Top Pain Points for Energy Companies

By Matt Boone, Datameer

The energy industry has its eye on big data. From solar energy startups to massive oil corporations, energy companies are putting data to work to not only streamline business processes and boost revenues, but also to better manage the world’s energy resources. Well efficiency (completion and production) and lowering energy consumption are a couple of examples that have already been pursued aggressively with tangible results.

We continue to witness energy companies evaluating big data to ignite business operations, yet they keep getting stumped on the same questions, time and again. Grappling with how to initiate big data projects, create a plan and execute on it, can be tricky business.

Here are a few suggestions on how to start tackling three common questions we hear from energy companies:

How do I get support?

It’s difficult to get buy-in on new, unconventional strategies–especially at large corporations when the current architecture seemingly isn’t broken. When working to implement big data analytics, operations and IT liaisons are often hesitant to implement dramatic strategies for fear of losing pace to competition. At the same time, they recognize that they are sitting on a treasure trove of data and they want to put it to use.

The problem? There is just so much information that it’s hard to know where to start. If you don’t know where to start, it’s hard to make a push for a different strategy, especially if your current strategy isn’t broken.

The sheer volume of data can easily dismay even the savviest professionals. Too often the first instinct is to dive in and see what insights work their way to the top. But much of this data is unstructured and this often leads to feeling ineffective and overwhelmed.

You can get a quick win with a single, simple use case that demonstrates tangible value. Once you’ve sold your organization on the value, they will be more likely to move forward with other data-driven projects.

Where do I start?

As mentioned, it works best to pick one use case, not only to get buy-in, but also to stay focused. But with so many ways to apply big data, where do you start?

Select a case that is targeted to your field, for example power companies may opt to optimize energy grid infrastructure. Work on that use case until you achieve measureable results. Better yet, choose a use case where you already know the answer. Then you know whether or not your new data-driven process works.

Rather than blaze a new trail right out of the gate, tackle a single use case first and then focus on more complex issues unique to your company.

Who has the answers?

The IT department is typically responsible for a company’s entire big data initiative. While this certainly makes some sense, the reality is that the entire organization should have access to the data. IT managers have to run their initiatives through the business intelligence (BI) team, the extract, transform, load (ETL) team and a database administrator (DBA), to fully understand the goals of a data strategy.

If IT is the sole group responsible for delivering on big data initiatives, then the process can resemble a laundry list of checkpoints. By the time the data passes through the funnel, it’s too late to make a quick decision. Organizations must make their data accessible across all business processes and teams. Namely, business analysts need the same access that IT has to the company data. Expanding data accessibility creates transparency, and, ultimately, empowers an organization to better delegate duties and reach decisions faster.

Entrusting all of your big data processes to just one department can lead to bottlenecks. It can also lead to losing valuable information in translation. Make your data accessible, eliminate the laundry list and stop asking where your answers are.

Big data is transformative for energy companies. But it’s vast, complicated and a lot to deal with all at once. Flailing wildly at your data can uncover as many pain points as it solves. Something as simple as establishing a plan, picking a use case, making the data accessible to all the relevant teams and going one step at a time will help ensure your organization is able to generate the insights it needs to stay ahead of competition.

Matt Boone is a regional sales director for Datameer, an end-to-end big data analytics application for Hadoop designed to make big data simple for everyone.


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