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<CourseUnit xmlns="http://www.manchester.ac.uk/CUICourseUnitDetails" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.manchester.ac.uk/CUICourseUnitDetails.xsd">
  <UnitCode Applicant="Y" Label="Unit code" Student="Y">
    <Code>BMAN31152</Code>
  </UnitCode>
  <UnitTitle Applicant="Y" Label="Unit title" Student="Y">
    <Title>Business Decision Analytics</Title>
  </UnitTitle>
  <MaxUnits Applicant="Y" Label="Credit rating" Student="Y">
    <Units>20</Units>
  </MaxUnits>
  <TeachingPeriods Applicant="Y" Label="Teaching period(s)" Student="Y">
    <Period>Semester 2</Period>
  </TeachingPeriods>
  <AcademicCareer Applicant="Y" Label="Academic career" Student="Y">
    <Value>Undergraduate</Value>
  </AcademicCareer>
  <UnitLevel Applicant="Y" Label="Unit level" Student="Y">
    <Level>Level 3</Level>
  </UnitLevel>
  <StaffList Applicant="Y" Label="Teaching staff" RoleLabel="Course Unit Role" Student="Y">
    <StaffMember>
      <Name>Dong Xu</Name>
      <Role>Unit coordinator</Role>
    </StaffMember>
  </StaffList>
  <OfferedBy Applicant="Y" Label="Offered by" Student="Y">
    <OrganisationList>
      <Organisation>
        <OrgName></OrgName>
      </Organisation>
    </OrganisationList>
    <GroupList>
      <Group>
        <GroupName></GroupName>
      </Group>
    </GroupList>
    <FheqLevels>
      <FheqLevel>
        <LevelNumber>1</LevelNumber>
        <LevelName>FHEQ level (Framework for Higher Education Qualifications) ' Last part of a Bachelors ' </LevelName>
      </FheqLevel>
    </FheqLevels>
    <Ects>
      <MaxUnits>European Credit Transfer &amp; Accumulation System Rating :   10.0</MaxUnits>
    </Ects>
  </OfferedBy>
  <MarketingOverview Applicant="Y" Label="Marketing Course unit overview" Student="">
    <Content>&lt;p&gt;The course covers a variety of decision analysis / analytics techniques and processes widely used in business and management to enhance productivity and performance, including&lt;br /&gt;- Linear Programming: formulation &amp;amp; graphical solution, simplex and dual-simplex methods &amp;amp; Excel Solvers, sensitivity analysis, applications&lt;br /&gt;- Transportation algorithms and software (TORA software)&lt;br /&gt;- Integer programming and software (Excel Solvers and TORA software)&lt;br /&gt;- Decision analysis under uncertainty and risk, Bayesian or multiple stage decision making model and method&lt;br /&gt;&amp;nbsp;- Modelling and analysis of decision maker&amp;#39;s attitudes towards risk, preferences and values&lt;br /&gt;- Multiple criteria decision models, methods, processes, tools and decision support systems&lt;br /&gt;- Introduction to game theory for decision making under competition, Markov chain process and time-dependent decision making under risk&lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</Content>
  </MarketingOverview>
  <UnitOverview Applicant="" Label="Course unit overview" Student="Y">
    <Content>&lt;p style="margin-left:5.7pt;"&gt;The course covers a variety of decision analysis / analytics techniques and processes widely used in business and management to enhance productivity and performance, including&lt;br /&gt;- Linear Programming: formulation &amp;amp; graphical solution, simplex and dual-simplex methods &amp;amp; Excel Solvers, sensitivity analysis, applications&lt;br /&gt;- Transportation algorithms and software (TORA software)&lt;br /&gt;- Integer programming and software (Excel Solvers and TORA software)&lt;br /&gt;- Decision analysis under uncertainty and risk, Bayesian or multiple stage decision making model and method&lt;br /&gt;&amp;nbsp;- Modelling and analysis of decision maker&amp;#39;s attitudes towards risk, preferences and values&lt;br /&gt;- Multiple criteria decision models, methods, processes, tools and decision support systems&lt;br /&gt;- Introduction to game theory for decision making under competition, Markov chain process and time-dependent decision making under risk&lt;br /&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</Content>
  </UnitOverview>
  <Aims Applicant="Y" Label="Aims" Student="Y">
    <Content>&lt;p style="margin-left:5.7pt;"&gt;To introduce modelling and optimisation methods to address decision problems in resource management. To introduce the concepts, processes, models, methods and software tools of decision analysis with real-world application examples for supporting better operational, tactical and strategic decision making in business and management.&lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</Content>
  </Aims>
