Have Data, Will Travel: A Data-Centric Approach to Enterprise Systems Development
Business drivers for more responsive application development
The data-centric approach has already gained acceptance in all corners of the enterprise. Analyzing
organizations that rapidly adopt this approach reveals these key business drivers:
- Imuroved Customer Service. Businesses everywhere are under pressure to provide quick and
improved customer service. The most requested need of customer service personnel is timely
access to an organizations critical business data. Unfortunately, traditional IT departments
often interpret this requirement as the need for a new "AM/FM/GIS Application". The quickest
way to empower employees is to give them the data now, and work over time to incrementally
improve their ability to analyze and process that data.
- Data Integration/Improvement. In utility industries especially, customer service and operations
personnel need to integrate geospatial and tabular data to allow quicker response to customer
requests and trouble spots. While it is eventually possible to build a complex data processing
system that automates decision making, such systems are notoriously complex and timeconsuming
to construct. Successes to date with data-centric systems implementations show that
nearly equivalent levels of end-user satisfaction can be achieved. These systems are developed
at a fraction of the cost and in less time then traditional approaches.
- Ouick Business Operations Improvement. Traditionally, geospatial information
provides only a narrow set of operations personnel, engineers and "GIS
Specialists", with corporate asset data. More than ever before,
businesses need to provide geospatial information to external partners,
customers, and workers in order to improve and streamline business
processes. This defragmentation of information, both spatial and
non-spatial data, supports a total system view. With this perspective
data users can see what effects their decisions have not just
departmentally, but from a total systems perspective.
Mitigating risks with the data centric approach
As with other systems development methodologies, the data-centric approach has some inherent
risks, but these are minimized with its proper application. Typical risks are discussed below:
Risk Number 1: Cost and Schedule Inflation
Ballooning costs and schedule creep is probably the greatest risk for any AM/FM/GIS project. The
authors have found that a data-centric application development approach has a lower risk of these
undesirable effects than other software development approaches, for some fimdamental reasons.
First, the data-centric approach avoids complex "complete" applications. Most of the benefit of
many GIS applications is achieved simply by "getting the data out" to the user. In the data-centric
approach, the data is typically organized and deployed in a map-enabled Web environment
Complex GIS processing systems and extensive requirement analysis are avoided.
Second, the data-centric approach is centered on deploying existing spatial data, and spatially
existing tabular data. These tasks are fundamentally less risky because the data sets involved have
been previously captured and are already understood.
Third, a phased-in or departmental approach can be used where specific data is added or brought
on-line. Departmental fimding is typically less costly and the results of the effort can be
demonstrated more quickly.
Risk Number 2: Hostile Res~onse from Traditional IT or GIS Organizations
Traditional information technology organizations generally prefer a highly planned and carefully
managed approach to applications development. For many, the risks of deploying an application
that does not fit into the long-range IT plan are dominant decision factors. The data-centric
methodology is an advocate of proper systems planning, but provides a mechanism to build upon
existing company assets (data), without having to construct a complete system to do so.
Likewise, traditional GIS organizations may feel threatened by the data-centric approach. In the
data-centric approach, the idea is to get the data to the end users as quickly as possible, with
minimal GIS applications and tools. This can cause consternation among GIS data producers;
exposing data to end-users will create additional demand for data maintenance, and potentially
reducing the end-user's dependence on the GIS department for map production.
