Companies that use data analytics to launch successful innovation leverage the data they collect rather than take a business risk on guesswork. A prime example is Netflix, a company that gathers vast user data, including viewing habits, ratings and search patterns, to develop their strategy for original content. The company analyzes the genres, actors and themes that resonate with viewers and uses that data to create hit shows like House of Cards. This strategy enabled Netflix to successfully transform a DVD rental service into a global streaming giant.
Through the online BSBA in Business Analytics and Economics program from Youngstown State University (YSU), students learn how to conduct statistical analysis and data visualization to turn raw numbers into clear insights. They also gain hands-on experience using software to analyze data and understand economic principles that drive business decisions. Graduates of the program qualify for roles such as data analyst and market researcher, enabling them to help companies gain a competitive edge in their industry through evidence-based, data-driven decision-making, not hunches.
Analytics and Insights
Analytics and insights are essential for driving decision-making. Analytics typically uses math and computers to find patterns and trends among the facts and figures in vast datasets.
Insights from analytics illustrate what is happening between the lines, uncovering details that help determine what needs to be adjusted. There are three basic types of analytics: descriptive, predictive and prescriptive:
- Descriptive analytics looks at historical data to help decision-makers understand what happened in the past.
- Predictive analytics uses various methods to forecast future outcomes based on what happened before. Leveraging math, statistical models and machine learning, this data offers insight into potential future trends.
- Prescriptive analytics not only predicts future outcomes, but also suggests what needs to be done to get results in line with business goals.
Like Netflix, Amazon is another example of a business that uses predictive analytics. They use customer data to accurately manage inventory. Data tells them which items to stock, which reduces delivery times and makes for happy customers.
General Electric uses prescriptive analytics to take sensor data from machinery and predict when equipment needs maintenance. This helps them avoid downtime and saves money.
Statistical analysis, data mining, machine learning, sentiment analysis and cluster analysis are techniques that make sense of information and reveal valuable insights. Depending on the business goals — customer satisfaction, profits, efficiency — insights from data analysis help ensure plans are on track.
Using Data Analytics to Boost Operational Efficiency
Every business can benefit from operating more efficiently. The obvious benefits include reduced costs, higher revenue and profits, happier customers, better staff engagement and retention and higher productivity. Gathering data from customer feedback, sales reports and market trends provides a reasonable basis for informed decision-making as opposed to intuition or guesswork.
Data analytics also helps companies target which tasks should be automated, freeing up valuable resources for more strategic activities. A simple switch from manual Excel spreadsheets to Python for data processing saved one business 48 hours per month while increasing leads by 13X.
Predictive analytics allows businesses to anticipate the future rather than merely reacting to the past. Using past data helps uncover trends, but predictive modeling helps optimize forecasting and allows for proactive decision-making.
Data analytics makes information more accessible, empowering decision-makers at all levels of an organization. This allows for faster decision-making and response times.
Techniques for Optimizing Data Analytics Processes
Businesses are constantly seeking ways to enhance efficiency and productivity. Business process optimization is a key strategy involving analyzing and improving organizational processes. Whether a company is looking to reduce operational costs, improve service delivery or gain a competitive edge in their industry, optimizing business processes helps an organization meet customer demands, adapt to market changes and sustain long-term growth.
The World Journal of Advanced Research and Reviews published a paper on techniques for efficiency and productivity improvement. The paper describes several methods, which include data collection and management and predictive and prescriptive analytics. They also discuss process mining in which the actual flow of activities within a process is derived and can be visualized in process maps. Process monitoring tracks performance in real time.
Continuous monitoring and evaluation, along with agility to adapt and iterate, are critical for ongoing process optimization and performance improvement. Reviews, audits and feedback mechanisms provide valuable insights into successes and challenges.
Move Your Career Forward With the BSBA Business Analytics
In Youngstown State University’s fully online Bachelor of Science in Business Administration in Business Analytics and Economics program, students gain hands-on experience in software programming and data science applications. Through carefully designed coursework, they develop proficiencies in industry-relevant software programs including Excel, Tableau, SPSS and AI tools.
These skills are vital for various business analytics roles including data analyst, business intelligence analyst, economic consultant, financial analyst and market research analyst. Graduates complete the program with a distinct competitive advantage in a growing field with strong job prospects and earning potential.
Learn more about Youngstown State University’s online BSBA in Business Analytics program.
