Analytics 3.0 – The World as it is Today
In the December 2013 issue of the Harvard Business Review, Thomas Davenport describes what he calls “Analytics 3.0” – essentially, the idea that we’ve entered an era in which “ever…

In the December 2013 issue of the Harvard Business Review, Thomas Davenport describes what he calls “Analytics 3.0” – essentially, the idea that we’ve entered an era in which “every firm in every industry … [has] the ability to embed analytics and optimization into every business decision.”
I had the opportunity to speak at a conference recently where Davenport also spoke. He observed that companies are seeking competitive advantages by embedding “data smartness” in their operations as well as in the products and services customers buy.
We refer to this as decision optimization at FICO. Our belief in this approach has helped guide our strategic roadmap for the past decade. In fact, many of our clients are well down the decision-optimization path.
We see this in our work with national retail chains that optimize millions of personalized offers based on each consumer’s preferences, purchase history, location and characteristics. We see it with our clients that use our software to optimize real-time consumer engagement and increase brand loyalty, such as Coca-Cola. And we see it with sports clients who work with us to optimize their schedules by cycling through trillions of possible permutations while juggling thousands of constraints and variables, such as the National Football League.
Embedding analytics into business processes is not only the smart, efficient way for companies to compete on analytics, it is becoming table stakes for any organization that wants to derive meaningful value from analytics.
For example, our fraud management technology, which screens two-thirds of all credit card transactions worldwide (that’s 9,000 per second) for fraud, is a case study in the use of embedded analytics to optimize business decisions.
Machine learning is built into the fraud management technology, allowing it to continually identify new fraud patterns by analyzing streaming transaction data. It is a feedback loop on steroids – it adjusts its analytic models and its decisioning on the fly so credit card issuers can stop fraudulent transactions.
Regardless of the label you assign to this era of analytics – decision optimization or Analytics 3.0 – it is how business is being done today. But what about tomorrow? That’s what I find really intriguing. I’ll talk about that in my next post.
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