May 30, 2010

How Many BI's can you pile before information

I recently ran into a case where we found 3 BI's one on top of the other to deliver some imformation. Sure would love to hear from your sides as to how many you have actually found / handled .
sedn to

May 26, 2010

Chapters of BI Valuenomics

Prologue 13

Introduction 15
The 2010 Gartner report on global BI 23
Gartner’s 2010 magic quadrant 30
So what should BI plan to Improve? 33
Who stole my BI Business expectations? 36
Crime identification 37
The Tangential Findings 46
How some BI Projects are Run Today 51
‘As-Is’ BI Project decision Flow 51
The Story of Business Intelligence 64
The Way BI Projects should be Run 72
Who should own BVA in a BI Project 85
The BI – BVA Goal 86
The world of the Information Consumer 90
Initial Self Analysis 95
BI Maturity Matrix 97
BI Fault Tree Analysis 99
BVA in BI 101
Business Focused BI Framework 106
The Mirage of BI Success 110
The Economics of Efficiency 112
How decisions impact BI Projects 116
Team Dynamics and BI Projects 125
Can Executive Thinking get Delusional 130
Redefining BI project Success 135
Personal success definition- Type 1 137
BI success definition- Type 1 139
BVA success definition- Type 2 141
BVA Success measurement 142
When to implement BI 149
IT Project Cycles 149
Concurrent ERP & BI Go-Live 150
BI implemented subsequent to the ERP 153
The value of Business Value Attainment 159
Selling approach 166
Marketing Approach 166
Gartner’s Key Findings 172
Gartner’s Recommendations 2 173
Building a sustainable BI BVA roadmap 174
The BVA Blink moment 176
The 360 degree BI Initiative 178
A simple definition of a data warehouse 191
Building a ‘Social Value Engine’ in BI? 197
The macro BI Strategy Environment 203
The three cornerstones of BI - BVA 209
Business Participation 209
BI Strategy 210
Hallmarks of a BI strategy 213
Enterprise BI Cookbook 218
Architecture, Modeling & Standards in BI 222
BI Architecture 224
Business case: 226
1 - Business Architecture 226
2- Information Architecture 228
3- Data Quality Architecture 230
4- Technical Architecture 233
5 – Functional Architecture 236
6- Information Delivery Architecture 238
7- FEDW 239
8- FEDW 241
Caution: Building a BI on top of a BI 242
BI Modeling 245
Manual modeling: 249
Automated modeling: 250
Modeling for Business Value 260
Evolving from Data to Information Modeling 265
BI Standards 269
Contribute to the Social BI Capital 272
Key stakeholders of a BVA Kaizen Workshop 276
IPod and the art of Project Management 285
Traditional Project Management 285
The BVA BI Project management method 289
The IPod approach to BI Projects 294
‘Spanking New’ Information Revolution 299
Dawn of Information Acceptance 311
Start with BI BVA concepts 318
Enterprise ownership of BI 328
Core BI Competency 331
The ‘Key Success Factor’ for a FEDW BI 337
Business Ownership 341
Documented & Communicated Best Practices 341
Prioritized report delivery without distractions 341
Capital allocation in BI Project 344
About CA 346
Higher performance, lower costs: 349
What contributes to BI Failure 350
Is BI Prone to Recession? 357
Data, Information and Intelligence 358
The Hot BI Issues of tomorrow 365
The Value of the Business Value Owner 368
The Business Value Productivity Worker 371
The principles of TBVM 372
TBVM Impact on Costs 374
Differentiate Between Value & BVA 376
Roadmap to BI-BVA 378
Information consumers 378
Leverage the Strengths of the Triad 379
Five key BVA BI deployment questions 381
Information Consumer Requirements 383
Your Business Value Owner’s profile 386
The IDCM’s Methodology 388
TBVM Quality methods 389
Readying for the BVA harvest 393
CAB & BI Business Value 394
From Knowledge to Value Workers 399
The Value Workers Framework 403
Self Sustaining functionalities 404
BI Valuenomics takeaway’s 409
Plan for the Information consumer 411
The Future of BI 414

