New survey reveals progressive CIOs tap machine
learning to solve everyday work problems
A survey of 500 Chief Information Officers (CIOs) from
around the world by ServiceNow (NYSE:NOW) finds that machine
learning has arrived in the enterprise making material
contributions to everyday work. To realize its full value,
technology leaders must find skilled talent to work side-by-side
with machines in addition to redesign their organizations and
processes.
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For “The Global CIO Point of View,” ServiceNow surveyed CIOs in
11 countries across 25 industries to uncover the competitive
benefits of adopting machine learning and hear how those leaders
are driving results. IDC estimates that investment in machine
learning will nearly double by 2020,* and recent analysis shows
that machine learning specialist are among the fast growing roles
in IT.**
Humans Work Side-by-Side with Smart Machines for Better
Accuracy, Speed and Growth of Business
The survey finds a growing sense of confidence among senior
executives that machine learning will lead to faster and more
accurate decisions. Machine learning software possesses the ability
to analyze and improve upon its own performance without direct
human intervention, allowing them to make increasingly complex
decisions over time:
- More than half (52%) of respondents say
they are advancing beyond the automation of routine tasks, such as
security alerts, toward the automation of complex decisions, such
as how to respond to alerts.
- 87% said that they would get value from
the accuracy of decisions. In fact, 69% say decisions made by
machine learning will be more accurate than those made by
humans.
- 57% said that routine decision making
takes up a meaningful amount of employee and executive time, so the
potential value of automation is high. CIOs expect this decision
automation to contribute to their organization’s top line growth
(69%).
“We see three kinds of processes as targets for machine
learning—anything requiring rating, ranking or forecasting,” said
Chris Bedi, CIO at ServiceNow. “Everyday work such as the
assignment of IT tickets and prioritizing sales leads are already
delivering results. Machine learning has rapidly moved from hype to
reality.”
Machine Learning Specialists Alone Won’t Help CIOs Succeed in
Digital Transformation
Nearly three-quarters (72%) of CIOs surveyed said they are
leading their company’s digitalization efforts, and more than half
(52%) agree that machine learning plays a critical role. Nearly
half (49%) of the CIOs surveyed say their companies are using
machine learning and 40% are planning to adopt the technology.
But there are key talent, organization and process areas that
must be addressed in order for companies to take full advantage of
machine learning technology:
- Only 27% of CIOs have hired employees
with new skill sets to work with intelligent machines.
- Fewer than half (40%) of CIOs have
redefined job descriptions to focus on work with intelligent
machines, 41% cite a lack of skills to manage intelligent machines
and about half (47%) say they lack budget for new skills
development.
- CIOs cite data quality (51%) and
outdated processes (48%) as substantial barriers to adoption.
- Fewer than half (45%) have developed
methods for monitoring mistakes made by machines.
“Machine learning allows enterprises to digitize in ways that
were not possible before,” Bedi said. “To realize the full
potential of machine learning technology, CIOs must elevate their
role to be transformational leaders who influence how our
organizations design business processes, leverage data, and hire
and train talent.”
First-Mover CIO Advantages – Delivering Results Today
A select group of CIOs surveyed (fewer than 10%) are running
ahead of their peers in the use of machine learning. These “first
movers” provide a model for how CIOs can better utilize machine
learning:
- Almost 90% of first movers expect
decision automation to support top-line growth vs. 67% of
others.
- Roughly 80% have developed methods to
monitor machine-made mistakes vs. 41% of others.
- More than three-quarters have
redesigned job descriptions to focus on work with machines compared
with 35% of others.
- More than 70% have developed a roadmap
for future business process changes compared with just 33% of
others.
“First-mover CIOs who combine machine learning with new business
processes and skillsets will better support their enterprise
growth,” Bedi said. “They report higher levels of maturity in the
use of leading platforms, which allows them to concentrate on
innovation, such as automating complex decision-making, which
immediately impacts the bottomline.”
Financial Services Leads, Healthcare Industry Lags
The survey uncovered viewpoints from CIOs in the financial
services and healthcare sectors. Of note:
- CIOs from financial services are more
likely to say their company is moving from the automation of simple
decisions to the automation of increasingly complex decisions (68%,
vs. 52% of others). They are more likely to have made
organizational changes to accommodate digital labor, including
redefining job descriptions to focus on work with machines (62% vs.
