A
future for mobile operators: The keys to successful reinvention
By
transforming their networks and operations with the newest technologies, mobile
operators could double their cash-flow conversion within five years.
The past several years have been tough for telecom companies. Their
revenue and cash flows have
dropped by an average of 6 percent a year since 2010. Consumption of mobile
data boomed, as masses of new wireless customers used their handsets to spend
ever-increasing amounts of time online. Companies responded by investing
heavily in their wireless networks, even as subscriber growth slowed. As a
result, the average ratio of capital spending to revenues has remained
stubbornly high, at around 15 percent, for the major players.
What can companies do to alleviate the
squeeze on margins and create more value? Major advances in data analytics,
artificial intelligence, network equipment, and other technologies have
rewritten the industry’s winning formula. With the newest software and
hardware, along with digital-age management practices, mobile operators can
achieve breakthrough cost savings and capital intensity while maintaining or
even increasing their scale.
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To capitalize on these opportunities,
executives must take bold action to transform their businesses. Managing
networks with next-generation technologies can cut the capital-spending and
operating expenses of wireless operators. And digital technology can help them
to streamline their business functions and please their customers, reducing
costs and raising sales.
Wireless operators have little reason to
wait before making these moves—the necessary technologies and management
methods are available now. Moreover, operators can launch a digital
transformation and begin reaping the benefits even as they move into fast-growing
adjacent markets or await favorable regulatory changes. In this article, we
take a closer look at the prospects of mobile operators for digital reinvention
and how they can exploit those opportunities.
Managing
networks with next-generation technologies
Doing more with less is seldom easy. But
leading-edge technologies help mobile operators do just that to meet the
burgeoning demands on their networks. Network equipment is more sophisticated
than ever, and analytics allows wireless
operators to make smarter decisions about how they deploy capital and adjust
their networks to maintain the quality of service.
The shift to small-cell networks has been
one fundamental step toward next-generation technologies. Until recently,
mobile networks consisted of expansive cells with modest capacity. To fix a
service problem affecting only a small area within a cell, an operator had to
enhance the network’s coverage and capacity over the entire cell, including
places where service was already good.
Now, technological advances have made it
possible for wireless operators to set up and operate dense networks of small,
high-capacity cells. These networks typically cost less to upgrade than
networks of large cells do. Network equipment has gotten better as well: it is
less costly to buy and operate, more flexible, and more powerful. Mobile
operators can also use sophisticated analytical tools to gain insights into
capturing the maximum value from capital investments.
Network technology is improving all the
time, and the advances will probably accelerate in several years, with the
establishment of 5G wireless standards, which make it possible to serve more
mobile users in a given area. Even so, mobile operators shouldn’t delay making
changes and await superior technology. The following applications can help
these companies create more value right away.
Analytics
for smarter capital spending
Advanced analytics can help mobile
operators to determine which capital investments in their networks will produce
the most value. Operators collect ample data about where, when, and how much
subscribers use their mobile handsets. These data are precise: they can
establish usage patterns within five-by-five-meter squares, roughly the size of
a studio apartment, over the course of days and weeks.
By running the data through algorithms, a
wireless operator can pinpoint where and when network overloads happen and
which customers they affect most. With that information, it can project how
much a possible upgrade might improve the satisfaction—and ultimately the
retention—of its more profitable customers. An operator can also determine the
highest levels of network performance that do not yield diminishing returns in
customer satisfaction. Such findings let the company avoid investments that
would make their networks better than necessary. With these techniques, mobile
operators planning capital expenditures can prioritize value creation rather
than network performance.
Machine
learning for increased efficiency
Networks made up of small cells are not
only less expensive to maintain than networks of large cells but also more
flexible. One benefit of flexibility is that operators can save money by
reducing or increasing each cell’s capacity as demand for service fluctuates.
(Adjusting capacity is harder with large cells. Even if some areas in such a
cell are experiencing low demand, its capacity has to be kept uniformly high to
maintain the quality of service in areas where demand is strong.)
Much as operators can use analytics to determine
where to make upgrades, they can also use machine learning to adjust wireless
networks automatically as demand changes or even to base adjustments on
predictions. If a machine-learning model has records of network usage and other
conditions (such as traffic or weather) and then receives new data in real
time, it can predict when usage might rise or fall across a network and adjust
capacity preventively.
