Living in the 21st century is truly living on a fast lane. Our world has been changing in a way we have never seen before. One very good example is the COVID-19 pandemic, which many people have described as “unprecedented” and “unforeseen”. Similarly, along with the pandemic, climate change is also something that businesses should take seriously. At the same time, the way people are doing business has also changed dramatically with the digital disruption, which has also changed the consumer behavior patterns. 

These changes and disruptions might not be pleasant to look at, yet to buffer ourselves against future shocks it is essential that we study them carefully. In addition to that, along with crises, these changes actually offer opportunities simultaneously. This is where predictive analytics comes in: to use big data to help businesses forecast impending risks so they can take adequate strategic preventive measures to mitigate the impacts of these risks.

Why predictive analytics?

This time, large data sets about human behavior have largely been available due to the business model employed by new technology, which allows the collection of extremely large sets of digital data. The online marketplace has kept abundant digital records of the preferences of different consumer demographics. Ride-hailing apps give us a clue about traffic density, while the fi0cial technology (fintech) platforms keep individuals’ transaction information’s digital trace. Not only that, surveillance and sensor systems have given scientists access to trends and patterns. 

Who will get the benefit from predictive analytics?

These digital records have given data scientists open access to mine any kinds of data they need to help businesses in strategic decision-making, including the formulation of a risk mitigation plan. At the same time, predictive analytics also help businesses boost their operational efficiency. An article by martech.com outlines several functions of predictive analytics: to identify churn and reduce customer defection, identify potential fraud, reduce employee attrition, adapt to change, reduce the risk for new business as well as fi0cial risk management. KDnuggets.com published an article that illustrated how different businesses could apply this. Food and beverage outlets can use predictive analytics to prevent delayed deliveries instead of reporting on delayed deliveries. Supermarkets can prevent spoilage instead of reporting on spoilage. Companies can prevent high employee turnover instead of reporting on a high turnover. The article then emphasized that by predicting possible risks, we can prescribe some actions to prevent negative impacts from the oncoming risks.

What predictive analytics can do for you?

Predictive analytics can help you perform various risk analysis functions. First of all, it helps you identify and reduce customer defection. For instance, American Express claimed it could identify 24 percent of accounts that would close in the Australian market within the next four months, based on insights on potential churns gained from transaction history and 115 other variables. It can help businesses prevent fraud, a long-drawn process which, without big data, could involve lots of people working long hours interviewing people in search of evidence. American national accounting and audit firm BDO, for instance, narrowed down the list of thousands of vendors down to a handful which has the most significant inconsistencies. Using the same technology, IRS has recovered more than US$2 billion of taxes, while stopping billions of dollars of fraud in its tracks.

Predictive analytics can also help you reduce employee attrition, determine whether a certain geographical location is lucrative enough to set up a new business, as well as helping companies provide risk-free fi0cial services.

In Indonesia, you can use Telkom DWS as your partner to analyze data based on location, demographics, and customer behavior to produce forecasts which will arm you against unforeseen future shocks. Together we can adapt to the future. For more information, please visit https://mycarrier.telkom.co.id/big-data