How Machine-Driven Decisions Will Affect IT

 
 
By Dennis McCafferty  |  Posted 10-19-2017 Email
 
 
 
 
 
 
 
 
 
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    How Machine-Driven Decisions Will Affect IT
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    How Machine-Driven Decisions Will Affect IT

    CIOs expect that, within the next several years, machines will make critical decisions about security, finance and other key business and operational areas.
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    Immense Interest
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    Immense Interest

    89% of the CIOs surveyed said their organization is using machine learning in some way—in business areas, as a pilot or in a research or planning phase.
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    Most Important Capabilities of Machine Learning
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    Most Important Capabilities of Machine Learning

    Automating repetitive tasks: 68%, Making complex business decisions: 54%, Recognizing data patterns: 40%, Establishing links between events: 32%, Supervising learning: 32%
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    Decisive Step
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    Decisive Step

    57% of the CIOs surveyed said even routine decision-making takes up a meaningful amount of employee and executive time, and 52% said they are moving beyond the automation of routine tasks and moving toward the automation of more complex decisions.
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    Spot On
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    Spot On

    87% said machine learning provides "substantial" or "transformative" value in coming up with accurate decisions.
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    Market Edge
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    Market Edge

    69% of the CIOs surveyed expect decision automation to contribute to their enterprise's top-line growth, and 64% said it will make their company more competitive.
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    Auto Focus: Best Defense
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    Auto Focus: Best Defense

    70% said decisions about security operations will be largely or completely automated by 2020, up from 24% currently.
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    Auto Focus: Consumer-Minded
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    Auto Focus: Consumer-Minded

    77% said decisions about customer management will be largely or completely automated—or at least automated in a way that will require some human intervention—by 2020, compared to 69% today.
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    Auto Focus: Fiscally Sound
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    Auto Focus: Fiscally Sound

    77% said decisions about finance will be largely or completely automated—or at least automated in a way that will require some human intervention—by 2020, up from 52% currently.
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    Biggest Barriers to Decision Automation
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    Biggest Barriers to Decision Automation

    Insufficient data quality: 51%, Outdated processes: 48%, Lack of human skills: 47%, Budget limitations for tech and skills: 41%, Inability of machines to make complex decisions: 32%
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    Under-Prepared
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    Under-Prepared

    Just 16% of CIOs have established workforce size and role plans to accommodate machine learning, and only 36% have developed a roadmap for future process changes.
 

With most enterprises now using machine learning in some way, CIOs and their tech teams are looking ahead to the next big step in this emerging technology: the automation of decisions that affect business operations and the achievement of strategic goals, according to a recent survey from ServiceNow. The resulting report, "The New Agenda for Transformative Leadership: Reimagine Business for Machine Learning," reveals that the majority of survey respondents believe that decision automation will contribute to their company's top-line growth, while also increasing its ability to compete. Cyber-security, customer management and finance are among the specific areas of focus for machine-driven decision making. To ensure success, however, CIOs will need to gain buy-in from top leadership to overcome barriers in the form of budget limitations, outdated processes and a lack of needed talent on staff. "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," according to the report. "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. For example, CIOs monitor the IT percentage of revenue, but the promise of an automated enterprise will allow them to focus on margin contribution as a measure of success. … Similarly, the 'run vs. grow' metric used to track productivity should evolve to a percentage of work eliminated or fully automated. CIOs should also consider building automated benchmarks against peers in their industry." An estimated 500 global CIOs took part in the research, which was conducted by Oxford Economics.

 
 
 
 
 
Dennis McCafferty is a freelance writer for Baseline Magazine.

 
 
 
 
 
 

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