CIOs Can Lead Change with Predictive Analytics
During a month-long visit to China this summer I read a well-written history which included a chapter on one of the early dynasties. The author mentioned a common curse at that time: "May you live in times of great change." It was a gripping read and I can imagine that Chinese peasant life, during dynastic ebb and flow, could be considerably more risk than reward.
Some think the "time of great change" we live in today is a curse.
Consider the accelerating rate of social technology adoption: it took Radio 38 years to reach 50 million listeners. Since then, TV reached that many viewers in one-third the time. The Internet got there in three years and Twitter in nine months.
Of course, change presents us with opportunities and risks. At IBM we believe seizing opportunities requires an understanding of what is behind the market changes. We work with clients to translate the overwhelming and accelerating tsunami of information into analytical models about what the authentic industry drivers really are. By iteratively maturing and exploiting those models, our clients can participate in leading change more often than reacting to it.
When uncovering the causes of market change, diversity of data and depth of perspective are key design points. With the advent of social networks we have an extraordinary window into the diverse factors behind consumer decision-making. Sentiment analysis is a fundamental methodology. After all, every human decision implies an emotional impulse. And, with more than 85% of consumer decisions being driven by peer advice today, understanding the social & emotional context is a critical success factor. As Deepak Advani pointed out in a blog last month, data richness ranges from the social web to transactional data to customer profiles. There is no such thing as too much data when it comes to modeling changes in the market.
But, deep perspective and domain expertise is equally important to data diversity. Typically, successful analytical work teams are split-out between: i) a data scientist familiar with the tool(s), ii) an industry subject-matter-expert and iii) a program manager looking through a "what matters the most" lens. Those qualities are rarely possessed by a single person. In fact, you may not want them to be because the most creative application of ideas and theories to the model development process is generated by diverse and expert perspectives.
Our most successful clients arrive at an understanding of market causality through a close collaboration between the CMO and CIO organizations. The diverse information and perspectives of each organization are irreplaceable. And, in changing times like these, where opportunity and risk are two sides of the same coin, there is no substitute for authentic engagement across the enterprise. Achieving competitive advantage without it is becoming nearly impossible.
In a forthcoming follow-up blog, I will focus more on social analytics - particularly inside the enterprise - and privacy issues when analyzing social networks.
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