Towards strategic management of complex systemic innovation environments: Integrating foresight, assessment, system dynamic modelling and societal embedding into a coherent model

Eu-SPRI Conference 2012: “Towards Transformative Governance? Responses to mission-oriented innovation policy paradigms” 12/13 June 2012, Karlsruhe

Mika Nieminen, Toni Ahlqvist, Anu Tuominen & Heidi AuvinenVTT Technical Research Centre of Finland

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Contents

1. Why do we need new methods?

2. Theoretical footing

3. Model

4. Case example

5. Summary

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Why do we need new methods?

There is a need for management models and tools to aid strategic decision-making in complex socio-technical environments

Why?

The growth of a social complexity Societal problems have became increasingly complex (e.g. Grand Challenges) and

interdependency in social systems is increasing Also our understanding of society has become more complex.

Technologies are increasingly convergent and hybrid by nature Technologies are interlinked and build up increasingly complex technological

systems and business “ecosystems” The development of systems is based on complex interaction between people,

structures, and technologies Thus, the traditional “technology push” or “supply side” policies do not function any

more

This accentuates the need for horizontal decision-making and policy planning The decisions made at one policy sector are interlinked to the processes of the

other sectors and therefore innovation policy cannot be limited to only one sector or a “silo”

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Why do we need new methods?

In order to tackle with the increasing complexity of socio-technical environments we need:

Methods which strengthen horizontal approaches

Steering mechanisms which are adaptive and able to respond to the rapidly changing situations

Approaches which support strategic thinking and interlink activities with a view of strategic management

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Theoretical footing

Complex social systems theory Self-organizing, adaptive and learning systems

Multi-level perspective on socio-technical change Interaction of landscape, regime and niche levels

Transition management Management of societal transition towards more sustainable

directions

Idea of strategic intelligence Complementary use of information for strategic management

and decision-making

610/04/23Value added of the different approaches in the model

Objectives/ Rationale for the data

Outcomes Tools

Foresight • Forward-looking data and dynamic, shared knowledge creation processes

• Supports strategic choices of alternative technological development paths

• Promotes networking of experts• Contributes to insights and shared visions

of future developments and consequent consensus of and commitment to future investments

• Roadmaps• Scenarios• Facilitated vision

building

System assessment

• Analysing the dynamics of the system elements and their development with a special view on impacts.

• Analysis of the current status of the system e.g. path dependencies, windows of opportunities

• Identification of system elements and their dynamics

• Strategic and operational targets to support policy implementation

• Future-oriented impact assessment of policy measures

• Follow-up of system development

• Evaluation• Monitoring • Network analysis• Ex-ante, mid-term

and ex-post assessment

System dynamic

modelling

• To solve a particular policy problem

• The simulation model is theory of the system, explaining its behaviour endogenously through feedbacks

• Model results are used to design good and robust policies

• Modelling

Societal embedding

• Facilitating development and introduction of new sustainable innovations

• Active and continuous dialogue among actors who set conditions for development and diffusion of innovations

• E.g. network building, and facilitating problem solution

Landscape

Regime

Niche

Time

Foresight

Modelling

Assessment Societal embedding

Increased strategic intelligence

Modified from original: Geels 2002

810/04/23Generic knowledge creation structure

Open technology spectrum

Partially focused technology spectrum

Focused technology spectrum

Open challenge spectrum

Partially focused challenge spectrum

Focused challenge spectrum

CASE TYPE I:Society

•Multiple potential angles•Multiple rule frames and structures, multiple contexts•Multiple value bases•Example: extensive foresight exercise

CASE TYPE II:Sector or cluster

•Bounded socio-technological system•Several strategic options•Entities are partially bound by similar rules and structures that condition differing contexts•Entities are under alike pressures from the action environment

CASE TYPE III:Organisation

•Several strategic options•Bounded context•Internal activity cultures

CONTEXTUAL ORIENTATION

TECHNOLOGICAL ORIENTATION

910/04/23Characterisation of the case types

Case type I:Society

Case type II:Sector or cluster

Case type III:Organisation

Core • Identification of challenges• Scoping of imaginable

socio-technological solutions

• Initiation and channelling of the societal transformation process

• Identification and evaluation of potential socio-technological solutions

• Charting strategic options for a sector or a cluster

• Engaging key actors

• Embedding and implementing of a socio-technological solution in a context

• Endorsing strategic decision-making at the points of transformation

Integration of three knowledge forms (foresight knowledge, modelling knowledge, assessment knowledge)

• Foresight oriented• Modelling knowledge is

integral part of the process and (potentially) a way depict results of foresight (see separate slide)

• Assessment knowledge (e.g. indicators) is an integral part of the process, particularly when defining the present state of the art

• Linkage to the embedding: the same actors in the process are the core actors of the embedding

• Foresight, modelling and assessment are somewhat balanced

• Assessment knowledge is in balance with foresight and modelling knowledge, e.g. path dependencies and systemic lock-ins

• Foresight means primarily the production of visionary solutions in a system

• Embedding is in a key role

• Foresight, modelling and assessment endorse the setting for the embedding

1010/04/23Characterisation of the case types

Case type I:Society

Case type II:Sector or cluster

Case type III:Organisation

Process emphases (examples)

