate on the most recent version of any installed programs consistently.

    Reclaiming procedures

    Regularly uninstalling software that has been idle for a certain prescribed period and return it to stock for future reuse or cancellation if suitable.

    Track contracts

    SLM analyzes contract databases and procurement records to enable easy compliance with contractual conditions and viewing important contract data such as license type, number of authorized users, and expiration dates with fewer steps than manually looking through them.

    Employ license management automation

    Software License Management solutions can help optimize your license management by developing vendor licensing profiles you can use to automate the process of moderating your license status to installed software. This can help the efficiency of license management, especially in preparing for a true-up or other large-scale audits.

    Establish and track software management objectives

    To measure the effectiveness of your SLM efforts or select licenses for cost-saving objectives and track your performance about goals over time that can be achieved with proper SLM.

    With a substantial portion of software costs resulting from inadequate software management, the case for software licensing management is a strong one. According to research from Gartner, many organizations can ameliorate software spending by as much as 30% via software license optimization via best practices. Besides revenue optimization, effective SLM can generate revenue, and there are also efficiency gains to be experienced by making better use of the software your organization has acquired.

    SLM can benefit telecom organizations by helping them effectively use their software to quickly react and adapt to changing market conditions, optimize operations, and stay in compliance with EULA. At a minimum, SLM can help you track and optimize your software policies to help your managers acquire and use the tools at the right time.

    Why is Network License Management crucial for Telecom Operators?

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    References:

    https://www.yumpu.com/en/document/view/37782291/software-licensing-in-telecom-industry-an-analysis-softsummit

    https://www.bmc.com/blogs/software-license-management/

    https://www.dell.com/en-us/blog/a-fundamental-shift-in-how-telecom-networks-are-built/

    https://www.researchgate.net/publication/260591298_Licensing_Models_and_their_Impact_on_the_Telecom_Software_Industry

    https://www.cisco.com/c/en/us/buy/enterprise-agreement/resources/what-is-software-license-management.html#~conclusion

  • A través de los ojos de un profesional de redes, cómo lidiar con la tormenta de incertidumbre

    A través de los ojos de un profesional de redes, cómo lidiar con la tormenta de incertidumbre

    El mundo de las telecomunicaciones está lleno de incertidumbre. Es durante estas situaciones de incertidumbre cuando el aumento de la demanda de los clientes y la carga en la red aumenta exponencialmente, el verdadero papel de un profesional de la red entra en juego. Durante estos momentos, cuando la red está bajo tensión, los profesionales de la red deben hacer un gran esfuerzo para garantizar la continuidad del servicio 24 × 7.

    Pero, ¿qué pasa con la “incertidumbre” que podría surgir de una calamidad natural, o interrupciones masivas del sitio, causa estrés en la red?

    En general, una red móvil sufre numerosos cambios. Estos podrían ser cambios planificados como ajuste de parámetros, optimización física, prueba / implementación de nuevas funciones, actualizaciones de software, etc., la mayoría de los cuales están dirigidos a mejorar el rendimiento de la red y la experiencia del usuario final.

    Sin embargo, por otro lado, son los cambios “no planificados” los que tienden a arrojar una llave inglesa al sistema. Estos cambios podrían ser estacionales o debidos a fluctuaciones a nivel del sistema en los elementos de la red que provocan una degradación severa en términos de rendimiento. Si tal incidente ocurriera en la hora más ocupada del día, entonces el impacto también se sentirá en el negocio.

    En ambos casos, planificados o no planificados, la acción para resolver un problema podría estar dirigida a cualquier dominio de una red, por ejemplo, radio, transporte, núcleo, etc. También requeriría la resolución de problemas de extremo a extremo y el análisis de la causa raíz.

    Tradicionalmente, los profesionales de la red manejan el impacto de tales cambios de manera reactiva, lo que a menudo resulta en casos en los que el “tiempo medio para reconocer” (MTTA) y el “tiempo medio para responder” (MTTR) potencialmente toman horas o, en algunos casos, días. De hecho, algunos casos complejos entre dominios pueden incluso quedar sin resolver.

    Sin embargo, a lo largo de los años, gracias a los avances en la automatización, los profesionales de la red han podido evolucionar hacia el manejo proactivo de dichos problemas. Al aprovechar las herramientas integradas con la experiencia en la materia, junto con los métodos estadísticos, los profesionales de la red pueden lograr una reducción significativa en MTTA y MTTR. Sin embargo, este enfoque está lejos de ser perfecto, ya que las acciones necesarias solo se pueden tomar después de que el impacto en la red ya haya ocurrido.

