Fueling growth through data
monetization
A new
survey finds that many companies are launching data-focused businesses. But few
have achieved significant financial impact, which requires the right
combination of strategy, culture, and organization.
Results from the
newest McKinsey Global Survey on data and
analytics indicate that an increasing share of companies is using data and
analytics to generate growth.1Data
monetization, as a means of such growth, is still in its early days—though the
results suggest that the fastest-growing companies (our high performers) are
already ahead of their peers. Respondents at these companies say they are
thinking more critically than others about monetizing their data, as well as
using data in a greater number of ways to create value for customers and the
business.2They
are adding new services to existing offerings, developing new business models,
and even directly selling data-based products or utilities.
Moreover, responses
from the organizations that are seeing the most impact from their
data-and-analytics programs offer lessons to others striving to make the most
of their data. Those companies have, according to respondents, established a
strong foundation for analytics in a few ways: clear data-and-analytics strategies, better organizational design and
talent-management practices, and a greater emphasis on turning new data-related
insights into action.
Data
and analytics are changing the way business is done
Overall, respondents
say that the use of data and analytics has brought important changes to their
companies’ core business functions. For example, nearly half of all respondents
say data and analytics have significantly or fundamentally changed business
practices in their sales and marketing functions, and more than one-third say the same about R&D.
Across industries, respondents in high tech and in basic materials and energy
report the greatest number of functions being transformed by analytics .
Data and analytics are also changing the
nature of industry competition. Seventy percent of all executives report that
data and analytics have caused at least moderate changes in their industries’
competitive landscapes in recent years. The most common change, cited by half
of respondents, is entrants launching new data-focused businesses that
undermine traditional business models. Across industries, respondents report
the most significant changes in high tech, media and telecom, and consumer and
retail.
Data
monetization is becoming a differentiator
Across industries, most respondents agree
that the primary objective of their data-and-analytics activities is to
generate new revenue. We asked about data monetization as one such way to
create revenue, and the results suggest that these efforts are fairly new. Of
the 41 percent of respondents whose companies have begun to monetize data, a
majority say they began doing so just in the past two years.
Though nascent, monetization is already
more prevalent in certain industries: more than half of the respondents in
basic materials and energy, financial services, and high tech say their
companies have begun monetizing data. What’s more, these efforts are also
proving to be a source of differentiation. Most notably, data monetization
seems to correlate with industry-leading performance. Respondents at the
high-performing companies in our survey are more likely than others to say they
are already monetizing data and to report that they are doing so in more ways,
including adding new services to existing offerings, developing entirely new
business models, and partnering with other companies in related industries to
create pools of shared data. Perhaps unsurprisingly, respondents at high
performers also see a top-line benefit: they are three times more likely than
others to say their monetization efforts contribute more than 20 percent to
company revenues.
The high performers’ focus on data
monetization may stem from a better ability—and greater need—to adapt to
change. Compared with their peers, high-performing respondents report that
data-and-analytics activities are prompting more significant changes in their
core business functions. For example, respondents at high performers are at
least one-third more likely to report significant or fundamental changes to
business practices in areas such as supply chain, research and development,
capital-asset management, and workforce management. Additionally, they are more
likely to report changes in competitive pressure, whether from new entrants
launching new data-related businesses, traditional rivals gaining an edge
through data and analytics, or companies forming data-related partnerships
along the value chain.
Get the
foundations right first
Before companies can
make meaningful strides with data monetization, they must first set up the fundamental
building blocks of a successful data-and-analytics program. We took a close look at a group of companies in which
respondents report seeing the greatest business impact from analytics. The
results reveal that these “analytics leaders”3offer important lessons
as to where, and how, companies can strengthen their foundations, particularly
in areas beyond the technical aspects of building data-and-analytics solutions
.
Strategy.
Many respondents report a lack of a
data-and-analytics strategy at their companies, even when the need for one
becomes compelling. For example, 61 percent of respondents who recognize that
data and analytics have affected their core business practices say their
companies either have not responded to these changes or have taken only ad hoc
actions rather than develop a comprehensive, long-term strategy for analytics.
In contrast, analytics leaders are nearly twice as likely as others to report
enacting a long-term strategy to respond to changes in core business practices.
Organization and talent.
