1. Justifying BI to Business
Amendra Pratap
Senior Manager
@amansyd

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Macquarie Group
Established in 1969
FY13 Net Profit $ A 851 M – up 17%
Net Income $ A 6.7 Billion down 4%
Net Operating Exp $ A 5.7 Billion down 10 %
Assets Under Management $A 347 Billion
International Income – 63% of total
6 Operating Divisions - from Managing Funds
to Aircraft leasing

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What is BI
Success Stories
Environment
Keys to Success

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So what is BI ?

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A corner shop example

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What Intelligence does the Store owner possess ?
Forecasting
Sales Analytics
Trend Analysis
Predictive Analysis
Capture Sentiments
Non Financial Analytics

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Insights
Action
•Forecasting
•Analytics
•Trends
•Predictive
•Non Financial
•Big Data

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GFC
Falling
Revenue
Highly
Leveraged
Decline in
Trading
Activity
Banks
Collapsing
Strong
Balance
Sheet
Decisive
Need to understand
Cost base
Data Based
Decision
External
Internal

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Group Rolling Forecast
Starting Point
•Took 3 months to do Budgets
• Siloed Approach
• Excel as a tool
• No governance or standards
• 80 % of time processing 20 % of
time Analysing
• Limited collaboration
• Non responsive to changes
End State
•Budgets/Forecasts in 2 weeks
• Group Wide approach
• IBM Cognos TM1
• Standard approach
• 20 % of time processing 80 % of
time Analysing
• Encourage/Force Collaboration
• Quick response to changing
business needs

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Group Rolling Forecast
1. Established Macquarie Group Forecasting Tool
• Eliminated 1000’s of Budget spreadsheets
• Distributed model – All areas input their own numbers (once)
• Automated Recovery allocation – In real time
• Budget Reports/Budget books updated - in real time
• Ability to slice & dice and Report
• Single source of truth (eliminates hours of reconciliations between versions)
• Reduced Annual cost to Run Budgeting tool

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Balance Sheet Projection
Starting Point
• No Source of truth
• Data Quality & Structure Issues
• Scenario Modelling not available
• Reporting using Excel
• No integration with Optimisation
tool
• Multiple teams having their own
eco system of same data
End State
• Single Balance Sheet Projection
model
• Forex capable
•Scenario modelling
• Adaptive to new requirements –
internal or regulatory
• All relevant teams work with
same data set
• Dashboard reports

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How did we do it/Lessons learnt
1. Smaller Projects – Quicker delivery and benefit realisation
2. Modular Architecture – Agile & Adaptive
3. Business driven BI – Delivered by IT
4. Data Governance/Project Governance
5. One Version of truth
6. BI Initiatives should align with organisational Strategy
7. Enterprise wide Perspective

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@ibmbaug
http://tiny.cc/ibm
baug
• Networking events
• Knowledge Share
• Real world customer stories
• “No Sales” pitches
• Vendor updates & Feedback
IBM Business Analytics User Group

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Thank you