    Para comprender el enfoque correcto que debe adoptarse, demos un paso atrás y profundicemos en la vida de un experto en planificación y optimización de redes involucrado en la gestión del rendimiento diario de la red.

    Convencionalmente, un profesional de la red realiza un análisis del impacto de la red en un conjunto de KPI críticos y toma las medidas necesarias para mejorar el rendimiento de la red. Se invierte mucho esfuerzo en otra ronda de análisis para concluir si la acción tuvo un impacto en cascada en cualquier otro KPI importante o no. Una vez que el impacto de la acción tomada se considera exitoso, el análisis pasa al siguiente conjunto de acciones. Muy a menudo, tales acciones son tomadas por múltiples partes interesadas para mejorar el desempeño de sus respectivas regiones / grupos / sitios.

    En una red 4G, podría haber miles de contadores / KPI y cientos de parámetros, lo que hace que sea casi imposible para un ser humano analizar el impacto de un cambio de un conjunto de parámetros en todos los contadores / KPI relevantes, de extremo a extremo, diariamente. Los servicios como la transmisión de video y VoLTE a menudo requieren un análisis entre dominios para garantizar la continuidad del servicio.

    Es en tales escenarios donde Machine Learning (ML) comienza a surgir como la respuesta para manejar estas complicaciones desde una perspectiva de extremo a extremo.

    Sin embargo, el término “Aprendizaje automático” tiene una forma de introducirse en tales debates. Es, de hecho, casi en su propio detrimento a veces, ya que el aprendizaje automático casi se ve como un trabajo de magia, en el mejor de los casos, o simplemente un truco de marketing, en el peor de los casos. Casi todos lo mencionan en algún momento.

    Entonces, permítame tomarme un momento para defender por qué lo menciono ahora y por qué creo que el análisis avanzado basado en el aprendizaje automático puede resolver significativamente algunos de los problemas críticos que enfrentan los profesionales de la red.

    La respuesta corta de dos palabras sería “Agilidad” y “Precisión”. Permítanme dar más detalles.

    Un CSP puede aprovechar los modelos de ML que capturarán todos los tipos de impactos de red de manera consistente a partir de los datos de red generados en forma de contadores / KPI y parámetros a diario y ayudará a proporcionar información procesable a los profesionales de la red, que de lo contrario pasarían desapercibidos.

    Además, estos conocimientos son especialmente útiles cuando se utilizan en la planificación y gestión de eventos especiales, como la proyección de un evento deportivo mundial. En tal caso, donde se espera que aumente el aumento del tráfico, el modelo aprenderá del desempeño del evento anterior y proporcionará aportes críticos para la planificación del evento.

    Según la misma lógica, los modelos de ML generarán ideas procesables cuando se produzca una crisis y equiparán a los profesionales de la red para hacer frente a cualquier evento anormal que ocurra en tiempos de incertidumbre. Además, al aprovechar los modelos ML, los profesionales de la red pueden estar equipados para ejecutar simulaciones múltiples para realizar con precisión el análisis de impacto de la red para cualquier acción que tengan la intención de realizar en el futuro. Algunos escenarios clave que podrían gestionarse con mayor agilidad en cualquier momento, pero que adquieren una dimensión adicional de importancia durante una situación de “red bajo tensión”, serían:

    • Pronosticar con precisión el tráfico peak, la utilización de recursos y el uso de aplicaciones para planificar con anticipación
    • Optimización y ajuste de los parámetros de red para la expansión de la capacidad y la mejora de la calidad en tiempos de tendencias anormales de la red.
    • Mejora de la experiencia del cliente al realizar una correlación de calidad de experiencia (QoE) con QoS de extremo a extremo para servicios de transmisión como video Full HD.
    • Mantener la continuidad continua del servicio VoLTE de extremo a extremo.

    Como dicen, las situaciones únicas requieren medidas únicas, y durante los momentos en que la red está bajo estrés, los profesionales de la red deben hacer un gran esfuerzo solo para mantener la red a flote. Es un esfuerzo que a menudo pasa desapercibido, pero ayuda a mantener a los clientes conectados y a mantener intacta la reputación de la empresa. Machine Learning puede asumir un papel esencial en la transformación de estos “héroes de la red” en “superhéroes de la red” al equiparlos con poderes de agilidad y precisión mejoradas.

