Download - The Control Chain Management Network

Enterprise Intelligence
Jean Vieille
05/2010
www.controlchainmanagement.net
[email protected]
Creative
Commons
licence
Agenda
■
■
■
■
■
Introduction
Information hierarchies
Biological and artificial computing
Intelligence and complexity
Enterprise IQ and performance
Enterprise Intelligence
Creative
Commons
licence
2
Introduction
■
■
■
Intelligence is a subjective and scalable topic.
 A simple computation linking the detection of an event to a
subsequent appropriate action can be considered an elementary
intelligent behaviour
 Consciousness, wisdom qualify much higher levels that are currently
unattainable by machines
This study discusses
 General aspects of intelligence
 Applicable in the context of the industrial enterprise and
specifically its manufacturing operations
 Its relationship with Performance
The following documents are prerequisite references for this study
 EnterpriseSystemUpperLevelModel_en.pptx
 Science for Enterprise Systems.pptx
Enterprise Intelligence
Creative
Commons
licence
3
Agenda
■
■
■
■
■
Introduction
Information hierarchies
Biological and artificial computing
Intelligence and complexity
Enterprise IQ and performance
Enterprise Intelligence
Creative
Commons
licence
4
Information Hierarchies
Syntropic
Type
Syntropic
Rank
Information
type
Representation
Potential
1 Things and Facts
Objective
Potential
2 Data
Language
Potential
3 Meaning
Language
Potential
4 Knowledge
Objective
Potential
5 Consciousness
Kinetic
1
Interactions
(Objective)
Kinetic
2
Communication
Language
Kinetic
3
Processing
Language
Kinetic
4
Intelligence
Language / Objective
Kinetic
5
Wisdom
Objective
Enterprise Intelligence
Creative
Commons
licence
5
Potential Information Level 1: Things and Facts
■
■
■
The « reality », the « Truth »
 The things as they are
 The facts as they happen
Independent of the observers
 Ourselves, sensors and computers
Not available for processing
Enterprise Intelligence
Creative
Commons
licence
6
Potential Information Level 2: Data
■
■
A local representation of disconnected facts and observations
 Interpretation of things and facts by the primary observer, from its
narrow local perspective
 The temperature is -50
 Riots are ongoing
Data relies on language
 Offering conceptual references…
 Physical measurement
■ Temperature, pressure
 Valuation
■ Numbering, string enumeration
 Social events
■ Riots, parties, meeting
 … implicit in the context of the observer
Enterprise Intelligence
Creative
Commons
licence
7
Potential Information Level 3: Meaning
■
■
■
An interpretation of data for use by (time and space distant) others
 Conditions and combines data in order to convey meaning to nondirect observers
 The temperature is -50 °C at the North pole, on April 21th 4PM
 20000 demonstrators in Teheran, which is a 17M inhabitant city
Meaning relies on language
 Offering conceptual references
 Describing the context placing the distant observer
 Closer to the direct observer understanding
 Potentially closer match to the actual facts and things
Meaning is subjective
 Elaborated or relayed by error prone observers with who might
convey a biased, misleading correspondence to things and facts
 Erroneous representation, or missing, key facts
Enterprise Intelligence
Creative
Commons
licence
8
Potential Information Level 4 : Knowledge
■
■
■
■
Knowledge is an objective state of understanding
 In the form of experiences, theories, practices explaining the Reality:
 Looking for the “truth” based on cross meaningful observations
 Can be
 Explicit: materialized in books, files, painting, artefacts…
 Implicit : resident in people’ minds
It is independent of its subjective usage
 Any entity influences its behaviour in dealing with actual things and
facts by interpreting, understanding and applying this knowledge
Is continually developed / improved
 The general tendency of Mankind
 Occasional losses
Variable domain space
 private, shared or publicly exposed
Enterprise Intelligence
Creative
Commons
licence
9
Potential Information Level 5: Consciousness
■
■
■
Consciousness is a lasting issue for philosopher
Dictionaries discard IT - Oxford:
 “the state of being conscious. The fact of awareness by the mind of
itself and the world. One's awareness or perception of something”
Consciousness relates to “irrational principles”
 Cannot be deductible from / linked to knowledge
 Culture, Traditions, Beliefs, Ego
Enterprise Intelligence
Creative
Commons
licence
10
Kinetic information Level 1: Interactions
■
■
The dynamics of the world results of inter-actions
 Actions are triggered by other actions
 Any happening results of a network of interactions
 Including in brain’s synapses
 Where / when / why the initial trigger fired?
