ISM-E1004 - Business Analytics 2, Lecture, 10.1.2022-21.2.2022

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Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

Management Science deals with the use of analytical models to help make better business decisions. This course focuses on models for supporting decision making under uncertainty, risk and multiple objectives. After the course the student can (i) recognize the types of real-life business problems where use of the models brings added value, (ii) interpret results of these models to derive defensible decision recommendations, and (iii) build and solve these models using a computer to support business decision making.

Credits: 6

Schedule: 10.01.2022 - 21.02.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Ilkka Leppänen

Contact information for the course (applies in this implementation):

Ilkka Leppänen ilkka.j.leppanen@aalto.fi

I am available for feedback and consultation, please message/email me to book a Teams meeting

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    Monte Carlo simulation, decision trees, value of information, expected utility theory, risk attitudes, stochastic dominance, risk measures, multi-attribute utility/value theory, modelling uncertainties and multiple objectives in optimization problems.

  • applies in this implementation

    Uncertainty and multiple objectives are inescapable features of many decision problems. We focus on management science methods that support decision making under uncertainty and/or multiple objectives. Please see schedule for a detailed list of topics.

    Some necessary background concepts from applied probability are also covered.

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Assignments 50%, exam 50%.

  • applies in this implementation

    Final points, which consist of exam points (50%) and assignment points (50%), determine the final grade:  >50p ->1; >60p -> 2; >70p -> 3; >80p -> 4; >90p -> 5. These bounds may be relaxed during final grading. To pass the course you need to attain at least half of the exam points.

    There are three assignments with deadlines during the course. Each assignment consists of 4–12 problems or cases, which usually require the use of spreadsheets or other mathematical software to solve.

    Assignments are individual work. You may discuss the problems with your fellow students, but you must submit individual answers. In the exam you will need to individually solve equivalent problems. Submitting a copied answer or a solution is academic misconduct and is strictly forbidden.

Workload

  • valid for whole curriculum period:

    Contact teaching 36h, individual work 121h, exam 3h.

  • applies in this implementation

    Contact teaching constitutes of lectures, assignment demonstrations, and assignment feedback.

    Individual work constitutes of lecture preparation (12h), work on the assignments (101h), and revising for the exam (8h).

DETAILS

Study Material

  • valid for whole curriculum period:

    Lecture slides, articles, assignments, computer implementations of mathematical models, and the textbook (An Introduction to Management Science by Anderson et al., 2014, ISBN Code: 978-1-111-82361-0).

  • applies in this implementation

    The textbook can be very helpful, but you will be able to perform well in the course even without it.

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    8 Decent Work and Economic Growth

    9 Industry, Innovation and Infrastructure

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    A maximum of 80 students will be admitted to the course. Priority will be given to Aalto ISM MSc students and students with strong analytical skills (see prerequisites).


    Teaching Period:

    2020-2021 Spring III

    2021-2022 Spring III


    Course Homepage: https://mycourses.aalto.fi/course/search.php?search=ISM-E1004


    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.

  • applies in this implementation

    The course will be delivered fully online as per the University policy regarding Period III teaching.

Details on the schedule

  • applies in this implementation

    Two 3-hour teaching sessions per week (Monday and Wednesday mornings)

    In each session, approximately 2 hours are spent on traditional lecturing and 1 hour for working towards the assignment submissions

    Recordings of the teaching sessions will be available after each session. However, please attend all the sessions at their allocated time slots. Attending the teaching sessions is highly recommended, as this is known to lead to superior learning outcomes and performance in the exam.

Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof