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All in with Analytics: Giving Students a Foundation For Business Analytics

In each business field, be it marketing or management, finance or supply chain, each discipline has specific questions, specific data sources, specific analytics techniques, and ways we communicate the findings.  Business analytics uses available data to address these questions across different disciplines.

As a relatively new core course in the business curriculum, it is essential to provide a foundation for all students.

One example of a way to frame business analytics for undergraduate students is the use of the SOAR Analytics Model to address business questions, which is comprised of the following: 

  1. Specify the Question
    There is an adage that says, ‘Your data won’t speak unless you ask it the right question”.  For this reason, it is important to carefully specify the question in a way that the data has a chance to address it. And to ensure that addressing that specific question actually ultimately helps instructors.
  2. Obtain the Data
    Finding the relevant data to address the question is critical.  Once the data is found, questions regarding its data type (numerical, categorical, etc.) and its data qualities (Is the data complete? Is it accurate? Is its use ethical?, Is data privacy maintained? etc.) are tantamount.
  3. Analyze the Data
    Once the question is specified and appropriate data is obtained, it is time to apply appropriate analytics techniques that might include summary statistics, box plots, pivot tables, regression, goal-seek analysis, time-series analysis, sensitivity analysis, etc.  Since several techniques are available, it is common to use multiple techniques.
  4. Report the Results
    Once the analysis is complete, it is time to communicate the findings to the stakeholders. Some will use statistics or tables, others use visualizations including dashboards.  Understanding stakeholder needs is critical for reporting results in a way that is most useful.

Using the SOAR Analytics Model, or other similar models helps give students the foundation they need to learn analytics.  They know what they are doing, and what the next steps are. Learn more about the SOAR Analytics Model in Introduction to Business Analytics

About the Author

Vernon J. Richardson is a Distinguished Professor of Accounting and the W. Glezen Chair in the Sam M. Walton College of Business at the University of Arkansas. He received his BA, MAcc, and MBA from Brigham Young University and a PhD in accounting from the University of Illinois at Urbana Champaign. He has taught at the University of Arkansas, Aarhus University, Baruch College, Brigham Young University, Chinese University of Hong Kong Shenzhen, Baruch College, University of Kansas, Xi’an Jiaotong Liverpool University, and China Europe International Business School (Shanghai). He was formerly an editor at the Accounting Review and is currently an editor at Accounting Horizons. He also served as associate editor at MIS Quarterly, Journal of Information Systems, and the International Journal of Accounting Information Systems. He has published articles in the Accounting Review, Journal of Accounting and Economics, Contemporary Accounting Research, MIS Quarterly, Journal of Management Information Systems, Journal of Information Systems, Journal of Operations Management, and the Journal of Marketing. Dr. Richardson has authored the four textbooks emphasizing data analytics with McGraw Hill titled “Introduction to Business Analytics (with Marcia Weidenmier Watson), “Data Analytics for Accounting” (with Katie Terrell and Ryan Teeter), “Introduction to Data Analytics for Accounting” (with Katie Terrell and Ryan Teeter) and “Accounting Information Systems” textbook (with Janie Chang and Rod Smith).

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