Insights

Automation

© MYCOM OSI Page 2 of 17

Table of Contents

1. Digitalization of telco business and the role of service assurance ....................... 3

2. Simplify Operations for the Telco Cloud ................................................................... 7

3. Q&A: Disrupting your OSS with analytics, automation and AI ............................. 10

4. Delivering a personalized digital experience ......................................................... 14

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1. Digitalization of telco business and the role of

service assurance

Written by Mounir Ladki, President and CTO, MYCOM OSI

CSPs need to simplify and rationalize their service assurance systems across

all networks: mobile and fixed, enterprise and IT/data center, so that they can

be maintained at peak performance and maximize the utilization of the

network resources. As a consequence of evolving digitalization, there is a great

need to build operation centers that are predictive, customer-centric,

analytics-driven and highly automated to help CSPs achieve speed and

massive opex savings. Another focus area is assurance of digital services.

Digital SQM systems assure and help to monetize the quality of Video/IPTV and

other digital services, which helps CSPs to offer a differentiated service

experience and monetize it through analytics.

There is a need to 'evolutionize' service assurance by introducing highly modernized

engine, analytics and automation, to combine data from various sources and make it

suitable for the digital service provider. Such evolved systems will be suited to address

the challenges of IoT and 5G as well, especially those of monitoring and assuring the

performance and QoS of network slices. This includes machine learning to help telcos

monetize IoT assurance and analytics capabilities.

How CSPs can benefit from automated operations

Automation of operations center processes is key to achieving success in the

virtualized and digitalized telco cloud environment. Accuracy, speed and error-free

operations are critical to the success of a digital business. This includes using auto-

detection of service policy violations, managing configurations, automating root cause

analysis and remediation, reducing MTTR.

By integrating analytics and automation, data can be visualized and actioned in the

predictive operation center in a totally new manner, removing human latency and

enabling real-time experience of the CSPs' customers.

CSPs have found new ways of combining analytics with automation for network

monetization; for example, for discovering untapped capacity in their networks. This

enables CSPs to direct services to those parts of the network that are underutilized.

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Alternatively, capacity can be dynamically moved to areas of network where it will be

utilized better. By automating the process of reducing or reorganizing capacity

bottlenecks in the network, the operator can save big chunks of opex.

Efficient automation requires planning and prioritization

CSPs are working towards realizing a fully automated, zero-touch operation center

using closed-loop corrective actions, complex algorithms and machine learning. And

to support the dynamic SLAs of the telco cloud, the Service Assurance system is

expected to support on-demand capacity configuration and dynamic topology

changes, which can happen only through automated real-time network feedback and

automatic configurations.

CSPs can identify processes and workflows that require a high level of automation and

those that need manual control. As an example, automation of the CSPs' radio

optimization processes, congestion management and backhaul optimization can

dynamically optimize network capacity and release teams for high-skill complex

analysis. Automation also includes use of open APIs and automating delivery and

assurance of new on-demand services.

Additionally, the combination of customer analytics with automation techniques can

help CSPs to create and drive new personalized services for locations and customers,

bringing almost instant monetization of available capacity.

Managing higher speeds and higher data volumes in the future

To make the digital business successful and to support the expected dynamicity, speed

and scale of the digitalized networks, certain technologies and functionalities are

necessary to be adopted into the Service Assurance platform.

Along with Open APIs and OpenStack for cloudification, it is important to develop a

micro-services architecture, which uses DevOps-enabled iterative processes to quickly

respond to customer needs by developing services faster. It also helps in faster

delivery of services, quicker root cause analysis and real-time customer issues'

resolution.

CSPs are now extending their business to become IoT service providers, offering high

quality, high reliability networks and soon supported by 5G. For this, Service Assurance

will be enhanced with elasticity of database, Hadoop cluster technologies and machine

learning to manipulate big data at faster rates in real-time.