Interactions media have many forms
 Different “forces” at the molecular, atomic and subatomic levels, to
build more complex material structures
 More tangible materials and energetic interactions
 Chemical, mechanical, electrical, thermal...
 Multimedia interactions between people through available senses::
 Sound, vision, smell, touch, taste, 6th sense
Enterprise Intelligence
Creative
Commons
licence
11
Kinetic information Level 2: Communication
■
■
Communication is the abstraction of interactions, making possible
 To implement artificial interactions
 Not naturally occurring
 To link separate, distant (in space and time) entities
 To link dissimilar entities ( people and machines)
Communication relies on language
 Only meaningful interactions are useful
 Language offers conceptual references for a shared understanding
Enterprise Intelligence
Creative
Commons
licence
12
Kinetic information Level 3: Processing
■
■
■
■
Processing applies existing knowledge
 To understand and act on he Reality
Information « flows » through systems’ components
 Communication exchanges « meaning » between thinking /
processing bodies / black boxes
 What happen inside brains and computers is « processing »
 Which itself results of interacting synapses in gray matter, gates in
integrated circuits, interfaces between networked applications
 IQ tests measure processing / cognitive capabilities, not intelligence
Processing relies on language
 Biological cognition as well as artificial computing
Some local, low-level, basic processing relies on direct interactions
 No language is required for walking or to the automated refill of a WC
water bin after a flush
Enterprise Intelligence
Creative
Commons
licence
13
Kinetic information Level 4: Intelligence possible attributes
An intelligence system
■
Makes a critical use of knowledge:
 challenges existing beliefs and theories
 Learning from experience : trial and error confronting theories and
reality
 Being creative, imagining new or amended theories
 Including its owns: auto-critics
 Suggests improvement to existing theories, develops new theories
 Intelligence builds knowledge - Processing sucks!
■
Focuses the limited thinking / processing capabilities
 Toward reaching conscious goals
 Beyond unconscious survival and reproduction
■
Decides and acts
 Takes initiative,
 Quickly adapts one's self to circumstances, leverages opportunities
Creative
Enterprise Intelligence
Commons
licence
14
Kinetic information Level 4: Intelligence and language
■
■
As a higher processing ability, language is generally involved
 “Artificial intelligence”,
 Mental representations of knowledge for cognition
“Intuitive” behavior results of an inner appropriation of knowledge
 Realizes a short cut from knowledge to a action / decision
 Language might be only involved at the last stage
Enterprise Intelligence
Creative
Commons
licence
15
Kinetic information Level 4: Intelligence loop
■
■
■
(1) Intelligence raises from
interactions
 Between processing entities
and actual world
 Enabled by communication or
direct perception
Intelligence
 (2) Exploits and feeds
knowledge
 (3) Determines and directs
processing
(4) Processing realizes
interactions
 Through communication
Enterprise Intelligence

Cliquez pour éditer le format
du plan de texte Objective
knowledge

Second niveau de plan
Troisième niveau2de
plan 3
Processing
Intelligence
 Quatrième niveau
de plan
4
 Cinquième
1 plan
Communication niveau de
 Sixième niveau
4 de plan
 Septième
Interactions
niveau de plan
 Huitième niveau
de plan

■
Creative
Commons
licence
Neuvième niveau de
16
Kinetic information Level 5: Wisdom
■
■
Common definitions – not applicable in this framework
 “The inner knowledge and experience needed to make sensible
decisions and judgments, or the good sense shown by the decisions
and judgments made” = intelligence
 “Accumulated knowledge of life or in a particular sphere of activity
that has been gained through experience” = Knowledge
 “An opinion that almost everyone seems to share or express”
Certainly not – might sometimes be stupidity
 “Ancient teachings or sayings that survives to Time”
