Patterns gleaned from the past should always inform planning for the future. In most enterprises, though, there’s been a serious
disconnect.
For years, business analysts have enjoyed a clear “rearview mirror” picture of the past based on loads of historical data
extracted with data-mining tools and massaged with business intelligence reports. The view “through the windshield,” however,
has largely been based on siloed, simplified roll-ups of those numbers crunched in desktop spreadsheets. With neither the
near-real-time access to granular data nor the tools to analyze it, many significant opportunities or pitfalls looming ahead
simply can’t be anticipated.
BI is now filling that gap with new analytical features plus the capability to access a broad, up-to-date array of data sources
made available recently through advanced integration technology. Meanwhile, the fruit of that higher-quality number crunching
is being delivered to a much broader range of users. Visually informative dashboards and scorecards are multiplying up and down the enterprise.
Much of the latest BI innovation has been driven by the only two consistent growth sectors in the economy: health care and
security. Ironically, both sectors are purely overhead functions. Therefore, both must constantly demonstrate their benefit
and -- for different reasons -- adapt to events in real time.
Instant Predictive Analysis
“Dashboards certainly are something you can apply to historical data, but they are exciting as a business tool only when you
use them in a real-time context,” says Nathaniel Palmer, chief analyst at Delphi Group.
Palmer thinks that advantage is even stronger with the addition of predictive analytics. “It’s hot,” he says, “and over time
we’re seeing an emergence of online analysis of the stream of real-time data.”
One organization that has embraced this model is Emergency Medical Associates (EMA), a hospital emergency-room practice with
a post-911 “syndromic surveillance” system.
EMA -- which has hospital contracts across New York and New Jersey -- realized that in the event of a biological terrorist
attack, early victims would end up at the emergency rooms it runs. With the right systems in place, EMA staff could not only
evaluate symptoms at the point of treatment but also keep abreast of what was transpiring at multiple emergency rooms, thereby
enabling them to identify possible outbreaks, note the geographic pattern of how they are moving, and broadcast medical knowledge
in real time to combat the spread.
Jonathan Rothman, director of data management at EMA, put into place a Business Objects Application Foundation in late 2003.
“We might not have done it without 9/11,” he says. “But having done it, we established ourselves as the analytics department
for the hospitals -- when we’re working out contracts, we sell them the idea of reports and analytics.” In other words, the
same technology used to detect an epidemic is being used to spot trends and analyze treatment effectiveness and customer satisfaction.
Retail Intelligence
As opposed to health care and security, home improvement and hardware retailers are not part of an overhead sector. Wafer-thin
margins and the ability of a few giant players to sell goods at a loss make the use of BI for defensive purposes essential.
As part of that effort, Christopher Dorsey, CIO of Chase-Pitkin, decided to tackle the rampant pilfering occurring at its
Northeast chain stores. Rather than just react to the problem, he says, “We decided we’d do better getting ahead of the curve.”
Dorsey says two years ago their BI system -- built on Hyperion’s BI solution -- indicated that 16 of the stores’ 38,000 items
made up half of all the pilferage. Dorsey added analytical capabilities from SPSS and altered processes to get the results
Chase-Pitkin was looking for. “Instead of doing inventory on every item during the slowest time of year, we started doing
a weekly one of the subset of most-pilfered items during the busy season,” Dorsey says.
The SPSS predictive analytics examined the attributes of pilfered products and then projected the next most likely theft candidates
when the current top choices were secured. According to Dorsey, “We moved from reactive to being ahead of them to actually
creating prevention. We can predict in real time what the next problem is likely to be" – and take steps to head it off.
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