36%), developing a roadmap for future process changes (52% vs.
35%), and recruiting employees with new skill sets (42% vs.
25%).
- CIOs in the healthcare industry remain
cautious. They are less likely to use machine learning across the
organization and less likely to say the technology will have a
positive impact on top-line growth, competitiveness, or reducing
risk. They are less likely to expect value from decision automation
in a number of functional areas, including security (70% vs. 80%),
operations (46% vs. 58%), risk and compliance (36% vs. 58%).
Five Steps to Achieve Value from Machine Learning
ServiceNow recommends how CIOs can jump start their journey to
digital transformation with machine learning:
1) Build the foundation and improve data quality – One of
the top barriers to machine learning adoption is the quality of
data. If machines make decisions based on poor data, the results
will not provide value and could increase risk. CIOs must utilize
technologies that will simplify data maintenance and the transition
to machine learning.
2) Prioritize based on value realization – When building
a roadmap, focus on those services that are most commonly used, as
automating these services will deliver the greatest business
benefits. At a high level, where are the most unstructured work
patterns that would benefit from automation? Commit to
re-engineering services and processes as part of this
transformation, and not simply lifting and shifting current
processes into a new model.
3) Build an exceptional customer experience – A core
benefit of increasing the speed and accuracy of decision-making
lies in creating an exceptional internal and external customer
experience. When creating a roadmap to implement machine learning
capabilities, imagine the ideal customer experience and prioritize
investment against those goals.
4) Attract new skills and double down on culture – CIOs
must identify the roles of the future and anticipate how employees
will engage with machines—and start hiring and training in advance.
CIOs must build a culture that embraces a new working model and
skills. That means establishing guidelines for executives,
engineers, and front-line workers about their work with machines
and the future of human-machine collaboration.
5) Measure and report – The benefits of machine learning
may be clear to CIOs, but other C-level executives and corporate
boards often need to be educated on its value. CIOs must set
expectations, develop success metrics prior to implementation, and
build a sound business case in order to acquire and maintain the
requisite funding. CIOs should also consider building automated
benchmarks against peers in their industry and other companies that
are of similar size.
ServiceNow applies machine learning to four of the biggest use
cases that IT has today. Preventing outages, categorizing and
routing work, predicting future performance, and benchmarking
performance against peers are examples of everyday work ServiceNow
automates in leading enterprises.
Additional Resources
- Video: “ServiceNow CIO Chris Bedi
Discusses Business Benefits of Machine Learning”
- Blog from CIO Chris Bedi: “Success in
Machine Learning Takes Transformational Leadership”
- Infographic
- CIO Landing Page
- Data Visualization
Survey Methodology
ServiceNow commissioned Oxford Economics to survey 500
CIOs about machine learning and automated decision-making.
Respondents are based in Austria, Australia, France, Germany, the
Netherlands, New Zealand, Singapore, Sweden, the United Kingdom and
the United States, and represent a broad range of B2B and B2C
sectors. The survey was administered via Computer-Assisted
Telephone Interviews (CATI). Founded in 1981 as a joint venture
with Oxford University’s business college, Oxford Economics
specializes in evidence-based thought leadership, forecasting, and
economic impact analysis.
*Worldwide Semiannual Cognitive/Artificial Intelligence Systems
Spending Guide, IDC, October 2016.
http://www.idc.com/getdoc.jsp?containerId=prUS41878616 Spending on
artificial intelligence and machine learning is expected to grow
rapidly from less than $8 billion in 2016 to $47 billion by 2020,
according to IDC.
**
https://www.ibm.com/analytics/us/en/technology/data-science/quant-crunch.html
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About ServiceNow
ServiceNow makes work better across the enterprise. Getting
simple stuff done at work can be easy, and getting complex
multi-step tasks completed can be painless. Our applications
automate, predict, digitize and optimize business processes and
tasks, from IT to Customer Service to Security Operations and to
Human Resources, creating a better experience for your employees,
users and customers while transforming your enterprise. ServiceNow
(NYSE:NOW) is how work gets done. For more information,
visit: www.servicenow.com.
ServiceNow and the ServiceNow logo are registered trademarks of
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ServiceNowMedia Contact:Colleen Haikes,
669-262-2001press@servicenow.comorInvestor Contact:Jimmy
Sexton, 805-453-8566ir@servicenow.com
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