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Big data analytics to unlock network monetization

Analytics are critical to understand the usage of the telco cloud, the services it offers

its customers and devices. They fuel the service agility expected in a virtualized

network, other than optimizing capacity of the hyper-converged network.

CSPs can obtain trends on performance, capacity and faults using sophisticated

machine learning-based analytics tools.

As an example, identification of revenue-generating locations, capabilities of handsets,

customer behavior, uplink and downlink video traffic, consumption of

video/conversational services, etc. allows optimal network investments and helps in

directing marketing campaigns for maximum business impact.

Network monetization and service personalization are only possible by running

powerful analytics on big data. CSPs can proactively identify low congestion zones/

locations and rapidly fill spare capacity with revenue-generating traffic from new

service offers such as video streaming, mobile TV or smartphone apps.

Next generation Service Assurance for supporting IoT services

IoT networks are currently being overlaid on existing communication networks and

many of the connected IoT devices will be controlled through reliable, cloud-based

management systems, operated by CSPs. These systems will not only check the

performance, but also provide real-time visualizations of the devices and insightful

data generated by the devices.

IoT management systems will ensure IoT data reliability by managing the end-to-end

performance of IoT gateways and inter-device communication, assuring that the IoT

network and devices are operating in a faultless manner, delivering on the promise of

100% connectivity and 100% reliability.

Key IoT performance measurements will include the performance of the sensored

devices, ensuring the QoS, reliability and security of those devices, specific to the

industry verticals. In addition, CSPs will use these platforms for monetizing IoT

analytics.

The business potential of an OSS-based data monetization platform can offer the CSP

huge benefits by supporting IoT initiatives such as smart city services, connected

factories and autonomous car industries, to start with.

© MYCOM OSI Page 6 of 17

Published in RCR Wireless News on 2nd May, 2017. This is an edited version of the original

article

Also available on http://www.mycom-osi.com

© MYCOM OSI Page 7 of 17

2. Simplify Operations for the Telco Cloud

Written by Sandeep Raina, Product Marketing Director, MYCOM OSI

As CSPs undergo digital transformation - which means offering digital services

through a Telco Cloud environment – they face a whole set of operational

challenges, including operating a new virtualized network, focusing on

customer experience more than before and providing high reliability and

availability for upcoming IoT services. Simplifying the operations can help in

tackling these challenges.

The complexity of the operations in a Telco Cloud owes to the following:

1. The high speed at which digital services will be deployed: Digital services

require real-time dynamic deployment, adaptation and customization.

Automation of many Operations Center processes, including monitoring,

orchestration, feedback, audit and messaging, are needed to support this

2. Running a hybrid network: part virtualized, part physical: Since the

process of virtualization will take 3-4 years to stabilize, extra vigilance is

required as new nodes/VNFs are added/removed. Seamless operations will

require systems that quickly adapt to the network changes

3. Dynamic services need constant and consistent management: Policy-

based management is required for constant and rapid management, leading

to automated simplified configuration in a virtualized environment

4. Additional attention to IoT operations: IoT traffic is expected to run on

highly reliable and error-free networks, which drive expectations or objectives

for the IoT network, service and devices to have minimum failures. Every new

piece of equipment, software and device will bring its own failure points and

requires upping of the fault management to ensure reduction in the number

of faults

5. Impact on life-critical or mission-critical communication: In a hyper-

connected world, failed devices or connections might not only breach SLAs

with massive penalties, but, more importantly, impact lives. Although complex

mesh topologies with high availability and redundancy will serve to minimize

failures, they still require a highly efficient system to discover, interpret and

manage the faults

6. Operation Centers need to be more proactive and predictive: This comes

from the need to minimize performance degradations, prevent failures and

eliminate critical customer-impacting problems

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Integration and consolidation of OSS components is the first step towards

simplification of the Telco Cloud operations. Automation – including machine learning

– is the next.

