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Tips to Build a Data Driven Culture

Paul Korzeniowski's picture
B2B Content producer, Self-employed

Paul is a seasoned (basically old) freelance B2B content producer. Through the years, he has written more than 10,000 items (blogs, news stories, white papers, case studies, press releases and...

  • Member since 2011
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  • Nov 9, 2021
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Nowadays, information has become corporate lifeblood, empowering utitliies to deliver products and services to customers more effectively. As a result, business objectives and processes are changing. To make the transition, energy company executives need to implement data analytics best practices.

The volume of information available in corporations has been rising at a rapid rate. In fact, the Energy and Utility Analytics market was valued at $1.8 billion in 2020, and is estimated to reach $3.9 billion in 2028, a CAGR of 15.83%, according to Data Labs Forecast.

As a result, the ability to collect and analyze information has become a key to energy businesss success or failure. So, how can an energy company create a data driven corporate culture?

The Data Analytics Process

The first step that managers need to take is understanding its business strategy and strategic areas. Then, the company needs to align analytic projects, with them so they positively impact the company in its most important areas.

Also, they must examine where their data lies. In many cses, information is siloed in various applications strewn across the organization. For instance, a customer record may be found in billing, marketing, and customer service applications. How the customer is described typically varies from system to system, so, the company needs to create consistency and consistency among its information sources.

Buiilding a data model takes time and effort. Trends only become evident after an organization has information that can be correlated. The more data points, the deeper the analysis. But the process takes time, and they must have the patience to examine information in a long term manner.

Data is becoming energy company organizational lifeblood. Consequently, utilities need to build up their data analytics expertise. They must understand what information is important, clean their data, correclate it, and be patient in order to reap analytics’ potential benefits.

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