Author:
Dean Ramsay,
Principal Analyst
Editor:
Ian Kemp,
Managing Editor
December 2021
inform.tmforum.org
contents
03
the big picture
13
section 3:
the leap to closed-loop
operations
20
section 6:
the future operating model
2
07
section 1:
humble beginnings
16
section 4:
digitally transformed
cloud operations
22
section 7:
make it happen – driving
transformation through
autonomous networks
10
section 2:
starting to join up the dots
18
section 5:
new business opportunities
24
additional
features &
resources
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the big picture
The progressive evolution of Communications Service Providers (CSPs) from traditional 20th century telcos to the
digital operators of the future, is the story of automation. From initially automating single, repetitive manual tasks
to developing a self-aware, self-governing operational model, the journey between these two points is fraught with
challenges. To address those challenges, TM Forum’s member group the Autonomous Networks Project (ANP) came
together in 2019 to define and standardize the industry’s approach to autonomous networks (AN) and to form a
standards developing working group to align and coordinate work in this area. A key piece of this process was to
develop a six-step maturity model for AN, against which a CSP’s progress can be measured. In this report we look at
some real-world evolutional projects and follow the progress of a hypothetical CSP, AN Telecom, as we detail each
step of this maturity model and map some examples of AN evolution against the theory.
B
ecause some of the projects
we have discussed with real
CSPs have not been publicly
announced, we will use AN
Telecom, invented for the purposes
of this report, to summarize
our findings in hypothetical
automation evolution scenarios.
The ANP defines AN and the six
levels of the maturity model in the
following way.
3
What are they?
Autonomous networks are the
key to making the concept of
zero-touch operations a reality.
The ANP aims to define fully
automated, zero-wait, zero-touch,
zero-trouble innovative network/
ICT services. CSPs can use these
services for vertical industries’
users and consumers, supporting
self-configuration, self-healing,
self-optimizing and self-evolving
telecoms network infrastructures
for telecoms internal users. These
users may be spread across
planning, service/marketing,
operations and management. AN
incorporate a simplified network
architecture, autonomous
domains and automated
intelligent business/network
operations for the closed-loop
control of digital business,
offering the best possible
user experience, full lifecycle
operations automation/autonomy
and maximum use of resources.
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the big picture
Simply put, autonomous networks
allow CSPs to:
Take away the repetitive work
that telco staff have performed
for decades
Maturity model
Each level of the maturity model has a set of characteristics describing
the evolutionary stage of the CSP’s journey from fully manual to fully
autonomous operations:
Remove the chances of
human error in these tasks and
processes
Vastly increase the speed at
which tasks and processes can
be performed
Achieve an end-to-end view
and awareness of services,
aligning service-level
information with specific
network operations
Drive AI and machine learning
intelligence into operational
decision-making without the
need for human intervention
Perform self-healing and selfoptimizing improvements as a
part of day-to-day operations
Offer differentiated new service
models and bundles to both
enterprise and consumer
customers
Realize the true potential of
5G and monetize considerable
radio access network (RAN)
investments.
5
4
3
2
1
0
4
Fully autonomous network
The system has closed-loop automation capabilities
across multiple services, multiple domains – including
partners’ domains – and the entire lifecycle.
Highly autonomous network
In a more complicated, cross-domain environment, the
system enables decision-making based on predictive
analysis or active closed-loop management of servicedriven and customer experience-driven networks.
Conditional autonomous network
The system senses real-me environmental changes
and in certain network domains will optimize and
adjust itself to the external environment to enable
intent-based, closed-loop management.
Partial autonomous network
The system enables closed-loop operations
and maintenance for specific units based on AI
modelling under certain external environments.
Assisted operations and maintenance
The system executes a specific, repetitive subtask
based on pre-configuration in order to increase
execution efficiency.
Manual operations and maintenance
The system delivers assisted monitoring
capabilities, but all dynamic tasks must be
executed manually.
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the big picture
13%
4%
83%
48%
13%
52%
4%
Level 0
48%
35%
32%
32%
Level 1
18%
Level 2
36%
41%
Level 3
CSPs’ progress in
implementing automation
14%
41%
23%
Level 4
63%
Level 5
We don’t see a clear path to this level and don’t have a proposed timeline
We see a clear path to get to this level within 4 years
We see a clear path to get to this level within 2 years
We have reached this level
TM Forum 2020
TM Forum’s research shows that
CSPs’ progress along this maturity
model is perhaps not as advanced
as you might think, with none
claiming to have reached Level 3
(see graphic above).
by taking advantage of AI, big
data, cloud computing, IoT and
5G, making services simpler to
consume, and by delivering a “Zero
X” (zero-wait, zero-touch, zerotrouble) experience.
End goal for Level 5
Automation of the enterprise will
enable operators to provide AN
capabilities in one of two ways:
The ultimate goal for AN is
for them to support a set of
innovative business models and
network services that enable
the digitalization of vertical
industries such as smart cities,
manufacturing and autonomous
vehicles. In addition, the aim is for
them to improve the digital life of
consumers through fully automated
and intelligent business, ICT and
network operations. This is done
5
as-a-service – a one-stop, realtime, on-demand, automated,
end-to-end lifecycle of
network/ICT services
as-a-platform, which will
enable ecosystem collaboration
between verticals and network/
ICT service providers.
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the big picture
a vision of autonomous networks
Smart
Industry
Smart City
“Zero X” Experience
• Deliver simplicity
to the users
• Leave the
complexity with
the providers
As a Service
One-stop, real-time,
on-demand,
automated, E2E full
lifecycle network/
ICT services
Smart
Government
Smart xxx...
24/7 Monitoring
Standardization
Backup & Disaster
Recovery
Remote
Help Desk
Online Support
ICT
Procurement
As a Platform
Enablement of
business collaboration
& ecosystem between
verticals & network
ICT service providers
Cloud Services
Vendor
Management
Proactive
Maintenance
Mobile Device
Support
Security
Solutions
Network
Documentation
Zero Wait
Swift
Zero Touch
• Launch
• Delivery
• Care
• Launch
Simplified • Delivery
• Care
Autonomous
Network
Agile
Operations
Zero Trouble
• Business
Self-healing • Services
• Infrastructure
All-inclusive
Services
TM Forum 2020
The graphic above, from
our report Autonomous
networks: empowering digital
transformation for smart societies
and industries, shows this vision of
AN. ICT functions are centralized
and can be selected as modular
components of any conceivable
future operating model. In this
way, CSPs are able to meet
current customer demands, but
also to pivot quickly towards
new, as yet unknown, business
opportunities.
Read this report to understand:
The business and operational
implications of CSPs
implementing a long-term AN
strategy
The typical evolutionary
steps that CSPs are making
today whilst driving increased
automation into their IT
ecosystems
The challenges of
implementing an AN strategy
for CSPs with a complex
legacy of IT systems
Which systems processes are
the typical starting points
for CSPs following an AN
transformation strategy
What AN could mean for
telcos in future.
Read this white paper to find
out more about TM Forum’s
drive to provide a common
understanding of AN:
The key drivers currently
leading CSPs to invest in AN
6
inform.tmforum.org
section 1:
humble beginnings
Level 0
Manual operations and
maintenance. The system delivers
assisted monitoring capabilities,
but all dynamic tasks must be
executed manually.
Level 0 is the state we often
describe as traditional, historical
or legacy telco operations.
At this level, our operator AN
Telecom has a vast array of
legacy operational and business
support systems (OSS/BSS) and
network management IT systems
– some commercial off-the-shelf
(COTS), some developed inhouse and some custom coded
by a third party such as an IT
vendor, a systems integrator or a
management consultancy.
7
Typical characteristics of Level 0:
Offline, full manual operations and maintenance
Expected effects of Level 0 operations:
Awareness, analysis, decision, execution and intent are fully manual.
There is no optimization of staffing cost.
