Group Assignment: Post # 3

1. Try any one of these decision support systems and describe two examples of decisions which they may help to support. For each decision, describe whether the decision would be made by operational, middle or senior management levels :





• Break-even Calculator


• Online Customer Lifetime Value Calculator (from Harvard Business School)


• Hong Kong Yellow Pages Online Map


• HSBC Mortgage Planner





2. Next, try out the different modules within the
   OpenBravo ERP demo. After you've familiarized yourself with these tools, identify which module can be used to handle each step within the Order-to-Cash business process below:





• Accept/Enter Order


• Order Acknowledgement


• Purchase Materials


• Receive Materials


• Production


• Packing


• Shipping


• Invoicing and Collection





3. Which departments need to coordinate from start to finish of the Order-to-Cash business process ? Describe how the ERP software makes their work easier. Also explain why ERP software can serve as the foundation or platform for decision support systems.

Session 6: Enterprise Resource Planning

Here are some reference links with videos or demos of ERP software:

SAP ERP Demos
OpenBravo ERP
Compiere ERP

Session 5: Decision-Support and Knowledge Management

On Week 5, we learned about the different levels and classes of decision-making within a company. There are structured decisions, unstructured decisions and semi-structured decisions to be made at each level of a business. Depending on the class and the level at which the decision is made, different information systems or technlogies may be used to assist the decision-maker.

The major decision-support systems we looked at include: management information systems, model-based decision-support systems and business intelligence (or data-based decision-support systems. MIS provides regularly scheduled hardcopy reports that can be used in structured decision-making, while model-driven or data-driven DSS supports unstructured and semi-structured decision making.

Sensitivity analysis or performing "what-if" analysis is a common technique for using model-driven DSS. Here are some examples of model-driven DSS that you may try out online:

Break-even Calculator

Online Customer Lifetime Value Calculator (from Harvard Business School)

As you try out the examples, ask yourself what types of decisions may be supported by asking "what-if" questions through these models. I've also posted a short movie of how a model-based DSS may be used on SOUL.

We also discussed the class answers for Tutorial 4: Business Intelligence with the Hong Kong Jockey Club as our case study company. Model answer will be posted on SOUL as well.

Group Assignment: Post # 2

This week we learned how B.I. tools (business intelligence) allow businesses to get more value and insight out of their databases.

1. Visit the OLAP Service Online Demo and design three different grid reports using at least three dimensions per report. Each report must have at least one measure which is being analyzed along the chosen dimensions.




• You may choose from any of the dimensions found along the left-hand side of the demo: Customer, Date, Employee, Delivery Date, Product, Reseller, Employee, etc.


• You may choose from any of the measures under Internet Sales, Reseller Sales or Sales Summary (found along the left-hand side of the demo).




2. Post the following content on your blog regarding the grid reports you've designed:




• A screen capture of a section of the report which shows the included dimensions and measure(s);


• An explanation of the insights contained in the report and how these insights can be used by the company to understand their performance or make better decisions;




3. Describe the benefits of allowing users to query a data warehouse in the form of an OLAP cube through their Web browser.

Session 4 - Business Intelligence

This week we learned that businesses can try to extract more use out of the data that they have collected in their databases over the years. The technology which allows them to do this belong under the category or umbrella called "B.I.".

Unlike query and reporting tools in regular databases, BI tools can help users find previously unknown patterns and trends in their data, or it can help them perform ad-hoc queries and comparisons on large amounts of current and historical data. BI is not meant for daily operational use but it is meant for decision-support and analytical use.

Here's a link to a demo of an OLAP cube. Try to query the cube along multiple dimensions to see how easy it is to gain insights from a data warehouse.