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IKW - Innovative IKW - Innovative Knowledge Worker Knowledge Worker The Driving Role of The Driving Role of Industrial Researcher Industrial Researcher in SME Rising Trend in SME Rising Trend 30/11/2009 30/11/2009 Giovanni Mappa Giovanni Mappa [email protected] [email protected] WORKSHOP 30/11/2009 – “Sala Byte” Città della Scienza - Via Coroglio 57 - 80124 Napoli Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] Part Part 1 1

IKW - Innovative Knowledge Worker The Driving Role of Industrial Researcher in SME Rising Trend 30/11/2009 Giovanni Mappa [email protected] WORKSHOP 30/11/2009

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IKW - Innovative IKW - Innovative Knowledge WorkerKnowledge Worker

The Driving Role of Industrial ResearcherThe Driving Role of Industrial Researcherin SME Rising Trendin SME Rising Trend

30/11/200930/11/2009

Giovanni MappaGiovanni [email protected]@anova.it

WORKSHOP 30/11/2009 – “Sala Byte” Città della Scienza - Via Coroglio 57 - 80124 Napoli

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 1Part 1

ConceptsConcepts

Part 1:Part 1: A New and Emerging OccupationA New and Emerging Occupation……1.1 - The “WWW” of a IKW1.1 - The “WWW” of a IKW (why-who-where)(why-who-where)1.2 - The Knowledge Engineering Concept1.2 - The Knowledge Engineering Concept1.3 - Basic Rules of a Knowledge Worker1.3 - Basic Rules of a Knowledge Worker1.4 - The KICS Strengths1.4 - The KICS Strengths of a IKWof a IKW1.5 - Innovation Management and R&D 1.5 - Innovation Management and R&D (skills-team-organization)(skills-team-organization)1.6 - Communication of Innovation and R&D Project/Business Idea1.6 - Communication of Innovation and R&D Project/Business Idea

Part 2:Part 2: The IKW’s Tool BoxThe IKW’s Tool Box2.1 - Basic Tools2.1 - Basic Tools2.2 - General Tools2.2 - General Tools2.3 - Advanced Tools2.3 - Advanced Tools2.4 - Specialist Tools2.4 - Specialist Tools

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

IKW: a New and Emerging OccupationIKW: a New and Emerging Occupation…… a new way to work a new way to work to emerge from the to emerge from the

recessionrecession or or to stay aliveto stay alive in the World Wide in the World Wide Market Scenario?Market Scenario?

a new a new opportunity for Post-graduatesopportunity for Post-graduates?? a new a new opportunity for SMEopportunity for SME??

Something old, something new, Something old, something new, something better…something better… perhaps perhaps something for yousomething for you..

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

GlossaryGlossary

Worker:Worker: who contribute Value Added in joining Demand-who contribute Value Added in joining Demand-Offer’s Life Cycle…Offer’s Life Cycle…

Knowledge Worker KWKnowledge Worker KW:: Learning-focused Workers Learning-focused Workers skilled in Knowledge Engineering applications…skilled in Knowledge Engineering applications…– Knowledge EngineeringKnowledge Engineering:: KE is an engineering discipline that involves KE is an engineering discipline that involves

integrating knowledge into computer systems in order to solve complex integrating knowledge into computer systems in order to solve complex problems normally requiring a high level of human expertise problems normally requiring a high level of human expertise (1983, Edward (1983, Edward Feigenbaum, and Pamela McCorduck)Feigenbaum, and Pamela McCorduck)

IKW-Innovative KWIKW-Innovative KW: : interdisciplinary KW able changes in interdisciplinary KW able changes in

thinking, products, processes, or organizationsthinking, products, processes, or organizations … …

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

KW at a glance…KW at a glance…% Knowledge Worker/Total Worker

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

70,0%

80,0%

90,0%

100,0%

USA Australia Irlanda Belgio Italia Portogallo

Workers

KW

IKW

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

1.1 -1.1 - The “WWW” of a IKW The “WWW” of a IKW

IKW: Why?IKW: Why?