 this is objective knowledge produced by intelligent people not yet
challenged by superior knowledge
More appropriate:
 “Consciousness of having limited knowledge and poor understanding”
 “Acting for the common interest, being unselfish”
Enterprise Intelligence
Creative
Commons
licence
17
Agenda
■
■
■
■
■
Introduction
Information hierarchies
Biological and artificial computing
Intelligence and complexity
Enterprise IQ and performance
Enterprise Intelligence
Creative
Commons
licence
18
Biological specific computational capabilities
■
■
■
■
Connection to the World
 Perception
 Motion and manipulation
Meaning and Knowledge representation
 Pattern recognition
 Verbal Language and other communication skills
Deduction, reasoning, problem solving
 Ability to complete missing information
 Planning
 Learning
 Creativity
 Social behavior
Ability to repair
Enterprise Intelligence
Creative
Commons
licence
19
Biological / Digital computing Comparison (Stonier)
Digital (Artificial)
Biological (natural)
Digital information processor based
on circuits of binary switches
Analogue information processor
involving a complex nervous system
with scores of chemical
neurotransmitters and modifiers
Information transported as pulses of
electrons along conductors and
across semiconductors
Information transmitted as pulses of
depolarization along membranes and
as neurotransmitters across synapses
Speed of pulses transmission
approximately 108 m/sec
Speed of pulses transmission
approximately 10 m/sec
Relatively simple circuitry but
increasing in complexity
Extremely complex circuitry: 1011
neurons with up to 1015 connections
Enterprise Intelligence
Creative
Commons
licence
20
Biological / Digital computing Comparison (cont’d)
Digital (Artificial)
Biological (natural)
Crystalline structure, extremely stable Bio-tissue, vulnerable to damage
Can operate under a wide variety of
conditions
Needs carefully regulated
environment to operate
Computer system may be shutdown
indefinitely with no damage
Brain requires continuous energy
inputs in order to maintain the living
system
No self-repair. Some self-correction
and by-pass of faulty areas
Tissue capable of significant selfrepair. Also extensive capability to
transfer function to other circuitry
Memory based on patterns of binary
switches
Memory based on patterns of neural
connections
Enterprise Intelligence
Creative
Commons
licence
21
Intelligence in artificial systems
■
■
By analogy to biological systems, an artificial system is considered
to only exhibit intelligence at the system level
 Not at the level of its own components
Local behaviour is considered effective only if It contributes to
increase the system intelligence through
 Effective communications leveraging complex interactions (4)
 Knowledge based processing implemented and directed intelligently
(3)
Enterprise Intelligence
Creative
Commons
licence
22
Agenda
■
■
■
■
■
Introduction
Information hierarchies
Biological and artificial computing
Intelligence and complexity
Enterprise IQ and performance
Enterprise Intelligence
Creative
Commons
licence
23
Nature of systems’ intelligence
■
■
Intelligence is an emergent property of complex systems
 Resulting of complex interactions
 Between behaving components
 From brain synapses /silicon gates to talking people / assembled
machines
Processing and Intelligence residence
 Processing can be localized in computing areas
 Monism: Processing is integrally embedded in the system
■ Control loops, servo-mechanisms
 Dualism: Processing is the purpose of a defined decision making
entity
■ Recipe sequencer, decision maker
 Intelligence is a diffused characteristic of the system as a whole
 Individual “intelligence” of a decision maker does not represent
the system intelligence – it can even impact it negatively
Enterprise Intelligence
Creative
Commons
licence
24
Feedback
■
■
■
■
Interactions imply that sub-systems
 Capture meaning from other sub-systems / environment
 Process information locally to perform their role
 Provide meaning to / act on other sub-systems / environment
The sub-system being « complicatedly coupled », Its action