• Visionary process• Emphasis on

imaginable futures and the formation of explorative visions

• Backcasting orientation

• Mapping the futures from the present

• Starts with the existing socio-technological structures and solutions

• Driver oriented process• Starts with present

understanding of the grand challenges

• Fixing the process against this view

• Analysis of a socio-technological system, e.g. sector

• Analysis of a specific activity environment, e.g. market

• Production of technological alternatives

• Technology models; modelling is in a key role

• Assessment of the potential of technology models

• Based on panels• Plausibility; maturity;

market potential; year of realisation

• Co-creation of the socio-technological solutions with the key actors

• Identification of key actor and topics; mobilisation; activation; empowerment

• Mapping the organisational dynamics and tensions

• Different frames of interpretation

• Implementation of the socio-technological solution

• Process target has evolved during the process of co-creation and therefore the implementation phase is important

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Frame for assessing scale and methods

12

3 4

Short duration

Long duration

BroadNarrow

1210/04/23Case type 1: Society 1) Broad, long duration

Duration ca. 1 year Ca. 50-100 experts Back-office Driver analyses (PESTEVL; matrices…); workshops;

questionnaires Delfoi, scenarios, roadmaps, modelling etc. Example: Broad and explorative foresight exercise, like

‘Roadmap for bioeconomy’ 2) Narrow, long duration

Duration could be up to three years Quite focused expert panel Example: Monitoring a trend, e.g. TrendChart

3) Narrow, short duration Duration ca. 1 month to 4 months Ca. 30 experts Focused roadmap or a model Focused drivers and technologies Example: Focused roadmap on a single energy source

4) Broad, short duration Condensed version of the option 1 Duration ca. 4 months to 6 months Several (5-7) researchers involved Activities simultaneously on multiple fronts

12

3 4

Short duration

Long duration

BroadNarrow

1310/04/23Case type 2: Sector or a cluster

1) Broad, long duration Duration ca. 1 year Ca. 50-100 experts Interviews; workshops; document analysis; statistics;

modelling Example: Sectoral foresight exercise, like ‘Renewable

energy sources in the traffic system’ 2) Narrow, long duration

Duration could be up to three years Quite focused expert panel Example: Monitoring sectoral indicators

3) Narrow, short duration Duration ca. 1 month to 4 months Ca. 30 experts Focused roadmap or a model Focused drivers and technologies Example: Focused SHOK foresight or an assessment

4) Broad, short duration Condensed version of the option 1 Duration ca. 4 months to 6 months Several (5-7) researchers involved Activities simultaneously on multiple fronts

12

3 4

Short duration

Long duration

BroadNarrow

1410/04/23Case type 3: Organisation

1) Broad, long duration Duration max 3 years Ca. 50-100 experts Emphasis on embedding Foresight and assessment knowledge endorse the process Modelling the health case system Qualitative methods: diaries and organisational narratives Example: Implementation of a technological innovation in a

health sector 2) Narrow, long duration

Long duration Example: Monitoring the results of embedding and

implementation 3) Narrow, short duration

Duration ca. 1 month to 4 months Example: Training sessions at the organisation, maybe

even embedding in a small organisation and a limited cases 4) Broad, short duration

More extensive training sessions

12

3 4

Short duration

Long duration

BroadNarrow

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CASE: EMISSION FREE TRANSPORT IN CITIES 2050

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Socio-technical frame for transport system

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Questions to be answered with the case –study

1. What kinds of societal transitions are required to reach the principle vision? → Stakeholders involved, changes and transitions required, impacts and implications…

2. How can the required transitions be made possible / assisted / sped up? → Vision paths, policies…

3. How can the collection of approaches (Foresight - Modelling - Impact assessment – Embedding) be put into use to analyse and align required transitions?

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Integrating different approaches into a coherent model

Foresight Principle vision − emission free transport in cities in 2050

(EU White Paper on transport) Vision paths − three alternative ways to make it happen:

1. electric vehicles

2. public transport

3. biofuels.

Impact assessment Identification of potential policy instruments and their impacts

to reach the vision

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Integrating different approaches into a coherent model

System dynamic modelling Modelling of the transport system and the impacts of policy

instruments Dimensions to be modelled:

environmental concerns developing key technologies and complementary technologies passenger transport, incl. public transport − user choices urban environments economic aspects societal issues

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Willingness to own a car and use

private transport

Infrastructure availability

Use, expectations

Attitudes, values

Investments, financing, business

models

Investments, cost structure (purchase and

use costs, fuel price)

Financing, volumes

Public transport (modes,

powertrains, fuels)

Willingness to use public transport

Public transport characteristics (service level)

Infrastructure coverage

Infrastructure requirements

Users by user segment

(transport demand)

Transport infrastructure

(networks, fuelling, charging, etc.)

Private transport

(powertrains, fuels,

ownership)

Vehicle characteristics

Infrastructure coverage

Infrastructure requirements

2110/04/23System dynamic model of a transport system

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5. Summary

Increasing complexity necessitates horizontal policy-making, which takes into account the systemic nature of innovation environments

Complex & multi-level information needs

We need to know the current status of the system (functional assessment) & the

possible future options (foresight) to create commonly shared policy & innovation options (foresight & societal

embedding); To have more precise information on the complex causal relationships &

feedback loops within the system in order to anticipate consequenses of policy actions (system dynamic modelling)

The proposed approach attempts systematically to combine the above mentioned approaches into a coherent whole

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5. Summary (cont.)

Challenging multi-approach project Work is still in progress

Current status: A framework for combining approches in various societal &

innovation situations created Testing started in three different cases (bio-economy, social &

health care; emission free transport) Tailor-made combination of approaches for each case

Emission free transport as an example

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