While doing a daily reading exercise about the innovations in the field of big data, I came across this interesting case study.
One of the world’s largest companies which provide refrigerated trucks wanted to increase their operational efficiency along with productivity. With this set objective they collaborated with a risk management application. The results were amazing. There was a reduction in the number of accidents by 15%. On further reading, I came across even more surprising stats wherein another company reduced the accidents by 81%. Also, the driver turnover ratio was down by 49% thus improved the productivity.
Surprising to know that how numbers can turn around the efficiency of an organization. How is it possible that a mere set of numbers bringing about a radical change which normal human beings can’t do even after a brainstorming session. The reason being analytics provide meaning to the numbers which help us dig out insights which have been unexplored before.
All the following mentioned techniques belong to a methodology termed as “predictive analytics”. This corollary of big data has provided a powerful tool especially to the insurance sector which is plagued with unpredictability. This technique helps to foresee the future scenario with the help of various complex mathematical algorithms. It is based on pattern understanding and coming up with certain outcomes which are probable in the future based on the current available data.
These types of analytics help to create predictive models with the help of a powerful combination of data and analytics. In order to compete in this competitive era, the companies should reduce the dependency on historical data which is a rear view mechanism and need to be more proactive in understanding the customer behaviour. If the company is ready with the tactics and strategies the customer is expecting in the near future, the company will be able to get more customers thus increasing their pie of the market share. The organizations have to be predictive and will have to gain more information which helps them to get more data patterns and trends. The data will help the organization anticipate certain situations which will help the company to be equipped with certain strategies and readiness to conquer such situations.
It is also used to understand the credit risk of any particular customer/client and based on that prioritize the customer who has the power to payback the debts. Predictive analytics is becoming a mainstream technology as more and more organizations are adopting the same to foresee the future. This is magic represented using data and analytics which is benefiting many companies.