The document discusses six emerging trends in business analytics:
1. Humans and machines will increasingly work together in complementary roles, with machines handling tasks like data processing and humans focusing on creativity, empathy, and oversight of machine performance.
2. Analytics capabilities are expanding across entire organizations, moving from isolated initiatives to enterprise-wide strategies aimed at creating "insight-driven organizations."
3. Cybersecurity is becoming more important and proactive, utilizing predictive analytics to anticipate threats rather than just reacting to attacks.
4. The Internet of Things is expanding to include people and generating new business models by aggregating and analyzing behavioral data.
5. Companies are getting creative in addressing talent shortages, collaborating more closely
2. As the discipline of business analytics matures,
it’s clear that some trends aren’t going away.
Instead, they are evolving at such a rapid pace
that they demand a fresh look every year.
This year, we’re taking stock of a mix of both new
and familiar trends that are shaping an “everywhere
analytics” world—where analytics, data, and reasoning
are embedded into the decision-making process,
every day, everywhere in the organization.
Analytics Trends 2016 | 2
4. The man-machine
dichotomy blurs
As cognitive capabilities advance, where do humans fit
into the picture? Fear not—there’s still a place for us.
In the near future, human insights and instincts will
complement machine-driven insights. What will this
more collaborative future look like?
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5. Humans and machines will find new
ways to complement one another
• Humans will build and implement
cognitive technologies
• Humans must ensure machine performance
and fit with work processes
• Humans will perform roles that computers
can’t – such as those involving creativity,
caring, or empathy
The way forward
• Examine knowledge-intensive processes
to determine which tasks are performed
by machines, and which by humans
• Plan for some degree of retraining
$1 billion
in venture capital funding
for cognitive technologies
in 2014 and 2015
Market revenue for
cognitive expected to exceed
$60 billionby 2025
The cognitive age is here
The man-machine dichotomy blurs
Analytics Trends 2016 | 5
Source: International Data Corporation
www.deloitte.com/us/AnalyticsTrends #AnalyticsTrends2016
7. Analytics expands
across the enterprise
Not long ago, it was enough to simply get targeted
analytics capabilities put in place. Today, a new goal is
emerging: The insight-driven organization. That will
require scaling small, current analytics initiatives to the
enterprise level. From “analytics transformation” to
“industrialized analytics,” get ready.
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8. A new goal emerges: The insight-driven
organization (IDO)
• Yesterday: Implement or improve targeted
analytics capabilities in a few key areas
• Tomorrow: Tightly knitted combo of strategy,
people, processes, data, and technology that
delivers insights every day, everywhere in the organization
Shaping an IDO future with today’s decisions
• Some leaders are already discussing “analytics
transformation” and “industrialized analytics”
• Decisions on issues such as data warehouses
and big data must be made in the context
of an IDO future
The way forward
• Take existing analytics initiatives and
scale them to the enterprise level
• Goal: Grow and connect analytics
capabilities across the enterprise
Analytics expands across the enterprise
Analytics Trends 2016 | 8www.deloitte.com/us/AnalyticsTrends #AnalyticsTrends2016
10. Cybersecurity:
A good defense
isn’t enough
Last year’s supertrend is still front and center—
growing in importance as more organizations
experience the losses in value and reputation that can
result from security lapses. Some organizations are
taking the offensive when it comes to cybersecurity—
which requires new thinking and approaches.
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11. Persistent and evolving
• Product design and other IP are vulnerable to
theft and sabotage—protecting data is only part
of the challenge
• Cybercriminals are becoming more skilled
Scanning the current cybersecurity landscape
• Leaders are taking steps to become proactive,
not reactive
• Big spending is expected to continue
• Rise in automated scanning of Internet chatter,
analysis of past hacks to create predictive models
that anticipate the next threats, and more
The way forward
• Enhance collaboration between analytics
and cyber professionals
• Adopt more predictive approaches
to threat intelligence and monitoring
U.S. federal government agencies
alone will have spent more than
$14.5 billion
on IT security in 2015
The worldwide financial
services industry will have spent
$27.4 billion
on information security and
fraud prevention in 2015
Growing investments
in cybersecurity
Cybersecurity: A good defense isn’t enough
Analytics Trends 2016 | 11
Source: International Data Corporation, “Big
Data and Predictive Analytics: On the
Cybersecurity Front Line,” February 2015.
www.deloitte.com/us/AnalyticsTrends #AnalyticsTrends2016
13. The Internet of Things
– and people, too
As the Internet of Things matures, it’s moving beyond the
interesting gadgets on which it relies to include tracking
people as “things.” And it’s spawning new business models
along the way.
