What are Predictive Business Analytics?

what are predictive business analytics

Small to mid-sized organizations find themselves in an increasingly complex and globalized economy. Coronavirus-related disruptions have negatively impacted millions of businesses, including restaurants, retailers, and other small operations. As a result, those who want to stay competitive and survive through the disruption are employing new tactics to increase revenue and save money.

One increasingly popular form of business intelligence is predictive analytics. Predictive analytics helps businesses plan and mitigate risk. As more uncontrollable external forces affect different industries, implementing PBA can be the best method to optimize finances and increase brand awareness.

The Inside Scoop on Predictive Business Analytics

the inside scoop on predictive business analytics 1608309986 7485

Predictive analytics employs a combination of data and complex algorithms to use historical information to pinpoint the probability of future events.

Unlike descriptive analytics that uses past and current data to gain a clearer picture of what's happening in real-time, predictive analytics is concerned with utilizing the most relevant data to plan for the future.

Because of the increase in available data and more inexpensive software solutions, many organizations turn to predictive analytics to increase their bottom line and maintain a competitive edge.

Importance of PBA

Organizations use BPA to solve complex problems and pinpoint new opportunities that may not be noticeable. Use cases include-

1. Identifies Fraud
Utilizing a combination of predictive and descriptive analytics, organizations can identify important trends and avert lawbreaking.

For example, the banking industry uses advanced predictive analytics to scrutinize all of the real-time activity occurring on a system to pinpoint any irregularities that might show criminal behavior or reoccurring threats. Preventing fraud can help save millions in dollars and protect the organization's reputation.

2. Improves Marketing Efforts
Many businesses save money by employing predictive analytics to optimize inventory management, which helps prevent over/underordering.

Airlines utilize PBA to determine their pricing while hotels use it to estimate how many guests to expect on a particular day or time frame. All of these use cases help to increase revenue and prevent wasting resources. As a result, those who use predictive analytics typically see an increase in operational efficiency.

3. Minimizes Risks
Organizations can help plan for and mitigate risk by implementing predictive analytics. For example, the banking industry uses PBA to analyze potential customers' credit scores before confirming approval.

Car insurance companies look at past behavior such as accidents to know how much to charge a customer and determine whether he/she should be covered at all. By minimizing and preventing risk, the organization protects itself, saves money, and standardizes best practices.

PBA Examples

There are numerous ways for an organization to use predictive analytics. Here are a few examples of how different industries employ BPA-

1. Retail Industry
Retailers use predictive analytics to pinpoint correlations between customer purchasing patterns. For example, many people who buy a toothbrush also purchase toothpaste at the same time. These insights are then used to optimize marketing campaigns and target a segment of customers.

Retailers also use PBA to streamline inventory management and improve pricing strategies so they increase the bottom line. For example, Staples used PBA to analyze customer behavior and improve their marketing campaigns. As a result, they saw a 137% return on investment.

2. Governments
Governments around the world have invested in predictive analytics and software solutions for a variety of purposes. Use cases include analyzing population trends, improving cybersecurity measures, and optimizing government-run programs. It is also frequently employed by the FBI to prevent financial crimes like tax evasion.

3. Manufacturing Industry
Manufacturers have found predictive analytics to be particularly helpful in identifying events that lead to equipment failures or a decrease in the quality of their product. It is also helpful to streamline warehousing and the distribution center to ensure all parts and services are fully optimized.

Some manufacturers have even employed PBA to gain a fuller understanding of warranty claims, or a claim for the repair and replacement of a product made by an organization. In doing so, manufacturers have been able to predict which product parts typically break down and why. As a result, they have saved resources and money on all warranty-related expenses.

Key Takeaways

In conclusion, here are the key takeaways to remember about predictive business analytics-

  • Predictive analytics uses historical and current information to predict future outcomes. As a result of employing PBA, organizations have saved money, improved marketing campaigns, streamlined operations, and minimized risk.
  • PBA is an essential component of an overall business intelligence strategy. It is used by various industries to identify fraud, optimize marketing efforts, and plan for future disruption.
  • Many industries use PBA for a variety of purposes. The retail industry uses it to improve customized marketing efforts, streamline inventory management, and optimize pricing strategies. Governments employ it to analyze population trends and enhance cybersecurity efforts. The manufacturing industry identifies events that result in equipment failures, streamline warehousing and minimize warranty claims.