Descriptive to Prescriptive Analytics: A Guide for Financial Analysts

Read more about the transition from Descriptive to Prescriptive Analytics.

As a financial analyst, it is essential to move from descriptive to prescriptive analytics in order to provide valuable financial insights. Descriptive analytics involves analyzing historical data to understand what happened in the past. In contrast, prescriptive analytics focuses on identifying the best course of action for the future based on current and historical data.

The transition from descriptive to prescriptive analytics involves five major steps: data collection and preparation, descriptive analysis, diagnostic analysis, predictive analysis, and prescriptive analysis. By following these steps, financial analysts can provide clients with informed recommendations that will help them optimize processes, improve decision-making, increase revenue, mitigate risks, and enhance the customer experience.

Step 1: Data Collection and Preparation

You must have high-quality data that is reliable and consistent to move from descriptive to prescriptive analytics. You must also ensure that the data is clean and prepared for analysis. This step involves identifying the relevant data sources, collecting data, cleaning the data, and preparing the data for analysis.

Step 2: Descriptive Analysis

The next step is to perform descriptive analysis, which involves analyzing historical data to gain insights into past events. This step helps you understand what happened in the past and identify patterns and trends. Common techniques used in descriptive analysis include data visualization, data aggregation, and data mining.

Step 3: Diagnostic Analysis

This step involves using advanced analytics techniques to diagnose the root cause of a problem or issue by examining historical data. It is an important step in data analysis because it can help identify the underlying factors that contribute to certain outcomes or trends. Common techniques used in diagnostic analysis include data visualization, hypothesis testing, and regression analysis.

Financial analysts often struggle to advance beyond utilizing these first two analyses because predictive and prescriptive analyses require a significant amount of high-quality data to provide accurate and informative insights. If financial analysts spend all their time on step one, data collection and preparation, it makes the transition into advanced analytics impossible.

Step 4: Predictive Analysis

The fourth step is to perform predictive analysis, which involves using statistical models to predict future events based on historical data. Predictive analysis helps you identify potential outcomes and risks associated with different courses of action. Common techniques used in predictive analysis include regression analysis, time series analysis, and machine learning.

Step 5: Prescriptive Analysis

The final step is to perform prescriptive analysis, which involves using advanced analytics techniques to identify the best course of action for the future. Prescriptive analysis helps you optimize decisions and take actions that will achieve the desired outcomes. Common techniques used in prescriptive analysis include optimization, simulation, and decision trees.

Bonus Step 6: Communicating for Action

Effective communication is crucial when presenting prescriptive analyses. Your audience must understand your logic and be convinced to take real operational action.

Common techniques used to communicate prescriptive analyses include:

  • Know your audience
  • Keep it simple
  • Focus on the key messages
  • Use storytelling techniques
  • Provide context and examples
  • Be transparent
  • Provide actionable recommendations
  • Encourage feedback

By following these tips, financial analysts can effectively communicate prescriptive analyses and provide valuable financial insights.

Conclusion

Prescriptive analyses are a powerful tool that can be used to optimize business processes, improve decision-making, and increase efficiency. The transition from descriptive to prescriptive analytics involves five major steps, and by following these steps, financial analysts can provide clients with informed recommendations that will help them achieve their goals. Effective communication is crucial when presenting prescriptive analyses. By using common communication techniques, financial analysts can effectively communicate prescriptive analyses and provide valuable financial insights.

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