Integration and consolidation: The introduction of NFV with network

functions and services hosted on common resources inherently helps to

achieve the required integration to an extent. Open REST APIs also help in

connecting the OSS layers. Finally, hosting of OSS functionalities (analytics,

automation and SQM) in the cloud can also accelerate the integration of the

required functionalities of the Operation Center. Introducing topology-based

root cause analyses integrates services with the underlying network, closing

the remediation loop

Automation: Automating the Operation Center means encapsulating the best

practices for standard operating procedures and using machine learning to

derive or improve them. This frees up resources by automating and

orchestrating complex processes across multiple domains and functions. Not

only does it reduce human error and increase employee productivity, but it

also greatly simplifies complex operations involving a large number of

processes. The simplification benefits can be reaped by various functions,

including planning, optimization and business teams. The highest level of

automation would lead to the desired zero-touch Operation Center. Building

a zero-touch Operation Center for the Telco Cloud will require the following

key steps:

Automating critical OSS actions

Exploiting machine learning for efficiency

Self-healing and optimization by feedback loop

Here are some suggested use cases for the simplified (Integrated and Automated)

zero-touch Operations Center:

1. QoS-driven orchestration in hybrid networks: Using integrated performance

and fault data on network/services, QoS policies can be derived and operated

to orchestrate both physical and virtualized (hybrid) networks. This requires

an integrated SQM/automation/orchestration system

2. Management of end-to-end IoT: Managing IoT traffic by using analytics to

forecast patterns and prevent IoT network, service and device failures. This

includes building dashboards for service availability, incident and

unavailability breakdown by location and geolocation-based service impact

3. Prediction of SLA breaches: Machine learning, when integrated with analytics

based on performance/fault data, offers powerful predictive management

capability to anticipate problems and helps in protecting customer SLAs

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4. Service impact analysis and root cause analysis: With SQM integrated with

fault data, faster service impact visualization is possible for the Telco Cloud.

Also by automating root cause analysis problems can be quickly identified to

reduce mean time to repair

5. Automating outage recoveries: By automating fault management, network

outage recoveries can be accelerated. Additionally, by integrating fault

management with the OSS ecosystem (Trouble-Ticket, Inventory,

Orchestrators, SQM, CRM, Work Force Management, etc.) problems are

reported and solved much faster

A simplified zero-touch Operations Center provides many benefits. However, it does

require drastic changes in the way OSS components integrate and interact with each

other and how network/service data is visualized and actioned in the Operation

Center. Introducing analytics, machine learning, messaging bots, automated RCA and

orchestration will simplify the operational complexities of the hyper-converged

network and its services.

Published in Vanilla Plus on 28th February, 2017. This is an edited version of the original

article

Also available on http://www.mycom-osi.com

© MYCOM OSI Page 10 of 17

3. Q&A: Disrupting your OSS with analytics,

automation and AI

Written by John C. Tanner, Editor at Disruptive.Asia

When people talk about disruptive technologies, they don’t usually think of the

backend. But that’s where some of the more crucial disruption needs to

happen – and is happening. In this exclusive Q&A, Mounir Ladki, president

and CTO of Mycom OSI, explains how analytics, AI and automation can take

the OSS to the next level, the challenges of integration and why service

assurance will be crucial for IoT services.

MYCOM OSI’s contribution to OSS disruption

We are playing a disruptive role in the OSS space. We came up with technologies that

we take natively to the cloud with an open-source, open architecture, REST API’s, a lot

of analytics and automation. And now we’re helping our customers to play a

constructive role in the ecosystem.

For example, in the IoT space, there are a lot of problems that are very similar to what

we see in the telecoms space in that they need to assure services. For example, in the

smart energy domain, the energy company wants to put sensors in the homes, so as

a service provider I can collect data, take it back to the cloud and remotely optimize

your settings for your thermostat – the idea is to give you the hot water and heating

and lighting that you need, but at the same time reduce your energy bill by 50%. But if

that entire chain is not working, if the service is not assured continuously, you might

end up without hot water.

