22783 Business Intelligence 2: Advanced Planning

Faculty of Business: Accounting
Credit points: 6 cp

Subject level: Postgraduate

Result Type: Grade and marks

Handbook description

Understanding and applying advanced planning and optimisation methods for supply chain management are essential skills of management accountants in today's business. This subject deals with techniques that generate optimised executable plans in response to rapid changes in supply or demand (demand planning, profit maximisation through demand and supply optimisation, integrated, value-based supply chain management). Interactive, problem-based lectures and seminars demonstrate these management accounting concepts and allow students to practise in real time how these techniques can be applied using the SAP products SAP SCM and R/3.

Subject objectives/outcomes

On successful completion of this subject students should be able to:

Understand the key issues and methods used in strategic, tactical and operational business planning,
Discuss alternative vertical business plan integration scenarios and information systems infrastructure requirements supporting vertical business plan integration,
Establish consistent cause-and-effect between operative business plans, tactical plans and strategic plans, and implement those links in multi-tier enterprise systems,
Simulate operative business plan scenarios in enterprise systems and analyse the impact of those scenarios on strategic financial plans and key performance indicators,
Interpret the impact of operative business plan scenarios on cash flows and liquidity, and understand how to modify drivers in operative business plans to achieve liquidity/cash flow targets.
Design and customise a planning infrastructure (structures, hierarchies, planning functions) and end-user interfaces in multi-tier enterprise systems.

Contribution to graduate profile

The hallmarks of today's business environment are volatile demand, decreased customer loyalty, shorter product life cycles, and tougher global competition. To survive, organisations need an information infrastructure that allows them to make accurate decisions in real time and to make customer satisfaction a top priority, while still remaining competitive and profitable. Miscalculations in forecasting and planning that result in excess inventory can prove fatal. Failing to meet promised delivery dates can drive away customers. To handle these challenges, management accountants are turning to new, advanced planning and scheduling techniques that generate optimised executable plans in response to rapid changes in supply or demand.

Huge amounts of data drive these planning and scheduling processes. Much of it comes from the organisation itself, but other data comes from outside the organisation – from suppliers, partners, and even customers. Unlike the data models used by existing Enterprise Resource Planning (ERP) systems, supply chain decision support systems require a new breed of memory resident data model that can handle vast amounts of complex data in real time.

Large software vendors (e.g. SAP) have introduced Supply Chain Management solutions to meet the challenges of managing the entire supply chain from end to end. Tools such as the SAP Advanced Planner and Optimizer (SAP APO) combine the execution power of ERP systems with advanced planning and optimisation methods and supply chain management tools.

Teaching and learning strategies

A variety of teaching and experimental learning methods and strategies are applied, including teamwork, discussions, and, above all, hands-on experience with an ERP-system (SAP ERP).

Students are required to use the SAP ERP systems outside normal class hours. They have to work on a collaborative case study project, in order to gain the ability to apply their knowledge in a problem-oriented, process-driven, integrated systems environment.

Content

Supply Chain Management in Perspective
Introduction to Supply Chain Planning
Forecasting, Models, Lifecycle Management, Promotion Planning
Forecast Data Flow
Collaborative Planning
Rough Cut Planning, Network Heuristics, Optimisation, Safety Stock
Deployment

Assessment

Mid-term exam (Individual)	20%
Assesses both the conceptual and application component of the first part of the subject, covering primarily objectives 1 and 2.
Case study (Group)	30%
Assesses mainly the application component of the subject, covering primarily objectives 3, 5 and 6, as well as their integration with the other objectives.
Final exam (Individual)	50%
Assesses the conceptual component of the second part of the subject and the integration with the application component covering all objectives.

Recommended text(s)

Eddigehausen, W. (2002): The SAP APO Knowledge Book: Supply and Demand Planning, Publisher: Eddigehausen, Wolfgang, ISBN 0-9581791-0-7

SAP-Online Help: help.sap.com

Indicative references

Lozinsky, S.; Wahl, P. (1998). Enterprise-Wide Software Solutions: Integration Strategies and Practices. Addison-Wesley Pub Co.

SAP AG (1998), SAP Advance Planner and Optimizer, White Paper, Available on: http://www.sap.com/search/apo1.com

Stadler, H., Kilger, C. (2000), Supply Chain Management and Advanced Planning, Springer, Berlin et al.

Wieder, B. (2003), Accounting and ERP – Integrated Event-Accounting with SAP R/3, Tekniks Publ., Sydney

Wieder, B. (2003), Business Process Integration with SAP R/3, Tekniks Publ., Sydney