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Copyright 2008 IDC. Reproduction is forbidden unless authorized. All rights reserved.
Business Intelligence as aStrategy for the New EconomicReality
IDC BI Roadshow 2009
Laurentiu Popescu
IDC Romania
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Trends in the Economy, Romania 2009 vs2008
Key Economic Indicators: 2008
GDP 2008: RON $ 504 billion= Euro 120billion
GDP has increased in 2008 by 7.1%versus 2007
GDP per capital: Euro 5454
Inflation: 7% in 2009Unemployment: 4.4% in 2008, thoughstarted to increase in Q4 in result ofeconomy slow-down
FDI: RON 90 billion in 2008 a year-on-year increase of 17.1%
Source: INS
Key Economic Indicators: 2009
GDP 2009: RON $ 463 billion= Euro 109billion
GDP is expected to decrease in 2009 by8.1% compared to the previous year
GDP per capital: Euro 4954
Inflation: expected decrease from 7% in2008 to average 6.3% in 2009
Unemployment: 6.8% estimated for2009
FDI: down by 42.9% in H1 2009
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Market in Economic Context 2008:IT Spending Ratios
Source: IDC, 2008
Lithuania
Greece
Estonia
PortugalLatvia
Poland
SlovakiaSlovenia
IrelandSpain
Czech Republic
Hungary
Italy
EU-15
0.8%
1.0%
1.2%
1.4%
1.6%
1.8%
2.0%
2.2%
2.4%
2.6%
2.8%
0 200 400 600 800 1,000
IT Spending/Capita ($ per year)
ITSpend
ing/GDP
Romania
Bulgaria
Turkey
FYROM
Serbia
Montenegro
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70%
18%
12%
Romania Total IT 2008US $2678,03 million
Romanian IT market in CEE Context
Source: IDC Black Book Q3, 2008
64%
23%
13%
CEE Total IT 2008US $62529,61 million
5,000
15,000
25,000
35,000
45,000
55,000
65,000
75,000
85,000
2007 2008 2009 2010 2011 2012 2013
-25%
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20%
25%
Total IT Market Hardware totalPackaged software total Services total
Total IT
500
900
1,300
1,700
2,100
2,500
2,900
3,300
3,700
2007 2008 2009 2010 2011 2012 2013
-40%
-30%
-20%
-10%
0%
10%
20%
30%
40%
Total IT Market Hardware total
Packaged software total Services total
Total IT
Forecast 2008-2013 Forecast 2008-2013
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Why did companies struggle despitehaving implemented BI?
The crisis hit so rapidly!
BI systems were focused on past performance with no
forecasting capabilities Companies underestimated the extent of slowdown
Companies initially did not believe the data and forecasts
Companies management (they are gone now) did not reactproperly to the data from BI systems (overconfidence,neglection)
Companies did see the doom coming, but we reacted in awrong way
Compared with other companies in their vertical somecompanies did well-BI helped make right decisions on time
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Questions to answer
Did we have enough data to make right decisions?
Did we have data good enough to make right decisions?
Did our systems support data and information based
forecasting? Did we assess past decisions to find mistakes?
Did we gather all knowledge existing in the company neededfor making the right decision?
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Key issues
Data quality
Pervasive BI
Knowledge base
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IDC Survey: Collaborative decisions
Users are NOT satisfied with the technologies supporting decision making
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IDC Survey: Collaborative decisions
Users are NOT satisfied with the technologies supporting decision making
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Decision types
Strategic decisions scope of decision: broad
number of decisions: low
level of uncertainity: high
level of collaboration: high
degree of automation: low
Operational decisionssomething in between
Tactical decisions scope of decision: narrow
number of decisions: high
level of uncertainity: low
level of collaboration: low
degree of automation: high
We willdiscontinue to
produce SUVs
10% discount can begranted when you are
buying two cars
We will start offeringpromotional version with
free AC in Poland
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Limitations of traditional BI as a decisionsupport
No access to all relevant information (data centric)
Not enough support for real-time monitoring, alerting, messaging
No support for collaboration
No documentation of lessons learned
DW and BI is not enough!
Additional requirements:
Predictive analysis tools
Multidimentional analysis tools
Search tools
BPM and BAM
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Four solutions that fill the gaps
Collaborative analysis and planning
Knowledge capture and learning
Unified access and analysis of structured data and unstructured content
Intelligent process automation
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Collaborative analysis and planning
Only 4.4% of respondents are very satisfied with collaborationtechnologies supporting decision making
Multiple, disconnected apps needed to accomplish informationanalysis and sharing is frustrating for 47% of respondents
--------------------------------------------------------------------------------------
SOLUTION:
Sharing information in the context of the application
Discussion wikis
Polling, ranking, tagging, annotating
Instant messaging
Searching
Source:/Notes:
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Knowledge capture and learning
Only 5% of respondents indicated that outcomes of decisions
are documented very frequently
Learning from experience is a key for more productive decisions
---------------------------------------------------------------------------------------SOLUTION:
Metadata constructs that allow defining decisions and relatedevents coupled with search tool enabling queries by relevantevents and/or decisions
Source:/Notes:
U ifi d A A l i d
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Unified Access, Analysis andManagement of Information
Software tools and applications are segregated to handleeither structured data or unstructured content
Users got used to the situation, but would appreciate solutionthat would merge both worlds
-----------------------------------------------------------------------------------
SOLUTION:Creation of an extended, semantic index rich enough to capturemeaning from both content and data*
Key requirement: ability to capture meaning of data andinformation in a form that can be represented within the structuresupporting the access.
* End to end solutions for unified access, analysis and management of information arestill in the early stage of development
Source:/Notes:
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Intelligent Process Automation
There is no need to make repeatable, tactical decisions whenthey can be automated
Analytics should drive the workflow in those cases
-----------------------------------------------------------------------------------
SOLUTION:
Business Activity Monitoring inspects the flow of transactionssending alerts when defined threshold, pattern or condition isobserved.
Predictive models evaluate decision alternatives and make
optimized recommendations.
Source:/Notes:
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Essential Guidance
Think about expanding your BI environment to better supportdecision makers
Make BI more pervasive to influence more corporate decisions Eliminate the disconnect between technical users and decision
makers
IT systems can only SUPPORT decision makers
Support collaboration
Track and monitor decisions
Capture best practice process for decision making