World Wide Market ScenarioWorld Wide Market Scenario Work Life Cycle Extension Work Life Cycle Extension Innovation Innovation essential driver for Competition essential driver for Competition Innovative Knowledge Worker Innovative Knowledge Worker Industrial Researcher ? Industrial Researcher ? How Industrial Researcher’s Skill is defined? How Industrial Researcher’s Skill is defined?

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

About 56% of Research and Technological Development Investment About 56% of Research and Technological Development Investment in the EU Member States ( R&D expenditure ) is funded by industryin the EU Member States ( R&D expenditure ) is funded by industry

IKW:Why? IKW:Why? Work Life Cycle Scenario Work Life Cycle Scenario (Extension) (Extension)

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

CareerStart -upYears

RetirementCompetitiveness

Work Life Cycle Work Life Cycle timetime

IKW Residual VA

Residual VA

IKW: Where?IKW: Where?

Value Added

WW Competition

VA = i / C i

WWC = Ki /A i

IKW

GlobalizationPre-Globalizationyears

Worldwide Market

Competition among companies is growing fastCompetition among companies is growing fast

To produce Value To produce Value Added is WinningAdded is Winning

Reduction of Reduction of production production

costscosts

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

IKW :Who?IKW :Who?

Performance

(Skill)

+ -

o 1 2

o

1

2

3

3

Negative Stress (-)

max

lim

Excellence

Normality

Optimality

Research & Innovation

Demand/OfferArea

IKW Creative Think = Fantasy + Concreteness

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

Care rate

1.2 - The “Knowledge Engineering” Concept“Knowledge Engineering (KE) is related with the ability to scaling down a

prefixed complex and implicit Knowledge Base (KB) toward a delivering

explicit target information”:

lim (KB) 0 (G.Mappa, ANOVA 2006)KE

In math words, given a prefixed Problem Solving domain, we may say that "the limit of a Knowledge

Base for the Knowledge Engineering process going on to infinity, reduce itself more and more, till

zero".

This generally it is possible by using a Systemic Approach and the Conceptual Tools of

Artificial Intelligence (like Data Mining, Knowledge Extraction, etc.):

So, according to KE approach, we can conclude that:

rather then a complex and Powerful Computation Systems (State of the Art), to a better

“Problem Solving” approach, we make use only of a good KE ability and the right conceptual

tools .

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

A Typical Knowledge Engineering Process…A Typical Knowledge Engineering Process…(Less unknown that you think…)

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

Target

Lots of Information

Cognitive Synthesis

Enterprise Conceptual (Economic) ModelEnterprise Conceptual (Economic) Model

(MOL)(MOL)max max = [R – CE]= [R – CE]max max -[CD+CI]-[CD+CI]min min -[CC+CG]-[CC+CG]min min

Sale - Buy Production Administration – Commercial …

Value Added

Revenue

Costs

year

-

Finance

Revenue

Costs

year

+

-

Finance

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

The Best Target of Knowledge EngineeringThe Best Target of Knowledge Engineering

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

Knowledge Knowledge ConceptualizationConceptualization

Knowledge ModelingKnowledge Modeling

Cognitive NetworksCognitive Networks

lim (KB) 0 KE

The Nurse/Doctor’s KE CaseThe Nurse/Doctor’s KE Case

P (x, y, z)

X [min, max]

Y [min, max]

Z [min, max]

Knowledge ModelKnowledge Model

x²+y²+z²+…..

