Prescriptive Analysis and Its Implementation in Business

Many business decisions taken by every company now rely on big data analysis. There are many things to consider before making a decision, especially if the impact is directly related to long-term business goals.

The decision-making process must involve several metrics from existing data, current conditions, and goals to be achieved. When you utilize all existing data, this will be a good lesson to help build your business.

What is Prescriptive Analytics?

Prescriptive analysis is a data analysis process carried out to provide instant recommendations in the decision-making process and validate actions before taking certain actions.

This process can analyze business goals and recommend the best steps based on complex algorithms and past examples. This solution can be formed from a combination of artificial intelligence (AI), machine learning, business rules and algorithms.

For example, prescriptive analysis helps marketing teams determine appropriate market segments for a product based on past and present consumer patterns and behavior. This can help teams find ways to use budgets and optimize marketing campaigns.

With predictive analysis, a prediction may or may not come true. However, there is an element of risk when using automatic recommendations for prescriptive analysis, namely that human behavior cannot be predicted. Statistical models that base results on analysis of human behavior require caution.

Use of Prescriptive Analytics in Business

Prescriptive analytics uses historical data to predict future events and does not answer questions with “what if”, but rather “how to”. Companies will be able to understand what can happen and how to achieve it.

Research, machine learning, and applied statistics can be explained in the decision-making process. This can benefit the business in the following ways.

1. Create measurable and repeatable processes

Companies can use simulations created from internal data to effectively evaluate multiple data sets. This allows companies to assess the situation, adopt the most effective options, and make them repeatable and measurable using historical data and market trends.

2. Optimize the business plan to meet ROI

The prescriptive analysis process can recommend the best time and sequence to schedule and update marketing, pricing, and sales plans to provide the best return on investment (ROI).

With insights that can be actioned into an action plan, you can speed up the business planning cycle. You can feel confident that you have invested well when you take advantage of market conditions while achieving your income targets.

3. Remove underperforming workflows

In an organization, underperforming workflows or assets may go unnoticed for some time and can reduce company profits. Prescriptive analytics allows companies to identify criteria to be able to take necessary actions and channel budgets to profitable projects.

4. Reduce human error

The increasing use of AI can eliminate human error in carrying out analysis. For example, companies use AI to consolidate and analyze large data sets. This can help reduce the possibility of human error in statistical calculations.

5. Increase agility

A business can find the best way to navigate the intricacies of the market to the organization's advantage by conducting simulations and scenario analysis. Additionally, a business has the flexibility to make real-time decisions due to its fast turnaround time.

6. Get sales leads

Through this process, product sales analysis can result in better lead assessment. Lead scoring is the process of assigning values to various actions along the sales pipeline. This can increase factors like page views, site searches, email interactions, and content engagement.

7. Generate customer insights

A business can get algorithmic recommendations based on engagement patterns on its website. Based on user interactions, weighted recommendations can increase customer engagement and satisfaction levels. This way, you can retarget ads based on customers' browsing history.

8. Real-time transaction anomaly detection

Every organization will be able to detect suspicious transaction activity in real-time. Algorithms scan and analyze transaction data patterns to notify and provide action recommendations to businesses when anomalies arise.

9. Improve product development

With predictive analytics, businesses can also better understand customer needs by identifying trends. You can find the reasons for a trend and predict the next trend repetition.

This analysis helps determine which features should be included or removed in a product. The goal is to overcome unnecessary characteristics in a product and optimize user experience in the future.

10. Predict churn rate

Churn rate is a metric that describes a customer's condition when they stop subscribing to a service. When having the ability to predict churn rates, businesses can determine warning signs of potential customer loss.

By implementing prescriptive analytics, companies can reduce consumer attrition rates and respond quickly to consumer changes. Companies can also actively increase revenue when implementing prescriptive analytics.

For company executives, it is important to be able to hone prescriptive analysis skills that have an impact on the continuity of the company. Through the Strategic Business Analysis program, managers will hone their ability to analyze factors that bring understanding, translation and characterization of strategic issues to achieve business targets in good teamwork.