Then there are the analytics that’s required. Because we’re now collecting data, you

need a brain – the analytics software – to process all the information. For example, if

there is high energy consumption because one of the appliances is consuming more

than what it should, you can propose solutions for that.

The point is that if you want to assure a smart energy service, making sure the

connectivity is working properly is only one aspect. You have to assure that the entire

chain is working, and then put an intelligence layer on top of that: analytics. These are

value added services that CSPs can offer to smart energy companies. I don’t

think Singtel or some other operator is going to become a smart energy service

provider or a healthcare provider or a smart transport provider – they will not be

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everything. But they can leverage platforms such as ours to be a critical managed

services provider to those other verticals and then share part of the benefit with them.

The role of automation

Our customers want to offer a digital experience, but this is incompatible with the

latency introduced by the human factor. If you look at any network operation center

(NOC) or service operations center (SOC), you see people looking at screens, trying to

identify problems and looking into them. But when you have a connected car

experience, which requires minimal latency, the human factor can no longer be in the

middle of the chain.

So we have introduced extreme automation where monitoring of the data, detection

of the problem, the identification of the solution, fixing the problem in the network,

the measurements and so on are done automatically. The idea here is zero-touch

operation and maintenance.

Tomorrow’s NOCs and SOCs for DSPs in the digital world should have no human

presence, or very little. It should all be algorithms, software, cognitive platforms,

robots – it’s not going to be a physical operator sitting there.

Challenges of integrating automation within CSPs’ existing processes

It can be difficult sometimes, because operators are very traditional or very

resistant to the idea of automation. So there are two important things here. One is to

choose a pilot project where you implement it in a specific context – IoT, for example,

because this is a new use case, so people will be a lot more open to it.

The second thing is to drive it from the top. If you talk to the people in the SOC and

you tell them you’re going to automate their job, naturally they’re not going to like

that. But on the management side, people understand it better and they see the

value. So with a pilot project, we can prove that works and prove the value and then

we can roll it out at a larger scale, but this has to go hand-in-hand with a broader

cultural shift or evolution – that needs to happen.

A cultural shift is required

This is a big challenge. When I talk to some of my customers, I talk to the CTO and they

tell us that their biggest challenge is that they’ve been doing this for 15, 20 or 25 years,

doing the same thing and using technology that was made in the 90s, so they’re not

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really at ease at all with the cloud, open software, machine learning, artificial

intelligence, open APIs etc. It is a big problem.

There’s another problem with agility. People are not used to delivering something new

every two weeks. At the same time, when you test and introduce new services in the

telco world, there is still high demand for quality and reliability. This has to be taken

into consideration as well – you have to be disruptive, and you have to be agile, but at

the same time you have to make sure to remember that this is part of an infrastructure

business and it should be able to manage itself.

Analytics and Artificial Intelligence

Right now we’ve started work in machine learning, and the first use case we started

with is fault management – where the system detects if there’s a bad incident, whether

minor or critical.

Ever since fault management systems were invented, their mission has always been

reactive. You look for faults, detect them, and process it very quickly to get to the root

cause of that problem and figure out how to fix it. With machine learning, you can

become predictive, and predict faults before they occur.

Netflix is doing this now. They use machine learning to detect the probability of faults

in certain nodes – maybe they find one that has a high probability of failure, and they

reroute the traffic away from it so as to minimize the chances of their service being

impacted. And they proactively change whatever needs changing.

We apply this to fault management systems to make them proactive and help them

predict what is going to go wrong and then fix it before it can even be impact the

customer.

Machine-learning use cases

You can also apply this to predicting consumption of digital content – what kind of

content people will consume, when and where, so that you are ready for it and you

can provide the right network resources and the right capacity, etc, to respond to

demand for that moment and maximize the efficiency of your capex investments. And

at the same time, it helps you to deliver a better customer experience.