While either a decentralized or
centralized organizational model for data-and-analytics activities can work,
the results suggest that a hybrid model incorporating elements of both is much
more common among the analytics leaders.4At
the leader companies, respondents are more than three times as likely as those
whose companies are struggling to see an impact from data and analytics—the
laggards5—to
say they are using a hybrid model led by a center of excellence, one of two
hybrid models the survey asked about.
For all respondents—and
regardless of the organizational model their companies use—attracting and
retaining talent appears to be even more difficult than it was in our previous survey on the subject. Nearly 60 percent of
respondents now say it is harder to source talent for data-and-analytics roles
than for other positions, compared with 48 percent in our previous survey. This
challenge is acute even for the analytics leaders, which have a harder time
than others do in finding people with both technical and domain
expertise—sometimes called translators. At leading companies, 24 percent of
respondents identify the translator role as their organizations’ most pressing
need for talent.
Leadership and culture.
Successful
data-and-analytics programs also require real commitment from business leaders,
along with a consistent message from senior leaders on the importance and
priority of these efforts. Overall, respondents report that senior-management involvement in data-and-analytics activities is the number-one contributor
to reaching their objectives. At the analytics leaders, senior-management
practices prove the point further. Respondents at these organizations are five
times more likely than those at analytics laggards to say their executive teams
spend more than 20 percent of their time at high-level meetings discussing
their data-and-analytics activities.
Overall, though, the survey indicates that
senior-leader alignment on data-and-analytics initiatives is still not optimal
at many companies. At some firms, CEOs differ from other senior leaders in
their perceptions of analytics program management, organizational structure,
and keys to success—a situation that creates the potential for mixed messages.
For example, CEOs are much likelier than other senior executives (53 percent,
compared with just 10 percent of others) to identify themselves as the leaders
of their organizations’ data-and-analytics agenda. CEO respondents
are also more likely than others to report effectiveness at reaching
data-and-analytics objectives and are less likely to view data scientists and
engineers as a pressing talent need. Finally, the CEOs differ from other executives
in their reasons for why their organizations have not responded to competitive
or core business changes in their industries. While the others overwhelmingly
cite a lack of senior-leadership commitment, CEOs are more likely to cite a
lack of financial resources and uncertainty about which actions to take.
Looking
ahead
Getting data monetization right requires
significant effort, but it’s becoming critical for staying ahead of traditional
competitors and new disruptors. Based on the survey results, here are some
steps executives can take to start their data-monetization efforts on the right
foot:
·
Focus
on yourself first. It is nearly
impossible for a company to succeed at creating externally focused data-based
businesses while still struggling to get clean, consistent data that are shared
internally across the organization. Before companies start down the path of
monetization, they should take the time to shore up their data
foundations—strategy, design, and architecture—which will help them build the
business case and technical platform they need to monetize data effectively.
Putting their data to work for internal use cases, such as improving decision making or optimizing
operations, can also serve as a testing ground for their data foundations as
well as for the data-monetization models of new data-based businesses.
·
Look
outside for innovation. Once
companies’ data-and-analytics foundations are in place, they may still find
that the most innovative solutions can best be sourced externally, by
partnering with others in the data ecosystem.
Such partners include analytics companies that can supplement the
organization’s existing capabilities, platform providers that host tools or
solutions, and data providers that can help the organization gain access to
unique data sets. Companies can even work with suppliers, customers, or their
industry peers to augment and enrich existing data; they can then offer those
data as unique add-ons to existing products or services, or sell the data as
part of an entirely new business.
·
Commit to an end-to-end
transformation, and get the business involved.Even as data monetization gains steam, many companies
are still struggling to drive major business impact. In our experience, this
happens for two reasons: failure to make the wholesale changes required to
enter new markets, and a lack of partnership between the business and IT. For a
transformation, such changes could involve the reconfiguration of operating
models and core business functions (from product development to marketing),
worker-reskilling programs, and change-management programs aimed at shifting
organizational culture, mind-sets, and behaviors. These sorts of substantial
efforts require full commitment from the C-suite, who must communicate to
senior managers—in both business units and technology centers—the priority of a
given initiative or program and the need to dedicate adequate time, human capital,
and financial resources to make it succeed. Many companies also struggle with
data monetization—and, in particular, finding the right strategy—when they
delegate all data-and-analytics efforts to IT. In reality, efforts to monetize
data are more effective when they are business led and focused on the most
valuable use cases.
https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/fueling-growth-through-data-monetization?cid=other-eml-alt-mip-mck-oth-1712
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