Jean-Louis ERMINE

Knowledge Management

CASE STUDIES

•Objectives :

Increase the competitiveness of the glass float plants sold all over the world

•Actions :

Knowledge Capitalisation (from interviews and modelling) with the best experts (the european «Glass Masters»- generally retired), validation of the delivered Knowledge Books by international workgroups

•Results :

Integration of the know-how (on supervision, diagnosis ...) in the quality system of the float plant (SMQF : Système de Maintenance de la Qualité du Float)

The SMQF Project

Saint-Gobain Vitrage

1998 -

•Objectives :

Transfer to newcomers the know-how of the best experts in personal loans (Five levels of expertise with long training periods, very fast acceleration of recruitment)

•Actions :

Knowledge Book on personal loans built with the seven best experts, rationalization of their practice, realization of a decision support system based on the Knowledge Book

•Results :

Operational DSS on line, time reduced for accepting or rejecting a file, training period for new comers highly reduced (roughly from 6 months to 3 days for the first level), risk analysis, ROI and audit on the THOT system have been performed in COFINOGA

The THOT Project

COFINOGA (one of the first financial institution in France)

1996-1998

•Objectives :

Guarantee the credibility and the reliability of the nuclear warheads of the French nuclear deterrence, after the test ban treaty

•Actions :

A strategic KM plan, including knowledge preservation (with MKSM) of rare experts and specialists on specific topics involved in design and realisation of nuclear warheads

•Results :

More than 10 pilot projects of Knowledge Books in five centres, 3 training sessions and coaching on Knowledge Engineering for internal appropriation, KM projects are now being done by CEA/DAM people themselves

The CEC Project (Conservation et Exploitation des Connaissances)

Military Application Division (DAM)

(CEA, French Atomic Energy Commission)

1996-2002

•Objectives :

Deliver to the industrial operator (COGEMA), the knowledge accumulated during the R&D phase (300 people, 10 years, 100 M$/year) on a new process for uranium enrichment, useful to design the industrial plant (to be operational in 2005-2006)

•Actions :

Knowledge Engineering project (interviews, modelling …) involving more than 120 experts

(for interviews and validations of the Knowledge Book) during two years

•Results :

A Knowledge Book of more than 2500 pages, with an electronic version, indexing a great part of the documentation of the project (5 GO), delivered on time to COGEMA with the industrial prototypes and the Process Book

The LCS Project (Livre de Connaissances SILVA)

Fuel Cycle Division (DCC)

(CEA, French Atomic Energy Commission)

1997-1999

•Objectives :

Share the scattered knowledge on optical system design within a department,

Build a knowledge repository to communicate with other departments involved in the design process, according to the process models

•Actions :

Capitalise the knowledge in the optics department, build consensual knowledge to be exchanged with others design units

•Results :

Knowledge Books of different units put in a common repository (Intranet Knowledge Space)

Thomson CSF Optronics

1999

• Corporate Knowledge, a strategic issue

• Setting up a Knowledge Management Approach

• The Knowledge Management processes

InvestmentHuman resources

+

Product/Service

Intellectual Capital

?

KNOWLEDGE AS A NEW TYPE OF VALUE

ECONOMIC VALUE OF KNOWLEDGE

• The value of Entreprises (market value, merger, acquisition, introduction to market...) relies increasingly on the valuation of intangible assets amongst which is Knowledge

Paul Strassmann («Knowledge Strategist»), according to his survey of 359 industrial Companies in the States, estimates that the value of their knowledge capital corresponds to 217 % of their net financial capital

There are methods and criterias to evaluate and manage this capital (ex : the Skandia Navigator)

KNOWLEDGE IS A PRODUCTIVE RESOURCE

• Innovative ways of working are emerging ( «Knowledge Workers») which rely more on Knowledge, Know-how and mobilized experience than on the qualifications required for pre-defined tasks

Work productivity is no longer related only to material investments and to work forces on pre-defined tasks ; there is now a concept of « knowledge productivity »

Knowledge is now seen as a strategic productivity resource

To face a non predictable environment, the enterprise must rely on its Corporate Knowledge Capital

KNOWLEDGE AS A STABILITY FACTOR

Dynamic production environment

Reactive & evolutive knowledge

Expansion of possible processes

Static production environment

Production process knowledge stable and

homogeneous

Restricted number of production

configurations

Stable Configuration « Chaotic » Configuration In a chaotic environment the Enterprise is either puzzled by the changes

Or...

