Predictive vs Prescriptive Analytics: What’s the Difference?
Every business should know what’s coming and what needs to be acted upon proactively. Some businesses do it perfectly well, while others fail to minimize security threats, cut operational costs, maintain maximum equipment uptime, and prevent fraud.
That’s where the power of analytics comes into play; however, predictive vs prescriptive analytics are often mistaken, and decision-makers use them interchangeably. To break down the concept and provide clarification, we have explained everything in detail.
What is Predictive Analytics?
As the name suggests, it offers insights proactively based on the data it learns from. It analyzes historical patterns, such as customer shopping history, sales trends, and product demands.
With the help of Machine Learning, statistical models, and data mining, predictive analysis makes forecasting. Based on your business objectives, the products or services offered, and the defined target audience, predictive analysis evaluates the data and provides insights to make strategic decisions.
For example, a company can use predictive analysis to predict a sales decline or customer shifting to other brands. Or a retailer might predict what quantity of products will be required during the holiday season.
What is Prescriptive Analytics?
Prescriptive analytics combines a proactive and a reactive approach. This process involves predicting what will happen and then suggesting remedial measures.
The use of optimization algorithms, simulations, and decision analysis evaluates the scenario for which it is trained and then recommends the best course of action to avoid hassles, eliminate security threats, and prevent equipment downtime, among other things. For example, an airline company may use prescriptive analysis to set ticket prices based on demand, season, and competition.
Apart from the approach, there are several other differences between prescriptive and predictive analytics that you should know before investing in them.
Key Differences Between Predictive and Prescriptive Analytics
These are key differentiators between predictive and prescriptive analytics that we have gathered here. Have a look at them and then decide which one fits your business.
When to Use Predictive Analytics?
Predictive analytics makes forecasting easier, meaning it helps manufacturing businesses identify equipment failure, retailers understand sales and revenue, banks detect potential fraud, real estate agents anticipate foot traffic, and many more. What might happen in your business can be known by implementing predictive analytics in your existing or new software.
Predictive Analytics Examples
Custom Churn Prediction: With predictive analytics, business owners can identify customers who are abandoning their products or services based on their historical patterns, which helps them design retention strategies.
Sales Forecasting: You can analyze past sales data and predict upcoming demand, helping businesses optimize inventory, staffing, and marketing campaigns.
Credit Scoring: It helps banking and finance services providers assess the probability of customers defaulting. It analyzes financial history and helps make better lending decisions.
Fraud Detection: Predictive analytics detects unusual patterns in transactions or claims that may indicate fraud, allowing for early intervention and risk management.
Patient Risk Prediction: If you are a healthcare services provider, you can use predictive analytics to evaluate patient history and medical records. As a result, you can offer preventive care to patients who need emergency care.
Equipment Failure Prediction: Another predictive analytics use case is related to the manufacturing or automotive industry, due to their high dependency on equipment. With analytics, you can predict and prevent downtime, ensuring proactive maintenance of your machinery.
Also Read: What is Predictive Analytics in Healthcare? Examples & Benefits
When to Use Prescriptive Analytics
As mentioned earlier, this approach combines proactive and reactive methods, meaning that as a business owner, it can help you predict challenges and even provide data- and technology-backed solutions. Now, it depends on the nature of the business to make the most of prescriptive analytics.
Several business-like cabs, as well as those involved in sharing, food delivery, logistics, and supply chain, can leverage prescriptive analytics for route optimization. It helps them save time, fuel costs, and ensure on-time deliveries. Another business dealing in energy can use this approach to balance supply and demand. Besides, prescriptive analytics also helps cut down operational costs.
Prescriptive Analytics Use Cases
Real Time Pricing: If you're in retail or a similar business, prescriptive analytics can help you identify customer demands, competitor pricing, and buying patterns to maximize your sales and revenue.
Route Optimization: For food, medicine, logistics, and or any kind of delivery, route optimization is utmost necessary. It helps avoid congestion and ensures faster, on-time delivery. Besides, it helps save time and money.
Energy Load Management: Another business dealing in energy can use this approach to balance supply and demand. It also recommends storing, producing, and distributing energy as needed. It improves grid efficiency and reduces wastage.
Inventory Optimization: It suggests when and how much to order based on forecasted demand and stock levels, avoiding both overstocking and stockout.
Resource Allocation: It guides how to best use machines, labor, and materials for maximum efficiency and minimal downtime. As a result, you can strategically plan, organize, and execute strategies to minimize downtime and maximize efficiency.
Final Thoughts
With the growing data, the decision-making process largely depends on the approach between predictive and prescriptive analytics. If you just want anticipation, predictive analytics is worth your investment. Prescriptive analytics, on the other hand, offers remedial or solution-oriented measures. Both can make your business thrive, empower your decision-making, and supercharge your business intelligence.
Consult with the leading predictive analytics company today to get a detailed idea about how to execute your idea.
FAQs
Which is better, predictive or prescriptive analytics?
It depends on what business challenge or purpose you want to resolve. Predictive analytics foresees future trends and risks that your business may face, while prescriptive analytics goes a step further. It even offers a solution to an upcoming trouble or challenge.
Is prescriptive analytics part of predictive analytics?
Not exactly. Although it frequently utilizes the findings of predictive analytics, prescriptive analytics is a distinct field. While predictive tells you what might occur, prescriptive tells you how to react to possible events. Consider prescriptive to be the next logical step after prediction.
Which companies use prescriptive analytics?
Several companies, such as Amazon, UPS, Netflix, Delta Air Lines, and Siemens, use prescriptive analytics for real-time pricing, route optimization, supply chain planning, and energy efficiency.
Which companies use predictive analytics?
Several organizations, including Walmart, Spotify, JPMorgan Chase, Target, and Pfizer, use predictive analytics for demand forecasting, fraud detection, customer behavior analysis, and healthcare diagnostics.