    La verdad es que la industria de las telecomunicaciones se encuentra en un punto de inflexión en el que los responsables de la toma de decisiones deben tomar una decisión sobre las capacidades que deben aportar a la red y cómo pueden equipar a sus héroes de red hoy en día. Estas decisiones críticas tomadas ahora proporcionarán beneficios en los próximos años.

    Para comprender los desafíos que enfrentan los CSP para ofrecer contenido de video de calidad a través de dispositivos móviles

    LEER BLOG

  • How to ride the storm of uncertainty through the eyes of a network professional

    How to ride the storm of uncertainty through the eyes of a network professional

    The telecom world is one that is fraught with uncertainty. It is during such situations of uncertainty when the surge in demand from customers and load on the network increases exponentially, the true role of a network professional comes into the fray. During these moments, when the network is under stress, network professionals need to put in a tremendous effort to ensure 24×7 service continuity.

    But what about ‘uncertainty,’ that might emerge from the likes of a natural calamity, or massive site outages, causes stress on the network?

    Generally, a mobile network undergoes numerous amounts of changes. These could be planned changes like parameter tuning, physical optimization, new feature trial/implementation, SW upgrades, etc., most of which are targeted towards improving the network performance and end-user experience.

    However, on the other side, it is the ‘unplanned’ changes that tend to throw a monkey wrench into the system. These changes could be seasonal or due to system-level fluctuations in network element(s) bringing severe degradation in terms of performance. If such an incident was to happen in the busiest hour of the day, then the impact will be felt in the business as well.

    In both the cases, planned or unplanned, the action to resolve a problem could be targeted towards any domain of a network, e.g., radio, transport, core, etc. It would also require end-to-end troubleshooting and root-cause analysis.

    Traditionally, network professionals manage the impact of such changes reactively, which often results in instances where the ‘mean time to acknowledge’ (MTTA) and ‘mean time to respond’ (MTTR) potentially take hours or, in some cases, days. In fact, some complex cross-domain cases can even remain unresolved.

    Over the years, however, thanks to advancements in automation, network professionals have been able to evolve towards handling such issues proactively. By leveraging tools embedded with subject matter expertise, coupled with statistical methods, network professionals can bring a significant reduction in MTTA and MTTR. However, this approach is far from perfect as necessary action can only be taken after the impact on the network has already occurred.

    To understand the right approach that needs to be taken, let us take a step back and delve into the life of a network planning and optimization expert involved in day-to-day performance management of the network.

    Conventionally, a network professional performs network impact analysis on a set of critical KPIs and takes necessary steps to improve the network performance. A lot of effort is invested towards another round of analysis to conclude if the action had a cascading impact on any other major KPIs or not. Once the impact of the action taken is deemed successful, the analysis moves to the next set of actions. Very often, such actions are taken by multiple stakeholders to improve the performance of their respective regions/clusters/sites.

    In a 4G network, there could be thousands of counters/KPIs and hundreds of parameters, making it almost impossible for a human to analyze the impact of a change of a set of parameters on all relevant counters/KPIs, end-to-end, daily. Services like video streaming and VoLTE often require cross-domain analysis to ensure seamless service continuity.

    It is in such scenarios where Machine Learning (ML) starts cropping up as the answer to handling these complications from an end-to-end perspective.

    However, the term ‘Machine Learning’ does have a way of creeping into such discussions. It is, in fact, almost to its own detriment at times, as machine learning is almost looked at as a work of magic, at best, or just another marketing gimmick, at its worst. Almost everyone brings it up at some point.

    So, let me take a moment to defend why I bring it up now, and why I believe machine learning-driven advanced analytics can significantly solve some of the critical problems faced by network professionals.

    The short two-word answer would be ‘Agility’ and ‘Accuracy.’ Allow me to elaborate.

    A CSP can leverage ML models that will capture all types of network impacts consistently from the network data generated in the form of counters/KPIs and parameters on a daily basis and will help in providing actionable insights to the network professionals, which would otherwise go unnoticed.

    Furthermore, these insights come in especially handy when used in planning and managing special events like the screening of a global sports event. In such an event, where the surge in traffic is expected to rise, the model will learn from the previous event’s performance and will provide critical inputs for event planning.

