School: Business and Law

This unit information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester.

  • Unit Title

    Data Driven Managerial Decisions
  • Unit Code

    MAN6777
  • Year

    2021
  • Enrolment Period

    1
  • Version

    1
  • Credit Points

    20
  • Full Year Unit

    N
  • Mode of Delivery

    On Campus
    Online
  • Unit Coordinator

    Dr Mohammad IRANMANESH

Description

In the contemporary business climate of hyper-competition, volatility and increasingly pervasive technologies, the demand for organisational agility and responsiveness accentuate the degree to which success is linked to managerial decision making: more business decisions need to be made, at greater speed, with superior precision in order to achieve effective business outcomes. This unit examines the different types of business decisions that managers make, embedding these within a variety of processes and contexts. Students will examine the role of data analytics and other technologies in the strategic decision making processes of organisations. Students will have an opportunity to familiarise themselves with the business decision-making processes by exploring and applying some analytical and data visualisation techniques.

Prerequisite Rule

Must have passed MAN6905 Databases and Business Intelligence for students enrolled in L71.

Learning Outcomes

On completion of this unit students should be able to:

  1. Critically analyse and evaluate situations using decision making-models and techniques to improve the quality of decision-making.
  2. Critically analyse the role of data analysis and technology in business and managerial decision-making.
  3. Plan, implement and apply complementary data analysis and decision-making technologies in organisational activities.
  4. Critically evaluate success factors in adopting data analytics and other decision-making technologies in various business situations.

Unit Content

  1. Creating solutions for structured, semi-structured and unstructured business decisions. Role of information systems in decision-making.
  2. Social media crowdsourcing and customer involvement in decision-making.
  3. Enterprise 2.0 - collaborative systems for decision making.
  4. Types of decision and decision making, distortions, criteria for assessing decision-making approaches.
  5. Business value of managerial decision making. Embedding data analytics into business processes.
  6. Introduction to data analytical tools (such as Power BI).
  7. Application of data analytics and technologies in organisational decision-making activities.

Additional Learning Experience Information

Students will be expected to study materials from a variety of sources prior to the seminar and participate in class discussion during the seminar. Communication skills will be practised via written exercises, oral discussion and presentations. Study materials will be distributed via the online learning environment Blackboard. The online environment for online students will mirror on-campus activities. Off campus students will be required to post their activities on forums and review the work of others, just as on- campus students will do in class. They will be required to use social-media and record digital presentations for sharing with other students. Students will be expected to research relevant issues of interest in their workplace and discuss them in class for their assignment portfolio. Teaching will be supported through industry representation and participation in order to analyse decision making issues and technologies from a real-world perspective. Industry leaders will feature as guest lecturers, enabling learners to make the connection between theory and practical application.

Assessment

GS1 GRADING SCHEMA 1 Used for standard coursework units

Students please note: The marks and grades received by students on assessments may be subject to further moderation. All marks and grades are to be considered provisional until endorsed by the relevant School Progression Panel.

ON CAMPUS
TypeDescriptionValue
PortfolioPersonal learning portfolio40%
AssignmentCase Study30%
ExaminationExamination30%
ONLINE
TypeDescriptionValue
PortfolioPersonal learning portfolio40%
AssignmentCase Study30%
ExaminationExamination30%

Disability Standards for Education (Commonwealth 2005)

For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Access and Inclusion website.

Academic Misconduct

Edith Cowan University has firm rules governing academic misconduct and there are substantial penalties that can be applied to students who are found in breach of these rules. Academic misconduct includes, but is not limited to:

  • plagiarism;
  • unauthorised collaboration;
  • cheating in examinations;
  • theft of other students' work;

Additionally, any material submitted for assessment purposes must be work that has not been submitted previously, by any person, for any other unit at ECU or elsewhere.

The ECU rules and policies governing all academic activities, including misconduct, can be accessed through the ECU website.

