Category: Capacity Management

¿Todavía se están cargando videos? Ya no es necesario.
El video continúa ejerciendo su influencia como el medio digital más popular, convirtiéndose rápidamente en la nueva norma de narración de historias, sobre texto e imágenes fijas. Sin embargo, el consumo de video de alta calidad a través de dispositivos móviles, que es la opción de visualización más popular, depende de tecnologías avanzadas como 4G, que es la tecnología móvil de transmisión predominante en la actualidad y en los años venideros. Con 5G en el horizonte, la tecnología promete una velocidad de datos ultrarrápida que aprovechará la base construida por 4G.

El gran volumen de contenido de video en línea ha sido testigo de un aumento exponencial en los últimos años y solo se espera que se dispare en el futuro cercano. Considere estas estadísticas:
- El 82% del tráfico IP total (tanto de negocios como de consumidores) será video para 2022 [1]
- El tráfico de video a pedido del consumidor (VoD) casi se duplicará para 2022 [2]
- El video móvil aumentará nueve veces entre 2017 y 2022, representando el 79% del tráfico total de datos móviles para 2022 a finales [3]
Es obvio que el video es ahora la norma y los próximos años solo serán testigos de la creciente demanda de los consumidores de contenido de video de alta calidad consumido en dispositivos móviles, incluso en formatos 4K y 8K (en dispositivos móviles que se lanzarán próximamente). La creciente demanda de experiencias de visualización ininterrumpidas y consistentes en múltiples dispositivos y plataformas conducirá a un aumento en la necesidad de tecnologías móviles avanzadas que admitan velocidades más altas, conectividad ininterrumpida y capacidad suficiente.

El sentimiento de la industria es que 5G será el factor de potencia para la entrega de video de alta definición sin interrupciones. Sin embargo, creo que 4G, siempre que esté planeado y administrado de manera inteligente, podrá entregar según sea necesario. Esto viene con la advertencia de que los CSP necesitan superar los desafíos que han surgido de sus procesos actuales de planificación de inversiones en redes.

Desafíos que enfrentan los CSP para ofrecer contenido de video de calidad a través de dispositivos móviles

Aunque los avances tecnológicos en la transmisión de video en vivo continúan proliferando, los proveedores de contenido se enfrentan a ciertos desafíos críticos a la hora de proporcionar experiencias fluidas a los consumidores. Algunos de los principales desafíos incluyen:

Crecimiento de la intensidad de la comunicación: La intensidad de la comunicación se puede definir como: la relación entre la cantidad de tiempo que los usuarios pasan en sus dispositivos, en comparación con el número absoluto de clientes digitales (suscriptores únicos, teléfonos inteligentes y dispositivos). En el ecosistema actual, ambas métricas están aumentando exponencialmente y, según Ovum, la intensidad de la comunicación crecerá un 63% en los próximos diez años. Esta tendencia se ve impulsada principalmente por el contenido relacionado con el video.

El aumento dramático en la demanda realmente ha desafiado a los CSP a mantener altos puntos de referencia para la experiencia del cliente, mientras que los suscriptores móviles consumen grandes cantidades de contenido de transmisión.

Falta de disponibilidad ubicua de 4G

Como se describió anteriormente, 4G puede ofrecer más del ancho de banda requerido para transmitir videos en tiempo real. Sin embargo, la velocidad es de poco beneficio si no es accesible. Se han realizado mejoras en términos de cobertura, sin embargo, la disponibilidad omnipresente de 4G todavía está muy lejos. Esta es una lucha que incluso las naciones más desarrolladas enfrentan la mayor parte del tiempo.

Para dar más detalles, cuando digo disponibilidad 4G, significa la proporción de tiempo que los usuarios con un teléfono 4G tienen una conexión 4G. Para ponerlo en contexto, la disponibilidad 4G del 80% de un CSP de nivel 1 significa que, en promedio, sus suscriptores están conectados a los servicios 4G el 80% del tiempo.

