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10 real examples why data analytics is the new oil


why data matters to oil operationsAre you convinced of the power and potential of data and predictive analytics, but still a bit hazy on what it can really do for you and your company, then I’m please to say that you’re in the right article.

Here are 10 very real and practical examples of what you could accomplish by using data analytics.

  1. Dialogue with employees in real time
    When an employee start his work day their smart phone will tell them what they need to do and what they may have forgotten to do. Data will also allow them to identify possible risk situations before an accident might occur.
  2. Re-develop your products
    Uncover the sentiments of your customers and even segment those in different geographical locations or among different demographic groups. You can test thousands of different variations of computer-aided designs in the blink of an eye so that you can check how minor changes in, for instance, material affect costs, lead times and performance. You can then raise the efficiency of the production process accordingly.
  3. Perform risk analysis
    Predictive analytics, fueled by data analytics allows you to scan and analyze reports so that you permanently keep up to speed on the latest developments in your operations. Detailed health-tests on your employees, suppliers and customers are another goodie that comes with data. This will allow you to take action when one of them is in risk of defaulting.
  4. Keeping your data safe
    With real-time Big Data analytics you can, for example, flag up any situation where numbers – potentially sensitive machine data – are stored or emailed out and investigate accordingly.
  5. Create new revenue streams
    By adding data analytics to your product offerings you can easily create a new revenue channel.
  6. Customize your field operations in real time
    Data analytics allows you to personalize the content or look and feel of your field operations in real time to suit each consumer entering your work sites, depending on, for instance, their roles, department, or from sub-contractors.
  7. Reducing maintenance costs
    Traditionally, factories estimate that a certain type of equipment is likely to wear out after so many years. Consequently, they replace every piece of that technology within that many years, even devices that have much more useful life left in them. Big Data tools do away with such unpractical and costly averages. The massive amounts of data that they access and use and their unequaled speed can spot failing grid devices and predict when they will give out. The result: a much more cost-effective replacement strategy for the utility and less downtime, as faulty devices are tracked a lot faster.
  8. Offering tailored OH&S
    By maintaining a zero-harm policy and tracking data (e.g. incidents) you can better tailor a solution for each employee to better help them understand areas they need assistance with.
  9. Offering enterprise-wide insights
    Previously, if business users needed to analyze large amounts of varied data, they had to ask their IT colleagues for help as they themselves lacked the technical skills for doing so. Often, by the time they received the requested information, it was no longer useful or even correct. With data tools, the technical teams can do the groundwork and then build repeatable algorithms for faster searches. In other words, they can develop systems and install interactive and dynamic visualization tools that allow business users to analyze, view and benefit from the data.
  10. Get a promotion by making better decisions
    The better you perform the better chance of promotion you might get. Data will help you understand your operations so you can make better decisions. And look more professional.