How Linear Regression Can Work For Your Business

Hello, I am Amanda Fetch and currently based in NYC. I have a little over 20 years of experience working within the areas of Analytics, Data Science, Machine Learning, and AI in the biotech, retail, and entertainment industries. I am starting my PhD in Technology combination MS in Research Methods program in the Fall of 2022. I currently serve on a cyber security advisory board for an executive education certificate program at Ithaca College. I am in the process of working on a course as a Subject Matter Expert in the areas of Big Data and AI through Emeritus and Bocconi School of Management in Milan. I hope that you enjoy my content.?

#data #analytics #tech #ai #business #technology #datascience #dataanalytics #marketing #machinelearning #automation #linearregression #regression #analysis #algorithm #strategy

How Linear Regression Can Work For Your Business

Like a game of chess, business decisions require strategic planning and analysis in order to make a move. Regression analysis aids organizations in better understanding relationships within their data turning the data into actionable insights in order to make better business decisions and that move.?This data-driven decision making eliminates assuming a hypothesis removing any guesswork. A simple linear regression explores statistically the strength of the relationship between one independent variable (X), and one dependent variable (Y). An independent variable, which may be referred to as an experimental or predictor variable, is the variable manipulated in a study to observe the effects on the dependent variable(s).

Patterns in data may be found which can be applied to business operations. Linear regression is helpful for businesses as it can be used in terms of forecasting and optimization of processes and strategy.

Business Cases For Using Linear Regression

Linear regression is used across organizations in many ways including evaluating trends and customer engagement patterns, forecasting sales, pricing impacts, risk management and more. Linear regression is consistently used in predicting consumer behavior and understanding your customer, studying trends, and assisting on which metrics to hone in on in order to stay profitable. When studying trends in consumer purchasing behavior, linear regression can predict peaks and valleys in demand forecasting which can then assist in budgeting appropriately. This logic can be applied to advertising spend and revenue. A relationship can be studied between the two to predict what medium, for example, tv, banner ads, or print may bring in the most revenue based on statistical analysis and what portion of a budget should be allocated to each medium to drive the most return on investment (ROI). In this example, a simple linear regression may be used with spending as the independent variable and revenue as the dependent variable. Once spend is allocated appropriately linear regression can be used to analyze consumer behavior and price elasticity. Data Scientists or Analysts can study when prices change how much volume of a product sells. The data can be analyzed with quantity sold as the dependent variable and price as the independent variable.

A newer phenomenon in the Data Science world is professional sports teams using linear regression to measure the effects of different training programs on players and their performance on the field or court. One example of this is the NBA tracking players doing weekly yoga sessions and weightlifting sessions as part of their training to see how many points a player may score in games after being exposed to a certain regimen. The linear regression was fitted with yoga sessions and weightlifting as the independent variables and total points scored as the dependent variables in the analysis.

A final example of this is in the medical field of which linear regression is being used to track prescription drug dosage and patient outcomes of vital signs. Depending on the dose, if for example a patient has improved vitals maybe the medication can be scaled back. If the reverse occurs and vitals become worse more drug may be administered. All of this is being done today using algorithms, simple data science, and analysis.?

Benefits of Using Linear Regression in Business

A huge benefit to using linear regression for small business owners is that it helps with prioritization and determining which areas of operations to focus on within your business. On the flip side it also shows areas of operations that you can scale back and place on the back burner without jeopardizing workflow. Resources within your business can be allocated more efficiently which can lead to supply chain optimization. Optimizing supply chain leads to cutting costs which positively impacts your bottom line.

Linear regression is a simple algorithm for businesses and Data Science teams to study, analyze, and interpret. This is a modeling technique that results can be found quickly in a time crunch compared to other algorithms. A small amount of variables can be studied versus more complex algorithms which may require many factors in order to make a judgement call. A downfall to this is with the potential use of only a few variables for analysis if the independent variables are correlated this can lead to false positive results and be misleading. There is also the issue of overfitting when the model becomes too complex due to a large amount of parameters in relation to observations.?

Conclusion

In conclusion, linear regression assists businesses in order to make more strategic decisions based on data and analysis versus gut intuition.?Most organizations, due to digital transformation, are becoming more data driven. Using linear regression to assist in optimizing business operations, making spend decisions, forecasting, and allocating resources and spend is a non complex and efficient way to making better informed decisions within your organization within many facets of your business.?