Business analytics is an important tool in the workforce. Organizations are generating huge amounts of data, in all industries, because it keeps getting easier and cheaper. As a result, business are faced with new questions. What value is our data giving us? Does our data give us an unfair competitive advantage? Questions like these increase the need for professionals who know their way around the data, can synthesize the information, and transform information into actionable insight.
Companies all over use data to:
In the coming years companies expect their investments in analytics to increase. So why wouldn’t you want to increase your knowledge with regards to business analytics? Who doesn’t want to make better decisions in the workplace, or have more influence in your organization? Many people have opinions, but if you have data to support your recommendations, you’re going to turn heads.
Before we get into the benefits of data analysis, you should understand what the term “business analytics” means.
Business analytics is the statistical analysis of the data you have acquired in order to make decisions that are based on evidence rather than a guess.
There are three primary methods of business analysis:
1 - 2 - 3 … Triple P
Determining which method to use will depend on the business situation and data maturity.
It’s important to note business analytics is different from data science. Each process analyzes data to solve problems, however there’s a difference in how the data is used.
Business analytics is concerned with obtaining useful insights, and visualizing data to aid the decision-making process using curated data sources.
Data science is focused on making sense of raw data by using algorithms, statistical models, and computer programming to populate curated data sources.
Despite their differences, each method can process data to better inform business decisions.
Let’s look at some examples to better appreciate how data insights can drive organizational performance.
Business analytics can be an invaluable tool when approaching strategic decisions.
In 2018 Uber upgraded their Cusomer Obsession Ticket Assistant (COTA). It’s a tool that uses machine learning and natural language processing in order to help their agents improve speed and accuracy when responding to support tickets. Through Prescriptive analytics they were able to discover the product’s newest version would be more effective than the previous.
Through split testing—a method of comparing the outcomes of two different choices—the company determined that the updated product led to faster service, more accurate resolution recommendations, and higher customer satisfaction scores. These insights not only streamlined Uber’s ticket resolution process, but saved the company millions of dollars.
Companies who embrace data and analytics initiatives find they can experience impactful financial returns.
When organizations invest in big data, they can increase their profits. When those same investments continue year over year, so do the profits.
There are many studies which illustrate the clear financial payoff that can come from a robust business analysis strategy—one that many firms can stand to benefit from as the big data and analytics market grows.
In addition to financial gains, analytics can be used to fine-tune business operations.
Many companies are now using predictive analytics to anticipate maintenance and operational issues before they become larger problems.
A mobile network operator surveyed noted that it leverages data to foresee outages up to seven days before they occur. With this information, management can prevent outages by more effectively timing maintenance, enabling them to not only save on operational costs, but to also ensure they keep assets at optimal performance levels.
If you’re going to collect the data, you may as well use it to leverage as many benefits as possible. Make better decisions, be more efficient, and more profitable. We’ll leave your with a few questions to consider:
You’re not alone if you answered yes to any of these questions. We felt the same way and it’s why we made Aureum. Aureum shrinks the time from data collection to actionable insight from months to minutes. We just wanted an easy way to see business activities and outcomes without a big budget and never-ending data projects.