The challenge for companies now is less about the maturity of the software tools and more about instilling an analytics culture.
Welcome to our week-long series on "IT's Golden Opportunity," a look at breakthrough technologies and approaches for CIOs looking to drive growth. In this installment, Rob Preston considers the power of analytics and business intelligence and IBM’s leadership role.
Among Gartner's top 10 strategic technology areas for 2010, "advanced analytics" (renamed from "business intelligence" in previous rankings) came in at No. 2, behind only cloud computing. In a presentation of the list last October, Gartner said: "We have reached the point in the improvement of performance and costs that we can afford to perform analytics and simulation for each and every action taken in the business."
What's different now from, say, five years ago? Organizations are capturing ever-more relevant data, structured and unstructured, to inform their business decisions. And at their disposal are more sophisticated software tools (and cheaper underlying processing power) to identify patterns and make correlations in that data with greater accuracy.
But as InformationWeek's cover story this week suggests, there's plenty of room for improvement, especially in the area of real-time decision support, where application vendors including SAP, Oracle, Microsoft, Lawson, and Epicor are starting to embed BI functionality into the transactional interfaces of their products, while dedicated BI and analytics vendors such as IBM, SAS, and MicroStrategy offer tools that are agnostic to the data source and application. Meantime, despite the industry's "BI for the masses" push, the software still has a ways to go in terms of mainstream usability, so that employees don't have to be stats geeks to crunch the numbers, divine results, and initiate actions based on them.
A survey IBM conducted in August 2009 of 398 C-level executives concluded that "high-performing organizations" -- those whose financials are in the top 20% of their industries -- are twice as likely to have mastered the three basics of BI than organizations in the bottom 40%. The basics, according to IBM, are the ability to gather and use information from inside and outside the company; the ability to extract the most relevant information; and the ability to align information with business objectives across functions. Culturally, top-performing organizations are also far more prepared to disrupt the status quo to improve the business, and they give their employees more authority to act on their insights to drive change.
No one is betting the farm on analytics quite like IBM is. CEO Sam Palmisano, in his annual letter to shareholders in January, called out analytics among four core growth areas for the company and has said it will be a bigger market opportunity than ERP. But it's not just a discrete software product group within IBM, centered on the company's $4.9 billion acquisition of BI leader Cognos in 2007 and its $1.2 billion acquisition of predictive analytics specialist SPSS in 2009. Since 2005, IBM has spent $11 billion acquiring 18 companies in what it calls "business analytics and optimization," a market segment in which it generated $9 billion in revenue in 2009 and projects to generate $16 billion by 2015.
Today, analytics pervades just about everything IBM does and sells. A series of interviews we did last week with IBM executives who are focused on services, collaboration software, and research all found their way back into the analytics realm. The company's analytics practice encompasses 4,000 consultants, mathematicians, and researchers, and the technology is integrated into industry-specific healthcare, insurance, telecom, consumer goods, crime prevention, and many other offerings.
For example, last week IBM announced that Japan's Dai-ichi Life Insurance Co. is using "semantic analytics" technology (developed in IBM Research; built on SPSS Statistics, the DB2 9 database, and IBM Cognos 8 BI; and offered through IBM Consulting) to analyze massive amounts of data in daily event logs to detect performance and quality problems, like if an employee is taking too long to answer a client's request. A telco in the Middle East is using IBM analytics to identify the alpha individual in its customers' calling circles -- those people who'd be most likely to take other customers with them should they switch carriers -- so that it can cater to those individuals. Kraft is applying IBM text analytics to blogs and chat forums to "detect sentiment," not just chase keywords, in order to gauge customers' reactions to its brand advertising and then adjust its marketing channels and messaging accordingly.
Customers of other analytics vendors, of course, are doing similar things. The challenge now is less about the maturity of the software and more about instilling an analytics-grounded culture and related processes to get the most from these valuable tools.
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