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

Distance

Time Trend

Color Index

Organic Index

Applicable Flux

Permeate Loss

Flux Loss

Fouling Index

IDQ Quality Index

IDF Filtration Index

WPRWaste Pollution Rate

Key Performance Indicatore

Remote Control Expert Node

Expert Expert KnowledgeKnowledge

Probe/Sensors

Example: Customized Water Quality Monitoring System Example: Customized Water Quality Monitoring System ……

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

WPR = (dissolved salts; dissolved organic substances; total suspended solids) pH[6,5÷9]

Example: The Glasses & Buckets’ CaseExample: The Glasses & Buckets’ Case The The Not-deterministic DecisionNot-deterministic Decision

Water in one o more of bucketsWater in one o more of buckets

More full Bucket More full Bucket best DECISION best DECISION

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

Water Glasses

Water Glasses

Data -

Data -

INFORMATION

INFORMATION

Higher Higher Water Water LevelLevel

Not-deterministic Computation:Not-deterministic Computation:

1) 1) Independence from Number of INPUTIndependence from Number of INPUT

2) 2) Always a Result: DECISIONAlways a Result: DECISION

3) 3) Common Sense RESULTCommon Sense RESULT

1.3 -1.3 - The Basic Rules of a Knowledge Worker The Basic Rules of a Knowledge Worker

1)1) Value Added VA Value Added VA = VE= VEpp · ∑ · ∑i /∑i /∑ccii

2)2) Effective Working LEffective Working Lpp = = VA · COMVA · COMee

3)3) Competitive Working P Competitive Working P = Lp/t= Lp/t4)4) Potential Working Ep Potential Working Ep == (1-n/(k+n))·SKILLm(1-n/(k+n))·SKILLm5)5) Quality Efficiency Quality Efficiency

qq= L= Lpp/L/Lpmaxpmax %Q%Qcustomercustomer

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

1.4 - The KICS Strengths1.4 - The KICS Strengths of a IKWof a IKW

Knowledge Knowledge ((interdisciplinaryinterdisciplinary))

Innovation Innovation Communication Communication StrategyStrategy

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

0102030405060708090

100Knowledge

Innovation

Communication

Strategy

1.5 -1.5 - Innovation Management and R&D Innovation Management and R&D(skills-team-organization)(skills-team-organization)

"Without order nothing can exist – without chaos nothing can evolve.“di Vadim Kotelnikov – BUSINESS COACH

Concept Development – Implementation – Market Introduction

AA BB CC DD EE FF

P1P1

P2P2

P3P3

P4P4

P5P5

P6P6

P7P7

P8P8

P9P9

……

AA BB CC DD EE FF

P1P1

P2P2

P3P3

P4P4

P5P5

P6P6

P7P7

P8P8

P9P9

……

Resources

Projects

Time

Costi

Productivity

time

Example: Example: The Multi-Project/Multi-Sharing Management The Multi-Project/Multi-Sharing Management CaseCase

Quality

Time

Costs

Quality Ability Correspondence

KPI =Quality

Time x Costs

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

P1P1

P2P2

P3P3

P4P4

P5P5

P6P6

P7P7

P8P8

P9P9

……

time

Multi-Project Multi-Project “Windows”“Windows”

time

- Project Value --

- S

AL

- I

nv

oic

ing

-

A

MB A

M

B

III

IIIIV

- Project Value -

- C

us

tom

er

Va

lue

- A

MB A

M

B

III

IIIIV

PriorityPriority Criteria Criteria

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

1.6 - Communication of Innovation and R&D 1.6 - Communication of Innovation and R&D Project/Business IdeaProject/Business Idea

Language - Trust – Intellectual Property

Innovations are key for a society’s performance and progress.Innovations are key for a society’s performance and progress. The information about and communication of new ideas, technologies,

products, and services play a crucial role.

Communication toward Exploitation Plan Communication toward Exploitation Plan Communication toward CustomerCommunication toward Customer Communication toward PartnerCommunication toward Partner Visionary CommunicationsVisionary Communications Trust – Intellectual Property Trust – Intellectual Property

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]

A good Idea comes from our genius or by fortune …,

but its Value comes from the Process Knowledge

which is able to changes it into a Competitive Benefit

(g.m.)

A good Idea comes from our genius or by fortune …,

but its Value comes from the Process Knowledge

which is able to changes it into a Competitive Benefit

(g.m.)

ENGINEERYOUR

KNOWLEDGE !

Copyright 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected] 2009 Anova – All Rights Reserved - Giovanni Mappa - [email protected]