Staying relevant in a changing marketplace is crucial to success in business. In today’s landscape, business analytics can deliver key insights that keep a company at the forefront of its industry. It can be a powerful tool—but only if it’s used effectively.

For aspiring business leaders, developing a thorough understanding of what business analytics is—and how to apply it—can mean the difference between a good growth or stability strategy and a great one.

To learn more, check out the infographic below, created by Washington State University’s Online Master of Business Administration and Executive Master of Business Administration programs.

What Is Business Analytics?

Business analytics involves collecting and interpreting data to drive informed decision-making. Those who master the process can turn their companies into industry leaders.

Business Analytics Definition

Business analytics is the collection and analysis of business-relevant data, conducted for the purpose of identifying patterns, trends, and consumer behaviors. It’s used for the development of business strategies based on these identified patterns and trends.

Business analytics has several core processes. These include:

• Determining the goals behind the analysis
• Choosing the best analytical methodology to achieve those goals
• Gathering comprehensive data, often from a wide range of systems
• Cleaning the data and integrating it into a single space, such as a data warehouse

5 Core Benefits of Business Analytics That Can Increase Profitability

Here are five essential benefits of business analytics for companies, each involving potential profitability boosts:

1. Improves business decision-making. Analytics eliminates guesswork, which minimizes potential financial loss.
2. Increases operational efficiency. Analytics can reveal vulnerabilities in processes like supply chain issues.
3. Optimizes customer outreach. Analytics can help target customers in a more personalized manner.
4. Mitigates risk. Analytics can empower companies to identify risk factors and take preventive measures.
5. Improves security. Analytics can spot vulnerabilities in a business’s system infrastructure.

Types of Business Analytics

There are four main types of business analytics:

1. Descriptive analytics interprets past data to identify trends and identifies consumer behavior patterns.
2. Predictive analytics interprets data to forecast future outcomes, uses statistical models and machine learning, and predicts future consumer opinions and behaviors.
3. Prescriptive analytics makes recommendations on how to handle future scenarios based on past data and proposes specific actions for achieving optimal results.
4. Diagnostic analytics reviews past performance to identify what influences specific trends, uses tactics like data mining and correlation, and uses algorithms to determine the likelihood of recurring influential elements.

Data Science vs. Business Analytics

Like business analytics, data science is a rapidly growing field. Executives realizing the power of analytics may think of business analytics and data science as one and the same. However, a close examination of the two fields reveals notable differences.

Data Science Definition

Data science focuses on the analysis of data. This analysis provides information that can yield new insights.

There are several similarities between data science and business analytics. Both focus on data analysis and use data to glean insights via statistics-driven methodologies. Both also aim to efficiently organize complex data and improve business operations. Additionally, data science and business analytics both use predictive modeling techniques.

The projected job growth for both fields is strong. The U.S. Bureau of Labor Statistics (BLS) projects 36% job growth for data scientists and 11% growth for management analysts between 2021 and 2031.

Differences Between Business Analytics and Data Science

Despite these similarities, business analytics and data science are fundamentally different fields in several ways. A major difference involves the way data is applied. Data science focuses on what causes trends and rarely makes recommendations regarding business strategy. Business analytics, on the other hand, focuses on the current and potential impact of trends and uses insights to make recommendations regarding business strategy.

A second difference between business analytics and data science involves coding. Data science combines computer science, data inference, and statistics, while business analytics almost exclusively uses statistical models.

Statistics is another key differentiator between the two fields. Data science uses statistics to determine the effectiveness of algorithms designed to collect data. Business analytics, meanwhile, uses statistics to identify trends and make strategic recommendations.

A fourth key difference involves data types. Data science uses structured and unstructured data to build algorithms. The structured data is organized via a database, while the unstructured data is in its original database. Business analytics primarily uses structured data for trend analysis.

The final key differentiation between business analytics and data science involves the tools each one employs. Data science uses programming languages like C++ and Python to build algorithms. It may also use machine learning to help build statistical models. Users of these tools need a higher level of tech skills than users of business analytics tools, which include spreadsheet programs and Structured Query Language (SQL) to help analyze and organize data.

How to Use Business Analytics

Several prominent companies are using business analytics to achieve greater levels of success. These results can inspire executives to use business analytics to develop their own strategies.

Microsoft

The computer company Microsoft used business analytics to study the effects of remote work on its employees. The project addressed key concerns such as work-life balance, employee relationships, collaboration impact, and manager engagement. The analytics highlighted key data such as shorter meeting times, increased one-on-one manager engagement, shifts in working hours, and stronger worker-to-worker networks. Ultimately, this data can be used to inform their long-term work strategies.

Uber

The ride-hailing company Uber uses business analytics strategies such as data mining to gather information on its riders and drivers. The data reports where customers and drivers are located, thus allowing the system to efficiently pair the two. It also tracks supply and demand. These metrics allow the system to activate “surge pricing” at peak times, a tactic that activates more drivers. Uber’s data has also been used in traffic- and vehicle-based collaborations. For instance, municipal partners have used the data to detect traffic patterns on local streets and highways. The National Center for Missing & Exploited Children (NCMEC) has also used the information for Amber Alert data.

Starbucks

The coffeehouse chain Starbucks uses business analytics to forecast the performance of future stores. Tracking metrics such as area demographics and consumer behaviors help mitigate the risk of opening a store in an unprofitable area. Starbucks also employs other business analytics strategies to build personalized marketing campaigns through its mobile app. For instance, it uses incentivization to encourage customers to routinely visit its stores.

American Express

The credit card company American Express uses business analytics to detect fraudulent activity on its customers’ cards. The company tracks metrics such as card membership information, merchant information, and transaction details. These metrics allow American Express to spot fraudulent activity almost as soon as it occurs.

Drive the Future of Business Today

Business analytics is here to stay. The insights it provides can help businesses operate with greater efficiency, build stronger consumer relationships, and improve their bottom line. Executives who understand how to harness its potential can transform their businesses.

Sources

G2, “Retail Analytics: How to Reap the Benefits of Consumer Data”

G2, “What Is Business Analytics and Why You Need It for Success”

Indeed, “Business Analytics vs. Data Science: What’s the Difference?”

Investopedia, “How Uber Uses Your Ride Data”

Microsoft, “Microsoft Analyzed Data on Its Newly Remote Workforce”

Oracle, “What Is Business Analytics?”

Stitch, “5 Benefits of Data Analytics for Your Business”

SupplyChain, “How American Express Uses Big Data to Transform Operations”

TechTarget, “Business Analytics”

U.S. Bureau of Labor Statistics, Data Scientists

U.S. Bureau of Labor Statistics, Management Analysts