Using Regression Analysis in Accounting

In today’s digital age, medium and large businesses have access to more data than they know what to do with. Over the next decade, the issue that many companies face won’t be data collection — it will be about understanding what to do with the massive amounts of data collected daily. As a result, there will be a drastic need for accounting professionals with regression analysis knowledge.

Regression analysis is a crucial tool companies use to draw insights from their data. It is not enough for aspiring accounting professionals to simply understand regression analysis. They must also know how to clearly communicate findings to upper management. Students can learn these concepts in an advanced degree program, such as the Eastern Washington University (EWU) online Master of Business Administration (MBA) with an Accounting Concentration.

What is Regression Analysis?

Regression analysis is one of the most valuable tools in an accountant’s arsenal for solving a wide variety of business problems. Business software site G2 defines regression analysis as “a statistical process that helps assess the relationships between a dependent variable and one or more independent variables.”

Regression analysis uses formulas and statistics to determine the relationship between two or more variables. One variable is always independent and impacts the other variables (dependent variables) in a measurable way. Simple regression is when you have just one independent and dependent variable, but multiple independent variables influencing one dependent variable is known as multiple regression.

You can calculate simple linear regression using this formula: y = x+ b.  In this formula, y is what you’re trying to find, x is the variable the outcome depends on, and b is the value if your activity is zero. However, this is just the beginning. You can analyze multiple variables at one time by using more advanced formulas.

Regression Data Analysis in Business

Regression analysis can help solve dozens of different business problems. According to InfluxData, most accountants use regression analysis to do the following:

  • explain events that they want to understand
  • predict the future occurrences
  • use data to decide what to do

For example, many companies use regression analysis to determine the effectiveness of their advertising spend. Let’s say that a company wants to figure out how the money they spend on advertising has impacted their sales. The first step is to collect data from past advertising campaigns and the corresponding sales data. Then, they can use simple linear regression to find a line that best fits this data — usually done with Microsoft Excel or a similar business analytics tool. Once they have a line of best fit, it will give them a formula that predicts sales volume based on advertising spend.

A line that slopes up and to the right tells the company that investing more money into advertising will likely lead to more sales, but a horizontal or declined line means that more advertising spend will not lead to higher sales.

Regression Analysis in Business

Business professionals can use regression analysis for much more than just finding the correlation between advertising and sales. Business intelligence platform Yurbi highlights other common areas where companies leverage regression analysis, such as the following:

  • Operational efficiency and optimization: Companies can use regression analysis to analyze operational efficiencies in business to eliminate guesswork from decision-making and provide actionable insights. For example, a company could analyze the relationship between wait times of callers and complaints in the customer service department.
  • Supporting decisions: Regression analysis supports management team decisions, reducing guesswork. For example, regression analysis can measure the impact of various factors (like training hours, work experience or education) on employee performance metrics such as sales targets, project completion times, or customer satisfaction scores. This data can then be used to make informed decisions regarding training programs, recruitment strategies or where to reduce headcount.
  • Correcting errors: Regression analysis can also help measure the effectiveness of decisions and backtrack on any poor decisions. For example, if a company decides to raise prices, it can measure how the price change impacts sales volume over the next quarter. If the price increase leads to lower sales, the company can reverse its decision and default to the original pricing.

Advancing Your Accounting Career

If you’re interested in pursuing a career as an accountant, you can expect regression analysis to play a big role in your career. You’ll lean on regression analysis heavily for actions like creating budgets and forecasts and analyzing which key performance indicators (KPIs) lead directly to increased revenue.

However, it’s not enough to mindlessly run these analyses — it’s much more important to communicate your findings to the company’s leadership team to support better decision-making. This is what separates you from a computer program.

To learn how to communicate with C-suite executives, many aspiring accountants will obtain an MBA. This degree will give you an overarching understanding of how a business runs so that you know how your regression analyses play into the bigger picture.

EWU’s online MBA with an Accounting Concentration program offers a course in descriptive and inferential statistics: Quantitative Analysis in Business. In this course, students learn basic regression analysis, chi-square analysis and quality control methodology. Those with an MBA in accounting are highly employable candidates in the job market, and students can complete this online program in as few as 10 months.

Learn more about Eastern Washington University’s online Master of Business Administration with an Accounting Concentration program.

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