The age of analytics: Competing in a data-driven world
Big
data’s potential just keeps growing. Taking full advantage means companies must
incorporate analytics into their strategic vision and use it to make better,
faster decisions.
Is big data all hype? To
the contrary: earlier research may have given only a partial view of the
ultimate impact. A new report from the McKinsey Global Institute (MGI), The
age of analytics: Competing in a data-driven world, suggests that the range
of applications and opportunities has grown and will continue to expand. Given
rapid technological advances, the question for companies now is how to
integrate new capabilities into their operations and strategies—and position
themselves in a world where analytics can upend entire industries.
Big data continues to grow; if
anything, earlier estimates understated its potential.
A 2011 MGI report
highlighted the transformational potential of big data. Five years later, we remain
convinced that this potential has not been oversold. In fact, the convergence
of several technology trends is accelerating progress. The volume of data
continues to double every three years as information pours in from digital
platforms, wireless sensors, virtual-reality applications, and billions of
mobile phones. Data-storage capacity has increased, while its cost has
plummeted. Data scientists now have unprecedented computing power at their
disposal, and they are devising algorithms that are ever more sophisticated.
Earlier, we estimated
the potential for big data and analytics to create value in five specific
domains. Revisiting them today shows uneven progress and a great deal of that
value still on the table. The greatest advances have occurred in
location-based services and in US retail, both areas with competitors that are
digital natives. In contrast, manufacturing, the EU public sector, and healthcare
have captured less than 30 percent of the potential value we highlighted five
years ago. And new opportunities have arisen since 2011, further widening the
gap between the leaders and laggards.
Leading companies are
using their capabilities not only to improve their core operations but also to
launch entirely new business models. The network effects of digital platforms
are creating a winner-take-most situation in some markets. The leading firms
have remarkably deep analytical talent taking on various problems—and they are
actively looking for ways to enter other industries. These companies can take
advantage of their scale and data insights to add new business lines, and those
expansions are increasingly blurring traditional sector boundaries.
Where digital natives
were built for analytics, legacy companies have to do the hard work of
overhauling or changing existing systems. Adapting to an era of data-driven
decision making is not always a simple proposition. Some companies have
invested heavily in technology but have not yet changed their organizations so
they can make the most of these investments. Many are struggling to develop the
talent, business processes, and organizational muscle to capture real value
from analytics.
The first challenge is
incorporating data and analytics into a core strategic vision. The
next step is developing the right business processes and building capabilities,
including both data infrastructure and talent. It is not enough simply to layer
powerful technology systems on top of existing business operations. All these
aspects of transformation need to come together to realize the full potential
of data and analytics. The challenges incumbents face in pulling this off are precisely
why much of the value we highlighted in 2011 is still unclaimed.
The urgency for
incumbents is growing, since leaders are staking out large advantages, and
hesitating increases the risk of being disrupted. Disruption is already
happening, and it takes multiple forms. Introducing new types of data sets
(“orthogonal data”) can confer a competitive advantage, for instance, while
massive integration capabilities can break through organizational silos,
enabling new insights and models. Hyperscale digital platforms can match buyers and sellers
in real time, transforming inefficient markets. Granular data can be used to
personalize products and services—including, most intriguingly, healthcare. New
analytical techniques can fuel discovery and innovation. Above all, businesses
no longer have to go on gut instinct; they can use data and analytics to make
faster decisions and more accurate forecasts supported by a mountain of
evidence.
The next generation of
tools could unleash even bigger changes. New machine-learning and deep-learning
capabilities have an enormous variety of applications that stretch into many
sectors of the economy. Systems enabled by machine learning can provide
customer service, manage logistics, analyze medical records, or even write news
stories.
These technologies
could generate productivity gains and an improved quality of life, but they
carry the risk of causing job losses and dislocations. Previous MGI research
found that 45 percent of work activities could be automated using current technologies;
some 80 percent of that is attributable to existing machine-learning
capabilities. Breakthroughs in natural-language processing could expand that
impact.
Data and analytics are
already shaking up multiple industries, and the effects will only become more
pronounced as adoption reaches critical mass—and as machines gain unprecedented
capabilities to solve problems and understand language. Organizations that can
harness these capabilities effectively will be able to create significant value
and differentiate themselves, while others will find themselves increasingly at
a disadvantage.
By Nicolaus Henke, Jacques Bughin, Michael Chui, James Manyika, Tamim Saleh, Bill Wiseman, and Guru Sethupathy
FOR Appendix
(PDF–533KB) Executive
Summary (PDF–1MB) Full
Report (PDF–3MB) GO TO
https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/the-age-of-analytics-competing-in-a-data-driven-world
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