<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-18T22:20:17Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/126905" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/126905</identifier><datestamp>2021-07-05T14:03:20Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Anjali Sastry.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Lawson, Angela Dawn.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Sloan School of Management.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">Sloan School of Management</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2020-09-03T15:52:00Z</dim:field>
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   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2020</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">https://hdl.handle.net/1721.1/126905</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1191623537</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, May, 2020</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from the official PDF of thesis. "May 2020."</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 84-86).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">With the rapid evolution of technology from more affordable hardware and data storage to artificial intelligence, companies must evolve their technology strategy to remain relevant. Federal agencies are no exception as they continue to deploy transformational technology to improve services for the American public. An important issue has surfaced in the evolution of technology and the increasing speed of innovation where companies no longer need to find technologies to solve their problems, rather they need to select the right technologies to focus their attention to best define the future of work. Methodologies are common across industries but how do they apply to public service? Is a qualitative or quantitative process possible for vetting new and existing technology implementations while remaining adaptive and service-oriented? This paper explores the development of a framework that provides guidance on deploying the right technologies. I will draw on desk research of existing methodologies while gathering information on effectiveness of past deployments to define a guiding framework for technology selection. These findings can assist in future decisions for technology investment along with tripwires for retiring existing technologies.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Angela Dawn Lawson.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.B.A.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="collection" lang="en_US">M.B.A. Massachusetts Institute of Technology, Sloan School of Management</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">86 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Sloan School of Management.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Deploying the right technology : a framework for digital strategy and selection at the United States Postal Service to shape the future of work</dim:field>
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   	&lt;Title>Deploying the right technology : a framework for digital strategy and selection at the United States Postal Service to shape the future of work&lt;/Title>
   	&lt;Subtitle>Framework for digital strategy and selection at the United States Postal Service to shape the future of work&lt;/Subtitle>
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   	&lt;Abstract>With the rapid evolution of technology from more affordable hardware and data storage to artificial intelligence, companies must evolve their technology strategy to remain relevant. Federal agencies are no exception as they continue to deploy transformational technology to improve services for the American public. An important issue has surfaced in the evolution of technology and the increasing speed of innovation where companies no longer need to find technologies to solve their problems, rather they need to select the right technologies to focus their attention to best define the future of work. Methodologies are common across industries but how do they apply to public service? Is a qualitative or quantitative process possible for vetting new and existing technology implementations while remaining adaptive and service-oriented? This paper explores the development of a framework that provides guidance on deploying the right technologies. I will draw on desk research of existing methodologies while gathering information on effectiveness of past deployments to define a guiding framework for technology selection. These findings can assist in future decisions for technology investment along with tripwires for retiring existing technologies.&lt;/Abstract>
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