Software
for better performance
Improvements in software allow mobile
companies to get significantly increased performance from hardware they already
own or to use less expensive hardware. New methods for compressing and managing
video, for example, let wireless companies offer video-streaming services to
ten times more households, thus creating new revenue streams. These methods can
also cut data-storage costs by 60 percent.
Two other key technologies are
software-defined networking (SDN) and network-functions virtualization (NFV).
These allow wireless operators to centralize the functions for controlling
networks and to administer changes and upgrades remotely rather than in the
field. Another benefit is that they let operators use generic network hardware,
which tends to be more cost-effective.
All of these network technologies promise
to lower costs and make it faster and easier to change networks in response to
problems or new customer needs. We estimate that the newest technologies would
let operators lower their capital expenditures by up to 40 percent—thus pushing
these costs down to under 10 percent of revenues—and their network-operating
expenses by a similar amount.
Using
digital to streamline operations and please customers
Mobile operators lag behind companies in
some other industries in doing business digitally. For example, they make a
smaller share of their sales online than insurance and retail-banking companies
do. Closing this gap isn’t just a matter of pride—it can boost financial
performance and create competitive advantages.
Using digital technology to automate
operations makes them leaner and more productive, which leads to lower costs.
McKinsey research has also found that providing customer service through digital channels improves customer satisfaction—and that in turn leads to increases in revenue. The
opportunities to digitize support for mobile customers
are especially promising. Our surveys indicate that more than half of European
subscribers want to deal with providers only through digital channels and that
more than a third of US subscribers are open to strictly digital interactions.
Both the technology and the know-how
needed to digitize wireless operators are available today. In our experience,
typical companies can make nearly every aspect of their business functions and
customer experiences simpler, easier, faster, and more cost-effective. Here are
the major opportunities we’ve identified.
Automation
and simplification in the back office
Many mobile operators have essential
processes that are more complex and labor-intensive, and therefore more costly,
than they have to be. These include dealing with business partners, budgeting,
preparing compliance reports, and other essential functions. We estimate that
just 20 to 30 processes generate 45 percent of the average operator’s operating
costs. Using advanced technologies, such as machine learning, to
simplify and digitize those processes can cut costs by as much as one-third.
Excess complexity also
pervades the systems and product lineups of mobile businesses. One
company we know had 600 IT systems; another had 3,000 prepaid plans. Many
wireless operators therefore stand to benefit from taking a fresh look at the
needs of their businesses and customers and eliminating superfluous systems. To
take one example, we estimate that a typical operator could trim the custom
code in its customer-relationship-management (CRM) system from 350,000 lines to
20,000—a 95 percent reduction—by removing unnecessary applications and features.
Digitization
in customer support
A mobile operator we know reduced the
number of support calls it fields by 90 percent after it set up sophisticated
systems to track and anticipate the problems of its customers and to give them
resources to solve those problems on their own. These systems typically provide
three levels of support.
The first is self-care. Providing
self-service guides and automatic tips about possible problems can help
customers solve 75 percent of the issues themselves. Customers can solve an
additional 15 percent of problems by using advice from instant-messaging chats
(with employees or artificial-intelligence agents) or from online discussion
groups. This leaves just 10 percent of problems to be handled at the costliest
level of support: a phone call with a customer-service agent.
Predictive
analytics in marketing and sales
With predictive models fed by customer
information, mobile operators can develop cross-selling offers that appeal to
individual customers and determine how best to reach them, down to the time of
day. This approach, we believe, can add as much as two percentage points to a
wireless operator’s EBITDA margins. One company increased its sales from
cross-selling campaigns by 25 percent once it started using analytics to plan
those efforts.
Similarly, mobile operators can use
analytics to increase their sales to existing customers. An analysis of
customer data (in compliance with privacy-related legal and regulatory
requirements) can suggest when each customer will be open to upgrading services
or hardware, so that companies can make timely, appealing offers. Operators can
also test and refine such offers before extending them widely.
