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Trends and Outliers

TIBCO Spotfire's Business Intelligence Blog

Category Archives: Business Intelligence Overview

01/18
2010

Critical Capabilities for Business Intelligence Platform Integration

j04431602 150x150 Critical Capabilities for Business Intelligence Platform IntegrationGartner, Inc. recently examined the most critical capabilities that enterprises should consider when selecting a business intelligence platform vendor in its report, “Critical Capabilities for Business Intelligence Platform Integration.” 

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01/12
2010

Real-Time Business Intelligence, Worth the Trouble?

j04004212 150x150 Real Time Business Intelligence, Worth the Trouble?In this great article on BeyeNetwork, Rick van der Lans looks at Operational (or real-time) Business Intelligence.  This is a long read but well worth your time as Rick provides definitions, addresses approaches, references survey materials, and looks at problems, concerns and opportunities for Operational Business Intelligence.

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01/06
2010

Ventana Research 2009 in Review: Innovation Expands Scope of Business Intelligence

j0443160 150x150 Ventana Research 2009 in Review:  Innovation Expands Scope of Business IntelligenceWe’ve highlighted several trend predictions for business intelligence and analytics for 2010; now we’ll look at Ventana Research’s 2009 Business Technology Priorities in Review.  According to Ventana, their look back “offers not only a history, but some lessons learned as well, and some food for thought as we enter 2010.”  Ventana’s perspective covers a wide range of business technologies, but we’ll focus on their observations regarding business intelligence and analytics.

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01/05
2010

Share Your Thoughts on Business Intelligence, Performance Management and More

j0438585 150x150 Share Your Thoughts on Business Intelligence, Performance Management and MoreEvery year at this time, BPM Partners launches its annual BPM Pulse Survey.  The Survey asks end users key questions on the usage of business intelligence, analytics, and performance management technologies. 

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12/23
2009

Forrester’s Analytics Predictions for 2010

j0216064 150x150 Forrester’s Analytics Predictions for 2010Forrester Analyst James Kobielus (@jameskobielus) shared his business intelligence and advanced analytics predictions for 2010 in a recent posting on The Forrester Blog for Business Process & Applications Professionals. 

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12/21
2009

Q-and-A Seth Grimes, Analytics Analyst

92949097 1  150x150 Q and A Seth Grimes, Analytics Analyst Seth Grimes is an analytics strategy consultant at Alta Plana Corporation, located near Washington DC.   Seth is also a leading industry observer, focusing on business intelligence, text analytics, and decision support as a long-time contributing editor for TechWeb’s Intelligent Enterprise, text analytics channel expert at the BeyeNETWORK, and founding chair of the Text Analytics Summit.

Q: Analytics of everything from online sentiments to real-time object status means the field is moving into non-traditional departments including marketing where people don’t use Excel or math much.  Is BI becoming mainstream, not just for data-crunchers?

A:  Oh, we’re there — marketers along with a gamut of other business users ranging from executives who need a strategic view to folks on the proverbial shop floor, by which I mean the folks who do the real, productive work. These aren’t non-traditional departments; they’re at the core of any and every business.  And they don’t (necessarily) use math a lot, at least not directly, much less Excel.   Instead, they’re getting analytics delivered in consumable, relevant forms that are tailored to their job functions.

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12/17
2009

Check Out the Data Visualization Game

j0435245 150x150 Check Out the Data Visualization GameA challenge for each of you over the holidays – grab one of your friends or relatives who is not a major techie and explain business intelligence and visualization to them.  Okay, stop laughing.

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12/14
2009
12/10
2009

Faster, Smarter Utilities Need Faster, Smarter Analytics

j0442296 150x150 Faster, Smarter Utilities Need Faster, Smarter AnalyticsIf you lost electric power while you were asleep, how would you know?

Probably not until you wake up and see the flashing LED clocks on your bedside table, coffee maker or cable TV box.  The same lack of ‘business intelligence’ has been the norm for electric utilities, which may not know about system outages until CUSTOMERS called to complain they were without power.

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12/08
2009

Prescribing BI and Analytics For The U.S. Health Care Debate

j0409702 150x150 Prescribing BI and Analytics For The U.S. Health Care DebateOne sure thing in the cloud of uncertainty regarding changes to the U.S. health care system: analytics and data verification will be critical to reviewing thousands of pages of documents and the charts, graphs and statistics used by various industries in the debate.  When Congress convenes to examine H.R. 3962 there will be a lot to analyze.  Entire global industries that have grown by sharing broad, unknowable risks– insurance and especially health insurance – now face the 21st century realty of predictable outcomes and specific forecasts.  Tom Davenport, co-author of Competing on Analytics: The New Science of Winning, writes about the future prospects of change with clear-eyed realism.

When a company or organization seeks health insurance for a large group of employees, the particular attributes of those employees aren’t usually assessed in detail.  “Increasingly, however, life and property & casualty insurers have attempted to increase their profits by predicting just how much risk a particular customer represents, and pricing the risk accordingly,” he writes at the Harvard Business School Press website. “Pooling the risk, it seems, is no longer an attractive proposition for life and property insurers.

Yes, some elements of your personal medical history are protected INSIDE of doctor offices and hospitals by HIPAA and other laws, there are plenty of other unsecured and correlated data outside those offices that can link to greater risk of early death, behavioral, financial or other risks.

“All you need to know is how much someone weighs, what kind of food he or she eats, how much exercise they get, and so forth.  Much of that information is publicly available, can be bought, or can be legally requested in insurance applications.  One health insurance actuary told me that such “lifestyle” data is a much better predictor than age of who is going to contract, say, diabetes.  Among 45-year olds, for example, there is an eightfold difference in annual medical spending between the highest-risk lifestyle group and the lowest,” Davenport writes.

Lifestyle indicators are already gaining popularity in health insurance firms, who enroll certain customers in “disease management” programs. Some can reduce risks of certain conditions.  But Davenport notes that data can also be used to refuse coverage, or to price coverage at a much higher level.  Sometimes the details unearthed by advanced analytics can have unexpected or negative results.

The prospect of universal coverage in the United States could move more people to shop for insurance as individuals (and trackable) instead of as employees who might be harder to classify as group.  It will be possible for insurance firms to identify which customers will be profitable, and which will cost too much money to insure.  And some insurers will be better at predicting risk than others.  “This will lead to dramatic differences in performance between the more and less analytical health insurers.

Some will go out of business, creating disruption for the entire industry and its consumers,” Davenport predicts.  “If there is a “public option” that takes consumers no one else wants, it will undoubtedly get the citizens who are most likely to acquire expensive diseases.  Taxpayers will foot the bill, while the private health insurers who are good at prediction will become much richer.”

Auto insurers, for instance, have used “risk adjustment” in many states, sharing losses when they arise and preventing companies from skimming only the most desirable clients.  Another view comes from the public radio program “Marketplace” which found healthcare outcomes showed worse care or repeat hospitalization for minority patients compared with native English speakers.  A Nov. 23 report explored ways hospitals and insurers are looking to better data for improving predictive, responsive information.  For example, cultural details identifying someone more specifically as Cambodian, Indian or Japanese instead of more generically as “Asian” can make a difference when communicating care or prescription drug use.

David Wallace
Spotfire Blogging Team

Image Credit: Microsoft Office Clip Art

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