What are the Benefits of Prescriptive Analytics?

What is Prescriptive Analytics?

Prescriptive analytics is a process that analyzes data and provides instant recommendations on how to optimize business practices to suit multiple predicted outcomes. In essence, prescriptive analytics takes the “what we know” (data), comprehensively understands that data to predict what could happen, and suggests the best steps forward based on informed simulations.

Prescriptive analytics is the third and final tier in modern, computerized data processing. These three tiers include:

• Descriptive analytics: Descriptive analytics acts as an initial catalyst to clear and concise data analysis. It is the “what we know” (current user data, real-time data, previous engagement data, and big data).
• Predictive analytics: Predictive analytics applies mathematical models to the current data to inform (predict) future behavior. It is the “what could happen.”
• Prescriptive analytics: Prescriptive analytics utilizes similar modeling structures to predict outcomes and then utilizes a combination of machine learning, marketing business rules, artificial intelligence, and algorithms to simulate various approaches to these numerous outcomes. It then suggests the best possible actions to optimize digital business practices. It is the “what should happen.”

Why Use Prescriptive Analytics?

The main benefit of this kind of analysis is that it helps managers optimize the efficiency of their operations. Prescriptive analytics can form the basis of other business intelligence tools. It offers the option to view real-time business information and long-term projections about digital business operations.

Prescriptive analytics also helps businesses make impartial decisions. AI processes data quickly and more accurately than a human could. This means human biases and emotion won’t creep into decisions.

How prescriptive analytics fills the gap?

Building repeatable and scalable processes:

To accurately predict outcomes, one has to create an in-house simulated environment. Keeping up with the fluid nature of the market, prescriptive analytics builds off historical data and allows businesses to run what-if analysis quickly. Once the business has run multiple scenarios, it can adopt the most efficient option and quickly make it repeatable and scalable.

Optimizing business actions with monthly plans to meet ROI:

Be it pricing, marketing, or sales, marketing business owners can predict the course of action that can deliver optimal ROI.

Removing underperforming channels:

In a large business, underperforming sources of revenue often go unnoticed for too long. Prescriptive analytics lets you identify such channels quickly and take necessary actions. You can divert the budget to those products that deliver maximum returns.

Achieving higher agility:

By simulating and running different scenarios of sudden market shifts, you find the best ways to respond to those shifts quickly and to your advantage. You get to make near-time decisions instead of waiting for weeks.

Creating long-term strategies:

It removes data silos and brings teams together in a collaborative model for the long run.

Managing risk management:

By answering complex questions related to demand and supply, your business can optimise investments and reduce risk.

Fighting retail fraud:

Prescriptive analytics is taking the guesswork out of fraud management. Especially after the pandemic, retailers are identifying fraud impact and using data and tools to detect fraudulent e-commerce returns claims and minimise cashier fraud in stores.