  <LearningOutcomes Applicant="Y" Label="Learning outcomes" Student="Y">
    <Content>&lt;p&gt;At the end of the course students should be able to:&lt;br /&gt;- recognise a variety of management decision problems addressed by different linear modelling techniques in operational research&lt;br /&gt;- apply a range of specific and generic linear optimisation methods and tools for solving the problems to achieve the effective and efficient use of resources&lt;br /&gt;- conduct sensitivity analysis to support managerial decision making&lt;br /&gt;- describe and apply the decision analysis models and methods covered&lt;br /&gt;- consider different approaches to particular decision problems and identify the assumptions, advantages and disadvantages of each approach&lt;br /&gt;- discuss how computer software tools are used to implement the models and methods, and how they are used in real-world decision problems in business and management&lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</Content>
  </LearningOutcomes>
  <Knowledge Applicant="Y" Label="Knowledge and understanding" Student="Y">
    <Content></Content>
  </Knowledge>
  <IntellectualSkills Applicant="Y" Label="Intellectual skills" Student="Y">
    <Content></Content>
  </IntellectualSkills>
  <PracticalSkills Applicant="Y" Label="Practical skills" Student="Y">
    <Content></Content>
  </PracticalSkills>
  <TransferableSkills Applicant="Y" Label="Transferable skills and personal qualities" Student="Y">
    <Content></Content>
  </TransferableSkills>
  <EmployabilitySkillsList Applicant="Y" Label="Employability skills" Student="Y">
    <Skill>
      <SkillId></SkillId>
      <SkillDescription></SkillDescription>
    </Skill>
  </EmployabilitySkillsList>
  <Syllabus Applicant="Y" Label="Syllabus" Student="Y">
    <Content></Content>
  </Syllabus>
  <TeachingMethods Applicant="Y" Label="Teaching and learning methods" Student="Y">
    <Content>&lt;p&gt;Four-hour lecture per week (see detailed schedule below) for 10 weeks, directed reading and computer based support&lt;br /&gt;Lecture hours: 40&lt;/p&gt;&lt;p&gt;Private study: 160&lt;/p&gt;&lt;p&gt;Total study hours: 200&lt;br /&gt;Total study hours: 200 hours split between lectures, self-study and preparation for classes, and examinations.&lt;/p&gt;&lt;p&gt;Informal Contact Methods&lt;br /&gt;1. Office Hours: 4:00pm-6:00pm Monday&lt;br /&gt;2. Online Learning Activities (blogs, papers, discussions, self-assessment questions and answers)&lt;br /&gt;3. Drop in Surgeries (extra help sessions for students on material they may be struggling with)&lt;/p&gt;</Content>
  </TeachingMethods>
  <AssessmentMethods Applicant="Y" Label="Assessment methods" Student="Y">
    <IntroText> </IntroText>
    <Method>
      <MethodId>0</MethodId>
      <MethodName>Other</MethodName>
      <MethodWeight>100%</MethodWeight>
    </Method>
    <OtherDescription>&lt;p&gt;Examination (100%)&lt;/p&gt;</OtherDescription>
  </AssessmentMethods>
  <FeedbackMethods Applicant="Y" Label="Feedback methods" Student="Y">
    <Content>&lt;p&gt;&amp;bull; Informal advice and discussion during lectures and office hours.&lt;/p&gt;&lt;p&gt;&amp;bull; Written and/or verbal comments on assessed or non-assessed coursework.&lt;/p&gt;&lt;p&gt;&amp;bull; Solution files to some exercises are published on Blackboard.&lt;/p&gt;&lt;p&gt;&amp;bull; Responses to student questions via Blackboard or emails.&lt;/p&gt;&lt;p&gt;&amp;bull; Generic feedback posted on Blackboard regarding overall examination performance.&lt;/p&gt;&lt;p&gt;In addition to the central unit evaluation questionnaire, student are encouraged to give feedback through emails and conversations at anytime, and questionnaire near the end of the semester&lt;br /&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</Content>
  </FeedbackMethods>
  <RequirementsList Applicant="Y" Label="Pre/co-requisites" Student="Y">
    <Requirement>
      <UnitCode>BMAN10750</UnitCode>
      <UnitTitle>Quantitative Methods for Accounting and Finance</UnitTitle>
      <RequirementType>Pre-Requisite</RequirementType>
      <Description>Compulsory</Description>
    </Requirement>
    <Requirement>
      <UnitCode>BMAN10960</UnitCode>
      <UnitTitle>Quantitative Methods for Business and Management</UnitTitle>
      <RequirementType>Pre-Requisite</RequirementType>
      <Description>Compulsory</Description>
    </Requirement>