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14. Beyond gadgetry
• New roles for people in the IoT: Connected customers
automatically transmitting data on aspects of their behavior
or preferences, workers outfitted with wearables that share
information on activities and whereabouts, and more
• This is spawning new business models and leading to
new ways to influence behaviors
A new source of innovation
• Data generated by IoT assets is being aggregated
and analyzed to create new products and services
• Big benefits to society at large are more likely as a result
− More energy- and time-efficient transportation
− More transparent, economical government services
… and much more
The way forward:
• Build on existing infrastructure: Much of what is
required to enable IoT is already in place
• Give people incentives for participating in IoT—like
health insurers offering discounts to track customer
fitness activities using wearables
The worldwide IoT market
is expected to grow from
$655.8 billion
in 2014 to
$1.7 trillion
in 2020
Too big to ignore?
The Internet of Things – and people, too
Analytics Trends 2016 | 14
Sources: International Data Corporation,
“IDC’s Worldwide Internet of Things
Taxonomy, 2015,”
“Worldwide Internet of Things Forecast,
2015-2020,” “Worldwide IoT Spending Guide
by Vertical”
www.deloitte.com/us/AnalyticsTrends #AnalyticsTrends2016
15. The Internet of Things – and people, too
Impact
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16. Companies bridge
the talent gap
The business world is coming to terms with the fact
that the supply of data scientists (and others with
related skills) can’t keep up with demand. So they’re
getting creative. From new recruitment strategies to
tapping the capabilities of a broader talent ecosystem,
expect the analytics leaders of 2016 to find a way.
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17. A deepening shortage
• Universities can’t crank out data scientists
and others fast enough to keep up
with business demands
• Only 17% of “analytically challenged”
firms report having the talent they need
Expanding avenues for talent
• Analytics and data science programs
are on the rise in universities
• Providers of analytics talent are also on the rise— often
in highly specialized areas such as business intelligence,
predictive analytics, data science, and cognitive
technology
The way forward
• Recruitment: Collaborate more closely
with university programs on internships
and student projects
• The talent ecosystem: Cultivate ecosystems
of external providers of analytics skills
International Data Corporation
predicts a need for
181,000
people
with deep analytics skills
in the U.S. by 2018
How much talent
is enough?
Companies bridge the talent gap
Analytics Trends 2016 | 17
Source: International Data Corporation
www.deloitte.com/us/AnalyticsTrends #AnalyticsTrends2016
19. Business borrows
from the sciences
Scientists have been applying advanced analytics
techniques to their toughest challenges for years, in
everything from molecular biology to astrophysics.
Now, their business-world counterparts are beginning
to borrow many of those techniques for their own
purposes – jump-starting their efforts with more
sophisticated capabilities.
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20. Scientists were into analytics before it was cool
• The discipline of analytics isn’t new—scientists have been
advancing analytics techniques for decades
• Techniques developed for scientific purposes hold
significant potential for addressing business challenges
Cross-pollination has already begun
• Analytics developed for DNA research have
been applied to text analytics initiatives
• One prominent private company hired dozens
of scientists from a major research university
• Developments like these are in their nascent
stages now—but a burst of activity is likely
The way forward
• Hire broadly from multiple disciplines spanning
statistical, biological, and physical sciences
• Expand and clarify the career track for data
scientists
• For companies that are not high-tech: Determine whether
your organization can viably compete with start-ups and
other advanced industries for the talent and skills you need
Business borrows from the sciences
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23. Forrest Danson
Principal
US Leader, Deloitte Analytics
Deloitte Consulting LLP
fdanson@deloitte.com
Tom Davenport
Independent Senior Advisor
Deloitte Analytics
tdavenport@babson.edu
Jim Guszcza
Senior Manager
Chief Data Scientist
Deloitte Consulting LLP
jguszcza@deloitte.com
John Lucker
Principal
Global Advanced Analytics
Market Leader
Deloitte Consulting LLP
jlucker@deloitte.com
Jon Raphael
Partner
Audit Chief Innovation Officer
Deloitte & Touche LLP
jraphael@deloitte.com
Adnan Amjad
Partner
Cyber Risk Services
Deloitte & Touche LLP
aamjad@deloitte.com
Steven Gold
Principal
Enterprise Science Leader
Deloitte Consulting LLP
stevegold@deloitte.com
Vivek Katyal
Principal
US Risk Analytics Leader
Deloitte & Touche LLP
vkatyal@deloitte.com
Beth Mueller
Partner
US Tax Analytics Leader
Deloitte Tax LLP
bethmueller@deloitte.com
Trend Watchers
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