Predictive analytics is software that involves the application of statistics and modeling techniques to give predictions about future outcomes and performance. It considers current and historical data patterns and determines if such patterns are likely to repeat or not. In this way, predictive analytics facilitates businesses and investors to modify the use of their resources so that they can produce maximum advantages in possible future events. Besides, predictive analytics is also being widely used to refine operational efficiencies and minimize risk. Multiple industries and disciplines of various fields are making use of predictive techniques to take important decisions.
How is Predictive Analytics Different from Machine Learning
There is a common misconception that Predictive analytics and machine learning are the same things. But, it is not the fact! Predictive analytics makes use of predictive modeling which may involve machine learning. The Predictive analysts in fact perceive machine learning as an extension of their practice and is an addition to their toolbox. Besides, the target of Predictive Analytics is a specified audience which is not the case with machine learning.
How Does Predictive Analytics Work?
There is a need for some upfront work to set up accurate and efficient predictive analytics. A predictive analyst needs to have an understanding of the existent business problem that needs to be solved, the data that must be prepared for analysis, what models need to be established and refined. To take advantage of predictive analysis, strong leadership is also required to execute actions based on the predictions to extract positive outcomes.
Listed below are the steps that successful predictive analytics projects follow:
- Identification of goals to be achieved based on previous data. It must be evaluated as to what questions need to be answered and what business decisions can take from the collected insights.
- Consideration of data to answer the questions determined in the above step. The data must be evaluated to check if it is clean and if it can help in the learning of predictive patterns.
- Training of system to acquire learning from data and predict outcomes. Training of system needs the establishment of right controls and algorithms. The training enables the predictive analytics model to identify trends and patterns of the concerned audience as well as their behavior. Moreover, continuous retraining of the learning module is also required.
- The modules obtained from predictive analytics can be scheduled to work on the data.
- Use of Insights and Predictions to make decisions and execute the required activities.
How is Predictive Analytics Helping Mankind – Use Cases
Predictive Analytics has made it possible to look more accurately and reliably into the future than the previous tools. Predictive Analytics has bestowed mankind with multiple benefits.
Predictive Analytics Used in Healthcare and Patient Wellness
Predictive Analytics in healthcare lets you input data from a range of different sources both from inside and outside the hospital.
Data collection from every department of the hospital helps to determine which treatments are most likely to be effective.
The incorporation of outside data sources facilitates more effective and comprehensive care. The social determinants such as behavioral data, zip code of residence, and others enable a predictive model to adjust treatment suggestions for doctor review.
Predictive Analytics refine Operations throughout the Software Testing Life Cycle
Predictive Analytics simplifies the analysis of the vast amount of data produced in the process of software testing by incorporating that to be used in modeling outcomes.
Predictive Analytics help to determine the impact of delays in the project which comes in handy while monitoring timelines and maintaining release schedules. Besides, the identification of issues and reasons also enables the course-correction in specific areas before the delay of a larger project.
Predictive Analytics Helps Improve Customer Experience
Instant measurement of customer experiences, opinions, and insights followed by data forecasting to display trends, craft instant actionable feedback to be used in the design and bug-fixing process is possible with Predictive Analytics.
Predictive Analytics also helps to analyze the customer’s behavior by conducting different surveys on social media which determine the trend that lets one stay ahead of any potential backlash before it gets out of control.
When predictive analytics software is implemented, considerable improvement can be witnessed in test efficiency and defect detection.
Predictive Analytics Prevent Unanticipated Equipment Down Time
Predictive analytics are used by Predictive Maintenance software to estimate if and when certain equipment might fail. It helps the company to carry out corrective measures well before the equipment fails. As a result, the workflow is halted for a very short duration as compared to the duration for which it would have stopped if the equipment stopped working all of a sudden.
Predictive Analytics Level up the Marketing Game
Since the marketing industry also operates on the basis of data and metrics, predictive analytics can be used here to achieve different goals.
Using a Predictive model based on a customer’s purchasing history one can know the ideal time to market a product.
Predictive Analytics enable the business owner to take actions ahead of time by regulating brand affinity so that they can avoid or reduce customer churn.
Besides, Predictive Analytics is being used by people of different disciplines. Some other use cases of this technology are listed as following:
Retailers are using Predictive analytics to foresee inventor requirements, run shipping schedules and customize store layouts.
Predictive Analytics Helping Airlines Set Ticket Prices
Predictive Analytics is being used by airlines to set ticket prices based on past travel trends.
Predictive Analytics in Other Industries
Hotels, inns, and hospitality industry players use this technology to foresee the number of guests on a certain day so that they can maximize occupancy and revenue.
Predictive Analytics also facilitate the optimization of marketing campaigns which enables organizations to generate new customer responses as well as to promote cross-sell opportunities.
Predictive Analytics is also playing a vital role in the identification of criminal activities that are likely to happen by studying user behaviors and actions, detecting out-of-the-ordinary activities such as credit card fraud, corporate spying, and cyber attacks.
When used in the field of Aerospace, the outcome of certain maintenance operations on aircraft reliability, fuel use, availability, and uptime can be predicted.
Manufacturers can use predictive analytics to forecast the location and rate of machine failures. They can also optimize the raw material deliveries based on projected future requirements.
There are multiple uses of predictive analytics in financial services, from the development of credit risk models to prediction of the impact of new policies, laws, and regulations on businesses and the market, predictive analytics is producing accurate results.
The above-discussed applications of predictive analytics depict that it is being used widely among different disciples. It can be used in any industry to solve the known problems as well as to identify problems that are unimaginable! It is not the future but the PRESENT, which is enabling organizations to have a comprehensive and accurate understanding of their proceedings and conduct and is also paving the way towards improvement and success!