What data analytics can do for your business

By Ben Coulter and Joe Dery 

Ben Coulter, Ed.D., is southeast regional director for Western Governors University and serves as chancellor of WGU North Carolina. Joe Dery, Ph.D., is dean of data analytics, computer science and software engineering at Western Governors University. “Information is the oil of the 21st century, and analytics is the combustion engine.”

— Peter Sondergaard, chairman of the board of Digitopia 

While many business executives and entrepreneurs have an idea of what data analytics is, we have a viewpoint for the term and it’s definitely not crunching numbers for the sake of crunching numbers. To us, data analytics is the creative use of data and statistical modeling to tell a compelling story that not only drives strategic action, but also results in business value. 

Types of data analytics

In the business and academic world, we speak about four types of data analytics. 

1. Descriptive analytics – examining data to determine trends and see what happened or is currently happening (think “BI,” or what’s traditionally been referred to as business intelligence).
2. Diagnostic analytics – comparing trends and determining causal relationships to answer the question, “Why did this happen?” (think “statistical analysis”).
3. Predictive analytics – analyzing historical data and current trends to make informed predictions about what might happen in the future (think “AI” and its subset, machine learning).
4. Prescriptive analytics – considers possible factors and scenarios to help make data-driven decisions about what to do next (think “action”). 

Regardless of if you run a small startup or multinational company, data analytics can help your business in the following ways, just to name a few:

• Inform and enhance decision making
• Streamline and improve operational efficiencies
• Manage risks
• Provide greater insights into target markets
• Identify new product/service opportunities 

Key players on your team

To incorporate this function into your business operations – and hopefully see the direct benefits – the first step is to hire qualified data analytics professionals. Our colleagues in this field like to say that data analytics is a team sport. Don’t just hire someone and leave them on a proverbial island only to be consulted when someone has a question. Make them part of the team! 

The best way to work with data analytics professionals is to embed them into your project teams. Let them collaborate with your employees with different areas of expertise. We also recommend hiring a variety of skillsets. Some professionals specialize in technical skills like programming languages, while others excel at statistical analysis or data wrangling and cleanup. 

Your company should provide opportunities to enhance empathy and storytelling among your team members, so they can better see, hear and feel the human impact of the data they are studying. Finally, use their findings and recommendations to drive actions for your business. 

To help train more experts in this fast-growing field, accredited online Western Governors University has introduced a new Bachelor of Science degree in data analytics. This degree program combines a surgically balanced, three-level approach including programming, math and business influence, with practical hands-on projects. WGU focuses on helping students learn to take data and turn it into meaningful stories that help leaders make decisions. The curriculum includes dedicated courses in storytelling, design thinking and change management, in addition to industry certifications like CompTIA’s Data+ & Project+, AWS’s Cloud Practitioner, and a custom Udacity Nano Degree. This intentional design ensures that students graduate knowing how to effect change in the workplace. 

If data analytics truly is the combustion engine that can drive your business forward, consider incorporating or enhancing this function in your business operations and upskilling your staff. Your employees and your bottom line could realize the benefits sooner than you think. 

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