Strategic Decision Support Systems Design: Integration Approach Between Expert Knowledge and Historical Data

Abdessamed Réda GHOMARILMCS « Laboratoire Méthodes de Conception de Systèmes»

INational Institute of Computer Science

BP 68M, Oued Smar, Algiers, Algeria.Email: a_ghomari@ini.dz

ICTTA'04 April 19-23, 2004 2

Content

� Research direction

� DSS

� Knowledge acquisition

� Combined Approach

� Conclusion

ICTTA'04 April 19-23, 2004 3

Research Direction

� The research work focuses on Strategic Decision support systems design� Decision = Knowledge

� Information systems: source for DSS

� Experience:

� CMEP Project (collaboration I.N.I-UniversityToulouse1 UFR computer science)

ICTTA'04 April 19-23, 2004 4

DSS: Definitions

Turban defines DSS as

“ an interactive, flexible, and adaptablecomputer-based information system, especially developed for supporting the solution of a non-structured management problem for improved decision making. It utilizes data, provides an easy-to-use interface, and allows for the decision-makers own insights.”

ICTTA'04 April 19-23, 2004 5

DSS: Definitions

� DSSs belong to an environment with multidisciplinary foundations, including (but not exclusive) � database research, � artificial intelligence, � simulation methods, � human-computer interaction, � software engineereing and telecommunications

� Central Issue in DSSsupport and improvement of decision making

ICTTA'04 April 19-23, 2004 6

DSS: Taxonomy

There is no all-inclusive taxonomy of DSSs.

Different authors propose different classifications .

ICTTA'04 April 19-23, 2004 7

DSS: Taxonomy � At the conceptual level , Power 1997

� Communication-Driven DSSs,

� Data-Driven DSSs,

� Document-Driven DSSs,

� Knowledge-Driven DSSs

� and Model-Driven DSSs.

� At the technical level , Power 2000

� Entreprise-wide DSS : linked to large data warehouses and serve many managers in a company.

� Desktop single-user DS: small systems that reside o n a individual manager’s PC.

� At user level , hattenschwiler 1999

� Passive DSS

� Active DSS

� Cooperative DSS

ICTTA'04 April 19-23, 2004 8

DSS: Other taxonomy

� Institutional DSS: � decisions of a recurring nature

� Ad Hoc DSS: � specific problems that are usually neither

anticipated nor recurring

� Personal, group, and organizational support

� Individual versus group support systems (GSS)

ICTTA'04 April 19-23, 2004 9

DSS: Components

1. Data Management Subsystem (DMS)

2. Model Management Subsystem (MMS)

3. Knowledge-based (Management) Subsystem (KMS)

4. User Interface Subsystem (UIS)

5. The User

ICTTA'04 April 19-23, 2004 10

Strategic decision making: Generic Structure

� Dichotomy between� Internal Information

� External information

ICTTA'04 April 19-23, 2004 11

SDSS: Architecture

SCM

External know ledge

Know ledge

Models

In ternal Know ledge

Decision-making

support

Know ledge

Models

SCM

SCM: Strategic Corporate Memory or Business Memory

ICTTA'04 April 19-23, 2004 12

Corporate Memory

� CM content covers various fields.

� In the Literature, CM content are:� product requirements,

� project tasks and planning,

� human expertise involved, � resources used,

� project cost elements and structure,

� monitoring and control supports,

� electronic documents and reports,

� design rationales, � lessons learned…

ICTTA'04 April 19-23, 2004 13

Knowledge acquisition: step of Knowledge management

A company produces goods or services, and, in the process, also produces knowledge .

Knowledge management(KM): great importance for companies.

KM objectives : to promote knowledge growth, communication and preservation in an organization and from a business point of view, to produce better business, competitive gain and greater profits.

ICTTA'04 April 19-23, 2004 14

Knowledge acquisition: multi-sources

� Documented (books, manuals, etc.),

� Undocumented (in people's minds),

� from Databases,

� via the Internet.

ICTTA'04 April 19-23, 2004 15

Knowledge acquisition: Methods

Three categories of K.A methods [16]

� Manual:� Interviewing (Structured, Semistructured,

Unstructured)

� Tracking the Reasoning Process

� Observing

� Semiautomatic:� Support Experts Directly

� Automatic (Computer Aided)� Expert’s and/or the knowledge engineer’s roles are

minimized (or eliminated)

� Induction Method

ICTTA'04 April 19-23, 2004 16

Automatic method: KDD

ICTTA'04 April 19-23, 2004 17

KDD: « data-pushed approach»

� Knowledge management is often investigated through knowledge discovery in data (KDD), using raw data mining and algorithms tools [7].

� This approach operate on an a-posterioriparadigm where data are already stored and easily available.

ICTTA'04 April 19-23, 2004 18

Combined Approach: characteristics

� Generic Approach with 3 points:� Strategic decisional Process

� Decision Support System

� Information Systems support

ICTTA'04 April 19-23, 2004 19

Aggregated K: an expertise

Relative importance of the 2 classes

� Repetitive Environment� Experts Knowledge: low

� Historical Knowledge : high

� Non repetitive Environment ( case: Strategic DSS )� Experts Knowledge: high

� Historical Knowledge : low

ICTTA'04 April 19-23, 2004 20

Combined approach

Knowledge

Database

KDD process

Experts Corporate Knowledge Memory

New items New items

DW process

1

2

2

Decision Makers

Ad hoc Requests

Database

Decision making support

Models

3 4

1

ICTTA'04 April 19-23, 2004 21

Conclusion

� Combined Approach Advantages� Enhanced use or Knowledge reuse pull

approach� Company referential building� Contribution to Improve strategic decision

making

� Application� New CNEPRU projet 2004-2008 at LMCS INI

algiers “Platform for Environmental risks management in industrial projects”

� method � Strqtegic DSS