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How Predictive Analytics can impact your business?
Technology - April 08, 2020
Big data along with Predictive Analytics has been transforming the way businesses run their IT. Along with IoT, which harnesses bulk volume of data from interconnected systems, predictive analytics is becoming the new norm by which businesses not only improve their operational efficiency but also target more traffic to their products and services.
One of the biggest examples is Amazon where Predictive Analytics has increased Amazon's sale by almost 30%. Amazon did this by studying the shopping pattern of its customers and by providing them product suggestions based on those patterns.
Not just numbers, predictive analytics technology is making our lives safe as well. Now car companies can monitor the performance of your car against wear and tear and warn you accordingly. This is saving countless lives.
Why Predictive Analytics Matter
1) Productivity: With predictive analytics, you don't need to rely on traditional assumptions. You can leverage real time data to make smart business models that result in greater operational efficiency.
2) Savings: Predictive analytics narrows down your targets and business objectives. It helps you make smart decisions such as which customers to targets and which investments to make. This also allows you to better allocate your resources and save on costs.
3) Risk management: Predictive analytics does thorough data assessments by taking in account the market sentiments and predictions. This way, you can take informed decisions against any prevailing risks.
4) Fraud detections: The methodologies on which Predictive analytics are built recognizes frauds and vulnerabilities before it affects your systems.
How Predictive Analytics is impacting different industries
Insurance companies can use predictive analytics to do appropriate risk assessments and accordingly advise their customers. For e.g. predictive analytics tools can determine which areas are more prone to burglary and they can use this information to further gather data on patterns related to time of crime. This information can be critical and insurance companies can pass on the information to their clients. This way they people living in those areas be better prepared against any mishaps.
Predictive analytics has transformed the automobile sector by bringing consistency and certainty to driver safety. Now IoT sensors can give insights on vehicle depreciation and the rider can then take appropriate steps. In addition, predictive analytics tools can also give real time traffic and road data which can save time and resources.
Predictive analytics is already doing wonders in health care. For e.g. it can analyze patient data and remind people to schedule their next appointments or update them about availability of medicines or new treatment methods. The biggest advantage however is how predictive analytics can use cumulative data of communities to predict spread of common diseases and advise appropriate actions.
Predictive analytics has the potential to improve the quality of produce. The predictive analytics tools constantly monitor the health of machines by observing the sensor data. This directly influences the quality and quantity of the produce. In addition, predictive analytics also helps manufacturers by forecasting demand and use customer behavior data to innovate in terms of types of products etc.
Predictive Analytics Processes
Predictive analytics tools usually follow a predefined process. The components of the processes are:
• Outlining the project
• Collecting data
• Analysis of the collected data
• Data modeling
• Monitoring of the model
Predictive Tools, Language and leading software
Predictive tools have evolved a long way. Earlier only personnel with advanced skills were able to deploy such tools. Today, these tools are not restricted to advanced IT professionals. With wider adoption and accessibility, these tools now come with easy data assimilation and provide the user with informative visual graphics and interfaces. Predictive Model Markup Language (PMML) was proposed as a standard language for creating predictive models. It is an XML based language. Few of the leading Predictive analytics software are listed below:
• Microsoft R Open
• Microsoft Azure Machine Learning Studio
• Wolfram Mathematica
• SAS Advanced Analytics
• Anaconda Enterprise
• TIBCO Statistica
• TIBCO Spotfire
• RapidMiner Studio
• KNIME Analytics Platform
• Dataiku DSS
• FICO Predictive Analytics
• Buxton Analytics Platform
• Funnel Science
• Salford Systems SPM
Predictive analytics is already here and is changing the ways companies do their operations and offer services to their customers. We live in the age of intelligent technologies like Artificial Intelligence, Machine learning, Blockchains etc. and as these technologies advance, predictive analytics is going to advance. The transformative benefits we are seeing as a result of predictive analytics are going to increase multi fold and the benefits would be even greater operational efficiency and direct customer benefits.