    By the same logic, ML models will generate actionable insights when a crisis strikes and will equip network professionals to deal with any abnormal events happening in times of uncertainty. Furthermore, by leveraging ML models, network professionals can be equipped to run multiple simulations to accurately perform network impact analysis for any actions they intend to perform in the future. A few key scenarios that could be managed with better agility at any point of time, but take on an additional dimension of importance during a “network under stress” situation, would be:

    • Accurately forecasting the peak traffic, resource utilization, and application usage to plan well in advance
    • Optimizing and fine-tuning network parameters for capacity expansion and quality improvement in times of abnormal network trends
    • Improving customer experience by performing Quality of Experience (QoE) correlation with end to end QoS for streaming services like full HD video.
    • Maintaining seamless end to end VoLTE service continuity.

    As they say, unique situations call for unique measures, and during times when the network is under stress, network professionals need to put a whole lot of effort just to keep the network afloat. It is an effort that often goes unnoticed, but it is one that helps keep customers connected and the company’s reputation intact. Machine Learning can take on an essential role in transforming these ‘network heroes’ into ‘network superheroes’ by equipping them with powers of enhanced agility and accuracy.

    The truth is that the telecom industry is at an inflection point where decision-makers need to take a call on what capabilities they must bring into the network and how they can equip their network heroes today. These critical decisions taken now will provide benefits for years to come.

    To understand the challenges faced by CSPs in offering quality video content over mobile devices

    Read Blog

  • Capacity Planning for 4G Networks

    Capacity Planning for 4G Networks

    As the telecom industry prepares to move to the 5G, it will look forward to the benefits that come with the technology such as faster speeds, low latencies, seamless connectivity, besides the possibilities of opening new business revenue streams for CSPs. 5G will bring with more unique use cases in areas beyond the consumer realm, with enterprise being a key focus area and a new point of entry for CSPs. However, while 5G does hold this promise leading to CSPs gearing up for this new technology, are they getting 4G right? Are their existing tools for 4G Capacity Planning and Network Capacity Optimization helping them make the most out of their 4G network investments done in the past?

    Most CSPs may not have a standard 4G Network Capacity Management tool in the first place, and those that do, may not be able to realize the return on their network investments recommendations generated in the past. One potential reason could be the limitations that come with their existing tool to ingest, process, and correlate data flowing from different domains.

    Another could be their current Network Capacity Management Process does not offer flexibility to network planners to run multiple iterations and simulations before zeroing on a final plan. Along with it, network capacity planning best practices often get lost because of lack of capability of a network planning tool to take feedback from past actions and record it for future usage.

    Traditionally, network capacity management metrics focus on technical KPIs as the only set of parameters used for network capacity planning. Though the approach worked fine a few years back, the drawback of this method is that the network capacity planning process outcome only generates a list of network elements required for capacity upgrade and augmentation. It doesn’t provide any priority-based investment decisions which can help a CSP invest in the areas capable of generating quick revenue while ensuring the customer experience is not compromised. All this can be achieved only with advanced analytics-driven network capacity and performance management systems built on Artificial Intelligence and Machine Learning. Such systems would be capable of providing meaningful insights from not just technical KPIs but millions of records flowing in the form of business and customer experience metrics, which otherwise gets missed.

    To know more about how advanced analytics can redefine what is network capacity Management for the 4G era.

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  • What is Network Asset Lifecycle Management?

    What is Network Asset Lifecycle Management?

    The telecom world is currently at a crossroad. On the one hand, the industry is at the forefront of innovation and technological development. On the other hand, it is one rife with challenges such as plateauing revenues, increasing customer demands, increasing Capex Intensity, and ever-growing competition. Both these aspects play into each other, as CSPs need to invest in new network technologies to provide customers with the latest services, with the best experience. However, investing in network technologies seldom allow CSPs to witness adequate return on their investments. In such a scenario, where ROI is rare, CSPs must ensure that their Capex is optimized. One of the critical areas where CSPs can enable Capex optimization is through the better utilization of their network assets lifecycle.

    Network Asset Lifecycle Management comes in many names, be it Asset Assurance, Asset Management, and so on. Telecom Network Asset Lifecycle Management refers to the process of optimizing revenues generated by assets throughout their lifecycle while optimizing costs. What do we mean by telecom assets? The variety of a CSP’s assets ranges from traditional telecom equipment to data center assets, NFV components, appliances, hardware and software licenses, IoT devices, OSS/BSS workload systems, and a multitude of access devices such as small cells, edge computing, home broadband, etc.