M
any of the systems have
been inherited as part of
mergers and acquisitions to
grow AN Telecom’s geographical
footprint or better compete in its
domestic market. The company has
eight billing systems, 11 different
order management systems and
more than two hundred other
different OSS and BSS systems.
Hardly any of these systems
have a software link between
them, so all transferring of
data is done manually by staff,
copying and pasting information
between records systems and
live operational graphical user
interfaces. Some consolidation
work has been carried out with
data migration and database
federation, but a great deal of
this has been done by a team of
around 30 people who have been
trained in multiple user interfaces
and can support the movement of
information between the systems
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section 1: humble beginnings
for processes like service order
fulfillment. Much of the work they
do is retrospective.
Data errors
The manual action of inputting the
data that allows software systems
to run through processes, such as
progressing a customer service
order or provisioning a new piece of
network, is highly error prone. Many
of the legacy systems have free type
fields, which allow users to input
any value. If this value is in a format
that the software doesn’t recognize,
it will derail any automated process
within the system until a user can
double-check the data.
In the best-case scenario, this
process stalls and sits in a redundant
state for hours or days. In a worstcase scenario, this process appears
to have continued but has stalled
and disappeared from sight. This
is the cause of order fallout, which
costs AN Telecom millions of dollars
a year to rectify.
Assisted monitoring
At this level AN Telecom’s network
operations team has a small
amount of simple automation built
into the network management
systems. That automation
helps run processes like batch
provisioning of consecutive circuits
or commissioning new backbone
network sections copied from
existing routes and the same
terminating equipment. The rest
of day-to-day operations is done
manually by a large group of highly
knowledgeable staff. Employing
this operations team makes up
a large portion of the company’s
quarterly opex bill.
One of the first areas to shift from
passive to proactive IT is network
and service assurance systems
such as performance monitoring
and fault management, because
they are mission critical in meeting
customer SLAs.
8
drawings stored and shared
locally on an exchange server.
The manual action
of inputting the data
that allows software
systems to run
through processes,
such as progressing
a customer service
order or provisioning
a new piece of
network, is highly
error prone.
Swivel-chair operations
Having many systems spanning
both network and service/
customer operations, each with
its own esoteric graphical user
interface, requires a large number
of staff that are familiar with these
applications. In Level 0, being able
to progress a service order may
require an operative to retrieve
information from many systems
and provide the correct set of
data to their colleagues at the
next stage of the process. Failure
to get these details right will
result in delays which then need
manual remedial action. Training
and retaining these staff is an
expensive process, because they
become subject matter experts
in a very specific discipline and
essential to the business.
Static RAN operations
The planning, deployment,
management and maintenance
of AN Telecom’s radio access
network has been done in a
similar way to a landline network
in the 1980s, with paper records
replaced with spreadsheets and
Load balancing and cell neighbor
relations are done by the
engineering team on site with
mobile test and measurement kits.
Cells are set to run, and then not
adjusted unless the immediate cell
mesh is altered – for example, by the
addition of a new macro cell nearby.
Weak links
At Level 0, AN Telecom has
very few direct links between
the overarching strategy of the
business and the senior leadership
team and what happens in
operations. Spending in operations
is driven by retrospective action
and the need to keep up with
orders coming in from sales, rather
than by any long-term plan to
optimize architectures, procedures
and spending.
Capacity planning
A large percentage of AN
Telecom’s capex budget is spent
on physical infrastructure to build
sufficient capacity overhead into
its network, which should exceed
the predicted needs of sales in the
following quarter.
Capacity overhead planning is
the principle of building and
commissioning network that is
unused until needed, so it has a
large associated capex and opex
impact, with no revenue until it
goes live. Accuracy in capacity
planning has been an expenditure
issue for many years: add too much
overhead and the total cost of
ownership of the network begins to
spiral out of control; add too little,
and new service orders can’t be
met without long lead times, which
may result in losing business to
competitors.
OSS interoperability
AN Telecom’s many operational
support systems have some custom
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section 1: humble beginnings
code adaptors at the interfaces,
through which some data
transfer can happen. But a lack of
standardization in the development
of these systems interfaces means
that a significant percentage of
data transfers contain errors which
are unrecognizable to the receiving
application. AN Telecom just
accepts this as an eccentricity of
the architecture and places more
staff on hand to deal with manually
pushing the processes through.
Data migration projects
AN Telecom has assessed the
possibility of transferring all its
data from tens of systems with
hundreds of databases into a single
inventory for physical assets and
logical connections. Data quality
issues mean that an estimated 30%
could be transferred automatically
and the rest would need a team
of data analysts to manually load
the information. The project is
predicted to take three years and
cost tens of millions of dollars.
Pockets of automation
For many operators in developed
economies, Level 0 operations
would have been familiar in the
9
1980s. No operators of any notable
size or age that we studied in
2021 are still at Level 0, although
some start-up interconnect
providers and niche B2B CSPs
are able to quickly and cheaply
run manual, localized operations
with a small team. However, this
model becomes untenable very
quickly as the company scales up
and systems are procured to drive
some automation.
In the late 1980s US operator MCI
was beginning its transformational
journey by writing custom code
to connect its in-house OSS
inventory system F&E (facilities and
equipment) with live status reports
from the network management
system. Links were also being
coded to connect F&E to various
billing systems, so that when a
new customer circuit went live a
status update was provided by a
provisioning engineer. This would
transfer the service details in a file
into the BSS where it would sit in
a job queue to be addressed by a
worker in the billing department.
This type of automation is still just
removing a small step in a very
manual process, but if the data
quality allowed the automated step
For many operators
in developed
economies, Level 0
operations would
have been familiar
in the 1980s. No
operators of any
notable size or age
that we studied in
2021 are still at
Level 0.
to take place it had an incremental
improvement on the speed and
reliability of the overall service
operations function. It took MCI
several years to make this first
step from Level 0 to Level 1, with a
great deal of remedial action on the
systems interfaces and code.
In the next section we look at the
difficulties with these new pockets
of automation.
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section 2:
starting to join up the dots
Level 1
Typical characteristics of Level 1:
Online, assisted execution.
Assisted operations and
maintenance. The system executes
a specific, repetitive subtask based
on pre-configuration in order to
increase efficiency.
Expected effects of Level 1 operations:
Awareness and execution are assisted by the system. Actions of
awareness, execution and intent/experience can be online, recorded
and traced. Part of staff time can be saved and more can be focused
on analysis and decision-making.
In Level 1, AN Telecom has
invested in the automation
of basic repetitive tasks. Its
automation strategy has been
based on a low hanging fruit
principle, automating the simplest
processes that will return the most
benefits in the short term.
10
T
he processes and subtasks
that AN Telecom is
addressing in this first
wave of automation are based
within specific operational
functions – for example, some
software scripts are developed to
automate provisioning of circuit
channels associated with predefined ports on transmission
equipment. This reduces the total
time that the operations and
engineering team take to activate
a service at the end of the service
fulfillment process.
Data quality becomes an issue
in automating this process. If
the modelled representations of
the network in the provisioning
systems do not match real-world
allocations, an engineer must be
sent to the site to audit the physical
cabling and update the system.
This first wave of automation
triggers many large-scale audit
programs as it becomes obvious
inform.tmforum.org
section 2: starting to join up the dots
key drivers for autonomous networks
Improving customer experience
Delivering new services
Efficiency gains/lowering costs
Faster time to market
Zero-touch partnering (e.g., with
hyperscalers or enterprises)
0%
20%
■ Very important
40%
■ Moderately important
60%
80%
100%
■ Not as important
TM Forum, 2021
that the data quality in the
records of the physical network
topology is poor, hindering
attempts to automate processes.
