Predictive Analytics in Child Welfare: Considerations in Contracting Vendors for Predictive Analytics

July 2018
Topics: Data Analytics, Government Agency Operations, Acquisition Management, Government Acquisition
Christopher M. Teixeira, The MITRE Corporation
Michelle M. Jacobs-Smith, The MITRE Corporation
Matthew G. Boyas, The MITRE Corporation
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Predictive analytics is a set of advanced analytical methods that may enable child welfare agencies to leverage a range of case-level data about families’ situations, turning hindsight into insight and improving child welfare outcomes. Some child welfare agencies are currently implementing predictive analytics, though these efforts are in their infancy. In most existing cases, child welfare agencies decided to partner with an outside organization to run the technical analyses, as opposed to building in-house statistical or predictive modeling expertise.

Many sections of an RFP are boilerplate and require nothing specific to predictive analytics or child welfare. In contrast to these standard RFP sections, three RFP sections can be tailored to predictive analytics applications intended to improve child welfare outcomes. The targeted RFP sections include Requirements Documentation, Special Contract Requirements, and Evaluation Factors for Award. This document focuses on these more complex aspects of the acquisition package for predictive analytics.

Given the different contracting dynamics in every jurisdiction and child welfare agency, as well as the unique requirements of the child welfare problem at hand, it is impossible to issue a blanket fill-in-the- blank RFP that can be used for predictive analytics project. Instead, each child welfare agency interested in pursuing predictive analytics should take this document to its contracting specialists, and work with data scientists and domain experts to ensure that a proposal is prepared that will best ensure the chance of success.


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