Like the efforts involved in single organization, the use of multiple data sources provide improved communications and coordination across different organizations, both in the same and different sectors of the economy. In addition, these efforts involved in the cases also tend to lead to the following benefits (Clark County Recorder's Office, 1998; QMAS Report, 1997; SEI's MassCHIP Program):

• Increased customers service quality
• Increased existing personnel efficiency
• Improved information quality, timeliness, and utilization
• Increased accessibility, and analysis of information
• The elimination of redundant data and tasks

While there are clearly advantages, using an integrated approach across multiple organizations also presents a number of challenges. For example, obtaining data from other agencies is often difficult, and in many cases will be impossible. Culhane and Metraux (1998) summarized these limitations as:

• Legal restrictions may prevent access to a particular data set
• Difficulty in obtaining the cooperation of agency heads, who will often make data sharing decisions based upon "perceived self-interest for the agency or the current political administration"
• Data sharing often requires compatibility between different computer systems as well as the availability of information system personnel with the requisite time and technical skills
• Integrating data systems frequently requires the concurrence of system administrators, directors of programs, and services consumers

Other barriers are also identified from the cases discussed above (QMAS Report, 1997):

• Cost -- Data integration across organizations can cause expenses to multiply. For example, conducting multiple performance evaluations simultaneously may be more expensive than using each tool separately
• Timing -- It takes much more time to collect needed data from different sources across organizations. This time lag may cause synchronization problems
• few data standards -- This will result in no clear vision of data strategy, and make the information decision support much more complex
• Information overload -- Organization staff may be overcome by the volume of information across multiple organizations. They may view this abundance of information as overly complicated, and may choose not to use it

Based on the experiences in the cases where organizations are either in the same or multiple sectors of the economy, the following important lessons regarding the implementation of a comprehensive data integration project are identified (QMAS Report, 1997):

• The objective of data integration should be defined clearly from the start
• Data integration projects require a significant time commitment
• Barriers to participation must be identified and addressed
• Early financial commitment is a key to ensuring ongoing political commitment
• MIS (management information systems) staff should be involved from the start

In addition, there are some important questions regarding the use of multiple data sources from external organizations (QMAS Report, 1997):

• Are the data current enough to be useful?
• What are the content limitations of the data?
• What are the limitations in terms of available methodologies for analyzing the data?
• What are the technological requirements? What confidentiality issues are relevant?

All these questions should be carefully addressed in the data integration across multiple organizations.

It is worth noting that several cases in this paper are in health care field, it probably indicates that health care is a leader in data integration efforts. It also seems to us that organization-wide data integration is done for operational reasons, while data integration across multiple organizations (at least in the cases) is done for research and evaluation purposes.