The growing need for quality data management has left many people seeking more profound knowledge of the specifics of data analytics. Analytics tools can streamline business processes and serve as the gateway to better decisions overall. So what is prescriptive analytics exactly? Prescriptive analytics is a form of business analytics that emphasizes practical actions regarding insight obtained from data.
How Does Prescriptive Analytics Differ From Other Types Of Analytics?
Prescriptive analytics is closely related to both predictive analytics and descriptive analytics. The critical difference is that instead of data monitoring, prescriptive analytics focuses on finding the most effective action plan in a given circumstance. This type of analytics determines the best course of action by using algorithms derived from computer science and mathematical statistic methods. The prescriptive approach represents the efficient utilization of the predictive model. Essentially, the best way to find out what you or your company can do to employ your existing analytical processes is to accompany the results with prescriptive analytics.
The Use Of Prescriptive Analytics Technology
There is a particular need for prescriptive analytics in fields that experience constant fluctuation. One example can be found in the oil industry. The oil industry is affected by several factors like environmental conditions, political atmosphere, and supply and demand. Prescriptive analytics helps this industry drive down costs and increase production by monitoring its most influential factors 24/7 and providing actionable insights to industry leaders. Insurance companies may utilize prescriptive analytics for risk assessment to ensure adequate premiums and plan details. Overall, prescriptive analytics can help achieve company goals like organization, customer satisfaction, and cost reduction.
Making Better Business Decisions
Knowing what specific actions to take in a given scenario is a big responsibility for those in leadership roles. There are often hundreds or thousands of components to consider. Therefore, the implications of each decision option usually can’t be measured equally due to time constraints and human biases. When it’s time to make a decision, the first thing to consider is the possible outcome. Predictive analytics utilizes machine learning to analyze historical data and prior experiences. These analytics then provide possible outcomes and the likelihood of the same. Now that predictive analytics has provided you with a few possible results, how can you know which actions will be the most effective?
This is where prescriptive analytics takes on an essential role in business strategy. This role is often referred to as decision optimization. A prescriptive analytics solution weighs future outcomes and makes specific recommendations, taking some of the heat off of executives with heavy decision-making responsibilities. Because prescriptive analytics software uses algorithms and statistical methods to come to an actionable conclusion, you can eliminate the possibility of decision-making bias. Therefore, your decisions will be based on hard data, devoid of reservations held by past experiences.
For example, if a retail company is contemplating how much product to order for the impending busy season, the inventory specialist may consider what last season was like for them. Perhaps last season, they spent hours sorting through an overstocked inventory. They may consider that the year before that experienced shortages, but maybe they will still be more inclined to limit their orders, to err on the side of caution. This decision is based on a personal experience. It may not take into account more technical observations like the state of the economy or the overall fluctuation of consumer demand for their specific product over the last five years.
For people unfamiliar with data sciences in general, prescriptive analytics applications can be an overwhelming topic. Those interested in building their knowledge of business intelligence and data science platforms may want to consider TIBCO’s products. Partially due to their low-cost high-quality software licensing options, TIBCO is an industry leader in data science software products. Their web pages house several helpful informational videos and resources.