    Beyond Capex and Opex optimization, there is a clear need for Network Asset Lifecycle Management emerging within many telecom operators to:

    • Meet auditory and regulatory requirements
    • Bring in digitalization and automation
    • Stay competitive in the industry
    • Generate a better return on capital

    What CSPs need to succeed is a Telecom Network Asset Lifecycle Management solution, which can ensure both physical and digital asset management.

    How can robust asset lifecycle management solutions help?

    A complete solution of network asset lifecycle management would encompass the continuous monitoring and management of asset lifecycles. Each stage of the asset lifecycle comes with features and analytical functions for Capex and Opex insights, rich dashboards & reports, process triggers, KPIs and alerting mechanisms, operational workflows accessed over both web app and mobile app. A few of the key actionable insights from asset lifecycle management tools include asset re-positioning recommendations, purchasing recommendations and supporting analysis, network asset lifecycle statuses visualization, license analytics, assets contract performance insights, and more.

    Benefits of Asset lifecycle management

    • Provides a Centralized Repository for Active, Passive and Non-serialized Network Assets
    • Reduces the under-utilization of assets
    • Reduces the need for manual auditing
    • Improves time-to-value of assets
    • Enables monetization of end-of-life assets to generate maximum value
    • Optimizes asset utilization

    Driving Multimillion-Dollar Capex Savings Through Optimal Utilization Of Network Assets

    Download Case study Now!

  • Customer Analytics : Gen X and Y and the Millennial Divide

    Customer Analytics : Gen X and Y and the Millennial Divide

    We live in a world where technology is like a digital liquid that’s flowed around every aspect of our lives. There’s no doubt that technology can help to oil the craggy wheels of daily life, and while some find this enabling and liberating, others consider the intrusion to be more insidious. Working out where people stand on this issue is generally just a simple matter of checking their birth date. Many born before 1980 tends to view social and on line everything with suspicion, whereas those consumers born after that date, referred to as Generation Y, or Millennials, are far more comfortable with social media and sharing everything online. In a recent report from Pew research it was shown that the Millennials are much greater users of social media than their parents.

    This is probably because Millennials are the first generation that have grown up entirely with the internet and mobile phones.  They are ‘digital natives’. It’s difficult to know exactly what effects this has on general culture, but one surprising change is that Millennials tend to be far more optimistic that their parents were when they were young. While Generation X and before are more inclined to have a cynical and pessimistic attitude towards the future, a recent report by the Pew Research Centre, Millennials in Adulthood, has found that, despite feeling detached from politics or religion and burdened by debt and recession, the Millennials are inexplicably much more optimistic. According to a recent Gallup poll, eighty percent of millennials, aged 18 to 29, feel positive about the future and say their standard of living is improving.  The reasons for this relentless optimism are unclear but researchers at Pew have pondered that it may be down to more nurturing parenting, or perhaps it’s because millennials always feeling at the centre of their own social network.

    Another characteristic of the millennial generation is that, contrary to predictions that technology would free us all from work, they are now working harder and are more driven to succeed than ever before. In his book ‘Generational Teaching: Motivating the Minority’ Christopher Alan has also found that Millennials are ‘more polite and considerate’, ‘attentive and respectful’ and prefer to work in teams rather than in a hierarchy. Goldman Sachs also says that they are also more health conscious and savvy than earlier generations.   But, as ever, the picture is never that simple, because it seems that the Millennial generation is itself divided in two, as Pew Research has written

    Just 40% of adults ages 18 to 34 consider themselves part of the “Millennial generation,” while another 33% – mostly older Millennials – consider themselves part of the next older cohort, Generation X.

    This all has very great implications on marketing, and how companies should reach out to different generations. Connecting with customers is one of the greatest challenges marketers face, and capturing Millennials is now one of the key battlefields for competing companies. As Leah Swartz of Millennial Marketing says

    ‘When it comes to fashion and shopping, there isn’t a more important demographic for retailers to reach than millennials.’