Entonces, ¿qué sucede exactamente durante el 20% restante? Cuando los suscriptores pierden su conexión a una red 4G, su teléfono inteligente generalmente se transfiere a una tecnología heredada como 3G para mantener la continuidad del servicio. En tal escenario, continuar transmitiendo un video de alta definición probablemente sea hasta 4-5 veces más lento que 4G, lo que resulta en una experiencia de transmisión de video extremadamente pobre.

Falta de planificación inteligente a prueba de futuro

La tecnología 4G, que puede ofrecer una experiencia de banda ancha móvil verdaderamente superior, ha sido testigo de un aumento extraordinario en el uso que resulta en un crecimiento exponencial de datos. Si este crecimiento no se gestiona de manera inteligente, dará lugar a la congestión de la red, degradando la experiencia del usuario final. Por esta razón, los CSP deben comprender su estado actual de la red en términos de QoS de extremo a extremo, condiciones de radio y requisitos de capacidad. En base a esto, los CSP pueden establecer mecanismos sólidos para medir QoE a partir de contenido de video cifrado transmitido a su red y aprovechar análisis avanzados para establecer correlaciones accionables entre QoE, QoS, condiciones de radio y capacidad. Solo entonces podrán estar verdaderamente preparados para el futuro para satisfacer las demandas de los consumidores de contenido de video y manejar el crecimiento exponencial pronosticado del tráfico de video de manera transparente y eficiente.

Además, una poderosa solución analítica permite a los CSP tener una visibilidad de 360 grados del impacto de la red y las tendencias de los consumidores en el crecimiento de los datos de video para mejorar los ingresos y obtener una ventaja competitiva.

[1] https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white-paper-c11-741490.html

[2] https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white-paper-c11-741490.html

[3] https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white-paper-c11-738429.html

Conozca más sobre los factores que permiten una experiencia de transmisión de video sin interrupciones, vea nuestro seminario web On demand sobre: “Los ingredientes esenciales para obtener una ventaja competitiva en la era del video móvil”

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January 7, 2020
From 4G to 5G, keys to digital transformation
The journey of digital mobile communications began with the inception of 2G technology in the 90s. In retrospect, the technology evolved multi-fold, mainly due to the promising growth the industry witnessed. One of the prime reasons for evolution was the constant progression of technological enhancement to overcome legacy technology challenges. One such challenge that has served as an impediment for a smooth technological transformation has been the need to do a hard transition from one standard to the next. I personally witnessed it as the technology evolved from 2G to 3G, as well as 3G to 4G, throwing multiple challenges to network professionals as we sought to ensure service continuity while maintaining user experience targets.

More recently, with the inception of 5G technology, the approach of network standard replacement has vanished away. Early adoption of 5G technology doesn’t need 4G replacement. As a matter of fact, it gradually builds upon the LTE network. Let’s get into a little depth on this:
- 5G technology primarily has two deployment strategies, refer to figure 1. Non-Standalone (NSA) is the first version currently being used by all existing 5G networks. NSA has its own limitations when compared to full standalone or SA, the other version of 5G.
  Setting aside the limitations and noting the fact that the time span taken for complete transition of previous generation technologies was quite high, I see the introduction of NSA deployment strategy as a good pragmatic move. 5G NSA lays a strong foundation to prevent such a repeated flaw in standards development, facilitating smooth transition from 4G to the full 5G SA standard.
Figure 1: Non-standalone and standalone deployments

