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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]