MAN6777|1|1

School: Business and Law

This unit information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester.

  • Unit Title

    Data Driven Managerial Decisions
  • Unit Code

    MAN6777
  • Year

    2021
  • Enrolment Period

    2
  • Version

    1
  • Credit Points

    20
  • Full Year Unit

    N
  • Mode of Delivery

    On Campus
    Online
  • Unit Coordinator

    Dr Mohammad IRANMANESH

Description

In the contemporary business climate of hyper-competition, volatility and increasingly pervasive technologies, the demand for organisational agility and responsiveness accentuate the degree to which success is linked to managerial decision making: more business decisions need to be made, at greater speed, with superior precision in order to achieve effective business outcomes. This unit examines the different types of business decisions that managers make, embedding these within a variety of processes and contexts. Students will examine the role of data analytics and other technologies in the strategic decision making processes of organisations. Students will have an opportunity to familiarise themselves with the business decision-making processes by exploring and applying some analytical and data visualisation techniques.

Prerequisite Rule

Must have passed MAN6905 Databases and Business Intelligence for students enrolled in L71.

Learning Outcomes

On completion of this unit students should be able to:

  1. Critically analyse and evaluate situations using decision making-models and techniques to improve the quality of decision-making.
  2. Critically analyse the role of data analysis and technology in business and managerial decision-making.
  3. Plan, implement and apply complementary data analysis and decision-making technologies in organisational activities.
  4. Critically evaluate success factors in adopting data analytics and other decision-making technologies in various business situations.

Unit Content

  1. Creating solutions for structured, semi-structured and unstructured business decisions. Role of information systems in decision-making.
  2. Social media crowdsourcing and customer involvement in decision-making.
  3. Enterprise 2.0 - collaborative systems for decision making.
  4. Types of decision and decision making, distortions, criteria for assessing decision-making approaches.
  5. Business value of managerial decision making. Embedding data analytics into business processes.
  6. Introduction to data analytical tools (such as Power BI).
  7. Application of data analytics and technologies in organisational decision-making activities.

Additional Learning Experience Information

Students will be expected to study materials from a variety of sources prior to the seminar and participate in class discussion during the seminar. Communication skills will be practised via written exercises, oral discussion and presentations. Study materials will be distributed via the online learning environment Blackboard. The online environment for online students will mirror on-campus activities. Off campus students will be required to post their activities on forums and review the work of others, just as on- campus students will do in class. They will be required to use social-media and record digital presentations for sharing with other students. Students will be expected to research relevant issues of interest in their workplace and discuss them in class for their assignment portfolio. Teaching will be supported through industry representation and participation in order to analyse decision making issues and technologies from a real-world perspective. Industry leaders will feature as guest lecturers, enabling learners to make the connection between theory and practical application.

Assessment

GS1 GRADING SCHEMA 1 Used for standard coursework units

Students please note: The marks and grades received by students on assessments may be subject to further moderation. All marks and grades are to be considered provisional until endorsed by the relevant School Progression Panel.

ON CAMPUS
TypeDescriptionValue
PortfolioPersonal learning portfolio40%
AssignmentCase Study30%
ExaminationExamination30%
ONLINE
TypeDescriptionValue
PortfolioPersonal learning portfolio40%
AssignmentCase Study30%
ExaminationExamination30%

Disability Standards for Education (Commonwealth 2005)

For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Access and Inclusion website.

Academic Misconduct

Edith Cowan University has firm rules governing academic misconduct and there are substantial penalties that can be applied to students who are found in breach of these rules. Academic misconduct includes, but is not limited to:

  • plagiarism;
  • unauthorised collaboration;
  • cheating in examinations;
  • theft of other students' work;

Additionally, any material submitted for assessment purposes must be work that has not been submitted previously, by any person, for any other unit at ECU or elsewhere.

The ECU rules and policies governing all academic activities, including misconduct, can be accessed through the ECU website.

MAN6777|1|2