By Natalie Burg
If hindsight is 20/20 for businesses, what is the value of laser-focused foresight? For companies like Amazon, it could mean beginning to ship customers' packages before they even order them, giving the retailer an unparalleled advantage in shipping speed. Today, the value of predicting the future of markets and consumers is on the rise, but the trend isn't based on anything as mystical as tea leaves or palm reading: Simply put, it's all about the data.
How important is predictive analytics today? According to a recent Accenture survey of 600 business executives, the use of forward-looking data analysis has tripled since 2009. The company attributes such growth in what its report calls this "advanced application of analytics" to increased "sophistication in analytics capabilities that anticipate tomorrow rather than explain yesterday."
What Is Predictive Analytics?
Data that can predict the future may seem like it must come from a newfound trough of metrics, but the data is closer than you think. According to Dr. Michael Wu, chief scientist at social customer experience management firm Lithium Technologies, it's not about finding new raw data, but about using data differently. With large amounts of data, organizations can identify patterns and build new models to predict future actions rather than simply analyzing the past through the old standard of descriptive analytics.
Wu told InformationWeek that predictive analytics utilizes "a variety of statistical, modeling, data mining, and machine learning techniques to study recent and historical data, thereby allowing analysts to make predictions about the future."
A Forward-Looking Advantage
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This edge can look very different depending on the company and the industry. For online retailers, Practical Ecommerce explains, predictive analytics can be used to automatically vary pricing over time based on purchasing trends, produce optimal search results, and pair the right promotion with the right consumer to close a sale.
Predictive analytics can be used not only to reveal what people will buy, but also how effective they will be in a job. Information Management revealed how Abbot Analytics used predictive data to help the U.S. Special Forces assess new candidates based on information such as the qualities of people who had done the job effectively in the past, as well as "acceptable trade-offs" for those qualities.
Even transaction banking companies are getting a boost from predictive analytics. Finextra reported that financial services companies have reduced their time-to-decision making by 13 percent with analytics (compared to 10 percent for companies not employing predictive data). By providing suggested outcomes in real time through single-screen dashboards, the analytics have helped transaction bankers improve their decision making in the areas of risk, fraud mitigation, liquidity and collateral management.
The Future of Looking Forward
As if predicting the future with data isn't business-meets-sci fi enough, the possibilities of predictive analytics are generating buzz. Some projections are as practical as using analytics to identify how market volatility will impact production plans or the way in which car navigation systems can suggest a driver's preferred restaurants based on time and proximity. Others take a more futuristic outlook, such as using data for predictive policing to pre-empt crime.
According to RCR Wireless News, the future of the wireless M2M (machine-to-machine) market is bound up in the future of predictive analytics. The site reported that analyst firm Berg Insight anticipates the next big step in the industry will be to use data from mobile network connections to expand their reach to more customers.
The future of using data to predict behavior extends into human services, as well. CITE World explained how the U.S Department of Veterans Affairs and the Dartmouth University Geisel School of Medicine are working to use predictive analytics to identify risk factors in military suicides using an opt-in database of 100,000 veterans and millions of social media posts in a program called the Durkheim Project.
It's easy to see how using data to predict customer and market behavior can be invaluable to businesses. Though far from a crystal ball--InformationWeek is careful to point out that Lithium Technologies' Wu said predictive analytics can only tell a business what could happen in the future, not what will happen--the forward-looking model could change the way many companies within a number of industries make decisions and get ahead.
With a Transparency Market Research report anticipating the market for predictive analytics software to reach $6.5 billion by 2019 -- as well as big moves like Amazon's anticipatory shipping program making waves -- one prediction is clear: there's a big future in using data to predict what's coming next.
With a background in community and economic development, Natalie Burg writes about growth, entrepreneurialism and innovation.
