Why Data Analytics Projects Miss the Mark

 
 
By Dennis McCafferty  |  Posted 10-31-2016 Email
 
 
 
 
 
 
 
 
 
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    Why Data Analytics Projects Miss the Mark
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    Why Data Analytics Projects Miss the Mark

    For many organizations, existing data-analytics infrastructures are too complicated, and it's difficult to find qualified job candidates to helm analytics projects.
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    Irreplaceable Function
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    Irreplaceable Function

    90% of survey respondents said data analytics is no less than "very" important to their organization, and 39% indicate that it is "critically" important.
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    Top Data Analytics Goals
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    Top Data Analytics Goals

    Increasing operational efficiencies: 76%, Informing strategic decision-making: 68%, Spurring growth: 59%, Managing costs: 58%, Responding to competitive pressure: 36%
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    Major Hurdles, Part I
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    Major Hurdles, Part I

    40% of survey respondents said user adoption of data analytics is much lower than originally planned, and 39% said these initiatives go well over budget.
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    Major Hurdles, Part II
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    Major Hurdles, Part II

    36% said data-analytics users will complain about what they receive as a result of these efforts, and 31% said that—while the projects get done—they are never "quite ready" for user involvement.
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    Rigid Structure
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    Rigid Structure

    51% said their existing data-analytics infrastructure is too complex and/or too inflexible to "do what we want."
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    People Problem
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    People Problem

    47% said they are not able to find the right personnel with the right technical expertise for data analytics.
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    Most Difficult Data/Analytics Skills to Find
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    Most Difficult Data/Analytics Skills to Find

    Database tuning: 45%, Data science: 44%, Data engineering: 39%
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    Inherent Obstacle
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    Inherent Obstacle

    70% said the existing infrastructure does not allow for them to deliver what business stakeholders want to do with data.
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    Unresolved Issue
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    Unresolved Issue

    71% said it is difficult to troubleshoot problems that they encounter with data-analytics technologies.
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    Off-Premise
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    Off-Premise

    53% said their organization either already has a cloud-based solution in production for data analytics or is piloting one—and another 27% either has plans to do this, or are considering it.
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    Available Avenue
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    Available Avenue

    92% said that a "pay as you go" approach to data analytics would at least present the potential for them to "try more things" with these projects.
 

While data-analytics projects have the potential to contribute greatly to organizational goals, professionals overseeing these efforts are encountering a wide range of issues that stand in the way of success, according to a recent survey from Snowflake Computing. The accompanying report, titled "Data Analytics: Beyond the Hype," indicates that companies are seeking to increase operational efficiencies while making better decisions about strategies through these technologies. They also want to spur growth while managing costs more effectively. However, they're discovering that user adoption rates are much lower than expected. At the same time, data analytics initiatives are going over-budget. In most cases, existing data-analytics infrastructures are too complicated, and it's very difficult to hire job candidates with the right technical expertise to make these programs work. "It is the norm for technology and business publications to discuss the importance of data in today's world," according to the report. "From cutting edge technology services to venerable enterprises that have been in the same industry for generations, businesses are looking to their data to find ways to reduce costs and grow revenues. But while innovative and inspiring stories about use of data to build businesses abound, on the ground the story is often different. What gets lost in the excitement is the reality that it's surprisingly common for analytics projects to fail." More than 375 employees and executives who work on data initiatives took part in the research, which was conducted by Dimensional Research.

 
 
 
 
 
Dennis McCafferty is a freelance writer for Baseline Magazine.

 
 
 
 
 
 

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