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Trends and Outliers

TIBCO Spotfire's Business Intelligence Blog

Category Archives: Enterprise

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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12/28
2009

Chevron “Blind Faith” Counts On Analytics and Business Intelligence To Fill Your Tank

j0422357 150x150 Chevron “Blind Faith” Counts On Analytics and Business Intelligence To Fill Your Tank Next time the price of gasoline has jumped or fallen a few pennies, you might pause a moment to consider the years of planning, billions in investment and the role of analytics and heavy-duty data and computing that made your transaction possible.  Chevron Corp. (disclosure – a Spotfire analytics client) has several videos and interactive illustrations explaining the path from oil discovery to well construction to actual production – a journey that can take as long as 10 years.

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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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12/18
2009

New Approaches and Targeted Analytics for the Data Center

j0400422 150x150 New Approaches and Targeted Analytics for the Data CenterCompanies are rethinking how to build a data center – from the ground up.  From automated air handling controls to bi-level design, improvements in both efficiency of footprint and reduced electrical demands for cooling can provide room for growth.  Add analytics to track consumption and performance and you have operational knowledge that many centers lack.

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12/14
2009
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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12/04
2009

Business Intelligence Can Stop The Spread of “Spread-Mart”

j03879531 150x150 Business Intelligence Can Stop The Spread of “Spread Mart”It’s a corporate equivalent of “when all you have is a hammer, everything looks like a nail.”  If a spreadsheet is the only tool you have for analytics, chances are good you won’t produce any business intelligence.  E-mailed spreadsheets multiply like, well, Excel formulas as the documents and attachments move throughout your network.  They can turn any organization into a SpreadMart with lots of data but no knowledge or insights that let you plan for the future.

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12/03
2009

Forget Massive Business Intelligence Projects

j0439587 150x150 Forget Massive Business Intelligence ProjectsWe recently interviewed BPM Partners’ John Colbert, who talked about five common attributes of failed business intelligence projects.  One of these attributes is having a very large scope for the business intelligence project.

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12/01
2009

Is Your Company Smart Enough? Business Intelligence From Customers Who Don’t Buy Anything

j0402015 150x150 Is Your Company Smart Enough? Business Intelligence From Customers Who Don’t Buy Anything Business Intelligence in the 21st century enterprise has as much to do with what your company “knows” as what it makes, sells or buys.   Companies like Priceline, Amazon and SmartBargains are just a few giants that have compiled huge databases of consumer preferences, pricing, packages of multiple purchases.  That data has tremendous value – even if they never sold another item.  And thanks to analytics from the streams of customer Web traffic, they can learn as much from tire-kickers who never purchase as from their most frequent buyers.

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