Reports or Informatics 414
Architecture: 418
Modeling 419
Executive Q&A 421

BI Valuenomics Resource List 424
Sample 1. Executive BI Best Practice Checklist 427
Sample 2: ‘BIOnTrak’ Checklist 428
Sample 3: BI BVA Checklist 429
Sample 4: Maturity matrix models 430
Sample 5: Source selection for Reports 432
Sample 6: The BVA Circle of BI Excellence 433
Sample 7: The global BVA process Flow 434
Sample 8: The BVA Project Management Life Cycle 434
Sample 9: Sample SIPOC for a BI Project 435
Bibliography: 436
Index 437


Just another 4 to 6 weeks of waiting and the book will be out

BI Valuenomics – The economics of Business Value in Business Intelligence

See the final front and bacl covers for the BookBI Valuenomics (Front Cover): :
BI Valuenomics (Back Cover) :

May 4, 2010

Taking BI from CFO to BVA

A. 1,500 CIO's tell us that only 55% of their BI investments are working
B. In 2008 they spent over $ 8.8 billion on BI, and they wasted almost $4 billion
THEY ALL WANT TO KNOW, along with Gartner, Forrester, AMR and Business Week
They do not achieve 'Business Value Expectations'
92% of BI Projects are declared successful in Week 1 of Go-Live
55% remain successful by Week 8
100% of Projects measure Cost, Time and Scope
92%  Achieve all three goals - thus they declare the project a success
55%  Realize they did not meet business value in 8 weeks, because it was never measured or audited
We manage our BW projects by the CFO & PMP rules
- we make weekly reports on time,
- we make weekly reports on cost
- we make weekly reports on budgets
- meet all cost, resource and budget obligations
HOWEVER- Throughout the end-to-end lifecycle, i.e.
1. Product selection process
2. Steering committee decisions
3. Busines Owner Approval
4. Project Processes
5. PMP guidance
6. Weekly reports
7. Monthly steering committee meetings
8. Integration tests
9. User Acceptance tests
10. Cutover Planning
11. Go Live
12. Go Live celebrations
***** WE NEVER CHECK FOR Business Value Attainment or Business Success *****
we  collectively lost $4 billiuon, or 45% of our BI investments in 2008 alone
As a project process:-
0. Don't just measure Cost, Time and Resources
1. Start measuring BVA with the same vigor and frequency
At time of Contract negotiating
2. Place a BVA Audit process, and
3. Place clear BVA conditions
Just like you currently for Cost, Respource and Budgets
As a Weekly Status report
4. Add a column to check BVA for all selected deliverables
At time of UAT
5. Measure BVA for each report planned for delivery
At time of Go-Live
Measure success not by Cost, time and resource values, as these are not BVA but CFO
6. Measure them by BVA Value Audits
    4.1 How many reports can business use TODAY without any changes whatsoever 
         4.1.1 Business can do this audit in under 4 days with a BVA owner
         This measure represents SUCCESS and USER SATISFACTION
    6.2 All the other reports represent degrees of failure
         This measure represents FAILURE or USER DISSATISFACTION


How Simple is Infocube Modeling

The Legacy method of InfoCube Modeling: How difficult can InfoCube modeling be. I used to teach this class and here is how the legacy course went
1. Identify all the data elements you plan to bring into the warehouse
2. Create a set of logical dimensions
3. Take all the characteristics and allocate them a dimension you see most fit
4. Some Chars always got left out. These the modeler randomly placed in any available or a single new dimension called Misc.
How difficult is modeling:Here is a scientific principle to solving the Rubiks Cube.

A. All of us have tried to solve a Rubik's Cube one time or another
B. A Rubik Cube is an InfoCube with 6 dimensions, each containing 6 absolutely identical characteristics
C. An average human takes four to six month of trying only to give up.
D. With scientific principles and rules
     D.1 The world record for solving the Rubiks cube is 7.08 seconds
            D.1.1 Blindfolded (including memorizing) is 32.27 seconds
The secret to success ‘Rules and a scientific methodology’

1. The average size of a N. American InfoCube is 10 dimensions and 70 Characteristics
2. This is over 10 Billion options for modeling the InfoCube
3. Manual modeling is a ‘Fool’s Paradise’ option to InfoCube modeling
Fact 1: Manual modeling is now impossible
Fact 2: Even the most intelligent human cannot model an InfoCube perfectly
Fact 3: Modeling directly impacts Query Performance, Data Load time, Footprint and Information Quality (not to be mistaken with data quality)
Fact 4: Modeling for BW is very different than BW Accelerator, is very different from modeling for BO Explorer

For an InfoCube write to