Robotic automation
Many communications service
providers (CSPs) went through
the scenario that AN Telecom
is experiencing in the 1990s
and 2000s, but in present-day
operations the mass automation
of high-frequency, manual,
repetitive, rules-based processes
can be done with robotic process
automation (RPA). RPA is a
low-code, low-cost option for
CSPs to automate high-volume
manual processes, delivering cost
savings, efficiency, accuracy and
transparency. RPA is well suited
to quick wins and straightforward
use cases – such as service order
provisioning, service assurance
and BSS checks – and in a telco
with many fragmented OSS/
BSS and network management
systems this quick win can
translate instantly into improved
operational efficiency.
11
But in the long term, RPA is
not an holistic, forward-looking
operational approach and is
more of a way to remove manual
processes in the short term. As
George Glass, CTO of TM Forum,
says in our recent report on
process automation: “All you’re
doing is treating the symptoms
and not fixing the cause of the
problem. Frequently you end up
with process fragments and not a
standard set of processes.”
Instead CSPs should look towards
the TM Forum Open Digital
Architecture (ODA), which is
a blueprint for modular, cloudbased, open digital platforms that
can be orchestrated using AI.
Read these reports for more
information on AN:
August 2021 | www.tmforum.org
Author: Ed Finegold, Contributing Analyst
Editor: Joanne Taaffe, Editor in Chief of Inform
CX as a key metric
TM Forum’s 2021 survey on
AN asked our respondents
to identify the key drivers for
implementation strategies (see
chart above). While many of
the popular responses were
about new services, operational
efficiency and faster time to
market, the top answer was
improving customer experience
(CX). This reveals something of
a change in thinking about what
CX is, how we measure it and
how we can positively influence
it and the nature of AN. CSPs
are not just thinking about AN
as a network advancement, but
as an overarching methodology
to revolutionize service-centric
operations and achieve vastly
more diverse business goals.
CX is a metric that can be
influenced from any point in that
methodology, and incremental
improvements all add to a better
way to provide services.
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section 2: starting to join up the dots
The wider picture
In Level 1 AN Telecom is thinking
about its wider approach to
processes like order to activation.
Many different legacy processes
are in place in parallel, making the
task of automating specific tasks or
functions difficult. The company is
looking at how the OSS processes
in service ordering, fulfillment,
activation and assurance could all
ideally work together as one entity,
while retaining some functional
separation. This more holistic
approach to service management
would have a positive domino
effect on the network systems and
processes below when trying to
drive more automation into the
whole system.
In a recent conversation at TM
Forum’s Digital Transformation
World Series 2021, Telia’s Head of
Products and Production Services,
12
Ida La Spisa, explained that this
problem is still commonplace. She
explained that as recently as two
years ago Telia had at least “six
different ways of doing order to
activation” and “proposing products
to customers”, with six or more
order-to-activation stacks across
B2C and B2B markets in different
countries. These were targeted for
transformation, which also entailed
rationalizing and unifying product
and customer data and processes
across all six countries.
While transforming order-toactivate processes, La Spisa said
Telia has also made sure to “fully
take into account service assurance
across the countries we operate”
and to “clean up assurance aspects,
rather than seeing it as an appendix
to our processes”. She explained
that Telia fully automated both its
customer SLAs and “the internal
operations levels we need to assure
those services for our customers”.
Telia also changed the ways it
worked, embracing Agile and
DevOps across the company.
The smaller releases allowed
for a faster pace. Although
that has introduced some new
challenges, La Spisa admitted
it “gives the ability to adjust
deliveries continuously”, with
new production releases every
two weeks. This also extends to
Telia’s vendors, La Spisa said,
with which it conducts common
governance and from which it
expects buy-in throughout the
transformation process.
In the next section we look
at the gathering pace of the
transformational journey as we
look at the first closed-loop
operations stage and the benefits
of DevOps methodologies.
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section 3:
the leap to closed-loop
operations
Level 2
Typical characteristics of Level 2:
Static rule/policy-based automation.
Partial autonomous network.
The system enables closed-loop
operations and maintenance for
specific units based on AI modelling
under certain external environments.
Expected effects of Level 2 operations:
Execution is automated. Some awareness and analysis functions can be
accomplished for certain scenarios based on static (human predefined)
rules/policies. Part of staff time can be moved away from simple and
repetitive work on data collection, pre-processing and analysis.
Level 2 is the state in which
many communications service
providers (CSPs) currently find
themselves worldwide. This
point on the transformational
journey means that an
operator has automated some
significant portions of their
network operations and has
process automation workflows
in place through sections of
the operational and business
support systems (OSS/BSS) in
service operations.
13
A
t this point, our fictional
CSP AN Telecom is focused
on working with several
systems integrators and its IT
vendor partners to link together
some of the business processes
that it relies on for streamlining
ordering and fulfillment.
As it is aware of the potential
benefits of automation across the
whole structure, work is going
on in most parts of the company
to automate existing manual
processes. In the network, AN
Telecom is starting to work more
extensively with its IT vendors
to insist on more automated
provisioning for orders which involve
new network assets or changes
to the existing configuration. This
should be for both physical network
components such as transmission
equipment and cabling and for the
logical allocations in the network
management and inventory
software systems.
inform.tmforum.org
section 3: the leap to closed-loop operations
systems & processes most in need of automation
57%
Service management & assurance
43%
Network planning & design
35%
Network build-out
30%
Customer experience management
29%
The fulfillment process
11%
Partner management
0%
10%
20%
30%
40%
50%
60%
TM Forum, 2021
Automation priorities
TM Forum’s 2021 survey of which
systems and processes are still
most in need of automation
shows that service management
and assurance is now the top
priority followed by some more
network-centric categories (see
chart above). This is telling of the
current trend to focus on servicelevel systems and processes in the
deployment of 5G.
apparent that monetizing new
5G SA service models is only
possible with extremely high levels
of automation in the BSS and
OSS, driving towards zero-touch
operations. It is also apparent
that this is the area that has been
neglected in terms of attention and
investment, so many initiatives are
underway to redress the balance.
that trend reflected in the staffing
patterns of CSPs. The balance of the
work being carried out within that
workforce, however, is changing as
fewer operations staff are needed to
fight fires and more IT-centric staff
are needed to operate systems and
work on incremental improvements
in the continuous integration /
continuous deployment (CI/CD)
DevOps model.
Impact on workforce
At Level 2, CSPs start to feel this
influence of increased automation
on their workforce as network
operations personnel start to
shift their roles from primary
troubleshooters to monitoring and
handling exceptions. In our survey,
47% of respondents said they
consider this scenario highly likely
as shown in the chart below.
Automation inevitably has an
impact on the workforce of any
business as manual tasks carried
out by people are reduced and
replaced with IT. But in recent years
the thought that automation will
put people out of work has abated
somewhat and we are not seeing
CSPs are keen to align their BSS
with the new technologies and
capabilities that have been driven
into the network over the past
few years, under the banner of 5G,
virtualized networks and the telco
cloud. With standalone 5G (SA 5G)
on the near horizon it is becoming
changing roles in operations
Roles will change from operations to
monitoring & handling exceptions
47%
Roles will shift from operations to
designing, training & explaining
34%
There will be little change
32%
Roles will be eliminated
11%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
TM Forum, 2021
14
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section 3: the leap to closed-loop operations
Accelerating change
Undertaking
a large-scale
DevOps program
requires significant
transformation
over a multi-year
period, and for
many CSPs it has
been difficult to
make a compelling
business case.
A large impact on AN evolution
and on workforces has been
the introduction of DevOps
methodologies into telco
operations. There are several
challenges for CSPs when
making this transition, however,
including a significant debt of
legacy technology, an historically
rigid divide between IT and
network teams, and the fact that
most software is procured from
vendors rather than developed inhouse. CSPs have therefore been
relatively slow to adopt DevOps.
To date, most of their efforts
have focused on customer-facing
digital initiatives, which tend to
be relatively standalone and built
on a cloud-native architecture
from the outset.
drivers for DevOps within CSPs
One example of a business that
has benefitted from a DevOps
approach is Softbank Corp.