We are part of the 5G Innovation Centre in the UK at the University of Surrey, where

they have been experimenting with machine learning to predict digital media player

consumption. The accuracy was over 90%. That’s a sample of what we can achieve with

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this technology – the ability to predict with such accuracy what people will do. There is

so much more you can do – not only in terms of selling data, but being really proactive

and prescriptive in your approach and be much better prepared for what people want.

Published in Disruptive.Asia on 9th February, 2017. This is an edited version of the original

article

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4. Delivering a personalized digital experience

Written by Sandeep Raina, Product Marketing Director, MYCOM OSI

In order to make the most of a virtualized network, implementing the right

analytics and automation processes is key. This will enable CSPs to better

understand their customer segments and offer highly personalized services.

Analytics & automation experience

In a virtualized environment, automation not only increases efficiency but also quality

and speed of service. Elements of human error and inefficient repetitions are

removed, reducing the time to delivery of new services.

With the advent of NFV, networks continue to move to the cloud which in turn

introduces velocity to the launch of new services. Discerning customers of these new

services, especially of video and high speed data, require automated monitoring,

says Sandeep Raina, director of Product Marketing, MYCOM OSI.

The slightest service degradation can result in customer care becoming inundated by

calls. New services almost always have a high speed, low latency, low jitter

requirement, which, even in the most advanced LTE-A networks, are hard to control

and manage. The better the operator’s control on these slippery KPIs, the more secure

the business.

Analytics, short term and long term, can not only identify the impact of such KPIs on

service performance, but also offer deep insights into customer usage and behavior

patterns. They can also identify the customer’s proclivity to a particular type of app,

device, location or time of day.

However, CSPs may have concerns about a fully analytics-driven automated system.

They might not want to handover all operational control until they understand the

reliability and security offered by such systems. The pragmatic way to introduce

automation is through:

1. Open Loop actions: Recommended corrective actions that can be carried out

through user action and verification

2. Semi-closed loop actions: A combination of open loop and selected

automatic actions whose outcomes are automatically monitored

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3. Closed Loop actions for those processes/activities which are repetitive, time-

consuming and whose outcomes can be automatically monitored and

corrected, in case of unsuitable results

Personalization experience

Although new technologies have varying uptake around the world depending on

region, geography and economy, the collection and correlation of data is gaining equal

importance to build context-specific or personalized services.

Network and customer behavior analytics-based insights provide real-time

understanding of when/where/which services need to be deployed. This enables

contextualized pockets of service roll outs in pertinent network areas, for specific

customers/customer groups.

Operators can introduce gradations of services for each customer group such as

analysing usage patterns and identifying the type, length and quality of videos being

streamed to offer plans and bundles that best suit customer needs.

As an example, if footfall is higher during a particular hour for 18-25 year olds in a

specific location, at a certain hour of the day, the CSP could target it instantly, without

having to wait for information, development and testing of a service over months.

Another example could be streaming a TV programme that is currently popular with

that age group or provide more info about a sporting event.

An analytics dashboard that allows drag and drop of targeted services, based on these

insights, will enable real-time personalization of services. Since service situations can

develop and dissolve fast, such rapid response can enable the contextual

monetization of customer situations.

Agile service experience

Finally, speed is the key enabler for a satisfying digital experience. Customer demand

leaves no time for months and sometimes years of design, test and launch of new

services. Instead, operators want rapid delivery and quick retrieval times to enable

them to deliver services at a quicker pace. With the ever changing technology trends,

it is vital to reduce the risk of CSPs developing services which no longer fit customer

needs before they get to market.

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Operators are now looking at cloud based automation techniques to deliver the

velocity of service as expected. New IT-centric methods of service creation and service

rollout are being considered.

It is not enough to know what the current trends are; operators must predict market

activity at least 6 months in advance. Operators seeking the skills of data scientists and

data modelers, and implementing OSS systems to utilize mathematical prediction

models to map customer behavior, traffic and revenue, are in a strong position to

introduce new services early on.

Published in Vanilla Plus on 5th August, 2016. This is an edited version of the original article

© MYCOM OSI Page 17 of 17

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