 spreads to many other sub-systems directly/indirectly, themselves
processing and spreading this information
 Hits it back at some point
 Intelligence results of these complex interactions of local processing
Positive feedback loops
 Example: Productivity enhancement, bankruptcy
Negative feedback loops
 Example: Traffic control, resistance to change
Enterprise Intelligence
Creative
Commons
licence
25
Conflicts
■
■
Conflicts raise from interactions between sub-systems
 Some of them being complex systems (i.e. Individuals, teams)
 Having individual references, goals, and motivation
 Having a certain level of autonomy with Internal priorities
regarding other components and environment, within a given
decision hierarchy
Conflicts are inevitable
 A perfectly stable system may be immune for some time
 Any change may trigger conflicts
 Any conflict may trigger changes
 Survival has timing and altruistic dimensions:
 One specific component’s interest may contradict other
components' / system’s
Enterprise Intelligence
Creative
Commons
licence
26
Conflicts, cooperation
■
■
■
Conflicts represent ineffective, negative interactions
 Communication issues,
 Structural and behavioural unfit
 System / Subsystems goals mismatch
Conversely, cooperation is linked to efficient, positive interaction
 Hypercritical positive feedback: improved cooperation increases
intelligence which falls back to sub-systems and favours further
cooperation
Conflict resolution and smooth cooperation are critical intelligence
enablers
 Revealers of interactions quality
Enterprise Intelligence
Creative
Commons
licence
27
Uncertainty
■
■
■
Systems are subject to perturbations that can be guessed
 Within standard Gaussian deviations
 Future is somewhat predictable, Exceptions are rare or of limited
impact (i.e. seasonal market demand)
Extreme events can arise without computable probability
 The modern World tends to offer more and more of these
Intelligence implies
 The knowledge of the real Gaussian domains
 Exercising reasonable forecasts and prudent classic risk
mitigation management
 The consciousness of the lack of knowledge of the uncertainty
 Be ready to address unpredictable, likely possible and potentially
large impact events
■ Bad : be ready to fight for survival
■ Good : seize the opportunities
Enterprise Intelligence
Creative
Commons
licence
28
Deterministic Intelligence
■
■
■
■
■
■
Example:
 Petrified strategy: keep making the same known mistakes to avoid
dealing with unknown
Decision hierarchy
 Classical Strategy / Tactic / Operations decision processes
HR management
 Motivation programs
Linear Feedback loops
 React on predictable events based on history
Process improvement
 Performance measurement, KPIs
 Management methods: TQM, TOC, 6Sigma, Lean…
Necessary, but not triggering quantum leaps
 Rarely endanger the system
Enterprise Intelligence
Creative
Commons
licence
29
Opportunistic Intelligence
■
■
■
■
Example
 Best performing companies strategy... are just lucky!
 = they did not miss the opportunities that made them successful
Noise and useful information
 Distinguish unimportant / important events
Leverage the Luck factor
 Be imaginative, Develop creativity
 Recognize opportunities
 Be adaptive, decide and act fast
 Make mistakes, fix and learn (don’t make it twice)
 Mitigate risk
The only source of rapid progress/success
 And cataclysmic failure
Enterprise Intelligence
Creative
Commons
licence
30
Agenda
■
■
■
■
■
Introduction
Information hierarchies
Biological and artificial computing
Intelligence and complexity
Enterprise IQ and assessment
Enterprise Intelligence
Creative
Commons
licence
31
Intelligence assessment
■
■
■
Darwinian: the ability to survive
 Applies statistically to a species
 Not measurable for a single organism: can only be valued at the
death of the organism
 Not related to computational performance – Insects appear to have
been more resilient than dinosaurs
 Does not involves consciousness
Pragmatic: the ability to control its own destiny
 Setting a Vision, keeping getting closer to it
 Enterprise IQ = the speed at reaching the vision
If the vision is not self-destructive, both can match!
