Transcript Presentation - Laboratory for Systemic Modeling LAMS

A Business Process-IT
Alignment Method for
Business Intelligence
Jun Sekine, Takashi Suenaga, Junko Yano,
Kei-ichiro Nakagawa, and Shu-ichiro Yamamoto
NTT Data Corporation
Copyright(C)2009 NTT DATA Corporation
Introduction

The concept of business intelligence (BI)
is to provide information for achieving
business goals.

The BI systems require business process
-IT alignment in order to provide
functionality useful for achieving the
business goals.
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Issues (1)

BI systems vary depending on the
maturity of target enterprises.
 Ex.
1: Visualization of KPIs and related data using
OLAP tools
 Ex. 2: Validation of hypotheses for achieving
business goals using data mining methods
KPI: Key Performance Indicator
OLAP: OnLine Analytical Processing
⇒We
need a business process-IT alignment
method for BI covering all the variations.
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What Is A Hypothesis?

A hypothesis is
 a written statement that may achieve
business goals (KPIs corresponding to effects).
 comprised of at least one causal factor (KPI
corresponding to causes) affecting the business goals.
Ex.
Outsourcing of parts of work of projects
improves profits.
Causal Factor
Control
Actions
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Business Goal
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Issues (2)

BI analysts need to convince enterprise
management that their proposed
hypotheses and actions are comprehensive
and rational.
⇒We need a kind of framework used to
clarify and organize the hypotheses and/or
the actions.
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Our Approach

A business process-IT alignment method
for BI
 with
two phase business processes for BI
 defining information that should be managed
by the BI systems
 covering four different levels of BI systems,
 with
a modeling process of the framework
 clarifying hypotheses and actions
 helping enterprise management understand
their target domains.
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Business Processes for BI ~ Phase 1
Phase 1
Extracts and
checks the validity
of hypotheses for
achieving business
goals.
Phase 2
Clarifies the actions
needed to
implement the
hypotheses for
achieving goals.
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1.Define
business
goals
2. Create
model
3.Extract
hypotheses
10.Improve
hypotheses
4.Choose
valid
hypotheses
9.Improve
actions
5.Choose
achievable
hypotheses
8.Monitor
actions
7.Execute
actions
6.List &
validate
actions
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2 Ways for Extracting Hypotheses (1)
2. Create
model
3.Extract
hypotheses
Extract hypotheses through interviews.
 Use a model for mapping the hypotheses
and checking their completeness.

Business
Goal
Model
Decrease the number of complaints of an electronic
apliance company it receives from service agents
Types of complaints were categorized by the business
tasks of selling products at service agents
Business Tasks
Planning
& preparation
Sales
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Service
ordering
Starting
service
Charging
Payment
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2 Ways for Extracting Hypotheses(2)
2. Create
model

3.Extract
hypotheses
Models are sometimes created automatically using data mining methods.
Ex. 1: Clustering customers based on their
purchase history.
 Ex. 2: Viewpoints of classifying profits,
such as the locations of branches or the
categories of products (These are usually
called “dimensions” in OLAP tools.)

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Business Processes for BI ~ Phase 1
Phase 1
Extracts and
checks the validity
of hypotheses for
achieving business
goals.
1.Define
business
goals
3.Extract
hypotheses
10.Improve
hypotheses
4.Choose
valid
hypotheses
9.Improve
actions
5.Choose
achievable
hypotheses
8.Monitor
actions
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2. Create
model
7.Execute
actions
6.List &
validate
actions
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Business Processes for BI ~ Phase 2
1.Define
business
goals
Phase 2
Clarifies the actions
needed to
implement the
hypotheses for
achieving goals.
Copyright(C)2009 NTT DATA Corporation
2. Create
model
3.Extract
hypotheses
10.Improve
hypotheses
4.Choose
valid
hypotheses
9.Improve
actions
5.Choose
achievable
hypotheses
8.Monitor
actions
7.Execute
actions
6.List &
validate
actions
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Choose Achievable Hypotheses
Ex.
The profits of franchise shops can be
increased by locating them near stations.
Business Goal
Causal Factor
(Distance from neaby station)
Moving existing
shops is impossible.
X
Actions
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Distribution of Data Analysis Cases
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Maturity Levels of BI
• Validate the
effectiveness of
actions.
Scope
Level 3:
Level 4:
Mgmt. of
actions
(Phase2)
Validation
of actions
Service
execution
Mgmt. of
KPIs
(Phase1)
Level 1:
Level 2:
Visualization
Data mining
• Visualize KPIs,
models.
• Validate
hypotheses.
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• Create new
services using
statistical
analysis, etc.
Functionality • Create models
Mgmt. of
info.
Creation of
decision
support info.
or hypotheses
using data
mining.
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Models

Frameworks for categorizing and
organizing hypotheses and actions, and
provide accountability for enterprise
management.
Three types of models:
 Type 1: Categorization of business objects
 Type 2: Description of relationships
among business objects
 Type 3: Description of business tasks
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Type 1: Categorization of Business Objects

Categorization of business objects (BOs)
that are the target of improvement.
Shops
Shops
in the suburbs
Shops
in downtown
Target
Ex. 1 Categorization of shops.
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Decrease medical expenses
Medical expenses
Increase the sales of shops
Cerebral infarction
Atherosclerosis
Hypertension
Target
Time
Ex. 2 Transition processes
between diseases.
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Type 2: Description of Relationships among BOs

Description of business goals, BOs
consisting of business environments, and
the relationships among them.
Increase the profit of each project
Organization
Employee
Employee
Employee
Profits (sales, costs..)
Project
Project
Project
Member
Member
Assign
Partner
Outsourcing
Hypotheses
A) High degree of
employee satisfaction
leads to large profits.
B) A certain number of
skilled managers is
necessary.
C) Proper outsourcing of
part of the work is
necessary.
Education (Skill) Employee Satisfaction
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Type 3: Description of Business Tasks

Description of business tasks that
enterprise management would like to
improve.
Decrease the number of complaints it receives from service agents
Planning
& preparation
Sales
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Service
ordering
Starting
service
Charging
Payment
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Conclusions

A business process-IT alignment method
for BI
 with
two-phase business processes,
 covering four different levels of BI systems.
 with
a modeling process,
 helping enterprise management understand
their target domains.
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Further Issues

It is not easy to reach levels 3 or 4. We
should start from levels 1 or 2, and then
proceed to the next levels.
 An education program

The types of models that are used in
different situations are yet to be
investigated.
 A catalog of modeling methods
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