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          <dc:identifier>https://hdl.handle.net/2286/R.I.51053</dc:identifier>
                  <dc:rights>http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
                  <dc:date>2018-12</dc:date>
                  <dc:format>21 pages</dc:format>
                  <dc:language>eng</dc:language>
                  <dc:contributor>Seiki, Kaila</dc:contributor>
          <dc:contributor>Licon, Wendell</dc:contributor>
          <dc:contributor>Garverick, Michael</dc:contributor>
          <dc:contributor>Department of Finance</dc:contributor>
          <dc:contributor>Department of Information Systems</dc:contributor>
          <dc:contributor>Department of Information Systems</dc:contributor>
          <dc:contributor>Barrett, The Honors College</dc:contributor>
                  <dc:type>Text</dc:type>
                  <dc:description>The purpose of the present study is to examine how the Sales and Operation Plan (S&amp;OP) process can be improved in the manufacturing industry by using a cost model to evaluate changes in the manufacturing forecast in addition to reviewing past financial performance. The additional use of a cost model transitions form using a standard traditional S&amp;OP process to dynamic modeling and scenario analysis that may lead to different decisions being made. The manufacturing company S&amp;OP processes in scope of this project is suspected to not be using a cost model when making financial decisions but rather the traditional S&amp;OP process. They do not have a rolling budget in place, but rather a static budget also known as an Annual Operating Plan.</dc:description>
                  <dc:subject>Finance</dc:subject>
          <dc:subject>Erd</dc:subject>
          <dc:subject>Cost Model</dc:subject>
                  <dc:title>Improving Forecasting Accuracy in the Manufacturing Business Cycle</dc:title></oai_dc:dc></metadata></record></GetRecord></OAI-PMH>
