Predictive Analytics

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What is Predictive Analytics?


Predictive analytics is a technique to understand future outcome and take informed decisions based on the findings. Predictive analytics uses various data, machine learning technique, statistical algorithms and past data to produce future scenarios.

The aim here is to move towards a more certain future by making better decisions and uncovering new stories from the data that leads to improved actions.

Predictive analytics help organizations to move beyond descriptive models (used to understand what happened) and diagnostic models (used to identify key relationships and reason for something happened). Predictive models factors in past results to develop a model that can often be used to predict the result from different data sets.

Organizations that are already using predictive analytics are able to make right decision at the right time and gain competitive advantage in the market.

Why does it make sense to use predictive analytics?


 

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To be certain in uncertain economic conditions.

To gain competitive advantage in the market.

Availability of easy, fast and cheaper technology.

Gain better insight from the data and take right decisions.

Increase in the volume and type of data that can help in uncovering stories, align marketing activities, produce better product, deliver better care, and enhance customer experience and more.

Predictive analytics is used for?


As per a TDWI report, top five use of predictive analytics are:

Understand customers.

Drive strategic decision making.

Identify trends.

Improve Business Performance.

Predict behavior.

Application of predictive analytics across industries:


Every industry uses predictive analytics in a specific way, few of them are explained below.

Manufacturing

Manufacturing industry use Predictive analytics to gain significant insight into the factors that reduces the quality of products, processes, yield, machine and operation failures, also to improve quality, forecast profitable demand, maximize equipment value and increase equipment uptime.

Banking and Finance

Predictive analytics plays critical role in banking and finance industries. It helps companies to identify the risk and improve cross sell and up-sell effectively, retain customers, segmentation, identify potential fraud at multiple levels like application, credit card or mortgage, transactional frauds, collections, account management and efficient liquidity planning.

Media and Entertainment

Predictive analytics help media industry by giving better insight into the audience behavior, the driving force behind a specific behavior change, their preference, trends, and influencing attributes. It can also help in scoring new audience. Companies integrate social media data with predictive analytics to see how they have performed and to predict future engagement and opportunities. Predictive analytics is also used to identify the right distribution channel, vendor performance and forecast and to control costs.

Insurance companies

Predictive analytics help insurance companies in detecting claims fraud, determining premium rates, identify high risk patients and provide the most appropriate policy as per business rules, retain clients, attract new customers, optimize claims processes, derive better marketing campaigns and improve performance and increase profitability.

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Healthcare

Predictive analytics has the potential to revolutionize care delivery around the world. Healthcare providers use predictive analytics to search through the massive amount of information and predict outcomes for individual patients. Physicians can use predictive algorithms to make more accurate diagnoses. Predictive analytics can help in identifying at risk patients and come up with lifestyle suggestion to lead a healthy life. It can detect diseases early and prevent it from becoming a risk. Physician’s get complete answers for individual patient, this helps in giving the right care. Pharma companies use predictive analytics to produce better medicines.

Government and Public Sector

Public sector is replete with data. Every second there is ginormous amount of data being produced for public sector to use. Government use predictive analytics for fraud detection, automating claims processing, operational analytics, tax and revenue collection, cyber security, workforce analytics, improper payment recovery and prevention, credit scoring and predicting default, crime prediction, text mining and more.

Oil and Gas

This industry is amongst the first one that adopted predictive analytics due to the nature of the work involved. The sector is involved in the process of extraction, refining, exploration, transporting oil and gas by tankers and pipelines and marketing petroleum products and more. Predictive analytics helps this sector in the areas of forecasting, analysis, energy trading, predictive maintenance, trade off, risk management and optimization.

Retail

Retail industry is inflicted with many challenges. Predictive analytics can help retailers to analyze customer behavior, buying patterns and search history through which retailers can provide better products as per the customers’ price preference, device better marketing campaigns to be in front of loyal customers, bring back dropped out customers and improve sales, enhance customer experience by providing intimate shopping experience and services. On the operational side, predictive analytics can help retailers to maintain inventory, control costs, ensure timely delivery of products, and improve supply chain and profits.

 

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