How to Use Prescriptive Analytics

Since businesses nowadays have access to huge amounts of data, companies are adopting analytical solutions aim at digging out meanings and conclusions, helping to improve their decision making process. As a prescriptive analytics practitioner, you would try aim to optimize your; sale planning efforts, analyze the historical data of a business, and forecast what may or may not happen in the future. It promotes organization driven by data. And as a result, businesses can optimize their operating costs, supply chain, revenues and customer service, in order to experience huge ROIs (Return on investment).

Exploring analytic options is a daunting task. Keeping that in mind, they are divided into three distinct levels. All the three categories complement each other, and we cannot say that one is more important than the other. If a business wants to an overall view of its industry, and wants to find out how a business can compete effectively in the market, then it needs to have a strong analytical environment. The three analytic categories include:

• Descriptive analytics provides insight into what has happened in the past
• Predictive analytics uses techniques and tools in order to understand what will happen in the future.
• Prescriptive analytics uses algorithms to recommend possible results and explain what should be done to promote a business.

Simply put, prescriptive analytics provides recommendations that you may use to help your business goals turn into reality. in order to achieve this, you need to acknowledge the right way in which to ask: appropriate questions, define your goals and optimize them for success. Some of these prescriptive model examples include:

• Understanding the effect of price on quantity.
• Ways to maximize revenue.
• Ways to maximize profits.
• Making best use of advertising for certain products or services.

Almost every business today has a website, or at least some kind of digital forum or activity. Thus, it has become easier to collect and analyze data with the intention of gaining more knowledge and buying patterns which tempt customers. Since entrepreneurs are very busy in their own everyday business operations, they cannot pursue such data technologies. In this case, a data analytics team can be hired as an outsource data service provider. This team can manage and handle all data related to technical tasks.

Some businesses have a greater need of prescriptive analytics than others. Prescriptive analytics can be beneficial both for businesses and their employees. With proper training in prescriptive analytics, businesses can improve their outcome in real-time.

While some marketing departments are considered more analytical than other business streams, prescriptive analytics is slowly gaining popularity in other business. Some business which are gradually benefiting from prescriptive analytics, include; operations, R&D, HR, sales and others. Prescriptive analytics also includes the optimization of supply chain, as companies need to know who to partner with and choose suitable partners who have a greater precision power. Prescriptive analytics both simplifies and speeds up the entire process. It also helps in identifying the best strategic plans which a business should pursue.

Most entrepreneurs want ready-made and quick business solutions when necessary. In case of emergencies, they need fast solutions and knowledge driven by available data. Prescriptive analytics can help to better operate a business without investing too much time and skill. Business executives, for example, who are looking for an immediate solution to their problems, will find prescriptive analytics quite appealing and helpful.

Prescriptive analytics allows you to prescribe a variety of possible actions which are required to achieve a goal or find a solution. Prescriptive analytics is all about giving advice. While using prescriptive analytics, it enables you to calculate the effects a future decision may induce. It is helpful in advising possible results before a final decision is made. At its best, this branch of analytics foresees not only what may happen, but also the reasons for it. In addition, it applies suggestions on how a business should make their next step.

Prescriptive analytics goes beyond predictive and descriptive analytics by suggesting possible action plans for future situations. A number of tools and techniques are used to achieve this purpose, including: algorithms, business rules, automated learning and modeling procedures. You may use such techniques with input from varied data sets, including big data, real-time data feeds, transactional and historical data.

In the beginning, prescriptive analytics may seem quite complex to both use and administer. Many companies do not yet use them in their everyday business courses. But if implemented correctly, it may leave a huge impact on your decision making process, and ultimately your business’ overall growth and progress. Many large-scale companies are successfully applying prescriptive analytics to optimize their: scheduling, production and inventory in terms of supply chain. Prescriptive analytics enables them to deliver the right kind of product at the perfect time, in turn, enhancing consumer experience.

Prescriptive analytics is a combination of machine generated action plans and human decision making processes. It is based on the balance between common sense and algorithmic calculations. While striking the right balance can be tricky, consider these tips to achieve success:

• Prescriptive analytics platforms are not all the same. Some may be suitable for certain types of businesses, while others may be best for others. So, while choosing a prescriptive analytics software, research is necessary to make sure that it meets your particular business requirements.

• Whichever software you choose, make sure that all members of your organization understand the working of the system and how it will benefit them. Sometimes, data generated by the software may not match the perspective of humans. When recommending the software to your employees, reasoning behind it should be clear.

• The functions of every businesses is based on a set of rules. On the other hand, learning systems generated by machines are quite different. They develop over time, and require huge amounts of data. Fresh data is also required to get an idea of a current status. If you are going to use predictive analytics for your business, for a long time, then you need to constantly monitor it. Make sure that the results received are not only productive, but moral and ethical, paralleling the credence you wish for your business.

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