EFFECTIVE USES OF STATISTICS IN KEY BUSINESS DECISIONS

 Operating a business of any size is a complex undertaking. In addition to day-to-day responsibilities, your company must engage in long-term planning, develop new products or services, streamline production or delivery and locate new customers while serving existing clients. Running a shop on instinct no longer suffices. Statistics provide managers with more confidence in dealing with uncertainty in spite of the flood of available data, enabling managers to more quickly make smarter decisions and provide more stable leadership to staff relying on them.

Effective uses of statistics in key business decisions

A recent study by ISS coaching in Lucknow found that by 2023, “more than 33% of large organizations will have analysts practicing decision intelligence, including decision modeling,” endeavors that only succeed with the contributions of statisticians. Statistical research gives managers the information they need to make informed decisions in uncertain circumstances. When managers analyze statistical research in business, they determine how to proceed in areas including auditing, financial analysis and marketing research. Future business professionals need to recognize the importance of statistics in creating accurate predictions. Companies that rely on analytics can be more effective when they work with the right statistics.

What Are Business Statistics?

Statistical research in business enables managers to analyze past performance, predict future business practices and lead organizations effectively. Statistics can describe markets, inform advertising, set prices and respond to changes in consumer demand.

Descriptive analytics look at what has happened and helps explain why. By using historical data, managers can analyze past successes and failures. This is also called “cause and effect analysis.” Some common applications of descriptive analytics include sales, marketing, finance and operations.

Predictive analytics uses a variety of statistical techniques (such as modeling and data mining) to predict future probabilities and trends based on historical data. This goes beyond reporting what has happened to create best estimates for what will happen. Some common applications of predictive analysis include fraud detection and security, risk assessment, marketing and operations.

Prescriptive analytics is the stage of determining the best course of action in a given business situation. This includes knowing what may happen, why it may happen, and how to navigate it. Constantly updating information changes prescriptive analysis, allowing managers to maintain action plans for their organizations in real-time.

Mean, Median and Mode

Those who use statistical research in business should be familiar with how statistics are calculated, including how the mean, median and mode work together to create meaning from a set of numbers. The mean is an average of a set of numbers, the median is the middle number within a set of numbers and the mode is the most common number in a set.

Successful managers understand that these concepts work in concert to create an accurate picture of a business’s condition.

Responsibility With Statistics

According to Six Sigma Online, managers should be prepared when they use statistical research in business to explain the research to other stakeholders and vouch for its authenticity. It is important to know the source of the data and ask questions such as What does this research represent, and why was it generated? Was the person who compiled this data capable of doing so, and were they unbiased?

Studying Statistics

Computer software makes analytics very accessible. Desktop tools can help create reports, charts and graphs to represent information visually, which helps communicate its meaning.Business professionals must master all of the tools available to them, including statistical research in business, in order to help their organizations succeed.

Focusing on Big Picture

Statistical analysis of a representative group of consumers can provide a reasonably accurate, cost-effective snapshot of the market with faster and cheaper statistics than attempting a census of very single customer a company may ever deal with. The statistics can also afford leadership an unbiased outlook of the market, to avoid building strategy on uncorroborated presuppositions.

Evidence to Substantiate Positions

Statistics back up assertions. Leaders can find themselves backed into a corner when persuading people to move in a direction or take a risk based on unsubstantiated opinions. Statistics can provide objective goals with stand-alone figures as well as hard evidence to substantiate positions or provide a level of certainty to directions to take the company.

For example, you may find it easier to convince board members of the value of international expansion by providing data on the available market for products in a given country. Break down demographics, average income and competitor products in the country.

Making Connections Between Variables

Statistics can point out relationships. A careful review of data can reveal links between two variables, such as specific sales offers and changes in revenue or dissatisfied customers and products purchased. Delving into the data further can provide more specific theories about the connections to test, which can lead to more control over customer satisfaction, repeat purchases and subsequent sales volume. For example, a free gift with purchase offer may drive more sales than a discount period.

Ensuring Product Quality

Anyone who has looked into continuous improvement or quality assurance programs, such as Six Sigma or Lean Manufacturing, understands the necessity for statistics. Statistics provide the means to measure and control production processes to minimize variations, which lead to error or waste, and ensure consistency throughout the process. This saves money by reducing the materials used to make or remake products, as well as materials lost to overage and scrap, plus the cost of honoring warranties due to shipping defective products.

 

Additional Considerations when Using Statistics

Know what to measure, and manage the numbers; don’t let the numbers do the managing for you, or of you. Before using statistics, know exactly what to ask of the data. Understand what each statistical tool can and can’t measure; use several tools that complement one another. For example, don’t rely exclusively on an "average," such as a mean rating.

Customers using a five-point scale to rate satisfaction won’t give you a 3.84; that may indicate how the audience as a group clustered, but it’s also important to understand the width of the spread using standard deviation or which score was used by the greatest number of people, by noting the mode. Finally, double-check the statistics by perusing the data, particularly its source, to get a sense of why the audiences surveyed answered the way they did.