Machine
learning in customer retention
Mobile operators can use analytics to
learn how to retain more of their subscribers yet spend less doing so. By
running massive sets of customer data (with as many as 300 variables) through
machine-learning models, an operator can identify people who appear likely to
cancel their service. Then it can woo them with offers aimed at the causes of
their dissatisfaction.
Research by one mobile operator determined
that 2 percent of its customers had a 48 percent likelihood of canceling their
service in the next three months—a rate much higher than the 5 percent
likelihood among its other customers. It divided the “likely churners” into
segments based on the reasons they might cancel. The offers it extended to
them, depending on their concerns, reduced cancellations by 15 percent. And
because the operator targeted its outreach efforts precisely, it spent 40
percent less than it usually did to carry them out.
The use of customer data to improve
retention points to other possibilities. Some telecom companies and banks have established data-sharing partnerships to gain customer insights that help them, for
example, to develop products and manage fraud. The subscriber data that mobile operators collect could also be valuable for
other kinds of companies, such as retailers, which might use the information to
predict where people will be at any given moment and give them time- and location-specific
offers.
Starting
a mobile transformation
Using advanced technologies to manage
wireless networks and digitize mobile operations can have a powerful effect on
a mobile operator’s financial performance. Although companies can implement the
changes selectively, the benefits of a comprehensive, coordinated program are
greater because many of these moves reinforce one another. We estimate that a
full digital-transformation effort would help a mobile operator to nearly double its cash-flow conversion within just five years.
Although each wireless operator will have
to devise its own approach, a few general principles can benefit all operators
as they embark on digital-transformation programs.
Aim
high—then raise your sights
Many operators have responded to the
steady pressure on margins by reducing costs incrementally—for instance,
cutting capital expenditures or call-center costs by 3 to 5 percent a year.
Such modest cuts can help sustain margins but seldom produce big, lasting
improvements. To make performance breakthroughs, the leaders of mobile
operators must change their organizations in a fundamental way, starting with
goals that might seem absurdly ambitious.
Reducing customer-service calls by 90
percent? Cutting lines of custom computer code by 95 percent? Doubling
cash-flow margins in five years? These improvements would be unprecedented—yet
they are realistic given the economics and structure of the mobile business
today. And they can be attained only if executives of wireless operators
challenge their companies to achieve them.
Reshape
mind-sets and reorganize
The telecom industry’s historical legacy as
a utility-like sector still informs its competitive outlook. But the future of
the mobile business will be defined in part by how well it develops capabilities essential in the digital economy, from designing products and user experiences to implementing
analytics and artificial intelligence. Few wireless operators possess these
capabilities today. To develop them, they will have to hire and train people in
new ways, from the C-suite down through the ranks.
Mobile operators must also transform their
organizations. If different departments handle activities related to the same
part of the customer experience, those might need to be unified. Product
managers might have to be reshuffled as operators consolidate portfolios.
Companies should find a balance between the benefits and costs of reorganizing.
One company we know chose to set up a new, all-digital mobile division rather than
overhaul its legacy business.
Focus
on execution
Setting ambitious goals and developing
plans to achieve them are the first steps in transforming a mobile company. For
those plans to succeed, managers must monitor them and take corrective action
when they fall behind schedule or veer off course. This focus on execution has
to remain steady over the period needed to complete a wireless transformation.
In most cases, the transformation will have to be directed by a team focusing
on it alone. Any successful transformation also requires a commitment from the
CEO and the rest of the leadership team, who must stay involved for the
duration.
Large, capital-intensive businesses can resist major
change. But technological advances in the mobile business have brought
operators to a critical juncture. Now as never before, they have access to
sophisticated network equipment, rich data on customers and operations,
analytical power, and organizational prowess. As a result, mobile operators
have an unprecedented opportunity to improve many measures of performance, from
cash-flow conversion to customer satisfaction. Those that move boldly to
transform themselves with these new capabilities stand to cut their costs and
increase their revenues significantly, while building decisive advantages over
their less ambitious competitors.
By Guido Frisiani, Jay Jubas, Tomás Lajous, and Philipp Nattermann
http://www.mckinsey.com/industries/telecommunications/our-insights/a-future-for-mobile-operators-the-keys-to-successful-reinvention?cid=other-eml-alt-mip-mck-oth-1702
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