2026-09-19T14:45:23Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/901172022-01-13T07:54:09Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Phillip L.Clay.
Reuter, George N. (George Nicholas)
Massachusetts Institute of Technology. Department of Urban Studies and Planning.
Massachusetts Institute of Technology. Department of Urban Studies and Planning
2014-09-19T21:40:45Z
2014-09-19T21:40:45Z
2014
2014
http://hdl.handle.net/1721.1/90117
890145716
Thesis: S.M., Massachusetts Institute of Technology, Department of Urban Studies and Planning, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 68-70).
Many community development corporations are broadening their program components while seeking efficient and effective ways of measuring their impacts. Recent advances in information technology have created "cloud" database platforms that are well suited for tracking individual information, and are customizable, extensible, and have built-in reporting functionality. Are these comprehensive individual level data systems feasible for CDCs to implement, and what utility do such systems provide for program improvement? I examine these questions using case studies from Greater Boston organizations that have begun to Implement these types of systems. I find that all organizations' initial system setup required intensive staff time, as well as consulting support in a range of domains. The direct cost of setup varies substantially ($8,000 -$100,000), and depends highly on the degree to which consultants are used. Although organizations are primarily motivated by an interest in understanding and improving their programs, they also believe that funders and partners will increasingly require data-driven evidence of program impact. Overall, organizations believe their new data systems are worthwhile investments that save substantial staff time in reporting and provide a richer understanding of programs. There are several best practices or recommendations for other CDCs or community based organizations. 1) Developing a database cannot be done in isolation, and requires a team with a breadth of expertise (technical, evaluation, program knowledge). 2) Be prepared for iteration: data systems will need continued changes and refinement as programs change. Organizations should have a plan to address these changes, including adequate staffing. 3) Before developing a data system, substantial strategic planning should be completed. Without agreement on metrics, and an understanding of the activities that will lead to intended outcomes, it is easy for organizations to waste time developing a system that collects information of little value.
by George N. Reuter.
S.M.
73 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Urban Studies and Planning.
Self evaluation and community development corporations : the utility of robust management information systems
Thesis
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<Abstract>Many community development corporations are broadening their program components while seeking efficient and effective ways of measuring their impacts. Recent advances in information technology have created "cloud" database platforms that are well suited for tracking individual information, and are customizable, extensible, and have built-in reporting functionality. Are these comprehensive individual level data systems feasible for CDCs to implement, and what utility do such systems provide for program improvement? I examine these questions using case studies from Greater Boston organizations that have begun to Implement these types of systems. I find that all organizations' initial system setup required intensive staff time, as well as consulting support in a range of domains. The direct cost of setup varies substantially ($8,000 -$100,000), and depends highly on the degree to which consultants are used. Although organizations are primarily motivated by an interest in understanding and improving their programs, they also believe that funders and partners will increasingly require data-driven evidence of program impact. Overall, organizations believe their new data systems are worthwhile investments that save substantial staff time in reporting and provide a richer understanding of programs. There are several best practices or recommendations for other CDCs or community based organizations. 1) Developing a database cannot be done in isolation, and requires a team with a breadth of expertise (technical, evaluation, program knowledge). 2) Be prepared for iteration: data systems will need continued changes and refinement as programs change. Organizations should have a plan to address these changes, including adequate staffing. 3) Before developing a data system, substantial strategic planning should be completed. Without agreement on metrics, and an understanding of the activities that will lead to intended outcomes, it is easy for organizations to waste time developing a system that collects information of little value.</Abstract>
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