    Goldman Sachs have even put together an infographic dedicated to marketing to Millennials in which they identify several key things to consider when marketing to the ‘largest generation in US history’. In summary they are

    • Living at home longer
    • Marrying later
    • Sharing, not owning
    • Exercise choice in purchasing
    • More health conscious

    From a non-millennials perspective it may seem that they are so immersed in instant messaging and playing computer games that they are oblivious to the real world, but, on the contrary, millennials are very much aware of the state of the world. It’s just that this revolution is a lot quieter than the ones before, taking place as it does silently from the screens of our phones and laptops. The silence is an illusion. The volume of noise is now measured in packets of data rather than decibels, and it’s loader than ever. If companies don’t engage with different generations of customers on their own ground then they will not be heard at all.

    In my next blog I will look at how Millennials and other demographic groups can be better served by adopting a customer-centric approach to marketing.

  • Operational Insights lead to CAPEX savings

    Operational Insights lead to CAPEX savings

    Telecom companies across the board often crisscross their blades with OTT players. While it’s true that Telcos are trying to find sustainable new avenues – few are succeeding, their current-state CAPEX keeps growing at an ever faster clip. This is mainly due to exponential data demand from customers resulting in increasing investments into network to keep up quality customer services. With ubiquitous mobile connectivity and video traffic demand spiraling-out, it puts enormous amount of stress on the networks. Telcos need to continue investing in this consumer trend [current-state CAPEX] and at the same time figure out alternative growth areas [growth CAPEX].

    To invest in new avenues with better ROIs, Telcos need to keep close tabs on their CAPEX that goes into network for present growing customer demand. And follow the traditional mantra – keep the current cash flow as cushion and invest for future. But for many Telcos, the worrying part is large chunk of the cash flow generated is ploughed back into network to meet current demands. This leaves little room to focus on new growth areas. Telcos are forced to raise money via debt or other means, resulting in further stress on balance sheet and reduced returns to investors.

    Let’s take a look at a snapshot of financial summary of a public listed global telecom major:

    [Figures are normalized]

    On a closer inspection of this summary one could observe,

    • The CAPEX has increased significantly (50%), but contributed only marginal increase in operating income (2%) and revenues (10%) over a year.
    • At the end of three year period, the CAPEX investment grew nearly to 20% of annual revenue but the corresponding incremental revenues seen marginal uptick only.
    • Return on Assets came down to single digit despite spending cumulative CAPEX of nearly half of average yearly revenue for this period.

    Without undue speculation and with publicly available data, one could do an educated guess: during this period, most of the CAPEX went into supporting & enhancing existing network infrastructure to keep-up quality services.

    This picture is not much different from any other typical Telco in the developed or emerging markets. While Telcos try to figure out the next wave of growth, it is equally important to keep a check on the current-state CAPEX.

    Telcos have no dearth of information in their siloed systems. It is just that few of these system’s data need to be unleashed to discover insights that can help in reducing CAPEX. For instance, reusing stranded assets in the network, warehouse and spare stores during purchase decisions would reduce CAPEX drastically. This would require deeper analytical insights generation, with collaboration among operation teams within the Telco towards achieving a common goal.

    Telecom operators with better equipped analytical tools to gather operational insights and actionable work flows can reduce their on-going CAPEX, draw more mileage from the pan-network assets and derive better return on assets in the network.

  • ..but that’s not my responsibility!

    ..but that’s not my responsibility!

    Now that’s something that we’ve all heard at our workplace at some point..and believe it or not, its not entirely incorrect.

    Traditionally most organizations have been created with a vertical structure having clear demarcation of responsibilities and identified handoff points for communication and information interchange between verticals. This was thought to be the most optimum way of assigning limited resources within the organization while allowing for specialization within verticals. Think of this organization as an architectural structure with three key layers:

     

    • Apex of the structure represented by executive management and strategy layer of the organization
    • Pillars represented by different verticals within the organization
    • Strong base represented by organizational infrastructure which acts as a common foundation

    While efforts are made by every organization to eliminate ‘silos’ in functioning, the inherent nature of this structure results in unidentified hand-offs, ineffective information sharing during hand-offs and compartmentalized view of processes leading to challenges in measuring, improving and most importantly identifying ownership of cross-functional processes. In many instances, different verticals end up shifting accountability of such cross-functional processes at the expense of progression. The pace at which technology, markets and customer demands are changing in present times demand a level of agility within the organizations to respond and keep pace with the market and competition. This places an enormous stress on the organizational structure, particularly on the handoffs between verticals.