Working with technology vendor
Red Hat, Softbank developed
a global IT platform strategy
supported by Agile and DevOps
approaches. Beginning with
an artificial intelligence (AI)
project as a pilot, Softbank has
now expanded DevOps to more
than 50% of its IT projects and
seen significant increases in the
cadence of its software releases.
Undertaking a large-scale DevOps
program requires significant
transformation over a multiyear period, and for many CSPs
it has been difficult to make a
compelling business case to
embark on a broad initiative. The
exception has been in some of the
tier-1 CSPs, which are deploying
software-defined networks on
cloud-based platforms and see
DevOps as a key element of
delivery at scale.
Yet as 5G, edge and other future
networks evolve, it is inevitable
that DevOps principles will be
an essential part of the rollout.
CSPs will therefore benefit from
initiating or growing their use
of DevOps now, in conjunction
with cloud and network
transformation, rather than seeing
them as separate entities.
DevOps
In the next section we look at the
evolution towards large amounts
of automation and the use of the
cloud across service and network
operations.
Cloud-based
b
architectures
Digital
t l
transformation
Software-defined
networks
TM Forum, 2021
15
inform.tmforum.org
section 4:
digitally transformed
cloud operations
Level 3
Conditional autonomous network.
The system senses real-me
environmental changes and in certain
network domains will optimize
and adjust itself to the external
environment to enable intent-based,
closed-loop management.
In Level 3, communications service
providers (CSPs) have likely
invested hundreds of millions of
dollars on IT, systems integration
and management consultancy
to streamline their operations
enough to begin aligning tightly
with business intent and have an
automatically reactive network
and service operations ecosystem.
This is the point at which the core
concepts of digital transformation
come into play and start to make
a significant impact on CSPs’ cost
structure, operational efficiency,
agility and responsiveness.
16
Typical characteristics of Level 3:
Dynamic rule/policy-based automation.
Expected effects of Level 3 operations:
Awareness, execution and most analysis are automated. Decoupled
common rules/policies/AI models which can be dynamically updated.
Some automatic decision-making can be achieved under human
predefined rules/policies.
P
ushing into Level 3, CSPs are
relying on the efficiencies,
agility and scalability of the
cloud to add more dynamic IT
capabilities to their operations.
Software in OSS, BSS and network
management and orchestration
are developed with the cloud in
mind. As such their microservicebased open architectures, modular
format and open API frameworks
allow them to interoperate across
multiple domains within the
operational framework.
Data passed between these
systems, both within the
operator and outside to a partner
ecosystem or customer’s IT
infrastructure, become the life
blood of 21st century telecoms
operations. There is, however,
some way to go on the journey
to cloud-native IT systems and
data storage, as shown by our
recent report Cloud migration:
Assessing strategies (see pie chart
on page 17).
inform.tmforum.org
section 4: digitally transformed cloud operations
percentage of IT
workloads CSPs have
migrated to public cloud
1%
7%
15%
40%
An open architecture with open
APIs is essential to orchestrating
industry vertical applications and
underlying network capability in
ways that result in a compelling,
differentiated and quality customer
experience. Moreover, service
providers need to deliver such
applications and services from
higher up in the value chain to avoid
missing out on the lion’s share of
revenue from industry verticals.
these stores and systems is being
groomed to meet data quality
standards of accuracy, validity,
reliability, timeliness, relevance,
completeness and compliance
with customer/partner regulations
and statutory obligations, as
established by an information or
data quality policy.
The start of zero-touch
0-10%
Data management
10%-25%
At this point AN Telecom is
becoming more involved in TM
Forum’s Open Digital Architecture
and the Architecture Toolkit
to refine its information model
framework, build standardized
architectures and align its
business process frameworks.
The company is paying specific
attention to how it uses data
internally and how it can expose
operational data to its partners
and customers in a secure and
open manner.
In Level 3, AN Telecom has the
beginnings of what we consider to
be zero-touch service operations.
A customer can order a service
package or element from the
online self-service portal (or any
other channel of their choosing),
which is enabled by cloud-native
omnichannel BSS. The order
management system can then
trigger an automated workflow
down through the OSS by using a
centralized product/service catalog
as a single data source to fulfill
the service. Additional workflows
are triggered by the service
orchestrator, which follows the
service fulfillment process through
checks and activation and will tell
the network orchestrator what is
required in network resources to
fulfill the order.
Information is being gathered
from all systems and stored in
a centralized data repository –
usually a dictionary or metadata
library – as an information library.
All of AN Telecom’s systems
will have the capability to store
logs and pertinent information
within an analyzable repository.
Information classified as
personally identifiable will be
managed through the enterprise
anonymization rules prior to being
committed to any repository.
This is where, at Level 3, manual
involvement from network
operations teams is significantly
reduced. The process of completing
the order, activating the service,
and triggering instantiations of BSS
elements like service assurance
and rating/charging/billing/partner
settlements in accordance with the
customer’s SLA, are now carried
out by automated workflows. This
whole order-to-cash process is not
yet zero-touch, but is showing signs
of large elements of automation.
Analytical systems are being used
to extract required data from
the repository and present it to
the user in the most appropriate
way. Information moving around
In the next section we look at how
the highly autonomous networks
of Level 4 can drive new business
opportunities for CSPs and the
role that AI and machine learning
will play in AN.
37%
25%-50%
50%-75%
More than 75%
TM Forum, 2021
Orchestration needs
Our fictional CSP AN Telecom
is investing in orchestrationbased software for both network
and service operations. The
company has developed a service
orchestration strategy which
will, in the first instance, enable
it to add intelligent overarching
management and control to its own
internal operations, and ultimately
to orchestrate the operational
requirements of partners in new
service model value chains.
Increasingly, service fulfillment and
assurance are being more tightly
integrated and becoming part of
the larger service and network
orchestration process – or dynamic
orchestration – ensuring the agreed
intent of the customer service is
maintained over its lifecycle. As
the network evolves with 5G and
becomes cloud-native or at least
interconnects with cloud-native
networks, and services become
17
more ecosystem-centric, fulfillment
must have the ability to orchestrate
across different domains and
communicate with multi-party
systems.
inform.tmforum.org
section 5:
new business
opportunities
Level 4
Highly autonomous network. In a
more complicated, cross-domain
environment, the system enables
decision-making based on predictive
analysis or active closed-loop
management of service-driven and
customer experience-driven networks.
Highly autonomous network and
service operations have been the
goal for many CSPs for the past
two decades. Rapidly evolving
computing and IT development
have driven the industry towards
this being a reality rather than
a pipe dream. One key feature
of Level 4 is the proactive or
predictive nature of the software
and systems taking on a more
holistic nature as the crossdomain integration intensifies.
18
Typical characteristics of Level 4:
AI-assisted automation capable of continuous learning and rapid evolution.
Expected effects of Level 4 operations:
Awareness, analysis, decision and execution are automated. Intent/
experience-driven closed-loop control can be accomplished for certain
scenarios under human supervision in emergency situations. Most of the
staff time can focus on expert experience, AI model management and
novel or unsupported scenarios.
I
n Level 4, our fictional operator
AN Telecom is investing heavily
in cloud-native solutions
throughout its operations. It is
driving initiatives to connect AI
and machine learning intelligence
to provide an end-to-end view of
the operational architecture. This
provides much more interlinked
decision-making at all levels and
tightly aligns customer-facing
business decisions with network
disciplines to optimize planning
and runtime functions.
AI is the best option
It is becoming apparent that
AI is the best option for telcos
processing extremely large data
sets that combine heterogeneous
data from multiple sources, and
where multi-domain or crossfunctional correlation is required.
AN use cases are driving interest
in the concept of AIOps, including
those instances where AI is not part
of the automation architecture.
inform.tmforum.org
section 5: new business opportunities
Platform-based IT
If operators
are prioritizing
autonomous
functions…for select
use cases, you end
up with different
operators, running
different types
of business, for
different groups of
customers, under
different regulation
guidelines.”