CONTROLS THEM

Knowledge as a decisive competitive element

Production system

Product

Quality system

Good product

Knowledge Management

system

Best possible product

Production Management

Quality Management

Knowledge Management

• Corporate Knowledge, a strategic issue

• Setting up a Knowledge Management Approach

• The Knowledge Management processes

Knowledge is an element of Strategic Management

Know where we have come from and where we are in order to know where we go

Switch fromindividual

intelligenceto collectiveintelligence

Develop andinnovateto survive

Capitalise Share

Create

3 CHALLENGES

GLOBALAPPROACH

• Capitalise

• Share

• Create

OPERATIONALAPPROACH (TOOLS)

• Intranet

• Extranet

• Internet

• Etc...?• What is our

Knowledge capital ?

• How to manage it in the organisation ?

INFORMATION

OVERFLOW

PATRIMOINE DES

CONNAISSANCES

KNOWLEDGE

CAPITAL

Information Capital :

Existing information (documentation, archives, Information System)

Knowledge Workers Network

KNOWLEDGEMANAGEMENT

PROJECT

KNOWLEDGE

CAPITAL

STARTINGPOINT

PATRIMOINE DES

CONNAISSANCES

KNOWLEDGE

CAPITAL

Knowledge Workers Network

Tacit Knowledge

Knowledge Engineering

Change Management

CRITICAL KNOWLEDGE

CAPITAL

STARTINGPOINT

KM SCOPE :What is the objective ?Where is the correspondingcritical knowledge ? How toreach the best leverage ?

Knowledge

Servers

Knowledge Based

Systems

( EXPLICIT )

Information Capital Hidden Knowledge

Knowledge Extraction (KDD)

Elicitation

Elicitation

PATRIMOINE DES

CONNAISSANCES

KNOWLEDGE

CAPITAL

Knowledge Workers Network

Tacit Knowledge

Knowledge Engineering

Structural Capital

Change Management

CRITICAL KNOWLEDGE

CAPITAL

STARTINGPOINT

KM SCOPE :What is the objective ?Where is the correspondingcritical knowledge ? How toreach the best leverage ?

Knowledge

Servers

Knowledge Based

Systems

( EXPLICIT )

Hidden Knowledge

Knowledge Extraction (KDD)

Elicitation

Elicitation

Needs• Re-use the concepts of existing factories• Work collectively wherever the geographical position

of groups

Solution• Introduction of excellence centers• Experts summarize their data in best practices

- Lotus Note on Intranet• Institution of a new retribution approach

Benefits• Major decrease of production delays and costs on

new sites• 5 Billion $ growth in market share

PATRIMOINE DES

CONNAISSANCES

KNOWLEDGE

CAPITAL

Knowledge Workers Network

Tacit Knowledge

Knowledge Engineering

Structural Capital

Change Management

CRITICAL KNOWLEDGE

CAPITAL

STARTINGPOINT

KM SCOPE :What is the objective ?Where is the correspondingcritical knowledge ? How toreach the best leverage ?

Knowledge

Servers

Knowledge Based

Systems

( EXPLICIT )

Hidden Knowledge

Knowledge Extraction (KDD)

Elicitation

Elicitation

Needs• Automatisation of cabins design

Solution• Knowledge modelling and creation of an interactive

configuration software

Benefits• Crossing of technological gaps• Production increase at constant strength ; pre-project

realization delays divided by 9

• Corporate Knowledge, a strategic issue

• Setting up a Knowledge Management Approach

• The Knowledge Management processes

Environment

The KM processes

Selection

CapitalisationAnd

Sharing

Learningand

Creation

External Processes Internal Processes

Environment

Interaction

Knowledge Capital

Evaluation

• Corporate Knowledge, a strategic issue

• Setting up a Knowledge Management Approach

• The Knowledge Management processes

• Capitalisation and Sharing• Interaction• Learning and creation• Selection

TacitKnowledge

TacitKnowledge

Explicit Knowledge

Explicit Knowledge

Elicitation(allows dissemination)

SocialisationDirect Transfer

Appropriation(allows efficiency

gains)

Sharing

The Knowledge Cycle

TacitKnowledge

Explicit Knowledge

Explicit Knowledge

The Knowledge Cycle

Indirect Transfer

Knowledge Books

Direct Transfer

Coaching,Workgroups,

COP, COIN ...

