Making strategic and informed decisions is certainly one of the biggest challenges for companies that are trying to achieve and grow better results. In this line of reasoning, prescriptive analytics appears to be a strong ally for entrepreneurs when it comes to making the best decision for their business.
This method allows the entrepreneur to understand what happened or even predict hypothetical and future scenarios , such as recommending that efficient actions take place to achieve goals and reap the results.
If you want to understand what prescriptive analytics is and how to use it to optimize your decision-making, continue reading this exclusive text and discover all the benefits of this strategy! Check out the details below:
What is prescriptive analytics?
Prescriptive analytics is a highly advanced approach to data analysis that goes beyond prediction or statistical interpretation. This method uses collected data and current technologies, such as machine learning and artificial intelligence (AI), to express clear tactics for a given situation.
Therefore, having this tool in your business’s possession means having an instrument at your service that helps you:
- Identification of the best course to follow in challenging scenarios;
- Optimization of external and internal processes that could be costly;
- Improvement in the operational and financial performance of the business;
- Reducing extra costs by making smart, definitive decisions.
Unlike other analyses, such as descriptive research , prescriptive analytics guides the next step to be taken by the entrepreneur with accuracy and in-depth research.
Difference between prescriptive, predictive and descriptive analytics
Even though these three types of analysis are interconnected, each one has a specific function within a company’s decision-making process, depending on its sector:
1. Descriptive analysis
The focus of descriptive analytics is to understand what happened in your company’s past . For example, knowing which financial reports show the company’s profit in the last six months. This method is suitable for evaluating past performance and capturing patterns.
2. Predictive analysis
As the name suggests, predictive analytics focuses on predicting what might happen in a future scenario. For example, forecasting sales of items based on seasonality of purchases and behavior. It is essential to help plan future actions and anticipate demands.
3. Prescriptive analytics
In prescriptive analysis, the main focus is to recommend what should be done . Suggestions of ideal prices, based on the type of purchases made by competing companies, are a good example of this method, since its purpose is to guide tactical and operational decisions with realistic recommendations.
How are prescriptive analyses performed?
Implementing and using prescriptive analytics may seem a bit complex, but it is a structured process that follows clearly outlined steps. Understand the step-by-step process of how it is put into practice:
1. Data collection
The first step is to collect meaningful information about your business , such as sales data, cash flow, performance of promotional campaigns and customer behavior.
2. Data collection and organization
Did you know that raw data can be inconsistent? This step is crucial to discarding useless information, resolving pending errors, and organizing the data so that it can be examined.
3. Use of analytical models
At this stage, machine learning and artificial intelligence come into play to process the collected data and identify patterns that could be trends or opportunities for commerce.
4. Creating recommendations
Based on the analyzed results, the prescriptive analysis analytical system will offer practical suggestions for your business, for example, adjusting the price of some products, digital marketing strategies or optimizing internal processes.
5. Implementation and monitoring
After following all these steps, the applications and results will be monitored to ensure maximum effectiveness of the method, in addition to adjusting the strategies, if necessary.
Main technologies and tools used
Like almost all types of analytics, prescriptive analytics also uses tools and technologies to accurately collect data. Here are a number of the most usually used ones:
- Artificial intelligence (AI): because it is capable of offering detailed data, artificial intelligence interprets a large amount of data and is able to learn from it;
- BI ( Business Intelligence ) software: to provide a broad and detailed view of the business, BI software integrates data from different sources in a detailed manner;
- Machine Learning : By learning from each new inspection, it allows systems to become increasingly accurate over time;
- CRM tools: Consumer data is the primary basis for identifying opportunities to personalize your business and can even improve the customer experience.
Benefits of prescriptive analytics for businesses
Prescriptive analytics will certainly be a success in your company if implemented correctly. Check out some of the benefits of adopting this method in your business:
- Confident decisions: when data is concrete, business actions are likely to create more organic and positive results;
- Increase competitiveness: even if there are few resources, this method will make small businesses act more strategically;
- Resource optimization: there will be a significant improvement in the company’s investments, staff and time;
- Reduced expenses: Prescriptive analytics will identify processes, services or items that are wasteful or inefficient for your business.
Investing in prescriptive analytics can be a way for you, as an entrepreneur, to benefit your company, optimize internal and external processes, and leverage results. If you want to start using the method, explore the available tools, invest in qualified professionals, and take a step towards success
