The art of mining historical data sets and extracting critical information from them is what goes into the making of predictive analytics. Predictive Analytics explains the important cause-and-effect mechanisms for business organizations who are operating in a market that is highly fluctuating. Predictive analytics not only enables businesses to keep up with the market trends but also adjust to boom and bust cycles of the market. That said, predictive analytics is not a standalone entity. It is taught as an integrated component of Data Analytics courses as well as Data Analytics certification. So, we can easily say that data analytics is one of the most important precursors to predictive analytics.
In this article, we attempt to analyze the different industrial applications of predictive analytics.
Healthcare industry witnessing a paradigm shift in operations
The healthcare sector has undergone a paradigm shift in recent times. The amount of data that has emerged from processes like operations, diagnosis and treatment is difficult to be analyzed through the traditional mechanisms. It is in this context that predictive analytics can help in tackling this large repository of data and use it to derive critical information. This critical information can be fed into the design and development of new diagnostic tools and techniques powered by machine learning and artificial intelligence.
Predictive analytics can also be particularly useful in a time when the whole world is gripped in the wave of covid-19 virus. With the help of predictive analytics, we can go for advanced tracing and predict the areas and regions where the possibility of the spread of the virus is relatively large. This can help us in taking necessary measures to curb the spread of the pandemic.
Manufacturing sector relying on advanced predictive analytics
The sector of manufacturing has undergone a rapid change in the last few years. The scope of manufacturing is no longer limited to fabrication of traditional machines and systems. In fact, the design and development of smart products as well as AI engineered products give glimpses of the new age manufacturing sector. Since the manufacturing sector involves the design and development of new products, it is likely that the commercial aspects of such products may come under question. It is in this context that predictive analytics comes to the aid of the manufacturing sector and helps in forecasting the commercial success of a particular product based on a wide range of tools and parameters.
Financial sector becoming more secure
Predictive analytics has revolutionized the financial sector by virtue of its notable applications. With the help of predictive analytics, a company can analyze the transaction history of a customer as well as the price range of products that he is interested in. This information can be outsourced to two different sectors at a specific cost. In addition to this, predictive analytics can personalize recommendations for different customers regarding their bill payment as well as their past payments. Moreover, predictive analytics can also help in setting up autopay options where bills are automatically paid at due date and time. Predictive analytics is also a great tool for investing in the stock market as it gives the information of the performance of different shares, thereby, helping in channelizing investment.
Business analytics acquiring stability
In the present times, businesses face very stiff competition from their counterparts. The survival in the business domain in the present time has become subject to the deployment of technological resources apart from the economic ones. Businesses that have a firm understanding of predictive analytics can invest in different products and adjust their business operations in accordance with dynamic market trends. Predictive analytics can help a business in decision making, customer recommendation, customer analytics, customer personalization, and many other things that give information about customer choices. Whenever valuable information becomes available to a business, it can use this as a critical resource for tapping the available business opportunities. Finally, predictive analytics can give an exact picture of the customer journey and enable a business to modify its operations in the corresponding direction.
The way ahead
The application of predictive analytics will increase by a large extent in the times to come. This is because sectors like manufacturing, logistics, insurance, retail, e-commerce, healthcare, and education will all be dependent upon predictive analytics in one or another way. The need of the hour is to fully integrate our machine learning capacities with analytics technologies so that predictive analytics becomes extremely advanced in the times to come.
