More and more companies are using analytics to drive their decision-making processes. But there's a right and a wrong way to do it.
The world is becoming more analytical. Even Lawrence Summers, the president of Harvard, who got into such big trouble recently for making sweeping statements about women in science, got this one right. At a Harvard School of Public Health conference, Summers said: "I suspect that when the history is written 200 years from now, it will emerge that something very important happened in human thinking during the time when we were alive, and that is that we are becoming rational, analytical and data-driven in a far wider range of activity than we ever have been before."
Ah yes, you say. You may not have thought about it this way, but, in fact, you know something of this territory. Business intelligence. Statistics, decision support and all that. It may strike you as a little nerdy, but you'd undoubtedly grant business analytics a place in the pantheon of IT applications.
But in some organizations, analytics are in first place. They're actually becoming the primary driver of strategy and competitive advantage. Analytics and quantitative decisions are being used to optimize business processes - to identify the best customers, select the ideal price, calculate the best supply chain routing or pick the best person to hire.
Success Through Analytics
There are many companies competing on the basis of data, models and prediction, and many have been fantastically successful with this strategy. Wal-Mart, of course, uses vast amounts of data and category analysis to dominate retail. Harrah's has changed the basis of competition in the gaming industry from building mega casinos to analytics around customer loyalty and service. Amazon and Yahoo aren't just e-commerce sites; they are extremely analytical and follow a "test and learn" approach to business changes. Capital One runs more than 30,000 experiments a year to identify desirable customers and price credit card offers.
In a recent study sponsored by SAS and Intel, a couple of colleagues (Don Cohen and Al Jacobson) and I contacted 32 organizations that were pursuing some analytical activity. Some were using analytics in the time-honoured fashion - that is, spottily and in pockets. They had an actuary here, a supply chain simulator there. As one manager of an analytics group put it: "In the past we were like the Aleutian Islands - our analytical activities covered a lot of territory, but they didn't attract much notice."
A third of them, however, were competing on analytics at the highest level. They captured and managed lots of transaction data and had a culture of fact-based decision making. They were using analytics in multiple functional areas; they were using sophisticated statistical analysis and predictive modelling, and managing business intelligence at the enterprise level. But there was one more attribute of analytical competition that truly set these organizations apart.
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Data grids and service-oriented architecture
When choosing an SOA strategy, corporations must ensure data availability, reliability, performance and scalability. A data grid infrastructure, built with clustered caching provides a framework for improved data access that can create a competitive edge and sustain customer loyalty. Read on to discover how this can be created within your organisation.
















