2000115-Strengthening-Communities-with-Neighborhood-Data

22 Strengthening Communities with Neighborhood Data
coalitions. Interest has grown as many local stakeholders recognize that
they have no solid basis for targeting resources or evaluating programs created
to improve conditions if they lack hard facts on the neighborhoodlevel
patterns and trends.
Program operators can often learn much just by analyzing their own
data (the administrative data they produce) more effectively. But almost
all of them need access to a variety of neighborhood-level trends to
understand the dynamics of the neighborhood context in which their
programs operate. Police departments, for example, now clearly recognize
that they cannot deploy crime prevention resources effectively by
simply analyzing data on crimes. They need to look at a number of other
indicators as well before they can understand a neighborhood and how
it may be changing.
The problem is that the trend toward government enterprise data systems
has still not reached many communities, and in many cities, the data
of interest are currently stored in individual agency database silos. Community
groups may recognize the need for cross-topic neighborhood-level
data, but it would obviously be extremely wasteful for all such groups to
go from agency to agency to try to collect the woefully inadequate data
typically being released to the public. Their time would be much better
spent on activities to further their own missions.
A more efficient approach is to assign the data assembly task to a local
data intermediary—one single institution or a formal collaboration of
institutions—that will assemble and organize the data across local government
agencies and build a system to serve as a one-stop shop for
community information. The goal is an entity that will provide accurate
and useful data on multiple topics to all groups that need it and that will
commit to continuing the data provision over the long term. These are
the kinds of entities and collaborations that have become a part of the
National Neighborhood Indicators Partnership (NNIP), introduced in
chapter 1.
Where such intermediary capacities have been developed, interviews
suggest that they are regarded as valuable by community groups, which
previously had hardly any access to relevant data. They are also valued
by public agencies and nonprofits that need a richer understanding of
neighborhood conditions and trends to plan their own work effectively,
but lacked the internal capacity to perform their own cross-agency data
assembly and analyses. Because the data are regularly updated, users do
not have to start all over again with a long period of data collection when