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Enterprise Business Processes and Reporting (IS 6214) MBS MIMAS 12 th Jan 2011 Fergal Carton Business Information Systems.

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Presentation on theme: "Enterprise Business Processes and Reporting (IS 6214) MBS MIMAS 12 th Jan 2011 Fergal Carton Business Information Systems."— Presentation transcript:

1 Enterprise Business Processes and Reporting (IS 6214) MBS MIMAS 12 th Jan 2011 Fergal Carton Business Information Systems

2 Last week ERP system sample screens ERP and control Evolution of ERP Integration is a question of design Cucina project overview Notes on Arbutus breads First IS 6216 class on Friday 7 th Jan, Lab 1.111

3 This week How managers work Managers require information ERP reports and getting “one truth” Main ERP modules and demos Types of data Latency and response times in entreprise reporting Refresh rates The requirement for real time information Recipe and inventory data for Cucina

4 How managers do their work What is happening? Actual What should be happening? Plan What therefore would happen if? What-if? Adjust plan and/or change actual Manage

5 Plan Buy Make Deliver Bill and collect Approve & Pay Report results Sell Install Maintain Recruit Manage Reward ManufacturingFinanceSales / CSHR Market DevelopBudget Management information ProductsCashCustomersPeople Integrated data (single point of entry) Managers require information

6 Different types of report exist: Scheduled reports (produced periodically) Exception reports (produced when something unusual happens) Demand (ad-hoc) reports (specific reports requested by a user) ERP Reports

7 Why is “one truth” so hard? Eg. Up to date picture of revenue? –Easy bit: all product shipped to date –Hard bit: Spares, loaners, replacement machines, … Deduct any current credit notes Add any outstanding debts from previous invoices Apportion revenue from service contract (12 months) Allow for discount to be applied if paid on time Currency exchange rate fluctuations … … –Revenue recognition “rules”

8 Production planning and forecast In theory, it’s simple –Sales forecast future demand for products –Production plan to meet forecast sales But, in real life, there are many contingencies: –Sales tend to be optimistic –Most businesses exhibit seasonality –Customers are unpredictable –Forecasts are based on average prices –Yield may be poor due to quality issues –…

9 Key modules

10 SAP demos Sales (order to cash) –http://www.youtube.com/watch?v=Qa0gRHw66XMhttp://www.youtube.com/watch?v=Qa0gRHw66XM –http://www.youtube.com/watch?v=LCtqrSEcpU4&feature=relatedhttp://www.youtube.com/watch?v=LCtqrSEcpU4&feature=related Financials –http://www.youtube.com/watch?v=ObIpO0X5iPA&feature=relatedhttp://www.youtube.com/watch?v=ObIpO0X5iPA&feature=related

11 Type of data : Cucina What are the types of data you have for Cucina?

12 Type of data : static What are the types of data you have for Cucina?

13 Type of data : dynamic What are the types of data you have for Cucina?

14 Type of data: soft information Data collection - –Grapevine –factory tours (talking and observing) Data storage - –managers’ minds –special reports Data usage: –ad-hoc basis –decision making

15 Latency in performance reporting Refresh rates can create latency across four levels –ERP to DW eg. every 8 hours DW updated with fresh sales transactions –The time it takes for the refresh to execute can lengthen eg. 2/3 hours –Running a query on the DW can take some time to complete eg. 10 mins –Report display on user machine can slow down eg. 10 minutes –Total latency of 11/12 hours can be critical at quarter end –Decision making not supported in information cannot be trusted

16 Response times Response times are a function of : – response time, –Infrastructure elements, –Database sizing –Transaction processing –Interfaces –Reporting –Other processing demands –Peak times –…

17 Extraction Cleaning Transformation Loading Relational Database on a dedicated Server De normalised, data Static Reporting Scrutinising Multidimensional Data Cubes OLAP tools Data Warehouse Source Systems Discovering Data Mining ……. Data Staging Area Exploiting the DW data

18 Refreshing databases Timing Criticality of information Volume of data Response time Real-time requirement Level of aggregation / granularity

19 Refresh Optimization

20 Determining the Refresh Frequency Maximize net refresh benefit Value of data timeliness Cost of refresh Satisfy data warehouse and source system constraints

21 Life cycle of the DW Operational Databases Warehouse Database First time load Refresh Refresh Refresh Purge or Archive

22 Real time information Up to date On-line Actual data Live feed Decisions made on what basis?

23 Real time requirement? Historical sales or accounting data, not real-time Sales as quarter end approaches Inventory levels for MRP Exchange rates, when is Visa rate calculated? Real-time processing: card transactions down


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