1. Business Friendly
Data Mining
James Taylor
CEO

2. Your presenter – James Taylor
CEO of Decision Management Solutions
Works with clients to improve their
business by applying analytic technology
to automate & improve decisions
Spent the last 9 years championing
Decision Management and developing
Decision Management Systems
©2012 Decision Management Solutions 1

3. Data Mining and Predictive
Analytics WORK
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4. Success Requires A Clear Target
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5. Success Requires Deployment
?
? Decision
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6. Success Requires Collaboration
Business
Decision
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7. Business-Friendly
Data Mining

8. Decision Management is the
proven approach used to
manage decisions, set goals
for predictive analytic
efforts, apply and deploy
predictive analytics
effectively
©2012 Decision Management Solutions 7

9. Step 1
Be clear which decisions
you are improving
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10. A Decision
A choice or selection
Based on facts
That ends
uncertainty
And results in action
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11. Discover High ROI Decisions
Risk decisions Customer decisions
How risky is this deal How profitable might this
and what should we do? customer be?
Predict risk of a bad Predict response,
outcome opportunity, potential
Rigorous, regulated Rapidly evolving
Fraud decisions
How likely is this to
be fraudulent?
Predict risk of fraud
“Black box”
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12. Use Questions to Define Decisions
For each decision
Name
Description
Question and a defined set of allowable answers
Any other results to be returned with the answer
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13. Step 2
Understand how those
decisions impact the
business
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14. Target Decision-making On KPIs
Strategy defines KPIs
KPIs measure operations
Operational decisions affect
KPIs
The link between decisions
and KPIs is critical
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15. Define The Business Context
Key Performance Business Processes
Indicators What processes does this
How is success measured business execute?
in this business area? Which business processes
How to tell good decisions will need decisions made?
from bad ones and the
value of focusing on a Business Events
decision What key business events
trigger business behavior?
Organizations When will decisions be
What is the basic required and in what
organization structure context
Teams, departments, Existing Systems
groups not individuals
What are the core systems
Who cares about the for this business area?
decisions
How will you have to
deploy decision making?
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16. Put Analytics In Context
Processes Know which business
Activities require decisions processes will be
improved by your
analytics
Events
Trigger decisions Know when your
analytics might be
Systems calculated
Implement decisions
Know how you will have
Organizational Units to deploy your analytics
Make decisions
Own decisions Know who cares about
Are impacted by decisions your analytics and who
will have to believe them
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17. Step 3
Decompose decisions to
understand them
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18. Decompose the decisioning
What is required to make decision?
Guidelines, policy documents
Human expertise
Regulations
Existing system logic
Data describing the case
External reference data
Predictive Analytic Models
Data Mining Results
The results of other decisions
©2012 Decision Management Solutions 17

19. Case study: Insurer
Business challenges Solution Benefits
Use analytics to Model and Find the decisions
improve decompose that could be
underwriting decisions impacted and
Map decisions to refocused analytic
Embed analytics in effort
claim processing systems and
application organizations Constrained
analytic effort to
ensure successful
implementation

20. Decision Models Are Revealing
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21. Decision Models Are Revealing 2
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22. Step 4
Deploy analytical decisions
to the systems and
processes that need them
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23. Build decision-making components
Operational
Systems
Decision
Analytic
Systems
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24. Create Decision Management Systems
Agil
e
Analyti
c
Adaptiv
e
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25. Questions?

26. Takeaways

27. Decision Management
Establishes a clear target
Enables rapid deployment
Creates a collaboration framework Business
Decision

28. Thank You
James Taylor, CEO
jtaylor@decisionmanagementsolutions.c
om