NTIC

TrainingExperimentation ...

Knowledge Books,Knowledge Acquisition …

TacitKnowledge

Supervision

Technological Surveillance

Configuration

Decision Support Systems

Customer Relationship Management

Quality ManagementKnowledgeCapital Intelligent documentation

Training, Knowledge Transfer

Knowledge Servers

Knowledge Book

The Knowledge Book MethodologyFor Indirect Knowledge Transfer

Example

Knowledge Models

Documentation ReferencesFiling System

(descriptive, scientific ...)

Pictures videos ...

Plans,documents ...

KnowledgeBook

Example

Information : Data

Flour :

Available quantity (Kg)Suppliers

Eggs :

Available quantity (Integer)Date laid (dd/mm/yy)Suppliers

Milk :

Available quantity (l)Type (skimmed, half-skimmed, full cream)SuppliersEtc ...

Oven :

Operating temperature (°C)preheating time (mn)Width (cm)Etc ...

Pastry :

Cooking time (mn)Quantity of flour (g)Number of eggs (Integer)Etc ...

Example

Information : Data Processing

Stocks management :

If available quantity of flour is < n kgThen Choose a supplier

and Place an orderWhile Order is not completed

Contact the supplierRecord new available quantityEtc ...

Oven process control :

Start the oven heatingAs soon as the preheating time is overLet during the given heating timewith the operating temperatureEtc ...

Pastry recipe :

Mix the quantity of flour and the number of eggsAdd the quantity of milkEtc ...

Example

Semantic Networks

Pastry

Pie Pastry Baker's dough Cake pastry

Biscuit pastry Choux pastryBread dough Bun doughFlaky PastryShort PastryShortcrust Pastry

UnsweetenedShortcrust Pastry

SweetShortcrust Pastry

ExpressFlaky Pastry

ClassicalFlaky Pastry

For rissoles, tartessalées, tourtes,

croustades and pâtés

For the tartes pâtissières

Example

Cognitive Tasks

Make a bread dough

Cook the

dough

Special

bread

Put the flour

in a big bowl

Put aside

200g of flour

Make a well

in the flour

Disolve the

baker's yeasts

Add slightly

salted water

Knead the

dough

Flour your hands

frequently in the

reserved flour

Make the

balls

Wrap the ball

in a floured clothe

for 11/2 hour

Knead the

dough again

Add the other

ingrédients:

olives, nuts, etc...

OK

Normal

bread

Example

- Flour

- Eggs

- Milk

- Butter

- Water

- Salt

- Sugar

Good knowledge

of ingredients

- Bowl

- Hands

- Kitchen tools

Pastry

Refrigerator

(fresh place)

Rested pastry

- Mould

- Rolling pin

- Special plate

Baker’s

Know how

Pastry ready to cook

- Oven

- Cooking

tools

- Knowledge on

cooking process

- Knowledge on

observed symptoms

Cooked pastry

Preparethe Pastry

Restthe Pastry

Shapethe Pastry

Cookthe Pastry

Example

Activity Model

Domain Model

Shortcut pastry :

Kneading the dough makes the particle of flour, which are coated in fat, sufficiently impermeable to the steam released by the cooking process. In trying to escape, the steam exerts a pressure on the dough which expands slightly, just enough to stay thin and crusty

....

Flaky pastry :

The method consist in enclosing, by a series of folds, layers of butter and air between layers of moist flour. In the cooking process, in trying to escape, the steam pushes up horizontally the strata of the dough, sealed by the butter

....

Example

Domain Model

- Type of flour- ...

- Release of steam- Slight expansion

Particules coated in fat

Shortcut pasteFlow :Steam

Source Target

Trigerring event :- Kneading- Cooking

Consequence:Thin and crusty paste

Influences

Example

Some organisations using Knowledge Book Methodologies(since 1993)

CEA (projets CEC, LCS, ...)