In practical terms, the early implementations of 5G will use a combination of 4G and 5G technologies to function. This combination will evolve across geographies and the ratio will vary across the regions, depending mainly upon the availability of spectrum and CSPs’ digital transformation strategies.
- The latest GSMA mobile economy 2019 report predicts that by 2025, 4G will remain the predominant technology with a market share of 59%. 5G will continue to grow but will only cover a market share of 15% by that time. The fact that 4G will remain the dominant technology by 2025 is not surprising, considering 3GPP standards for 4G is being developed and enhanced to LTE-advanced pro, which is often termed 4.9G (or the more dramatic “Road to 5G”).
This will lead us to a very interesting phase in the mobile communication industry and eventually to a very important question: “How should a CSP plan for 5G networks or most importantly how should it plan the transition from 4G to 5G technology?”. Frankly, there is no fool-proof guiding principle but there are some real-world use cases that I would like to take you through.
- Case 1: Rakuten network in Japan will not initially offer 5G services. Instead, it will leverage its 4G LTE network with macro and small cells. Most interestingly, it will be fully virtualized from the radio access networks (RAN) to the core, with end-to-end automation for both network functions and services. This approach is intended to construct a network quickly and cost-effectively, which should put them in the pole position when it comes to launching and monetizing 5G. Obviously, Rakuten has had the luxury of being a greenfield operator, however, there are still some key lessons that other CSPs can take from their approach. These will come handy towards balancing the Capex lift of 5G while fighting an uphill ARPU battle.
- Case 2: US operator AT&T, from the current state of 5G deployments, is encouraging the upgrade of 4G networks to its most advanced versions. LTE advanced and LTE advanced-pro have been available for some years now and CSPs like AT&T in the US are referring to it as “5G Evolution” (5GE), even though it is most definitely not an official 5G standard, but rather the latest version of 4G.
Each of the above cases demonstrates that consolidating the existing LTE network and gradually making it 5G ready may be the most optimal and cost-effective way of evolving from 4G to 5G. Moreover, as the technology itself provides this smooth and seamless transition capability, CSPs should leverage it.

The bottom line is, while 5G clearly points the way forward, it’s the foundation of 4G that will be a critical part of its planning, operation, and success. Additionally, the strength of the current 4G foundation depends on how seamlessly and smoothly content on LTE networks (primarily data-driven) is delivered to the end-users. Mobile users want both smooth experiences and obvious incremental improvements in network speeds to feel satisfied with network performance. Evolving networks toward 5G is crucial to keeping up with the appetite for higher speeds and quality user experience.

Subex network analytics offerings take into account the key aspects of digital transformation and help a CSP consolidate its current 4G LTE network and plan for 5G network in a most cost-effective way with focus on enhancing the customer experience and maximizing returns on network investments.

To understand more on Network Investment Planning

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December 17, 2019
Videos still loading? They don’t need to anymore
Video continues to exert its sway as the most popular digital medium, quickly becoming the new storytelling norm, over text and still images. However, the consumption of high-quality video through mobile devices – which happens to be the most popular viewing option – is dependent on advanced technologies such as 4G, which is the prevailing streaming mobile technology for today, and the years to come. With 5G on the horizon, the technology holds promise for lightning-fast data speed which will leverage on the foundation built by 4G.

The sheer volume of online video content has witnessed an exponential increase in the last few years and is only expected to skyrocket in the near future. Consider these statistics:
- 82% of total IP traffic (both business and consumer) will be video by 2022[1]
- Consumer Video-on-Demand (VoD) traffic will nearly double by 2022[2]
- Mobile video will increase nine-fold between 2017 and 2022, accounting for 79% of total mobile data traffic by 2022 end[3]
It’s a no-brainer that video is now the norm and the coming years will only witness burgeoning consumer demand for high-quality video content consumed on mobile devices, including in 4K and 8K formats (in soon-to-be-released mobile devices). Growing demand for seamless and consistent viewing experiences across multiple devices and platforms will lead to an increase in the need for advanced mobile technologies supporting higher speeds, seamless connectivity, and sufficient capacity.

Industry sentiment is that 5G will be the powering factor for true seamless, high-definition video delivery. However, I believe that 4G, provided it is smartly planned and managed, will be able to deliver as required. This comes with a caveat that CSPs need to overcome challenges that have emerged from their current network investment planning processes.