Given the complex and often
disparate state of most operations
environments, CSPs can use
basic criteria for automation to
determine where to start. Most
of the hard work is practical and
detail oriented, but AI/machine
learning at Level 4 on our maturity
model will begin to perform a
great deal of the heavy lifting
when it comes to data crunching
and deriving actional insights
from extremely large and dense
data sets.
A recent TM Forum Catalyst
proof of concept project called
AI empowers 5G intelligent
operations sought to demonstrate
how CSPs could achieve AN
Level 4 by 2025 and specifies the
objectives and approaches.
19
A platform-based IT architecture
enables the concepts and thinking
of modern software architectures
– such as service-oriented
architecture, modular software
components, software contracts
and microservices – to evolve and
develop OSS/BSS IT solutions.
Platforms can set a governance
boundary around a set of current
TM Forum-defined Open Digital
Architecture functionalities such
that they can only be accessed
via defined Open APIs. In this
context the platform model
decouples the platform’s users
from its architects, which leads
to the modularity, isolation and
reusability that are prerequisites
for agile solutions. This approach
also enables the internal platform
implementation to evolve without
changing the exposed platform
capabilities, which enables internal
IT rationalization, improvement in
agility and reduction of capex and
opex costs without affecting the
platform consumers.
Collaboration is key
In a 2020 TM Forum Digital
Transformation World Series event
presentation, Dr. Che Haiping, Chief
Digital Transformation Officer
at Huawei, identified the need
for industry partners to develop
“deeper and broader collaboration
to push the autonomous network
initiative forward” by defining a
reference architecture using a
common technology approach and
unified language.
Lingli Deng, Lead Researcher
and Technical Manager at China
Mobile, also warned that for any
operator to achieve Level 4 or
even Level 5 network autonomy,
the industry needs to address
a serious and all-too-familiar
roadblock: fragmentation. Deng
said progress from Level 0 to
Level 5 will likely happen in two
stages: first, improving functional
requirements for specific, highpriority use cases; second, scaling
those functional requirements
to cover all remaining scenarios.
She said the problem is that the
activities in stage one are leading
to fragmentation, which makes
it difficult to scale autonomous
functionality across all scenarios.
“If operators are prioritizing
autonomous functions…for
select use cases, you end up
with different operators, running
different types of business, for
different groups of customers,
under different regulation
guidelines,” she explained.
Lingli said the industry needs
an open collaboration platform
to “build, test and certify
a common, case-agnostic,
functional architecture with
open implementation and open
standards”. Such an architecture,
she added, “could be used to
identify common requirements
from different use cases that can
be applied to different operator
scenarios”. It is this fragmented
approach that we see in levels 3
and 4 that hold CSPs back from
progressing to Level 5.
In the next section we look at the
final stage of the currently defined
AN journey, into fully autonomous
operations.
inform.tmforum.org
section 6:
the future operating
model
Level 5
Fully autonomous network. The
system possesses closed-loop
automation capabilities across
multiple services, multiple domains
(including partners’ domains) and
the entire lifecycle.
Typical characteristics of Level 5:
Auto-evolution, full autonomy, all scenarios.
Expected effects of Level 5 operations:
Awareness, analysis, decision, execution and intent/experience are
autonomous. The whole autonomy mechanisms, including expert
experience and AI model management, can be auto-evolved for all
scenarios. Staff time is only needed to generate intent and monitor the
progress and status.
At Level 5 AN Telecom is at the pinnacle of our story outlining the journey
to autonomous network operations. The company’s cloud-based, fully
automated operational platform is now capable of entirely zero-touch
operations. An order can be placed in the customer’s self-service portal,
triggering intelligent automated workflows which will percolate down
through AI-powered service operations software in operational and
business support systems (OSS/BSS). From there service activation
processes ensure that the software-defined network has all the specific
information it needs to provide personalized service characteristics, and
ultimately trigger revenue management arrangements and customer
notifications. AN Telecom is using the TM Forum Autonomous Networks
Toolkit to fine-tune its operational configurations.
20
A
s we have covered many
of the core concepts of
automation on the journey
to Level 5, it is worth examining
the profound impact on telecoms
if the operational platform were
truly capable of managing its
own evolution from this point
onwards. The heavy native use of
AI and machine learning that is
ingrained in every aspect of the
company is also joined together
in an overarching master control,
inform.tmforum.org
section 6: the future operating model
The heavy native
use of AI and
machine learning
that is ingrained in
every aspect of the
company is joined
together in an
overarching
master control.
21
which can imagine highly complex
scenarios involving both business
challenges and operational
capabilities, without these two
concepts being approached in
isolation. As such, it is possible
to deliver continual selfoptimization towards goals set by
the operations team. Actionable
advice can also be pushed
from the live AN into DevOps
processes to continually improve
the constant development cycles
of IT systems and architectures.
In the next section we look at the
key changes CSPs are making
to drive their transformational
strategies using AN.
For more whitepapers, guides
and videos on AN take a look
at TM Forum’s Autonomous
Networks Project.
inform.tmforum.org
section 7:
make it happen – driving
transformation through
autonomous networks
The journey we have mapped out is a complex proposition for any operator and will be different for every
company. Our research has shown that there are several common factors essential for a successful autonomous
networks (AN) strategy, and they align closely with the broader evolutional changes taking place within
communications service providers (CSPs) in the TM Forum member community. Here we summarize the key
changes that CSPs are making to drive their transformational strategies using AN:
Move to the cloud
End-to-end thinking
Data management
The use of the cloud, both for
a new medium in which to
move essential data around
operational frameworks and
to move to cloud-native IT
systems, is the basis for any longterm AN strategy. Maximizing
elasticity, agility, scalability, and
fundamentally altering operational
cost structures, are essential
characteristics of the evolved
CSP’s infrastructure.
Making the leap from traditional
manual telco operations to AN
requires CSPs to abandon the
idea of islands of functionality
and adopt a more end-to-end
approach. Customer-facing BSS
systems, and systems down in the
depths of the network, need to
have an awareness of the holistic
goal needed to provide services.
We are seeing that an overarching
approach to data governance and
management is very beneficial
for many CSPs in Level 1 of their
AN journey. The old approach
of trying to harmonize disparate
data types by using adaptors
at the systems interfaces has
shortcomings that can lead to
repetitive failures in automation.
Standards-based IT systems are
combating these problems for
large multivendor environments.
22
inform.tmforum.org
section 7: make it happen
Automate everything
Adopt a wide platform
Trends like robotic process
automation (RPA) are currently
accelerating the transformational
journey for many CSPs as even
the smallest repetitive task is
automated, shaving off opex and
speeding up processes.
The concept of platform that
AN enables should not just
be seen as a concept within
CSP operations. The new
business value chains for digital
services and models like IoT
will require the operator to
have automated, orchestrated
workflows interacting across
other companies’ IT domains.
Open APIs and common software
frameworks are required to make
the platform model successful.
Protect your workforce
Use technology cycles as
a circuit breaker
The first few years of the cloud
era of telco operations will be
typified by a shortage of the
right kind of skills in the global
workforce. As CSPs are training
and building teams of IT-focused
people, it is in their interests to
retain this pool of people and
acquire more where possible.
23
Refine orchestration
strategies
Several CSPs with service
orchestration strategies in
their OSS/BSS told us that the
hierarchical proliferation of
orchestrators they currently have
is causing problems for end-toend service operations. They are
refining these orchestrator stacks
in readiness to supply network
slices in standalone 5G. Simplicity
is apparently the key.