COFINOGA

EDF

DCN

TECHNICATOME

SAINT GOBAIN

SEP

THOMSON CSF

FRAMATOME

LA POSTE

RHÔNE-POULENC

PSA

ONERA

INRS

CABINET PLENITUDES, IRSO (SMEs)

GAZ DE FRANCE

ERNST & YOUNG

HYDROQUEBEC ...

Example

• Corporate Knowledge, a strategic issue

• Setting up a Knowledge Management Approach

• The Knowledge Management processes

• Capitalisation and Sharing• Interaction• Learning and creation• Selection

EnvironmentKnowledge Capital

Projection

Distortion Identification

Knowledge

Integration

Relevant FeedbackRepresentation

The interaction process between Knowledge Capital and Environment (Business Intelligence, Technology Watch)

EnvironmentKnowledge Capital

- Filter, profile, query,

- Watching Groups

- IR tools,

-Distributed interpretation

for weak signals discovery

- IR tools

- Signal analysis

Statistics and

linguistic tools

Indirect

Reformulation

?

The interaction process between Knowledge Capital and Environment (Business Intelligence, Technology Watch)

Source : F. Rousseau, CEA

An example of Knowledge Modelling in a process of interaction K-ETechnology Watch on « Instrumentation in nuclear reactors »

Ultrasonic sensors in reactors

[ ultrasonic NEAR ( sensor? OR transducer? OR detector? OR device? OR probe? OR array )OR [ ultrasonic NEAR ( image? OR echograph? OR endoscop? OR camera? )NOT ( biomed? OR medecine OR medical) ] ] AND ( reactor OR nuclear )]

Direct formulation of the problem (classical methodology)

Creation of a diphasic part

Primary circuit water

Detection of a diphasic part

Instrumentation of detection

Existing bubblesPressure decreasing

- Reactor supervision- detection of a incidental functioning

Flux : Bubbles - Ultrasonic sensors- ...

Indirect reformulation of the problem

Knowledge modelling for representing effects to instrument

Example

Physical or chemical effects to detect

Source of the effect

Kind of measurement to be done

Instrumentation

Constraints forthe action

Triggering events Objectives of measurement

Flux

Objectives of the system

Implied physical effects

Technologies of the system

Complex system

of measure

- Mechanics (Aging…)- Thermo hydraulics- Neutronics- ...

- Signal processing- Transmission

- Sensors, detectors- ...

- Reactor supervision- Safety mastering

- Fault diagnosis- ...

Synthesis of models and determination of axis of information retrieval

Source : F. Rousseau, CEA

Example

Objectives of measures

Knowledge on physical effects

Technology of measure

Complex system of measure

Emerging of new way to instrumentEX : Modelling of fluxin diphasic case

Emerging of new applications for known technologiesEX : Use of optic fibres in strongly irradiated ambiance

Emerging of new needs for sensorsEx. :- Research programs (reactors of the future, RJH, RES, REP 2000,…)- Return on experience on incidents- Increase of Nuclear Power Plant life time

Emerging of new Knowledge

Source : F. Rousseau, CEA

Example

• Corporate Knowledge, a strategic issue

• Setting up a Knowledge Management Approach

• The Knowledge Management processes

• Capitalisation and Sharing• Interaction• Creation• Selection

Environment

Environment

Knowledge

Capital

The innovation process

TRIZ,

Créativité

?

CAUTIC,

BCG,

Marketing,

CRM

?

Evolutionist hypothesis :The innovation process includes a process of evolution of the Corporate Knowledge Capital(Evolution is based on the « genetic capital»)

« Path dependency » hypothesis :The evolution of the Corporate Knowledge Capital is determined by its former evolutions(Past evolutions guide future evolutions)

Two fundamental hypothesis

Capitalisation of the history of ideas:- Describe the evolution of the system which has ledthe company to innovate on its concepts - Describe the genealogy of the innovative solutions designed through time.

Analysis of the story of innovations in the company and propositions :- Discovering of the « evolution laws » that were pre-eminent - Discovering of « innovation pits » and possible innovative path.

Knowledge Engineering for Innovation

Example

OPEN QUESTIONS