Challenges Faced by CSPs in Offering Quality Video Content over Mobile Devices

Though technological advancements in live video streaming continue to proliferate, content providers are faced with certain critical challenges when it comes to providing seamless experiences to consumers. Some of the top challenges include:

Communication intensity growth: Communication intensity can be defined as: The ratio of the amount of time users spend on their devices, as compared to the absolute number of digital customers (unique subscribers, smartphones and devices). In today’s ecosystem, both metrics are increasing exponentially, and according to Ovum, communication intensity will grow by 63% over the next ten years. This trend is being fueled predominantly by video-related content.

The dramatic increase in demand has really challenged CSPs to maintain high benchmarks for customer experience while mobile subscribers consume copious amounts of streaming content.

Lack of ubiquitous 4G availability

As described above, 4G can offer more than the required bandwidth to have videos stream in real-time. However, speed is of little benefit if it isn’t accessible. There have been improvements made in terms of coverage, however ubiquitous 4G availability is still far away. This is a struggle which even the most developed nations deal with most of the time.

To elaborate further, when I say 4G availability, it means the proportion of time users with a 4G handset have a 4G connection. To put it into context, 4G availability of 80% of a tier 1 CSP means that on an average their subscribers are connected to 4G services 80% of the time.

So, what exactly happens during the remaining 20%? When subscribers lose their connection to a 4G network, their smartphone usually gets handed over to a legacy technology such as 3G to maintain service continuity. In such a scenario, continuing to stream a high definition video will likely be up to 4-5 times slower than 4G, resulting in an extremely poor video streaming experience.

Lack of intelligent future proof planning

4G technology, which can offer a truly superior mobile broadband experience, has witnessed an extraordinary surge in usage resulting in exponential data growth. If this growth is not managed intelligently then it will lead to network congestion, degrading end-user experience. For this reason, CSPs must understand their current state of the network in terms of end-to-end QoS, radio conditions, and capacity requirements. Based on this, CSPs can establish strong mechanisms to measure QoE from encrypted video content streamed into their network and leverage advanced analytics to establish actionable correlations between QoE, QoS, radio conditions and capacity. Only then can they be truly future-ready to meet the demands of consumers of video content and handle the forecasted exponential growth of video traffic seamlessly and efficiently.

Moreover, a powerful analytics solution enables CSPs to have a 360^o visibility into the network impact and consumer trends of video data growth to improve revenue and gain competitive advantage.

[1] https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white-paper-c11-741490.html

[2] https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white-paper-c11-741490.html

[3] https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white-paper-c11-738429.html

To learn more about the factors that enable a seamless video streaming experience, Watch our on-demand webinar : “The essential ingredients to gain competitive advantage in the mobile video era”

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September 25, 2019
Actionable predictive analytics: overcoming the analysis paralysis
Why standard forecasting analytics models fail to deliver in today’s world of complex digital networks and why telcos need a domain-specific analytics solution.

“Your analytical dashboards and visualizations look good, but I prefer actionable reports and insights”, said the deputy CEO of a Southeast Asia-based telecom service provider during one of our meetings last year. This was not just one odd instance. We have heard this many times in the past year from other CSP executives. There are many domain-agnostic AI/ML based analytics solution providers in the market, but what telcos really want is an analytical solution which provides end-to-end domain-specific actionable insights. Forecasting traffic or pointing out anomalies is one thing, but how to incorporate those recommendations into capacity planning? What is the root-cause for that anomaly so that it could be prevented in future? Instead of getting lost in analysis paralysis amidst thousands of fancy statistical metrics; a simpler, actionable and reliable predictive analytics solution is the need of the hour.

With the right mix of domain knowledge and analytics advantage, centered around the actual requirements of the network planners; Subex has come up with the concept of actionable predictive analytics. Network planners should be enabled for efficient, reliable and cost-effective capacity planning. Hence, here the focus is more on what matters to the telco network teams, i.e. the business values such as capex optimization, network performance improvement, customer experience enhancement and operational efficiency; rather than on underlying analytical components such as configured models or feature engineering.