    Managing millions of dollars’ worth of Network Capex within a Telco is a cross-functional process which experiences similar issues of ownership, handoffs between verticals and lack of a common, centralized view leading to ineffectual Capex tracking much less calculating effectiveness of these Capex investments or return on investments. Typically, Finance is the identified owner of Capex investments in a Telco but most Finance teams struggle with deployment of Capex in the network and more importantly tracking and calculating the return on network Capex investments as they are heavily reliant on Operations team for this information.

    Solving this Network Capex conundrum calls for a two-pronged approach, creating a cross-functional Network Capex Assurance team and enabling a supporting technological component to create a Network Capex Control framework. Lets have a closer look,

    Network Capex Assurance Team

    A cross-functional team which acts as the owner of Network Capex investments within the Telco – typically lead by the CFO or CTO. This team delivers critical insights and drives actions to enhance capital management practices in all phases of the business and comprises of representation from Finance, Planning, Procurement & SCM, Deployment, Operations and IT. The key responsibilities of this team would comprise of,

    • Custodians of Capex management processes
    • Capex planning and validation
    • Ensure data integrity across supporting systems
    • Capex tracking and analysis
    • Standardization & Reporting

    Network Capex Control Framework

    An enabling technological component which supports the Capex Assurance team in delivering their responsibilities by providing a centralized end-to-end view enabled by Network intelligence. Key insights from the framework would cover,

    • Centralized view
    • Standardized processes
    • Utilization and effectiveness
    • Capex & Opex optimization
    • Insights & Analytics

    Enabling strong capital management practices is much more than operational or process changes in the organization; it is a fundamental change in the outlook of an organization. Embracing this change will enable agility, data integrity and measures for optimization, better equipping Telcos to respond to the rate of change in the industry..and that should be everyone’s responsibility!

  • The SDN & NFV world: Things not to lose sight of!

    The SDN & NFV world: Things not to lose sight of!

    Natural human tendency is to focus more on things that affects our present rather than the future. Coming to things that affect us for which there is a lack of awareness about the “extent” of issue caused, there would be little or no attention from us to resolve them.

    Let us look at the priority with which investment decisions are made by telecom service provider on the software systems that they wish to have. Before a service provider can go live with a product offer for their end customers, they need to have the network in place to support the product. The priority for the software systems they should have to support their products are:

    • The first and most important is the billing software. They do not want go wrong in the billing as it would directly affect their revenues.
    • Second is the assurance software to make sure the network and the services are up and running.
    • The fulfillment software to automate as much as possible the order to activation process
    • A software which will help in strategic decision making like a planning software.

    Above are the verticals, now let us look at the horizontals which are the domain.

    • The first and most important aspect that is recorded well is that of the end customer. The entire lifecycle of a customer, right from acquisition to end of service to the customer in most operator environments is maintained well.
    • The second would be product life cycle management. This is important to know what needs to be billed based on the product that the customer is using.
    • The next important aspect is the maintenance of service life cycle.
    • By the time Telecom service provider gets all of the above going and fully operational, it is already a mammoth task for them and they tend to lose focus on Resource lifecycle management.

    A recent survey that was conducted by TMForum led by Subex revealed the following findings:

    • 1 in 3 operators do not measure returns on CAPEX investment
    • 77% of the respondents believed that inadequate asset utilization leads to increase in costs
    • 55% of the respondents believed that network planning is based on guesses
    • 64% believed that capex planning is driven by technology and not business objectives

    From the above findings it is clear that getting the right business process and tools around resource life cycle management is extremely critical for the long term health and efficient operations of a telecom service provider.

    In this blog, I would like to discuss about the exciting new world of SDN, NFV and cloud technologies and the relevance of resource lifecycle management in this new world. While a part of the telecom operator community is very aggressively embracing the concepts of SDN and NFV already into their network, there are others who are waiting and watching to see how things progress. I strongly believe, for the telecom industry to break the shackles of “reducing margins” and “increase in the need of CAPEX/OPEX investments” that it is currently facing, the key answers can be provided by SDN, NFV and cloud technologies.

