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The Role of Statistics in Business Decision Making

Business colleagues working together on a laptop. They are both young business people dressed in business attire in a modern office. Could be an interview, training or consultant working with a client. There is a TV with a presentation with charts and graphs.. There is paperwork, coffee and technology on the table. Mixed ethnic group.
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Published: September 15, 2023

Alexandra Levit
Inspiration at Work
Summary

Explore the importance of statistics in business decision making and how data interpretation and trend analysis can boost profitability.  

      Small business owners who want to drive innovation and grow their companies can capitalize on the usefulness of statistics.     

      The field of statistics involves collecting, analyzing, interpreting, and presenting data. Statistics like correlation, hypothesis testing, and others can be useful in forecasting business trends and understanding and anticipating customer data and behavior, among other things.

      Here we'll describe the role of statistics in business decision making and how statistical tools may help you achieve your business goals.   

      The Mechanics of Analysis   

      Collecting customer information from your website or database is one thing, but effective data interpretation can open new opportunities for useful insights. Fortunately, both legacy and newer statistical tools can make business statistics easily accessible.    

      Correlation    

      This core statistical measure expresses the extent to which two variables change at a constant rate. In business, it can describe relationships without necessarily saying that one variable causes the other. Correlation might be used, for example, to determine how closely your advertising spend and revenue are related.   

      Linear Regression Analysis    

      Linear regression analysis can evaluate the relationship between two variables and forecast a variable based on its relationship to another one. The variable you want to predict is called the dependent variable, while the variable you're using to predict the other’s value is called the independent variable. For example, you can use linear regression analysis to determine how your year-long uptick in e-commerce sales is likely to play out in the near future.   

      Hypothesis Testing    

      This method can be used by owners to substantiate claims about current business issues. It involves first formulating a null hypothesis and an alternative hypothesis. The null hypothesis is a statement you believe to be true based on historical data. The alternative hypothesis represents the assumption being tested and is generally the opposite of the null hypothesis.    

      A hypothesis test always assumes the null hypothesis is true and then tests to see if it can be nullified. If the data nullifies the null hypothesis, it substantiates the alternative hypothesis. In business, hypothesis testing can be a good way to ensure your assumptions are sound before taking action based on them.    

      For instance, if you believe opening up several new brick-and-mortar locations will dramatically increase your sales, you might try hypothesis testing to implement the plan on a smaller scale: perhaps one new location can bring the desired results.     

      Random Sampling    

      Also known as probability sampling, this tool selects participants at random from a given population. You can then collect extensive data from this subset and extrapolate an assumption about the larger population.   

      For example, suppose you're curious about whether your customer base will respond positively to a new product type. You aren’t able to provide samples to every customer in your database, so instead you can offer them to 50 customers selected at random. If the new product is a hit, you might decide to proceed with a roll-out.   

      AI Data Analysis    

      Artificial intelligence can examine large amounts of data to identify patterns and trends, which can then help optimize your business processes.  

      A benefit of data analytics can be not having to necessarily know what you’re looking for up front. For instance, your AI-based tool might review all customer purchase data from the last year and proactively suggest you're experiencing greater churn due to a change in your shipping model.    

      Starting from Scratch    

      You can start using statistics to inform decisions by building a culture of data literacy and data fluency in your business. Utilizing online courses or certifications, every leader can learn the basics of data and technology tools that can help solve vexing problems.    

      As a team, you can brainstorm the key metrics you want to track and measure, such as customer satisfaction, and then determine the tool that can provide the most informative data.    

      The Takeaway  

      In today’s rapidly shifting business environment, it can be critical for owners to understand what’s happening in their organizations in real-time. Utilizing statistics in business can ensure you always have solid insights at your fingertips without needing to become an expert yourself. By implementing just a few of these strategies, you can begin using your data as a competitive advantage and tool for consistent improvement.   

      A version of this article was originally published on September 12, 2018.  

      Photo: Getty Images     

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