Singapore University of Social Sciences

Operations Analytics

Operations Analytics (BUS352)

Applications Open: To be confirmed

Applications Close: To be confirmed

Next Available Intake: To be confirmed

Course Types: Modular Undergraduate Course, SkillsFuture Series

Language: English

Duration: 6 months

Fees: To be confirmed

Area of Interest: Business Administration

Schemes: Alumni Continuing Education + (ACE+), Lifelong Learning Credit (L2C)

Funding: SkillsFuture

School/Department: School of Business


Synopsis

Improvements in data-collecting technologies have changed the way firms make informed and effective business decisions. BUS352 Operations Analytics focuses on the use of analytics, together with data, to analyse and solve operational problems in various business settings, and transform data into information to support decision making. In BUS352 Operations Analytics, students willgain a better understanding of the classic operations problems with data support, as well as learn to describe and present operational data in a meaningful and informative way. Students will also be exposed to analytics techniques and learn how to apply them to construct quantitative models, e.g., forecasting, optimisation and simulation models, to solve operational problems. Students will learn how to choose the best course of action in the face of uncertainty.

Level: 3
Credit Units: 5
Presentation Pattern: Every July

Topics

  • Introduction to operations management
  • Efficiency vs effectiveness in operations
  • Data-driven operations
  • Interpretation and visualisation of operational data
  • Descriptive and diagnostic analytics in addressing operational problems
  • Predictive analytics in addressing operational problems
  • Prescriptive analytics in addressing operational problems
  • Decision analysis under uncertainty
  • Service operations
  • Inventory management
  • Aggregate planning
  • Quality management and emerging topics in operations

Learning Outcome

  • Appraise the role of operations in an organisation.
  • Discuss the trade-off between efficiency and effectiveness in addressing operational
  • Evaluate complex operational decisions with different degrees of uncertainty.
  • Assess operational problems with supporting data.
  • Distinguish between descriptive, diagnostic, predicative and prescriptive analytics.
  • Select appropriate analytics techniques to analyse and solve problems in operations.
  • Examine, visualise and interpret operational data.
  • Apply the essential knowledge and interpersonal skills to work effectively in a team.
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