The evolution to 5G has
shown that the introduction
of fundamentally different
technology, such as softwaredefined networks, allows CSPs to
eliminate classic telco problems,
as long as they don’t simply
replicate old processes and
business models. Partnering
with external IT specialists is
becoming more commonplace
for CSPs looking at how digital
natives and companies like
hyperscalers and digital retailers
construct their IT stables.
inform.tmforum.org
additional features
& resources
25
| Huawei iMETHOD Framework Realizes Operations Transformation for CSPs
30
| BMC: Evolving Service Assurance to Support Future Autonomous Networks
33
| TM Forum Open Digital Framework
34
| TM Forum research reports
35
| Meet the Research & Media team
24
inform.tmforum.org
SPONSORED FEATURE
Huawei iMETHOD
Framework Realizes Operations
Transformation for CSPs
SHIFT
to Service-centric
transformation
5G network deployment is on
the rise. Coverage density of 5G
compared to 4G means 10x more
connected devices per square
kilometer of network, compared
to 4G. The challenge here is that
the shorter range of 5G means
more network sites to operate and
maintain. As more devices get
connected and become clouddependent, hardware and software
decoupling introduce more
complexity to manage, which leads
to an increasingly complex network
operations environment. In such
a landscape, manual and legacy
approaches to Operations can no
more scale.
With 5G enabling multitudes
of industries to embrace digital
transformation, the need for stricter
SLAs for end-to-end services has
become pivotal to business success.
Deterministic networks that can be
programmed to meet stricter SLA
reliability requirements demand
real-time and proactive assurance.
It is clear that traditional operations
environments lack adequate
network quality measure rules, thus
25
making it difficult to evaluate and
maintain network conditions to
support consistent business SLAs.
The shift to a Service-centric
approach transforms the isolated
and passive assurance model built
on manual fault and performance
management. It ushers in a
model that facilitates sharing
operations information, accurately
processing floods of alarms and
data, and effectively identifying
and processing service impact intime. This presents an opportunity
to meet the requirements of
deterministic connectivity business.
In a deterministic network
assurance model of operations,
the complexity related to
network scale, network structure,
service types, and network SLA
requirements are managed with
a new framework that embodies
digital and intelligent automation.
ADOPT
a Digital intelligent
Operations
transformation
Framework
(CSP) into Digital Service
Providers isn’t an option anymore.
B2B models will drive new and
emergent business opportunities
for Service Providers to mine.
Innovation, organization culture and
process transformation will play key
roles to enable adoption of digital
and intelligent Operations. This
evolution will transform the humancentred Operations paradigm
to one that brings man-machine
collaboration to the Operations
workforce.
A traditional Operations approach
is persistently fraught with “firefighting” and continued pressure
to manage cost efficiency. In an
era of growing industrialization,
new network technologies,
better customer experience and
SLA guarantees, an operations
transformation framework like
iMETHOD is essential to deliver new
B2B models, and assure service
revenues.
Digital transformation of
Communications Service Providers
inform.tmforum.org
SPONSORED FEATURE
iMETHOD:
A best-practice digital
Operations transformation
Framework, defines key
features for next generation
service-centric Operations.
The iMETHOD Framework with the
Six Key features of NG Operations
iMETHOD, an alias for intelligence
and six key features of NG
Operations, defines an intelligent
approach needed to capitalize on
the value of digital technologies and
growth of trends beyond traditional
connectivity business. It unlocks
effective Operations delivery and
operationalizes the next generation
of Service-centric Operations.
Huawei’s iMETHOD framework can
enable service provider Operations
teams to acquire key capabilities
that leverage data and AI to support
digital business agility, operations
intelligence, and achieve higher
levels of Operations automation.
The following section defines what
the iMETHOD acronym means to a
service provider.
intelligent
Integrate data and AI platforms
into Operations domains to
facilitate lowering the threshold
for open use of AI in Operations
activities. Data and AI platforms
will facilitate domain AI algorithms
and models, telecom domain
sample and theme data, advanced
data analysis services and data
openness.
Models & Algorithms of
Telecom (MAT)
Leverage all-domain (RAN,
Core, Transmission etc.) telecom
knowledge and Operations
experience (planning, maintenance,
optimization, and operation)
to formulate, and accumulate,
telecom-specific models and
algorithms (e.g. algorithms for
forecasting, prevention, and root
cause analysis).
Ecosystem Enabler (EE)
Facilitate ecosystem construction
by exposing ‘support service
capabilities’, ‘telecom data assets’
and ‘openness’ through adoption
of APIs that enable integration
on east-west and north-south
interfaces. This will enable
developer ecosystems to flourish.
Telecom Knowledge
Platform (TKP)
Build Telecom knowledge Platforms
that intelligently manage explicit
domain-knowledge and provide
knowledge services (leveraging
knowledge graph technologies).
In addition, TKP can intelligently
iMETHOD’s Six Key Enabling Features
Deterministic Network Assurance (DNA)
Challenge 1: Real-time, connection-level SLA monitoring,
prediction, and prevention
A) 2B determinative network - connection-level SLA
Challenge 2: Lower-threshold, trustworthy Devops
B) 5G service indicator system
Challenge 3: Integrated Framework and integrated Assets
C) Reliability model of complex system
Challenge 4: Assets and Reusability in the Telecom Domain
Challenge 5: AI-enabled Operations Efficiency Doubles
Ecosystem Enabler (EE)
Hyper-Automation (HA)
A) Developer ecosystem: platform and enablement
A) RPA/RBA
B) Asset Capability Exposure in the Telecom Domain
B) iBPMS
C) Integrated Assets - East-West/North-South
C) Causal inference
Data & AI
Model & Algorithm of Telecom (MAT)
A) All-domain data model (Full network domain and
full life cycle (providing, construction, maintenance,
optimisation, and operation)
B) Algorithms and models in the telecom domain
(prediction, prevention, and root cause)
One Trustworthy DevOps (OTD)
A) Low threshold (No/Low Code)
B) Trusted and reliable
C) One-stop shop
Telecom Knowledge Platform (TKP)
A) Native Telecom knowledge graph (KG-Native)
B) Knowledge recovery
26
inform.tmforum.org
SPONSORED FEATURE
AUTIN solution capabilities and iMETHOD’s key features
Key Capabilities
Intelligent
event
management
AI/ML
Cloud Core
Intelligent
Operations
ToB/toH
Intelligent
Operations
Smart Fault
management
Smart
Performance
management
Data and
Topology
Data & AI
4
4
4
4
4
4
4
MAT
4
4
4
4
4
4
4
4
EE
4
4
TKP
4
4
4
4
4
4
4
HA
4
4
4
4
OTD
4
DNA
4
4
4
4
Algorithms in the telecoms domain
Ecosystem establishment
Telecommunications knowledge
Hyperautomation
Trusted Devops
determinative network assurance
extract knowledge from routine
Operations data and continuously
accumulate domain-knowledge to
increase smartness. This is key to
achieve higher levels of intelligence
and automation.
Hyperautomation (HA)
Embrace hyperautomation (HA)
approaches to combine automation
technology. Prior to HA, robotic
process automation (RPA) and
iBPM were used independently. By
adopting an HA approach, RPA,
iBPM, AI/ML and other automation
technologies can be combined to
scale Operations automation and
capitalize on data to improve cost
savings, boost productivity and
attain efficiency gains.
One Trustworthy DevOps (OTD)
Orchestrate trust in the adoption
of DevOps by employing the
use of ‘Low Code/No Code’
platforms in order to successfully
merge priorities and goals of
both developers and operations
teams and achieve a cohesive
DevOps effort. OTD facilitates
one stop orchestration of data,
27
ADC
4
4
processes, applications, UI and
API across design and runtime of
Operations domains.
Deterministic Network
Assurance (DNA)
Assure Operations reliability for
all networks by correlating 5G
service performance indicators
with real customer service quality,
and experience indicators. This
can be achieved through use of
high-precision simulation that
connects SLA guarantee and
target performance requirements
together. In the case of B2B
customers, deterministic network
needs can support near realtime intelligent automation,
and service-centric closed-loop
assurance solutions. These solutions
can leverage expertise and AI
models to accurately predict and
detect service interruptions and
performance deterioration events,
which effectively identify servicerelated risk-events in advance. This
guarantees that CSP assurance
teams can achieve reliable network
assurance.
