6 Ways To Master The Data-Driven Enterprise - InformationWeek

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IoT
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Data Management // Big Data Analytics
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5/4/2015
07:06 AM
Lisa Morgan
Lisa Morgan
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6 Ways To Master The Data-Driven Enterprise

Data-driven companies share characteristics that enable them to achieve more with their data than others in their industries. We reveal what separates the masters from the wannabes.
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Forward Thinkers 
Data-driven enterprises consider where they are, where they want to go, and how they want to get there. To ensure progress, they establish KPIs to monitor the success of business operations, departments, projects, employees, and initiatives. Quite often, these organizations have also established one or more cross-functional committees of decision-makers who collectively ensure that business goals, company practices, and technology implementations are in sync.
'The companies that have integrated data into their business strategies see it as a means of growing their businesses. They use it to differentiate themselves by providing customers with better service, quicker turnaround, and other things that the competition can't meet,' said Ken Gilbert, director of business analytics at the University of Tennessee's Office of Research and Economic Development, in an interview with InformationWeek. 'They're focused on the long-term and big-picture objectives, rather than tactical objectives.'
(Image: Unsplash via Pixabay)

Forward Thinkers

Data-driven enterprises consider where they are, where they want to go, and how they want to get there. To ensure progress, they establish KPIs to monitor the success of business operations, departments, projects, employees, and initiatives. Quite often, these organizations have also established one or more cross-functional committees of decision-makers who collectively ensure that business goals, company practices, and technology implementations are in sync.

"The companies that have integrated data into their business strategies see it as a means of growing their businesses. They use it to differentiate themselves by providing customers with better service, quicker turnaround, and other things that the competition can't meet," said Ken Gilbert, director of business analytics at the University of Tennessee's Office of Research and Economic Development, in an interview with InformationWeek. "They're focused on the long-term and big-picture objectives, rather than tactical objectives."

(Image: Unsplash via Pixabay)

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PeterF028
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PeterF028,
User Rank: Moderator
5/27/2015 | 2:51:53 PM
Forced reality
IoT is making the move toward data even more significant. Fortunately most CIOs (81%) already have it heavily factored into ongoing plans.  Without a good strategy of course, data can rapidly get out of hand. Peter Fretty, IDG blogger working on behalf of CSC. 
PeterF028
50%
50%
PeterF028,
User Rank: Moderator
5/27/2015 | 2:49:01 PM
Forced into data
As IoT becomes a reality, far more organizations will be essentially forced into being data driven organizations. According to the CSC CIO Survey, 81 percent already say data plays a heavy role in their operations. Peter Fretty, IDG blogger working on behalf of CSC
LisaMorgan
50%
50%
LisaMorgan,
User Rank: Moderator
5/6/2015 | 2:35:50 PM
Re: Very very frightening...
True and LOL.
batye
50%
50%
batye,
User Rank: Ninja
5/5/2015 | 2:09:08 AM
Re: Think Big
@Li Tan, I would say you are right on the money :) but would like to say with technology developing soo rapidly this days - it like we could not even trust the past - knowlege...
Mike Cuddy, Toromont CIO
100%
0%
Mike Cuddy, Toromont CIO,
User Rank: Apprentice
5/4/2015 | 5:09:27 PM
Very very frightening...
New insights from data can be threatening.  Tribal knowledge comes under attack. Foundations of assumptions start to crack. Oh Oh.
LisaMorgan
50%
50%
LisaMorgan,
User Rank: Moderator
5/4/2015 | 2:29:02 PM
Re: Think Big
Great points.
Li Tan
100%
0%
Li Tan,
User Rank: Ninja
5/4/2015 | 9:03:10 AM
Think Big
I think the critical aspect here is to think big in big-data era. We cannot simply use the experience from the past when we work with RDBMS. Furthermore, we need to think big - instead of just focusing on data itself, we need to mainly focus on how we can draw useful, reliable conclusion by using efficient analytics method.
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