Enterprise Intelligence
Creative
Commons
licence
32
Pragmatic Intelligence dynamics
■
■
Intelligent organism always looks forward
 Never satisfied by the current situation and its own state
 Sets unreachable vision, shifts the vision when it become reachable
 The vision conditions the system temporal course
 Shall be beyond its current state, or ever escaping - « To be alive
in 2 Centuries »
 Example:
 Bill Gates might have wished to the richest man on earth
 He now aims at being the first charity donator on Earth
 Once done, he might finally set the goal to wipe hunger of the
surface of Earth – or to extend the Windows dominance to the
whole galaxy
IQ = 100+K.∆(Vision - Situation)/ ∆t
 Average (poor) IQ= 100 corresponds to a steady state – absence of
vision
Creative
 LowerEnterprise
IQ means
better situation than vision: successful
and stupid33
Intelligence
Commons
licence
Expressing Enterprise Vision
■
■
■
■
Vision is traditionally a high level, pompous, abstract, nonactionable statement
 Called “Vision”, “Mission”, “Goal”, “Objectives”, “Target”, “Draw”,
“Think” depending on the strategic planning method
Vision needs to be expressed in specific topics according to the
I/Os and parties involved in enterprise exter-actions
Based on the CCM enterprise system upper level model, these
topics can be precisely focused
As a result:
 Vision can be expressed in expressive, detailed and extensive goals
 Measuring Vision fulfillment – pragmatic IQ becomes possible
 Strategy definition and implementation benefit of a formal guidance
Enterprise Intelligence
Creative
Commons
licence
34
Vision Dimensions
■
■
■
Parties
 The relationship entities of the enterprise
Processor
 Knowledge
 Finance
 Product
Flows
 Information
 Energy
 Matter
 Money
Enterprise Intelligence
Creative
Commons
licence
35
Example of Enterprise Vision – General goals
Parties
Shareholders
Pty
1
General goals
To retain involved shareholders privileging long term secured revenues
Employees
State
Society
Nature
Suppliers
Customers
Competitors
1
1
1
1
1
1
1
To become a source of pride for happy employees
To leverage laws and regulations perceived as positive constraints
To be a source of happyness and wellbeing for the Mankind
To be an effective industry, optimizing its impact on Nature
To be a source of progress and sustainability for Suppliers
To provide both syntropic and economic value to Customers
To make sure we perform best in every point
Banks
1
To eliminate any kind of liability to banks, borrowing only to responsible investors
Insurances
1
To become self insured, by minimizing risk and building adequate provision
Enterprise Intelligence
Creative
Commons
licence
36
Example of Enterprise Vision – Knowledge goals
Parties
Shareholders
Pty
1
Knowledge related goals
have an appropriate view of the enterprise functioning
Employees
1
State
1
Benefit of ongoing progress of physical, intellectual capablities
Enjoy their work, are proud of their job and company
Has the full, realtime and accurate compliance information on our operations
Society
1
Contribute to increase product and finance related public knowledge
Nature
Suppliers
1
1
Customers
1
Competitors
1
Banks
Insurances
Benefit an extensive feedback of their product and services
Enjoy a smooth relationship allowing them to optimize their operations
Perceive a very positive image of the company
Benefit of every needed information to access and use the products
Do not access our sensible knowledge
‘ knowledge is captured and appears always behind ours
1
Are impressed
by our financial health
Creative
Enterprise
Intelligence
Commons
1
Are convinced of the very low risk linked to our operations licence
37
Example of Enterprise Vision – Finance concern
Parties
Shareholders
Pty
1
Finance related goals
get a regular and sufficient stream of income
Employees
State
Society