Here are two of the most important aspects about Subex’s approach to predictive analytics which are different from the traditional forecasting models –

Multi-variate analysis

Unlike the traditional forecasting systems which predict the future trends for a metric based on the historical pattern of that given metric, in multivariate approach, the system understands the lagging or leading effect on the given KPI from other KPIs. With this, the telco can predict, in near real-time, what is going to happen in the future and adopt appropriate measures to prevent capacity issues. A multi-variate, self-learning forecasting model which runs on the in-house machine learning platform is complemented by domain-specific configurations and expertise which is equally essential for intelligent forecasting.

The figures below compare a multivariate model scenario that considers the lagging effect of KPI1 (e.g. customer complaints) on KPI2 (e.g. capacity utilization) with that of a traditional model that does not give such insights. In the first case, the operator does not get accurate results as yielded in the second case because there is a direct relation between traffic and customer complaints. For example, if there was an aberrant increase in traffic, the operator can take that fact into consideration for accurate prediction of future customer complaints.

One more use-case could be accurately predicting the time to capacity exhaust for a site if one of the neighboring sites is planned for decommissioning soon. In this case, with the help of geo-spatial analytics, the additional load on the given site due to decommissioning of the neighboring site would also be considered for calculating time to capacity exhaust.

Domain Specific Insights

Be it wireless or hybrid fiber-coaxial networks, even an accurate capacity forecast is incomplete without the required domain-specific insights. Without a proper root cause analysis for a network element exhausting soon (in terms of capacity), the network planners won’t be able to make the right decision about its proactive mitigation.

These are some questions to consider when developing your network augment action plan:
- How many customers will be impacted when a given network element hits a capacity exhaustion threshold?
- Will prioritizing the given candidate for capacity augment above other options result in the best customer experience improvement and maximized ROI?
- What is the reason for this capacity exhaust? Is it because of seasonality, periodicity or cyclicity? Is it an anomaly due to some one-off event?
- Will new Capex be required to address the capacity bottleneck, or are there alternatives to new spending?
Some of the insights that could be useful for the planners leveraging predictive analytics for capacity planning and management are shown below –

Apart from the above two key differentiators, some other important aspects for a pragmatic, accurate and reliable predictive analytics solution are scalability and flexibility.

Multi-variate forecast models need to run thousands of simulations across the network to identify the correct correlated metrics for accurate predictions. Such models need to be configurable, flexible and easy-to-understand for non-data scientists.
September 17, 2018
Smart Performance Indicators — Redefining the KPIs
What is measured, is managed. Are you measuring the right metrics?

While driving, most of us would want to reach our destinations on time. An unexpected congestion on the way can easily turn a nice Friday evening into a frustrating start to the weekend. As the world progressed, it changed a lot the way we planned our journeys. Instead of going with the route that we took yesterday; we listened to the traffic updates on radio, kept ourselves updated with any special events around, based on the evening plans we tried to estimate our start time etc. Sounds better than driving with nothing but rear-view mirror & front view, but still too many things to monitor. Then came the Google Maps — one stop solution to get accurate real-time updates based on multiple data sources, scenario planning capability based on different available options & routes. You are still on the driving seat, but you have all the means to make the right decision. Friday evenings are no more frustrating.

This got me thinking – in our work, aren’t we too trying to reach our destinations — in terms of performance, goals & objectives — on-time every day, every quarter, every year? Having worked at two of the largest Telcos in the world, I thought that the performance management systems, in their current form today, need smarter metrics than just measuring what is easy. On their road to 5G and future technologies, Telcos would need something as smart as Google Maps to guide them to their destination.

With this idea and a small team of talented software engineers & data scientists, we have built — what we like to call it — a machine learning based Smart Performance Indicator framework. Using some of the multi-variate principal component analysis techniques, this framework creates meaningful Smart Performance Indicators out of the available metrics.