Huawei AUTIN realizes
the key features of
iMETHOD to support CSP
business agility and digital
intelligence transformation
Huawei provides the AUTIN
platform using cloud computing
and microservice architecture to
facilitate seamless development
and operations of digital services.
AUTIN enables agile network digital
transformation with the following
capabilities:
Providing a series of cloudenabled services for CSP
network operations and
management, business process
management, asset and
resource management, and fault
and performance management.
Enabling studio-based
development and operations
(through an App Dev Centre)
of Operations software
components. This empowers
app developers / designers to
inform.tmforum.org
SPONSORED FEATURE
collaborate together through
drag-and-drop gestures,
leveraging AUTIN’s Low Code/
No Code features.
processing capabilities to automate
service analysis, service decisionmaking, service recovery, and
service verification.
Improves network experiencemanagement enabling
capabilities by intelligently
managing, altogether, assets,
fault, performance and work
orders etc.
Step 1 (Optional):
Automate traditional fault
management processes for
Operations efficiency
Brings artificial intelligence,
hyperautomation, data processing,
and knowledge management
components together.
EVOLVE
with Options
Huawei Service and Software offers
a two-step path to address the
typical evolutionary needs of CSP
Operations. This two-step path
provides the option to address
near term Operations targets of
improving traditional Operations
process efficiency, and sets up
CSPs in readiness to advance
towards hyperautomated intelligent
Operations targets.
With traditional fault management
workflows, where point-topoint data source for processes
are used, AUTIN can inject
digital technologies like AI and
ML into Operations processes
to intelligently improve fault
association, and achieve
automation of Operations fault
handling. This is helpful when there
is a need to effectively improve, say,
alarm handling efficiency.
By overlaying event management
processes into Operations
workflows, we are immediately
able to harness data from diverse
sources, analyse and deduce
service impact awareness, and
proactively inform remedial actions.
The overlay of event management
is aimed at becoming more servicecentric in defining, establishing and
managing Operations objectives.
This enables higher automation
while fostering closed-loop event
28
Fault management in complex
heterogenous networks and 5G
sites with multi-RAT can meet a
slew of challenges– like having to
handle a large number of crossdomain faults, and need to rely
on human-experience for fault
management. In such network
environments, AI-based fault
analysis capabilities can improve
fault handling automation to reduce
workload and increase the speed of
Operations personnel activities.
Huawei’s Automatic Alarm
Behavior Discovery (AABD Pro), a
component of AUTIN, can provide
self-assuring capabilities, using AI
algorithms and expert experience to
mine fault propagation relationships
using three functional capabilities:
1) Fault Propagation Diagram
Construction (FPDC) based on
data mining algorithms;
2) Spatiotemporal Clustering;
3) Root Cause Inferencing (RCI),
based on both FPDC and expert
experience.
In Operator X in China, AABD use
across multiple domains (wireless
access domain and transport
domain) for self-assurance and
service management, of mission
critical multi-vendor backbone
switches and 4G network elements,
resulted in remarkable business
value, including:
vastly improving fault clustering
accuracy by 90%;
dramatically increasing accuracy
of RCI in network elements by
93%;
7% decrease in number of
wireless trouble tickets.
Step 2:
Leverage Intelligent Event
Management (iEM) solution
to realize Service-aware
Operations
Huawei iEM is a key cloud-enabled
solution developed and run on the
AUTIN platform. iEM deploys all key
features of iMETHOD to transform
the traditional fault management
or performance management
paradigm. By using multidimensional data, iEM solution can
identify events and combine its
advanced technologies (e.g AI, RPA,
RBA etc.), using hyperautomation
approaches, to handle changes in
service behaviour, service operation
and service impact. This achieves
greater efficiency in understanding
the network.
Anomalous events indicate early
warning signs to potential service
impact, or flag already impacted
services. These events can span
multiple domains, systems,
devices etc., and can come from a
variety of data types and sources.
In a DNA model, streamlining
data and Operations break-points
requires focus on problems that
affect services in a timely manner.
This means quickly identifying
and handling these anomalous
events in a timely and closedloop manner.
Through use of advanced
technologies, closed-loop
processing of anomalous events,
and TKD (to reconcile rules,
policies, and insights), iEM can
use its recommendation engine
to advise actions that mitigate
anomalous events based on
closed-loop processing of data.
This ensures catching and handling
anomalous events before they
result in failure or major problems.
Also, knowledge models in iEM
are continuously updated to adapt
to event processing changes.
This adaptation reduces repeat
processing with ‘possible root
cause’ suggestions and ‘resolution
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recommendation’ that improve
efficiency of event handling. The
use of knowledge models reduce
dependence on human-skills in
managing complex networks,
which results in improved network
maintenance efficiency.
iEM is bringing outstanding value
proposition to service providers
across the globe. It is helping to:
Improve the efficiency of
Operations workforce by
enabling CSPs to automatically
identify faults in complex
network environments based on
AI algorithms. On average, iEM
29
achieves accuracy of 85% faults
detection rate every 5 minutes.
Increase effectiveness of
fault demarcation through
automation of expertexperience rules. In active
deployments, average fault
demarcation accuracy is
greater than 80%, with average
demarcation time shortened
from 60 minutes to 15 minutes.
MTTR of typical faults is
reduced by 35%.
To learn more about AUTIN
iEM/AABD Pro, please contact
wangxiangke@huawei.com or go
to https://carrier.huawei.com/en/
products/service-and-software/
AUTIN
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SPONSORED FEATURE
Evolving Service Assurance
to Support Future
Autonomous Networks
The evolution to autonomous networks is a critical element of modern telecommunications. As network
environments become more complex and dynamic, CSPs are already moving to deploy intelligent, interconnected,
automated systems that help reduce reliance on human involvement and optimize processes across the technology
environment. As network operations tasks are shifted to these autonomous systems, staff members can turn their
full attention to matters and responsibilities that require human judgment, while operators drive competitive
differentiation through agility, customer centricity, and actionable insights. Ultimately, high levels of autonomy
within the network will allow the network to make decisions without human interaction via policy, AI, and closedloop activity.
A
be done by the network, and to
determine whether Y needs to
change based on dynamic factors
in the network environment.
As this transformation proceeds,
we’ll also see a shift in the way
automation is implemented.
Traditionally, automation has
been used to automate discreet
tasks and activities through
deterministic logic: see X, do Y.
While this can be effective as a
tactical shortcut, it fails to capture
the context and purpose for doing
Y. It remains the operator’s role
to translate what’s needed by
the business into what needs to
Modern automation takes a
less deterministic approach,
focusing on the goal rather than
the tactic. In this intent-driven
model, the system begins with
the intent—e.g., maintain service
at quality X—and undertakes
activities as needed to achieve
this outcome. This shift reflects
a change in the role today’s
CSPs need automation to play.
Beyond increasing operational
efficiency and reducing human
error—though these remain
important—operators need to
be able to avoid and predict
issues, and anticipate changing
capacity demands, in time to
prevent service degradation from
affecting customers.
s the six levels of network
automation discussed
by TM forum make clear,
the move to a fully autonomous
network can’t be accomplished
in a single step. Instead, CSPs are
making incremental moves from
manual operations and maintenance
through increasing levels of AI
assistance across a broadening
scope of tasks and domains.
30
To implement this model in
a network context, CSPs are
deploying closed-loop automation
in which real-time analysis of
traffic, faults, and resource
availability is leveraged to deliver
the intent of consistent service
quality and reliability. To fully
close these loops—and to realize
the vision of fully autonomous
networks—CSPs will need to
evolve their approach to service
assurance at the same time.
