What is Predictive analysis?
As the name suggests, predictive analytics is the technology that enables users to make predictions about possible trends and forecast outcomes of different actions. This is achieved by a series of techniques including Artificial Intelligence(AI), Machine Learning, modeling, Data Mining, and statistics. Through these techniques, one can easily identify recurring patterns and make predictions on their next emergence. These techniques not only increase the operational efficiency of organizations but also mitigate supply chain risks.
Predictive Analysis Tools
There are quite a few Predictive analysis tools available in the market known for their niche data and pattern identification abilities. The best tools include:
- IBM SPSS Statistics for advanced data analytics
- Sap Predictive analysis for Predictive Modeling
- TIBCO data science Statistica for Full Spectrum Analysis
- OCI Data security for self-driving machine learning
- H20 for Automatic feature engineering and scoring pipeline amongst others.
These tools can be used for a variety of functionalities and can be revolutionary for businesses worldwide. Let us have a look at the avenues where predictive analytics tools can help businesses achieve growth and success.
Uses cases of Predictive Analytics
Credit Scoring is another upcoming avenue readily employing predictive analytics when it comes to assessing tools and techniques. Predictive analysis techniques uses ML tools to assess the creditworthiness of businesses and the chances of the borrower defaulting on their financial obligations. It does so by studying and analyzing customers’ previous credit history. This application of predictive analysis tools can be extremely beneficial for banks loaning facilities.
Forecasting can be instrumental in saving resources by ensuring optimal usage and guaranteeing sales. By forecasting the latest trends businesses can predict trends and understand crowd favors while investing in procuring and manufacturing the same. The quality of these forecasts can further be improved by unique predictive modeling techniques that optimize these forecasts and cleans them for a better end-user experience.
Underwriting refers to lenders verifying borrowers’ income, assets, debts, and property details in order to issue them monetary support and loans. A financial expert, along with the help of predictive data analytics tools, determines the likelihood of having to pay out for a future claim based on the current risk pool.
Predictive analytics is also being used in the financial sector to identify any fraudulent transactions, patterns, and trends. An organization can amp up its security by employing the best predictive analysis tools. This is achieved by examining activity across bank accounts or by looking at the timing of certain transactions.
Supply chain analytics are used to anticipate and manage inventory levels and pricing strategies. Using historical data and statistical models, supply chain predictive analytics evaluates the performance, demand, and potential disruptions of the supply chain in the future. This helps businesses make smarter decisions, optimize their resources and processes, and manage risks proactively. Businesses may predict what supplies will be available at any given moment and whether there will be any shortages by adopting these steps.
Predictive analytics is used by human resources to optimize a number of activities, including predicting future skill and workforce requirements or looking at employee data to determine the causes of high turnover rates. In addition to predicting diversity or inclusion activities, predictive analytics may analyze an employee’s performance, talents, and preferences to anticipate their career growth and assist with career development planning.
Predictive analytics tools are the future and are bound to be adopted across more and more industry verticals. With businesses realizing the hidden potential of predictive analysis techniques, the industry is all set to grow exponentially. This is the major reason why businesses are investing in building smart software solutions equipped with predictive analytics capabilities along with Artificial Intelligence and Machine learning.