Telcos today are sitting on enormous amount of data and measuring thousands of KPIs but –
- Are they measuring the right metrics?
- Are they combining several metrics and analyzing their correlations & causations instead of just looking at some simple metrics?
- They are surely measuring the past performance and comparing it with today’s, but are they looking ahead?
- Instead of looking at the current values, are they looking at trends and statistics?
- Are they measuring their KPI responses for an unexpected scenario?
- Are they able to store enough amount of past historical data to be able to predict the future?
- And most importantly, are the traditional KPIs learning from the changing trends, anomalies and proactively acting to it?
The traditional KPI dashboards today indicate more about how the network performance has been than about where it is going. The focus is more on short-term operational performance rather than long-term strategic performance. We manage what we measure, hence it has become more important than ever to measure the right metrics, smart metrics. Telcos need to measure what’s important, not just what is easy.

Sample dashboards with SPI outcomes

If you are working with a Telco and think that the above problems need to be addressed in your organization, we exactly know what you need. Your Fridays should no more be frustrating, feel free to reach out to me at anshul.bhatt@subex.com
May 24, 2018
Telcos CAPEX is here to stay. Optimizing it is the way to go.
“A lot of people have been talking about how capex is going to come down with SDN and I’ve said, ‘No, it’s going to stay the same for Verizon’ – Fran Shammo, CFO, Verizon. May 2016

This comment right from the head honcho of one of the largest Telcos in US cannot be taken lightly. Despite lot of talk in the industry about SDN / NFV CAPEX reduction benefits, we’re seeing skeptical questions around smooth transition to virtualization. But I will keep SDN /NFV discussion for some other day. Let us focus on the topic – CAPEX spends. Verizon’s CFO has confirmed its CAPEX spend going to stay, despite network virtualization!

The CAPEX focus could be different for different Telcos. For some Telcos like Verizon, their CAPEX spend mainly focused on future technologies, leading the market, greater customer experience etc. For some other Telcos, their budget constraints force them to think hard and do delicate trade-off between strategical “revenue-growth” projects and tactical maintenance projects to keep up with network growth, retain customers, improve quality of experience etc. With this hard balancing at hand, what if Telcos are equipped with smart tools & methodologies that could help in optimizing their on-going CAPEX? But, is such thing exist? I will get there in a moment. Please bear with me.

First, let us go through few industry trends. In our recent study from Gartner, we got few interesting insights.

Here is short summary on the insights:
- On an average Telco spends 15% – 20% of annual revenue on yearly Capital Expenditure
- Increase in Capex spends w.r.t revenue (CAPEX Intensity = Capex / Revenue) is not translating into equivalent increase in revenue growth
- Correlation between CAPEX Intensity and Revenue growth is a weak factor for Telcos mentioned in the regions. This means revenue growth is not linearly correlated with CAPEX spends
- 5-year flat growth in revenues across geographies is not encouraging. Max 20% 5-year top-line growth in North America region and deep negative for Europe region (-11%)
- Cost of capital over last decade is higher than RoI on an average across the industry
- Notable positive point is the margins are maintained in 25 – 35% range across geographies. And it is imperative to maintain this margins to generate free cash to fund next CAPEX cycle but if not completely.
The above stats where CAPEX spends are not reaping substantial revenue growth indicates two major viewpoints:
1. Strategic capital investments have a slightly long gestation period but not comparable to capital cycles of traditional industries like manufacturing industry.
2. Bulk of CAPEX go into maintenance projects. That is, to keep-up with current network demand juggernaut, customer retention, quality of service etc.
For instance, a good chunk of leading Tier 1 North American operator’s CAPEX goes into wireless network for densification and getting future ready for 5G deployments. This could be a case for many big Telcos – investing on future technologies. On the contrary, we have also seen majority of Telcos’ CAPEX going in for second type of investment – meeting current network data growth. This is nothing wrong as such and very much required to keep customers happy.

However, if one looks at this fact in light of recent market research findings from one of the big four audit firms, it gives a different perspective. The research reveals that majority of the Telcos not equipped with enough tools or industry best practices to assess the CAPEX spends on projects, evaluate ROI for each such investment and perform sustainable capital allocation. This is a surprising revelation. It simply means that many Telcos are servicing on-going CAPEX without rigorous assessment on actual RoI vs planned RoI, are not taking forward lessons learned from previous CAPEX cycle. Even the Telcos who do have rigorous processes, right incentive structure, accountability of results etc. actually misses a critical point.