Nature
Suppliers
1
1
1
1
1
get satisfying salaries, sensibly higher than the average
gets the right share of taxes based on our actual revenue
gets an increase of gobal wealth
Customers
Competitors
1
1
Perceive a high value and pay our products accordingly
Banks
1
Insurances
1
get the smallest fee from our operations
get insignificant interests from our investments
we don’t deal with them anymore
get sufficient margins to sustain their operations and provide quality products
Enterprise Intelligence
Creative
Commons
licence
38
Example of Enterprise Vision – Product/Information concern
Parties
Shareholder
Pty
1
Product/Information
Are aware of our products, they like them and are motivated to support them
Employees
1
State
Society
Nature
Suppliers
1
1
1
1
Are proud of our product
Have the best knowledge available to make
Apply the best methods to produce efficiently
Our products comply with the regulation
Objectively benefit of our products
Customers
1
Improve their product based on our the actual fit in our product
Optimize their planning based on our own
Have the relevant information for the best experience and confidence
Competitors
1
Have a lower knowledge than us
Banks
Insurances
1
1
Are confident about the relevance and value of our products
Are convinced that our product is harmless for the customers
Enterprise Intelligence
Creative
Commons
licence
39
Example of Enterprise Vision – Product/Matter concern
Parties
Shareholder
Pty
1
Employees
1
State
Society
Nature
Suppliers
Customers
1
1
1
1
1
Competitors
1
Banks
Insurances
1
1
Product/Matter
Don’t suffer matter related nuisance
Our scrap is minimized or properly recycled
Logistics is optimized
Demand fulfillment is optimized and satisfactory
Enterprise Intelligence
Creative
Commons
licence
40
Example of Enterprise Vision – Product/Energy concern
Parties
Shareholder
Pty
1
Employees
1
State
Society
Nature
Suppliers
Customers
1
1
1
1
1
Competitors
1
Banks
Insurances
1
1
Product/Energy
Don’t suffer matter related nuisance
We minimize our energy consumption
We leverage dynamic energy tarifs
-
Enterprise Intelligence
Creative
Commons
licence
41
Example of Enterprise Vision – Product/Money concern
Parties
Shareholder
Pty
1
Product/Money
we maintain a high margin on our products
Employees
1
State
1
Our products have a positive impact on the payment balance (exportations)
Society
Nature
Suppliers
Customers
1
1
1
1
-
Competitors
1
Banks
1
Are useless for supporting our operations - Low working capital needs
Insurances
1
The potential of failure of our product is low and impact is minimized
-
Enterprise Intelligence
Creative
Commons
licence
42
Measuring IQ/progress – unweighed example (Priority = 1)
Xi :-1: regress 0 = steady 1 = progress
Shareholder
G
K
F
Product
I Ma
1
1
1
1
Total
E
Mo
1
Each cell = Xi*PYi
Here, every aspect improved
(Xi =1) with same priority (PYi = 1)
5
IQ = 100 + [100*( Xi*PYi) /
Employees
1
1
1
1
State
Society
Nature
Suppliers
Customers
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Competitors
1
1
Banks
Insurances
1
1
1
1
4
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Enterprise Intelligence
6
7
3
7
7
IQ = 100 + 100*52 / 52 = 200
=> max. progress
Other limit values:
IQ = 0 => max. regression
IQ = 100 => no progress
3
1
1
5
5
52
PYi]
Creative
Commons
licence
43
Assessing impact of changes
■
The same approach can be used to assess the relevance of a
proposed change in the system
Relevance in % = 100* (Xi*PYi) /
■
PYi
To answer the question:
 Will this change (investment, reorganization, new practice…) impact
positively and significantly the system intelligence?
 The -1 / 0 / +1 values in each cell, and their weighed summation will
provide the answer in the range -100 / +100
Enterprise Intelligence
Creative
Commons
licence
44
Thank You !
Enterprise Intelligence
Creative
Commons
licence
45