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Enterprise Decision Support - A Commercial Perspective Pete Catley Supervisor, Sales Reporting Systems, Ford Europe Thursday 18 November, 1999 SEM304 -

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Presentation on theme: "Enterprise Decision Support - A Commercial Perspective Pete Catley Supervisor, Sales Reporting Systems, Ford Europe Thursday 18 November, 1999 SEM304 -"— Presentation transcript:

1 Enterprise Decision Support - A Commercial Perspective Pete Catley Supervisor, Sales Reporting Systems, Ford Europe Thursday 18 November, 1999 SEM304 - Commercial Programming

2 Agenda: l Introduction l Enterprise Decision Support Overview l Case Study: Smarts

3 Why Do Businesses Have IT Departments?

4 Only Small Businesses Can Survive Without IT

5 As Soon As You Start to Scale up As an Enterprise You Begin to Recognise the Need for an IT Department

6 IT Departments Have Developed Over the Years

7 Adding Machines Business SystemsTechnical Systems Operational Analytical Transaction Processing Database Applications Process Control CAD / CAM / CAE Reporting Applications Analytical Applications

8 Why Do We Analyse?

9 Beware: Paralysis By Analysis

10 Business Reality: Difficult to Turn “Data” Into “Information”

11 Reporting Decision Support Actionable Intelligence Everything That Happened Everywhere All The Time Key Things That Happened In Important Locations At Relevant Times Some Things You Could Do To Address The Issues Fixed Format High Redundancy High Effort To Interpret Dynamic Format Focused Output Low Effort To Interpret High Value Add Very Rapid Response

12 Imagine If Your Car Had No Instrument Panel?

13 Now Imagine You Are A Captain Of Industry At The Helm Of The SS “Shareholder Value”

14 So the Vision is: Wouldn’t It Be Nice If We Had A System Which Told Us Where The Issues Were?

15 Vision Enablers l Reporting By Exception l “Traffic Lighting” l OLAP “Slice & Dice” l Key Performance Indicators l E-mail Notification Of Exceptional Events l Use of “Push” Web Technology l “What If” Analysis & Modelling l Thematic Mapping

16 What Do You Need To Do To Gain Actionable Intelligence?

17 Operational Systems Capture Data Warehouse Staging Areas Cleanse Meta-Data Layer Data Marts Store Aggregate Interpret OLAP Deliver Ad-HocReportsExecutive Information Normalised Relational Model De-Normalised “Star Schema” Mainframe Data Sources Simple Relational Tables

18 That Looks Pretty Straightforward Let’s Do It!

19 Case Study: SALES MANAGEMENT ANALYSIS & REPORTING TOOL SET smarts

20 First: Sell The Vision

21 “How Much Is All This Going To Cost Me?”

22 “Ouch!”

23 Build A Cast-Iron Business Case

24 Gain A Powerful Sponsor

25 Who, In Their Right Mind, Would Develop A Mainframe-based Spreadsheet In-House?

26 Nobody - They’d Buy Excel!

27 Pick An Architecture MOLAP 4High Performance 6No. Dimensions 6Data Volume ROLAP 4No. Dimensions 4Data Volume 6Performance HOLAP 4High Performance 4No. Dimensions 4Data Volume 6Devt. Complexity DOLAP 4Cost 4Devt. Complexity 4Implementation Ease

28 Front-End Architecture l Buy OLAP Tools –Web-Based Ad-Hoc Query –Reporting –Web Publishing –Personal Web Portal Concept

29 Back-End Architecture l Re-Use Existing Data Extract l Build Staging Areas l Build Data Transformations l Build Data Warehouse l Build Data Marts

30 But: Choose The Right Tools

31 Pick “Best-In-Class” (But Teacher Chooses Who’s In The Class!)

32 Tool Selection l ATAD /FSIC l Shortlist l “Proof Of Concept” Workshops l Tool Selection Matrix l FSIC Architecture Review

33 Pick A Good Team and A Strong Project Manager

34 Metrics l 7 Months To Gain Funding Approval l 6 Months To Deliver Phase 1 l Team of 9 l 120 Gb Database l Sun E4500, 10 x 337mhz CPUs, 4Gb l $1.4m per annum Cost Saving l Launched On Time (to the day!)

35 But: Do The Users Like It?


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