What Telcos underestimate?

The critical point is – generally the assets, especially the network assets are viewed from monetary value perspective only in this whole CAPEX scheme of things. The value that can be derived from un-lit or under-used network asset capacities for the CAPEX planned is not given deserved thought or action. This is because of the fundamental reason that financial and network data of assets are lying in silos. This data is never used together to gather useful insights to put the network assets to sweat to furthest possible aligning with ever growing network demand and broader strategic CAPEX – RoI goals. Telcos can do more with their data. It would require collaborative efforts with right partner to unleash the power residing underneath the siloed systems.
September 27, 2016
The legacy network is dead, long live the legacy network!
I was recently asked by a Tier 1 client in North America if Subex can use our network discovery technology to retrieve information from D4 channel banks. I honestly had not crossed paths with these relics of the voice network since my days doing central office engineering in the late 80’s. So you may be wondering, in a day-and-age when the buzz is about SDN/NFV, IoT and everything in the “Cloud”, why is someone worried about the humble channel bank?

As it turns out, there’s plenty to worry about. End-of-life technology can be a significant Opex drain. Operators incur costs for energy (power, HVAC), maintenance and real estate to keep such equipment in place. Compounding the problem is that much of this old equipment typically sits racked, stacked and powered… and idle (no traffic). Channel banks are just one example. Arguably, the entire fixed-line TDM network is retirement-age (I’m talking about SONET/SDH DACs and ADMs, voice switches, local loop equipment, etc.) and needs to yield to IP/MPLS and VoIP.

In a previous blog post, I wrote about what operators need to consider when planning a transformation from legacy technologies to future state. For this post, I will stay grounded in the present and focus on this question: What strategies can operators employ to reduce their Opex and Capex burdens when operating a legacy network? For starters:
- Use network discovery techniques to determine the operational status of your actively deployed network assets.
- For all unutilized assets, apply a deliberate strategy to disposition everything. Too often, because operators don’t have adequate visibility to operational status and utilization of assets in the legacy network, they default to what I call a “rust-in-place” strategy. Since they lack the visibility, they ignore the problem. Equipment sits idle or underutilized and costs add up. My suggestion is to proceed with purpose—if an asset is carrying adequate revenue-producing traffic, fine. If not, do something about it!
For assets with reuse potential, then the options include:
- Harvest and reuse elsewhere in the network. Benefit: Avoid Capex for new purchases.
- Perform grooms to more densely pack some assets and free up others for reuse or end-of-life monetization.
- Allocate as spare. Benefits: Reduced maintenance costs when spares are optimized in terms of count and location. Customer experience is improved and exposure to SLA penalties is reduced when spares are well managed.
If there is no reuse potential, then consider:
- Reselling on the secondary market if there is still industry demand for the asset.
- If not, then recover and sell for salvage value.
- In both cases, remember that the NPV of averted monthly energy and real estate costs may actually exceed any direct cash received when the asset is sold or salvaged.
- Don’t overlook other possible financial benefits from disposing unneeded assets such as tax write-offs and reduced insurance premiums.
Most importantly, seek an asset management and logistics partner who can help you squeeze the most value from legacy assets. Elements of a legacy network cost reduction program include:
- Automated audits via network discovery
- Asset evaluation and disposition recommendations
- Capacity utilization trending and related analytics
- Asset tracking
- Turnkey asset recovery services
- Resale valuation and brokerage services
- Eco-friendly recycling
- Analytics for sparing level optimization
- Spares management
- Warehousing and related logistics services
- Warranty and annual maintenance contract management
- Test, repair and engineering services
Subex provides industry-leading asset management solutions and services. With our forward and reverse logistics partners around the globe, we can help you to establish a turnkey and highly effective legacy network cost reduction program.
December 8, 2015
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.

