6. Learning from Experience Flashcards

1
Q

Organisational Learning

A
  • shapeless, lifeless and formless entities
  • requires systems and processes to be put in place
  • collecting, reflecting and sharing information to improve their performance
  • methods: single and double loop learning, learning organisations and analytics
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2
Q

Single Loop Learning

A

repeated attempts at the same problem with no variation of method and without ever questioning the goal
- doing things right

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3
Q

Double Loop Learning

A

having attempted to achieve the goal on various occasions, to modify the goal in light f experience or possibly even reject it

  • constantly challenging the assumptions and goals about the world (for potential transformative changes)
  • doing the right thing
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4
Q

Difficulties in Double Loop Learning [SBP]

A

Status Quo Bias

  • required to challenge and question business models and organisational assumptions
  • managers think they are always right since they have experience

Bandwidth
- managers are not given enough time and resources to think about the bigger issues and implement fundamental changes

Power and Social Equation Dynamics

  • lack of power and authority to implement changes (balance of top down and bottom up approach)
  • system-wide change is necessary
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5
Q

Creation of Learning Organisations

A
  • recognise that learning is a system-level phenomenon (knowledge management and codification; actionable intelligence)
  • to institutionalise knowledge and making sure it stays in the system even when people come and go
  • learning organisations = learning orientations + facilitating factors
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6
Q

Learning Organisations: 3 Stages of Learning

A

Knowledge Acquisition

  • development or creation of skills, insights, relationships
  • through discussions, surveys, interviews, etc

Knowledge Sharing
- dissemination of what has been learnt

Knowledge Utilisation

  • integration of learning so it is broadly available and can be generalised into new situations
  • inscribing knowledge into organisational processes
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7
Q

Learning Organisations: Assumptions [CALF]

A
  • learning conforms to culture (the need to pose a learning method that is relevant to your culture)
  • all organisations are adaptive learning systems (with well-developed core competencies, continuous learning attitude and the ability to renew and revitalise)
  • style varies between learning systems (depends on learning orientations)
  • generic processes that facilitates learning (facilitating factors, always enhanced regardless of learning orientations)
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8
Q

Learning Organisations: Learning Orientations

[1 source, 4 focus, 2 modes]

A

Values and practices that reflect where learning takes place and the nature of what is learnt (highly contextualised to operating climate)

  • knowledge source: internal vs external; innovate vs imitate
  • product-process focus: accumulation of knowledge about what products are vs the process of developing products and services
  • learning focus: incremental vs transformational; corrective learning vs transformative/ radical learning
  • value chain focus: design vs deliver
  • skill development focus: individual vs group
  • documentation mode: personal vs public knowledge
  • dissemination mode: formal vs informal
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9
Q

Learning Organisations: Facilitating Factors [O LEVElS]

A

Structures and Processes that affect the difficulty in learning to occur and the amount of effective learning that takes place

  • *climate of openness
  • *involved leadership
  • *experimental mindset
  • *operational variety
  • *continuing education
  • *systems perspective
  • scanning imperative
  • performance gap
  • concern for measurement
  • multiple advocates
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10
Q

Analytics 1.0

A

The era of business intelligence

Data - rudimentary, sourced in-house

  • about production processes
  • small and static data sets

Outcome - objective, deep understanding of important business phenomena; give managers the fact-based comprehension to go beyond intuition

  • no predictions, no explanation
  • descriptive analysis

Skills - more time was spent preparing for analysis than the analysis itself; low computing and analytical power

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11
Q

Analytics 2.0

A

The era of big data

Data - generated in-house, sourced externally

  • the help of the internet
  • large data sets

Outcome - to build models and make sense of data to transform to strategy

  • predictive analysis
  • analyse data quicky

Skills

  • the need for new methods
  • the need for data scientists: computational and analytical skills
  • to generate, curate and consolidate data vs to interpret
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12
Q

Analytics 3.0

A

The era of data-enriched offerings

Data

  • everywhere due to the Internet of Things
  • seamless integration of data into our lives and decisions
  • online footprint

Outcome

  • generate algorithms to analyse browsing patterns
  • information providers –> insight providers
  • for enriched offerings: the benefit of the customer and for creating more valuable products and services

Skills

  • prescriptive analysis: foresees what will happen, when it will happen and explains why it will happen
  • provides recommendations on how to act upon it in order to take advantage of predictions
  • modelling
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13
Q

Challenges in Big Data Analysis [D-HHAM]

A

Figuring out which data to use

  • mixed-method analysis of quantitative and qualitative data
  • quantitative: strength and direction of relationship
  • qualitative: underlying explanations of those relationships

The need for a hypothesis

  • to give a direction and focus, but also need to let data speak for itself
  • balancing between direction and exploration

Balancing data with a human touch

Transforming data into actionable plans

Analytics and Modelling
- specialised training is required

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