Importance of Business Stastics in Market Research

Importance of Business Statistics

Business Statistics refers to applying statistical tools and techniques to business and managerial issues for decision making. What is Statistics? Insights are necessarily an investigation of numerical information, realities, ideas, and estimations. Statistics is used to convert raw statistical data into useful information for relevant users. According to Bowley, "Statistics are the science." 

He defines the data as "numerical explanations of facts in the interrogation unit." The help of statistics determines most of the information around us – 

  • Weather Forecasts Medical Studies 
  • Quality Testing 
  • Stock Markets 
  • Predicting Emergencies 

In business statistics, the relevant information is collected to determine statistical tools in marketing, production, finance, research and development, and human resources planning. Professional managers use analytical tools and techniques to explore almost all government and private companies' sectors or business functions. Depending on the statistical method used, the data can be broadly divided into two categories: 

  • Descriptive statistics - Descriptive statistics use graphs, tables, charts, and other analytical tools to generalize or describe a specific event. 
  • Inference Statistics - Not all stereotypes made by descriptive statistics are necessarily correct, and therefore inferential statistics can be used to test the validity of generalizations made. It involves assessing and verifying facts and statistics for decision-making purposes. Statistical significance 

In Business - It helps in making fast decisions by providing useful information about customer trends and variants, cost customer trends and modifications, value customer trends, and options. 

In mathematics - it helps to explain measurements and to provide accuracy of formulas. 

In economics - it helps find the relationship between two variables: demand and supply, cost and revenue, import and export, and the relationship between inflation rate, per capita income, income distribution, and so on. 

In Accounting - It helps to find trends and make predictions for the next year. 

In physics - it helps to calculate the distance between objects in space. 

Research - It helps to formulate and test hypotheses. 

Government - The government takes data to help with budgeting, determining minimum wage and cost of living. 

Importance of business statistics helps business:  

  1. Deal with uncertainties by estimating seasonal, cyclical and general economic fluctuations  
  2. Providing accurate estimates of cost, demand, price, sales, etc. can help the right decision. 
  3. Assists with business planning based on sound assessment and evaluation  
  4. It helps to measure differences in the performance of products, employees, business units, etc.  
  5. It allows you to compare two or more products, business units, sales teams, etc. 
  6. Helps identify the relationship between various variables such as the impact of advertising on sales and their impact  
  7. Helps to validate the generalize ability and theoretical concepts that managers create  

Statistical advantages in business  

Most companies naturally collect a lot of data during the activity. It is especially true in the Internet age. It is often possible to gather comprehensive information about everything users do, from open email to specific products on the company's website. The role of statistics in business is to evaluate this information about the company says about its operations and strategy. 

Statistical advantages in performance  

The role of statistics in business is to inform the manager who works on employee performance. The manager collects data about employee productivity, such as the number of completed tasks or the number of units produced. The employee must analyze the data to find ways to improve the employee to achieve maximum productivity. Many companies collect data about employees' busyness and happiness at work, which may motivate workers and help them move elsewhere. 

For example, suppose the manager finds that the employee's output number decreases by 20 percent every Friday. In that case, he must communicate with the employee so that his product is expected to work weekly. The day is beyond the minimum. 

Most companies also compile aggregated statistics about employee performance. Suppose a company knows that all employees are doing less work before or after the weekend. In that case, their managers may want to look at ways to motivate employees, or it may be due to external factors during uselessness. Companies can avoid collecting more data about employee activities; however, it can be scary for workers. 

Evaluation of alternative scenarios  

Beyond managing the performance of their workers, a manager engages in joint decision-making with other managers. Statistics help managers to compare alternative scenarios and choose the best option for the company. The team must decide which software to use to automate the customer ordering process. 

They can determine which software products are used successfully by competitors and select the most popular ones, or find out how many orders the average system can process per day. The team collects performance data from independent sources, such as software manufacturers and trade journals, to inform their purchasing decisions. 

Importance of data collection  

One advantage of a business is to use data or capture data if the manager uses a logical approach and collects and ethically reports the data. For example, he may use statistics to determine if the sales level of specific products launched is close to the sales forecast. He may decide whether a low-performance product requires additional investment, or the company must transfer resources from that product to the new product. 

In some cases, it may be necessary for employees or data consultants to disseminate customer data or disassemble sensitive data to minimize data breach or misconduct. Privacy laws also heavily regulate how companies use or store personal data, so it is essential to ensure that your business complies with the regulations inactive areas. 

Statistics in Research and Development  

A company uses statistics in market research and product development, using a variety of products, such as random samples of customers, to estimate the market for the proposed product. To determine whether the manager is adequately demanding or not among the surveyed target customers. 

Survey results can justify spending on product development. Product launch decisions also involve break-even analysis, which means how many of the customers should try to make a new product success. 

Statistical significance for industry and commerce  

Business managers use statistics to help them make decisions in situations of uncertainty. Statistics can be used to create sales forecasts, financial analysis of capital expenditure projects, profitability estimates for a new product, quantitative analysis of the product, and quality analysis. Using statistics provides real data about complex situations rather than making decisions based on unsatisfactory humps. 

Performance evaluation  

The most common use of statistics is to measure performance. For example, you can collect data about a small number of product units to assess the quality of a whole batch of products; This is called statistical sampling and is used to decide whether to accept or reject a shipment. Analysis of the employee's production's output may be another use for determining whether the worker meets the desired productivity standards. If not, adjustments may be required, such as equipment improvements, changes in the work environment, or improved communication. 


Managers analyze past data to find statistical trends and make predictions. For example, you can analyze recent sales of all products sold to estimate future sales volume under certain economic conditions. In turn, these estimates are used to determine the production schedule. 

As an example, consider a farmer who has to decide whether to plant soybeans or corn. The farmer wants to increase the number of bushels produced in excellent or adverse weather conditions; There is a definite probability of being in every weather condition. Analysis of historical data shows the amount of soybean or maize produced on the climate model in a particular geographical area. With this statistical model, the farmer can tell which seed to plant. 

Risk/return on investment  

The new capital expenditure project is to optimize return on investment and reduce risk. Statistical techniques can allow the manager to evaluate the project in different economic environments, changing consumer preferences, and competitive strengths. 

Market research  

Companies use statistics in market research and new product development. They conduct random surveys of customers to assess market acceptance and the potential for a proposed product. Managers want to know if there is enough demand for the product. Is there enough demand to justify spending money to develop a product and eventually build a plant? From the statistical analysis, the break-even model is constructed to determine the number of sales required to make a product successful. 

Limitations on using statistics  

Using statistics helps in decision making, but it has limitations. For example, the sample size used in market research is one factor. Larger models produce better quality results, but larger models cost more money and are more sensitive to the law of reducing revenue. It is a classic Trade-off between the budget and the cost of getting more accurate results against time constraints. 

Using historical data to build statistical models for estimation does not take any causal changes in the market. Financial conditions are continually changing, as are shopper conduct and interests. Managers need to be aware of these changes and incorporate them into their decisions. 

When used correctly, statistical techniques can significantly simplify the decision-making process. However, the application of statistics is both art and science and should not be used as the sole basis for decision making. When interpreting statistical analysis results, make judgments based on your own real-life experience and other qualitative factors not included in mathematical models. 


About the Author

Akshay Patil

Regional Sales and Marketing Director     

Passionate International Business Professional with 3 Years of experience in Sales & Marketing and Business Development of market with deep understanding of Chemical Industry.

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