10.09
Agung Budi Prasetio, S.T, M.Eng
Companies can gain significant long-term benefits of using predictive analytics to their operational and historical data, analysts and IT managers said at Computerworld BI Perspectives and Analytics conference held this week here.
Unlike traditional business intelligence practices, which are backward looking in nature, predicting analytical approaches to help companies collect usable information based on historical data.
If properly applied, predictive analysis, enabling companies to identify and respond to new opportunities faster, they said.
In the speech, James Taylor, CEO of decision management solutions, said predictive analysis is especially useful in situations where companies need a quick decision with large volumes of data.
Predictive Analytics practices can help companies in three key areas: to minimize risk, identify fraud and pursue new business opportunities, Taylor said .
For example, predictive analytics can help companies fine tune their ability to identify risks in areas such as loans and loan originations, or fraud in areas such as insurance, he added.
Importantly, loading them into predictive analysis of operational data, companies can put into a better position to identify new revenue opportunities, Taylor said. For example, by looking at historical customer buying patterns, companies can make reasonable predictions on the kind of promotional offers and coupons that might resonate with the customer.
Blue Cross and Blue Shield System (BCBS) is an organization that is already considerable benefits of predictive analysis. As an organization that provides health insurance, nearly one in three Americans, Blue Cross Blue Shield system amassed huge amounts of claims data related to over the years.
A few years ago, BCBS Association, a body that has the blue brand, created a database called Blue Health Intelligence (BHI) to consolidate all claims information held by each of the 39 companies that are part of the BCBS. The database is one of the largest repositories for de healthcare data, anywhere and includes requirements relating to information on more than 100 million people.
BHI operates as a separate unit, and offers a wide range of services, business intelligence, which allows for better health care for members and also changing the way it is governed by the BCBS.
The impetus for the effort came from the need to BCBS, as well as other health insurers, to control spiraling costs, he said Swati Abbott, president and CEO of BHI, during the presentation.
Disproportionate share of the cost of health care goes to care for people with chronic disease, the abbot said. In fact, the top 5% of health care users account for more than 55% of the cost of health care, she said.
When using predictive analytic technology to its vast trove of claims data, BCBS were still better not to identify risk factors that lead to several chronic diseases, but also in identifying individuals who are at increased risk for these diseases, she said.
"For each member enrolled in a health plan we have health, Score," which represents the probability that an individual in need of lifelong chronic disease, the abbot said. BHI even developed a disease-specific modules, eg one for diabetes that predict individual risk of developing diabetes based on previous data, she said.
Unlike traditional business intelligence practices, which are backward looking in nature, predicting analytical approaches to help companies collect usable information based on historical data.
If properly applied, predictive analysis, enabling companies to identify and respond to new opportunities faster, they said.
In the speech, James Taylor, CEO of decision management solutions, said predictive analysis is especially useful in situations where companies need a quick decision with large volumes of data.
Predictive Analytics practices can help companies in three key areas: to minimize risk, identify fraud and pursue new business opportunities, Taylor said .
For example, predictive analytics can help companies fine tune their ability to identify risks in areas such as loans and loan originations, or fraud in areas such as insurance, he added.
Importantly, loading them into predictive analysis of operational data, companies can put into a better position to identify new revenue opportunities, Taylor said. For example, by looking at historical customer buying patterns, companies can make reasonable predictions on the kind of promotional offers and coupons that might resonate with the customer.
Blue Cross and Blue Shield System (BCBS) is an organization that is already considerable benefits of predictive analysis. As an organization that provides health insurance, nearly one in three Americans, Blue Cross Blue Shield system amassed huge amounts of claims data related to over the years.
A few years ago, BCBS Association, a body that has the blue brand, created a database called Blue Health Intelligence (BHI) to consolidate all claims information held by each of the 39 companies that are part of the BCBS. The database is one of the largest repositories for de healthcare data, anywhere and includes requirements relating to information on more than 100 million people.
BHI operates as a separate unit, and offers a wide range of services, business intelligence, which allows for better health care for members and also changing the way it is governed by the BCBS.
The impetus for the effort came from the need to BCBS, as well as other health insurers, to control spiraling costs, he said Swati Abbott, president and CEO of BHI, during the presentation.
Disproportionate share of the cost of health care goes to care for people with chronic disease, the abbot said. In fact, the top 5% of health care users account for more than 55% of the cost of health care, she said.
When using predictive analytic technology to its vast trove of claims data, BCBS were still better not to identify risk factors that lead to several chronic diseases, but also in identifying individuals who are at increased risk for these diseases, she said.
"For each member enrolled in a health plan we have health, Score," which represents the probability that an individual in need of lifelong chronic disease, the abbot said. BHI even developed a disease-specific modules, eg one for diabetes that predict individual risk of developing diabetes based on previous data, she said.
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