    It is obvious that maximum energy is spent by telecom service providers, vendor community and standards bodies like ONF, ETSI, IETF, OPNFV etc. on how the network will work in this new world. Also, what I observed is that a bulk of the energy is being spent on defining standards around next gen BSS and OSS by TMForum, ETSI and ONF are in the following areas:

    1. Orchestrator
    2. VNF Manager
    3. VI (Virtualized Infrastructure) Manager
    4. SDN controllers
    5. Network and Application adapters
    6. Protocols used for communication with the devices and applications
    7. Policy engine
    8. APIs etc.

    As we go about defining the standards, let us look at covering the life cycles of all the domains starting from Customer life cycle, product life cycle, service life cycle all the way to resource life cycle. In this new world, resources can be physical compute, storage and network resources or virtual resources like software licenses. Let us not restrict ourselves in defining standards only on the operational aspects of resource life cycle management (OSS inventory) which was done in the eTOM model of TM Forum. Some work is being done by one group under the ZOOM initiate of TM Forum to define standards on onboarding of the software resource. This is definitely good, but we need to cover all aspects of the life cycle right from onboarding till end of life.

    So what if we do not do it, the systems will work, be operational and deliver services to the end customer. But we will probably end up being in the same state that we are in today, i.e. not being able to monitor how the CAPEX decisions of the past have fared, optimize on the investments already made, learn and improve in order to make better CAPEX decisions going forward.

    I would like to leave you with the following thought before I end my blog. If we ask any telecom service provider on the number of database or web server licenses they currently have deployed in their data centers, they may or may not have an answer. But if we go to the extent of asking how many of these licenses are in use and in how many cases we have a compliance issue, I am pretty certain that almost all of them will not have a precise answer to the question. Going forward, if all the network functions are going to be software running on COTs hardware, the need to have answers to the above questions will be even more important.

    Join the webinar on ” Telecom Asset Management in SDN & NFV world” to discuss more.

  • Making the Connection

    Making the Connection

    risk of congestion

    It’s 7AM and I can’t put off getting up any longer, so I look out the window and see there’s a light frost on the grass, which the weather channel warned me about 3 days ago. An hour later I’m at the train station waiting for the 7:42 which is delayed because the frost has caused the points to seize up in a town 50 miles away, so now the entire South East rail system is completely snarled up. They predicted the weather and probably knew there would be a point’s failure, but still the network crashed. So I need to phone work to let them know I’m going to be late, but I can’t connect. Thousands of other commuters around me are also trying to phone ahead, but the network can’t handle it. It seems to happen every day.

    We are surrounded by events which are beyond our control, but often they happen in predictable ways. The points failure was perhaps less predictable than my alarm, but we always knew that when the temperature dropped there would be some kind of failure somewhere that would lead to cancellations and a breakdown of the network. We always knew that rush hour would become an agonising crawl into town on overcrowded trains. The congestion could probably have been avoided if they could have predicted which parts of the network were under the most stress and the impact on the network in the event of failure or congestion at those stress points. Additional resources could then be provided at those points, or alternative routes planned to bypass the congestion and limit the ripple out effect, like a fire break.  The problem is only likely to get worse, and the network more unreliable, as the population increases and more people than ever rely on the rail network to get to work.

    With the arrival of LTE and rapidly increasing popularity of Video on Demand then telecoms networks are also facing increasing levels of congestion and instability. Global data traffic is predicted to increase by 10 to 20 times by 2019 (Cisco).   In order to meet regulatory obligations and maintain customer experience Capex is set to spiral upwards. MNOs, who are already facing a year on year decrease in ARPU, will struggle to keep pace with demand and the risk of congestion will be ever present.

    As with rail networks MNOs need a longer term strategy in place to understand where and when future choke points in the network will occur so that the risk of congestion can be eliminated for the least cost. Subex Capacity Management provides the capability to predict these points of congestion by monitoring and correlating metrics from across the network to provide detailed forecasts of network utilisation. Additional factors can be brought into the forecasts, such as the impact of major events or the rolling out of M2M services and different scenarios played out to understand how the network will respond. By automating the forecasting process network managers can be alerted long before issues become critical and congestion begins to occur. They can evaluate different options for either re-homing traffic or augmenting the network for the least possible cost. Stranded or un-utilised assets can even be recovered and re-located to satisfy demand for very little cost.

    CFOs need to find ways to keep increasing revenue while controlling costs, and CTOs need to keep network delivering ever greater speeds as volumes of traffic increase exponentially.  Both need to look into the future to avoid a future of network instability, falling quality, crippling network costs and lost revenue.