    <AdditionalRequirement>BMAN10960 or BMAN10750 are pre-reqs of BMAN31152 (not for Maths Stats &amp; OR). Students must be registered on BSc Mgt/Mgt specialism, IM, IMABS, Acctg, Maths, Stats &amp; OR, MathswBuss&amp;Mgt to enroll onto BMAN31152.&lt;p&gt;Pre-requisite course units have to be passed by 40% or above at the first attempt unless a higher percentage is indicated within this course outline.&lt;/p&gt;&lt;p&gt;Pre-requisites: BMAN10960 Quantitative Methods for Business &amp;amp; Management or BMAN10750 Quantitative Methods for A+F. For BSc Mathematics with Business and Management, BSc Mathematics with Finance, BSc Mathematics and Statistics no pre- requisites are required.&lt;/p&gt;&lt;p&gt;International exchange students may be permitted to take this course unit provided that the equivalent pre- requisite courses have been taken and checked by the course co-ordinator.&lt;br /&gt;&amp;nbsp;&lt;/p&gt;</AdditionalRequirement>
  </RequirementsList>
  <AcademicPrograms Applicant="Y" Label="Academic programmes" Student="Y">
    <AcademicProgram>
      <Program></Program>
      <Plan></Plan>
      <Level></Level>
      <Requirement></Requirement>
    </AcademicProgram>
  </AcademicPrograms>
  <FreeChoice Applicant="Y" Label="Available as a free choice unit?" Student="Y">
    <Content>N</Content>
  </FreeChoice>
  <Accreditation Applicant="Y" Label="Accreditation" Student="Y">
    <Content></Content>
  </Accreditation>
  <RecommendedReading Applicant="Y" Label="Recommended reading" Student="Y">
    <Content>&lt;p&gt;Taha, H. A. (2017), Operations Research, An Introduction, Prentice-Hall Inc. 10th Edition, Precinct. Earlier or later editions are fine. Search topics in Index of the book to find the right pages to read about the relevant topics.&lt;/p&gt;&lt;p&gt;Hillier, F.S. &amp;amp; Lieberman, G.J. (2015) Introduction to Operations Research 10th Edition, McGraw-Hill, Precinct. Earlier or later editions are fine. Search topics in Index of the book to find the right pages to read about the relevant topics.&lt;br /&gt;Belton, V., Stewart, T. J. (2002), Multiple Criteria Decision Analysis -An Integrated Approach. Kluwer Academic Publishers: Dordrecht, ISBN 0-7923-7505-X.&lt;/p&gt;&lt;p&gt;Keeney, R.L. and Raiffa, H. (1993), Decision with Multiple Objectives: Preference and Value Tradeoffs. Cambridge University Press.&lt;/p&gt;&lt;p&gt;Sen, P. and Yang, J. B. (1998), Multiple Criteria Decision Support in Engineering Design, Springer. All libraries&lt;/p&gt;</Content>
  </RecommendedReading>
  <StudyHours Applicant="Y" Label="Study hours" Student="Y">
    <IntroText> </IntroText>
    <ScheduledHours Applicant="Y" Label="Scheduled activity hours" Student="Y">
      <ActivityHours>
        <ActivityType>Assessment written exam</ActivityType>
        <Hours>3</Hours>
      </ActivityHours>
      <ActivityHours>
        <ActivityType>Lectures</ActivityType>
        <Hours>40</Hours>
      </ActivityHours>
    </ScheduledHours>
    <PlacementHours Applicant="Y" Label="Placement hours" Student="Y">
      <ActivityHours>
        <ActivityType></ActivityType>
        <Hours>0</Hours>
      </ActivityHours>
    </PlacementHours>
    <TotalHours Applicant="Y" Label="Independent study hours" Student="Y">
      <Hours>160</Hours>
    </TotalHours>
  </StudyHours>
  <Notes Applicant="Y" Label="Additional notes" Student="Y">
    <Content>&lt;p&gt;Other staff involved:&amp;nbsp;&lt;/p&gt;&lt;p&gt;Pre-requisite course units have to be passed by 40% or above at the first attempt unless a higher percentage is indicated within this course outline.&lt;/p&gt;&lt;p&gt;Pre-requisites: BMAN10960 Quantitative Methods for Business &amp;amp; Management or BMAN10750 Quantitative Methods for A+F. For BSc Mathematics with Business and Management, BSc Mathematics with Finance, BSc Mathematics and Statistics no pre- requisites are required.&lt;/p&gt;&lt;p&gt;Co-requisites: None&lt;/p&gt;&lt;p&gt;Dependent courses: N/A&lt;/p&gt;&lt;p&gt;International exchange students may be permitted to take this course unit provided that the equivalent pre- requisite courses have been taken and checked by the course co-ordinator.&lt;/p&gt;&lt;p&gt;Programme Restrictions: This course is available to all students registered under the BSc programmes at MBS, provided that they meet the requirements set out in the course pre-requisites. Students for the following programmes can take this course: BSc Mathematics with Business and Management, BSc Mathematics with Finance, BSc Mathematics and Statistics; students from other university programmes may be allowed to take this course by discussion with the course coordinator.&lt;/p&gt;&lt;p&gt;For Academic Year 2025/26&lt;/p&gt;&lt;p&gt;Updated: May 2025&lt;/p&gt;&lt;p&gt;Approved by: March UG Committee&lt;/p&gt;</Content>
  </Notes>
</CourseUnit>