From operator support to
true autonomy
Closed-loop automation
potentially spans multiple,
historically separate technologies
and operational processes which
need to operate together to
deliver a given service. To date,
the automation deployed in
this systems has been strictly
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SPONSORED FEATURE
tactical—Level 1 or 2, to use the
maturity model outlined by TM
Forum. In other words, they
remain primarily operator support
systems, designed and focused on
supporting human-driven activity
within operations. For example, in
service assurance:
Fault management has focused
on tactical automation to
improve visibility of critical faults
in a network, but still remains
focused on a human operator
consuming and responding to
the resulting alarm.
Trouble ticketing has focused on
supporting NOC/SOC-delivered
workflows to manage disruption
in the network, and remains
orientated around providing
an optimal user experience for
human operators.
Change management processes
are highly manual, still driven,
managed, and in many cases
executed by a human operator.
Advancing automation in the
network requires that these
associated processes adapt in
tandem to reflect a more machineto-machine future, rather than
continuing to focus on human
interaction. Indeed, it will be
very difficult for CSPs to achieve
higher levels of maturity (Levels
5 or 6 in the TM Forum model)
without service assurance being
significantly adapted to support
greater closed-loop automation.
For example, without highly
automated, context aware, and riskbased change management, gains
in automation at the network may
be constrained by an overly manual
or rigid change process.
Advancing automation
maturity to transform
service assurance
Improving automation maturity
beyond the low levels typically
found in service assurance
31
processes will transform the way
these processes are delivered.
Taking resource trouble ticketing as
an example:
At Level 2, mundane and
repetitive activities will be semiautomated, such as the creation
of trouble from alarms and
the correlation and grouping
of multiple tickets to identify
common or wider issues.
High-volume, low-complexity
issues will be increasingly
automated, either fully or as
operator-guided activities.
This is an extension of existing
processes rather than a true
transformation, and likely as far
as you can go without adapting
processes.
At Level 3, specific ticket
journeys are completely “lightsout,” with full automation of
issue creation, assessment,
diagnosis, and remediation.
Specific types of troubles
will be eliminated, as the
network resolve these issues
automatically without recourse
to fault/trouble processes.
At Level 4, most mundane,
high-volume ticket activity
is managed directly within
the network, resulting in
significantly fewer tickets
needing operator involvement.
Those that do include highly
complex faults or issues
that cannot be managed
by conditional network
automation, often spanning
multiple technologies or
locations; those falling
outside of existing intent
driven automation; and those
requiring hands-on attention,
such as a hardware failure
in a remote site. Faults and
issues resulting from failed
automation may require
human interaction as well.
Aspects of these exceptions
can still be automated, but
Service Assurance
today, tomorrow
and in 5 years
Download
TM Forum’s eBook:
Service Assurance Steps
Out of the Shadows
may be at a lower level
of maturity, such as the
automation of “truck rolls”
for tickets requiring a visit by
field services.
At Levels 5 and 6, automation
will further reduce the amount
of faults and troubles within
Service Assurance. The
improved prediction of future
issues may call for some level
of human interaction, but this
will increasingly influence
preventative maintenance
activity, rather than fault
resolution.
As automation transforms the
delivery of service assurance,
service assurance in turn will play
an essential role in supporting
greater network automation. To
fuel the analytics and intelligence
required for intent-based
automation, and enable closed-loop
management, service assurance will
need to increasingly support:
Automated remediation
through closer integration with
fulfilment and orchestration
systems
Improved diagnostics and
testing integration, allowing
issues to be automatically
diagnosed
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SPONSORED FEATURE
Greater context and visibility
of complex network issues,
supporting the resolution
of the highly complex, highimpact issues that cannot be
automated at medium levels of
maturity (Levels 3–4)
Improved support for fully
machine-to-machine activity,
rather than human-to-machine
AI-driven processes to improve
accuracy of service impact and
root cause visibility in an active,
software-based network where
traditional methods are no
longer applicable
Greater governance and
visibility of automation to
mitigate the potential risks
associated with reduced human
involvement
32
While automation can drive value
for CSPs across a broad range of
technologies and processes, its
impact on service assurance will
be especially significant. Beyond
its immediate utility for ensuring
consistently high service quality
and reliability, the automation of
service assurance activities will
remove friction from processes
such as change management which
can otherwise constrain the value
of automation within the network.
By helping to close the loops in
closed-loop automation, a more
mature and automated service
assurance capability will help CSPs
realize the benefits of intent-based
automation as they evolve to a fully
autonomous network.
For more information, please
visist: www.bmc.com/csp
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tm forum open
digital framework
A blueprint for intelligent operations fit for the 5G era
The TM Forum Open Digital Framework (ODF) provides a migration path from legacy IT systems and processes
to modular, cloud native software orchestrated using AI.
The framework comprises tools, code, knowledge and standards (machine-readable assets, not just documents).
It is delivering business value for TM Forum members today, accelerating concept-to-cash, eliminating IT &
network costs, and enhancing digital customer experience.
Developed by TM Forum member organizations through our Collaboration Community and Catalyst proofs of
concept, building on TM Forum’s established standards, the Open Digital Framework is being used by leading
service providers and software companies worldwide.
Goals of the Open
Digital Framework
The framework comprises TM Forum’s Open Digital Architecture
(ODA), together with tools, models and data that guide the
transformation to ODA from legacy IT systems and operations.
Open Digital Architecture
Architecture framework,
common language and
design principles
Open APIs exposing
business services
Standardized software
components
Reference implementation
and test environment
33
Transformation Tools
Guides to navigate digital
transformation
Tools to support the
migration from legacy
architecture to ODA
Maturity Tools & Data
Maturity models and
readiness checks to baseline
digital capabilities
Data for benchmarking
progress and training AI
The aim is to transform
business agility (accelerating
concept-to-cash from 18
months to 18 days), enable
simpler IT solutions that
are easier and cheaper
to deploy, integrate and
upgrade, and to establish a
standardized software model
and market which benefits
all parties (service providers,
their suppliers and systems
integrators).
Learn more about
member collaboration
If you would like to learn
more about the Open Digital
Framework, or how to get
involved in the TM Forum
Collaboration Community,
please contact George Glass.
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tm forum research reports
knowledge
on the journey
to cloud native
Author:
Mark Newman,
Chief Analyst
SPONSORED BY
Editors:
Dawn Bushaus,
Contributing Editor
Ian Kemp,
Managing Editor
October 2021
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REPORT
REPORT
enterprise
verticals
lessons
learned
knowledge
knowledge
REPORT
Author:
Dean Ramsay,
Principal Analyst
the growing
importance of
data
governance
placing the
right bets
Editor:
Ian Kemp,
Managing Editor
Author:
Charlotte Patrick,
Contributing Analyst
December 2021
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Editor:
Dawn Bushaus,
Managing Editor
SPONSORED BY:
December 2021
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November 2021 | www.tmforum.org
next generation
the Telefónica way
Author: Mark Newman, Chief Analyst, TM Forum
Editor: Annie Turner, Contributing Analyst
sponsored by:
34
with the support of:
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meet the Research & Media team
Report Author:
Report Editor:
Dean Ramsay
Ian Kemp
Principal Analyst
dramsay@tmforum.org
Report Author:
Mark Newman
Chief Analyst
mnewman@tmforum.org
Customer Success &
Operations Manager:
Ali Groves
Joanne Taaffe
jtaaffe@tmforum.org
Commercial Manager,
Research & Media:
Tim Edwards
Senior Analyst
tedwards@tmforum.org
Global Account Director:
Digital Marketing Manager:
Carine Vandevelde
Anna Kurmanbaeva
Report Design:
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ISBN: 978-1-955998-10-9
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Editor in Chief, Inform:
agroves@tmforum.org
cvandevelde@tmforum.org
Published By:
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akurmanbaeva@tmforum.org
© 2021. The entire contents of this publication are protected by copyright.
All rights reserved. The Forum would like to thank the sponsors and
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researched report. The views and opinions expressed by individual authors
and contributors in this publication are provided in the writers’ personal
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for more about tm forum’s work
on autonomous networks, please
contact Aaron Boasman-Patel