May 18, 2015
A Thorn in the Side? – Handling Over-the-top Content Demands
As I interact with more and more service providers about their network capacity issues, I’ve become sure about one thing – what worked before, isn’t really working anymore. The CapEx requirement for network equipment just to keep up with the exponential growth in data traffic (i.e., Data Tsunami) is still not getting them ahead of significant congestion issues and customer impacting events. Why? Traditional capacity management paradigms are not working.

Essentially, feedback from carriers of all sizes and types has exposed one of the most significant shifts in thinking regarding how to go about managing and planning for network capacity. They know that the rules are all changing and today’s content demands are outpacing the CSPs ability to keep pace. The first key question is how to get back in front of the capacity demand (we’ll talk about monetization next…stay tuned). So, why aren’t today’s processes scaling?
- CSPs use a multitude of human resources and manual processes to manage network capacity. This may have scaled under slower and more predictable capacity growth curves, but thanks to services like You-Tube & Netflix, entire network capacity is shifting in quantum leaps.
- Solutions provided by equipment vendors are often platform specific, and reinforce a silo approach to Capacity Management when a holistic view is needed. Service demand congestion is a network phenomenon which doesn’t care about individual equipment vendors or devices.
- CSP planning groups leverage data and make decisions based on systems which have 20 – 40% inaccuracy in comparison to the actual capacity availability in the network.
- Today’s CSP solution approach is often homegrown where 90% of the time is spent on acquiring and understanding raw data. As a whole, everyone is trying to answer the question of how to proactively eliminate the possibility of congestion, but most are still focused on addressing the symptoms and not preventing the problem
It is surprising to note that even top tier/technology leaders cannot accurately predict where and when capacity issues will impact their networks. This lack of visibility hurts CSPs considerably because as per our own studies, network events are behind can account for up to 50% of customer churn in high value mobile data services.

And the Capacity Management problem doesn’t really end there; in many ways it’s like a supply chain process. Marketing owns the function of forecasting where service uptake will drive capacity needs across the network. When Marketing underestimates service uptake, there is a real and significant impact to potential revenue: On average, it can take about 3 months from when capacity is fully tapped in a Central Office (CO) to when new capacity can be added to your network. During that time, customers expecting service availability become hugely frustrated and begin to churn. Engineering groups are pushed into panic-mode, trying to react as fast as possible – often putting capacity in the wrong places due to inaccurate data – resulting in further congestion, service degradation, an inefficient use of capital.

The message from CXO’s is crystal clear – there is an urgent and dire need to find new ways of monetizing the data crossing their networks. This need is exacerbated with OTT content and net-neutrality. SLA and authentication based revenue models are absolutely dependent on knowing what types of content/services are traversing your network, how much capacity they consume, and how utilization is driven by your consumer’s interests and activities. This type of analysis requires a critical and intelligent binding of network and services data with business data to truly assess the financial impact to the CSP. Many Business Intelligence (BI) solution leaders will lay claim to abilities here, but actually fall very short of the mark. Instead, real experience suggests that solutions in the marketplace today either:
- Can handle the financial aspects of your business but have no understanding of today’s network dynamics in terms of capacity issues and services;
- Can handle parts of your network very deeply, but do not correlate or provide a holistic view at the service level; or,
- Can collect some network and service level information, but have no ability to incorporate business data to understand the impact to the business – i.e,. cost, subscriber behavior, propensities
All the above challenges bring us to the inevitable question – what kind of approach does one take in order to tackle capacity management issues? How does one stop chasing traffic and focus on flattening the CapEx curve instead? In order to attain ‘Capacity Management Nirvana‘, a proactive and scalable approach needs to be adopted by CSPs. An approach which not only intelligently binds network and business strategies based on the Data Tsunami realities but also brings proactive and predictive capacity management to the table. At the end of the day, a CSP should have access to all their capacity, the ability to leverage real and immediate feedback on the change in capacity as service uptake increases, and finally, the right tools and intelligence to get in front of what’s coming.

To know more about how a Capacity Management solution can help you address the above issues, download the whitepaper “Energizing Smart Growth with Network Intelligence“
March 15, 2012