AN EXPERT SYSTEM FOR SUPPORTING STRATEGIC BUSINESS DECISIONS

İlter İrdesel, Gürdal Ertek, Neslihan Beyhan

Faculty of Engineering and Natural Sciences, Sabanci University, Orhanli, Tuzla, 34956, Istanbul, Turkey

ilterirdesel@su.sabanciuniv.eduertekg@sabanciuniv.edu

nbeyhan@su.sabanciuniv.edu

OUTLINE• Project summary• Methodology

Stage 1: Knowledge extractionStage 2: Mind MapStage 3: Domain Objects Map (DOM)Stage 4: Rule Map (RM)Stage 5: Java implementation

• Unique aspects of the system• Future work• Conclusion

• Popularity of mind maps

• What did we develop?

A multi-stage methodology that generates rule-based

expert system from a mind map

PROJECT SUMMARY

• Importance of strategic issues compared to decisions

at tactical and operational levels

• Extracted knowledge

- Extensive researches of business thinkers based on strategic

issues in the real world

- Printed and online media

- Interviews with domain experts

• Extension of this knowledge by generating ideas

through brainstorming.

STAGE 1: KNOWLEDGE EXTRACTION

• Adrian Slywotzky, a director at Oliver Wyman

• Profit Patterns, presenting 31* profit

patterns and numerous leading scenarios related

with central business-oriented objects (channel,

customer, value chain, product, industry, knowledge and

organization)

* Downstream has been added after the book waspublished as the last pattern

STAGE 1: KNOWLEDGE EXTRACTION

Figure 1: Knowledge form of Knowledge to Product pattern

STAGE 1: KNOWLEDGE EXTRACTION

• Freemind software

• Decision tree structure

• Starting from centre with profit patterns and are

branched out with business-oriented objects, object

attributes and attribute values in hierarchical order

• Standardized symbols and icons

STAGE 2: MIND MAP

STAGE 2: MIND MAP

Figure 3: Decision Tree Representation of Knowledge to Product pattern by using FreeMind

• In order to let managers and investors make

object-oriented investigation

• Domain objects (business-oriented objects)

at the root node of the tree

• Suggestions (profit patterns) at the leaf nodes of the tree

STAGE 3: DOMAIN OBJECTS MAP (DOM)

STAGE 3: DOMAIN OBJECTS MAP (DOM)

Figure 4: Knowledge to Product portion of product in Domain Objects Map

• Visirule software

• Visual node&arc-based model of the business rules

generated from a mind map

• Elements used in the model (Start box, question box, input

box, continue box, finish box)

• Implementation of the logic operators

• Modular structure (use of continue boxes)

• Generated Flex and Prolog codes for the decision support.

STAGE 4: RULE MAP (RM)

STAGE 4: RULE MAP (RM)

Extra figure 1: Representation of the logic and elements usedin Rule Map implemented through the Visirule software

STAGE 4: RULE MAP (RM)

Extra figure 2: Implementation of the OR operator used in Rule Map generated from related mind map

STAGE 4: RULE MAP (RM)

Extra figure 3: Implementation of the AND operator usedin Rule Map generated from related mind map

STAGE 4: RULE MAP (RM)

Figure 6: Generated Flex code of object-based investigation in knowledge category

• Generated from the Visirule map

• User interface, including four windows:

- Occupation window, asking the user his/her name,

surname and occupation

- Main window, representing the menu for category

(module) selection

- Question window, asking questions and getting

the answers as input

- Suggestion window, listing all the suggestions

given for individual module

• A special logic to give suggestion (a critical ratio)

STAGE 5: JAVA IMPLEMENTATION

Activity Diagram of the Java code

STAGE 5: JAVA IMPLEMENTATION

Extra figure 4: Occupation window of the Java application interface

STAGE 5: JAVA IMPLEMENTATION

Figure 8: Category selection window of the Java application interface

STAGE 5: JAVA IMPLEMENTATION

Figure 9: Question window of the Java application interface

STAGE 5: JAVA IMPLEMENTATION

Figure 10: Suggestion window of the Java application interface

STAGE 5: JAVA IMPLEMENTATION

Following version of Java implementation:

• Fuzzy logic extension

• Cumulative probabilities for multiple-choiced answers

(0, 0.17, 0.33, 0.5, 0.67, 0.83, 1)

• Updated form of category selection

(illustrated in Extra figure 5)

Activity Diagram of the followingversion of Java code

• Attractive features of our system for SMEs, such as increased

availability/accessibility, reduced cost and multiple expertise

• Being free of spending lots of money for consulting firms

• Big chance to benefit from world-wide

• Chance for the managers to test their knowledge with the

business gurus and business thinkers’ strategic ideas.

• Use of symbolic reasoning rather than numerical computation

• Concerning with the situations that might arise in business

platform and the action that can be done in these situations.

UNIQUE ASPECTS OF THE SYSTEM

UNIQUE ASPECTS OF THE SYSTEM

Extra figure 6: Use-case Diagram of the expert system

• Role-based interventions throughout the system

• Experts that are capable of each stage, collaborating

to create the system and updating it in later periods

• Parallel process among the stages

• Modifications by conflict resolutions

• Consistency-verification mechanism

UNIQUE ASPECTS OF THE SYSTEM

• An extreme case: A complex single software

in which all stage transactions are included

• Other related categories concerning the business world

(such as finance, marketing, etc.) can also be analyzed and

and added as new modules of the system

• Answers given from system users might be analysed to

have some knowledge about how strategic the managers

and investors are thinking. Visual analysis of the given

answers might be done.

FUTURE WORK

• Rapid generation of rule-based DSS from mind maps, consisting of business categories,

business-oriented objects and profit patterns as strategic solutions (Extra figure 7)

CONCLUSION

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