Communication lors de la 1ère conférences ICTTA, Damascus, Syria, April, 2004

1. Strategic Decision Support Systems
Design: Integration Approach
Between Expert Knowledge and
Historical Data
Abdessamed Réda GHOMARI
LMCS « Laboratoire Méthodes de Conception de Systèmes»
INational Institute of Computer Science
BP 68M, Oued Smar, Algiers, Algeria.
Email: a_ghomari@ini.dz

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Content
Research direction
DSS
Knowledge acquisition
Combined Approach
Conclusion

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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-University
Toulouse1 UFR computer science)

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DSS: Definitions
Turban defines DSS as
“an interactive, flexible, and adaptable
computer-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.”

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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 DSS
support and improvement of decision
making

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DSS: Taxonomy
There is no all-inclusive taxonomy
of DSSs.
Different authors propose different
classifications.

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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 on
a individual manager’s PC.
At user level, hattenschwiler 1999
Passive DSS
Active DSS
Cooperative DSS

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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)

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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

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Strategic decision making:
Generic Structure
Dichotomy between
Internal Information
External information

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SDSS: Architecture
SCM
External know ledge
K now ledge
M odels
Internal
K now ledge
D ecision-m aking
support
K now ledge
M odels
SC M
SCM: Strategic Corporate Memory or Business Memory

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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…

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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.

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Knowledge acquisition:
multi-sources
Documented (books, manuals, etc.),
Undocumented (in people's minds),
from Databases,
via the Internet.

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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

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Automatic method: KDD

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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-posteriori
paradigm where data are already stored
and easily available.

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Combined Approach:
characteristics
Generic Approach with 3 points:
Strategic decisional Process
Decision Support System
Information Systems support

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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

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Combined approach
Knowledge
Data
base
KDD
process
ExpertsCorporate
Knowledge
Memory
New items New items
DW
process
1
2
2
Decision Makers
Ad hoc
Requests
Data
base
Decision making
support
Models
3 4
1

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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