Marrying Business Intelligence to GIS Data: A Power Couple for Your Business
As Hurricane Katrina swept into the Gulf of Mexico late
last summer, there were a lot of unanswered questions: Would the levees
in New Orleans hold? Would the roofs of houses along the fragile
Mississippi coastline withstand the storm? What would happen to the oil
rigs in the Gulf and to the refineries in the region?
For companies selling roofing supplies, government officials planning
evacuations, or oil industry execs estimating the impact on production,
data from previous storms and company records provided clues, but they
were often cumbersome to sift through. And geospatial data is often
left out of the equation. The ï¿1⁄2whereï¿1⁄2 question ï¿1⁄2 rarely answered
through traditional means ï¿1⁄2 is becoming increasingly important.
Geospatial data and analysis add value beyond simple visualization of
relationships. Marrying GIS and business intelligence (BI) software
provides a visual means of forecasting and analyzing data to assist in
making better-informed decisions. Companies need to know not merely
what happened, but what is likely to happen. Being able to extract,
manipulate, store, retrieve, report and forecast complex data,
including geospatial data, helps us understand the rest of the story.
Storms aren't the only situations in which forecasting and analytics,
coupled with mapping software, can provide governments and companies
with critical information. For example, real estate executives
searching for the right location for a new outlet can make better
decisions if they can combine demographic data with mapping. Which is
easier to understand - a list of zip codes with the right demographics,
or geospatial software that highlights busy intersections in those zip
codes? Maps can convey a significant amount of information in a
digestible form. You can identify a region, select and interact with
the data for that region, and then narrow and pinpoint what data you
want analyzed using BI software.
A question of 'where'
As Hurricane Katrina began to turn toward the Gulf Coast, the National
Hurricane Center had reams of data that showed the paths of every
hurricane since the mid-1850s, and updates ï¿1⁄2 several times a day ï¿1⁄2 on
the path of Katrina itself. How the hurricane would impact oil
production was critical from an economic standpoint, which is why the
Mineral Management Services website
exists. This is a U.S. government-maintained site that contains a
wealth of GIS data. The site has data specific to oil and gas
production from the Gulf of Mexico, as well as historical oil and gas
production data reported monthly over the last 10 years for every
productive well in the Gulf of Mexico.
But all this information is useless unless the user can understand
relationships between a location and its accumulated data. To get to
this level of understanding, data must be turned into intelligence that
informs decisions. Raw data alone does not suffice; it is the ability
to analyze it that makes the difference.
Returning to the Hurricane Katrina example, oil markets got shaky as
the hurricane gathered strength in the Gulf of Mexico. The Gulf is the
country's leading oil-producing region, with production valued at $282
billion over the past 10 years. Some areas are richer in hydrocarbons
than others ï¿1⁄2 specifically, the Mississippi Canyon protraction area,
which is located off Louisiana's southern tip. This protraction area
accounts for 17 percent of the value of oil pumped from the Gulf of
Mexico during the past 10 years. MC807, also known as ï¿1⁄2Mars,ï¿1⁄2 is the
most dominant production platform in that protraction area, accounting
for 7.5 percent of overall Gulf hydrocarbon value produced over the
past 10 years. Mars was hit hard by Hurricane Katrina. As of April
2006, it is still not back online.
There's no question that Mars' owners were aware that Hurricane Katrina
posed a threat, but could they have handled the damage control
afterward if they'd had the right tools and data available to them?
Could they ï¿1⁄2 in a matter of minutes ï¿1⁄2 have pointed and clicked their
way through the projected path of Hurricane Katrina to understand
exactly how, to the last dollar, this was going to impact production?
Could the company have examined information from previous hurricanes ï¿1⁄2
and company data on how long it took to get rigs back online ï¿1⁄2 and
figured out how long production would be curtailed?
These ï¿1⁄2what ifï¿1⁄2 scenarios help companies make decisions before a
catastrophic event ï¿1⁄2 from getting people out of harm's way, to
positioning supplies or preparing shareholders for the impact. What if
the hurricane moves through a more populated sector of platforms but
ones that aren't as productive? What if it makes a beeline for a
critical refinery? Forecasting is ultimately about being proactive,
being able to anticipate what needs to be done next rather than waiting
helplessly to see what might happen.
It's important to note that ï¿1⁄2what ifï¿1⁄2 scenarios don't need to be
created by a programmer in the IT department. Geographic data coupled
with analytics and a forecasting tool can be available on the desktop
to the financial analyst, the production specialist, the sector
executive, the foreman assigning staff to the rig, even to the people
responsible for repairing a hurricane-damaged rig. These people don't
need to learn a new system or be statistics experts. This type of
ï¿1⁄2intelligentï¿1⁄2 information can be deployed via Web interfaces to reach a
much broader community through tools with which the user is already
Combining geographic data and maps with powerful BI software helps
uncover previously hidden connections and relationships. Users can
easily and quickly pan and zoom, drill up and down, expand the fields
they're looking at or collapse them, filter and rank, create calculated
measures, export the data and analyze it. An oil company, for example,
could use these data to figure out quickly which rigs need to be fixed
first (based on productivity) and which might wait until later.
Forecasting can help a company quickly set priorities.
BI software helps separate the important from the unimportant, turning
data into strategic information. Programs and applications can be
stored in a way that allows numerous users to access them, view
metadata and create customized applications that export accurate,
critical data to a company's BI system.
The power of 'where'
Businesses in almost every industry can benefit from coupling
geographic data with powerful BI software. Retailers, for instance, are
always looking for the perfect location. They buy reams of demographic
data. Hundreds of developers pitch their shopping malls and strip
centers to retailers. What if a coffee shop's real estate department
could sort for highest-income zip codes with the most coffee drinkers
and literally call up a map that shows major intersections under
development or existing properties in the areas they most desire?
Integrating geospatial information with BI software can also help save
lives. Epidemiologists can track outbreaks of deadly illnesses like
SARS or bird flu. In the public sector, local governments could work on
ï¿1⁄2what ifï¿1⁄2 scenarios before changing zoning, helping them to better
understand how new development would affect tax revenues or commuter
Analyzing data that has been merged with geospatial software will be a
critical step in helping organizations succeed and grow in today's
competitive markets ï¿1⁄2 from oil refineries to retail stores to medical
research labs. The combination of BI and geospatial information will
give decision makers an accurate picture of the future and the ability
to reliably measure the impact of economic and marketplace factors, so
that they can operate more efficiently. Today, a primary use of spatial
data in BI is with location information, which is becoming readily
available: GPS-enabled cell phones, RFID-tagged packages, etc. BI
analytic processes allow decision makers to answer not only the ï¿1⁄2whereï¿1⁄2
question, but also to understand why ï¿1⁄2whereï¿1⁄2 matters.