Strategic Intelligence revisited GÖRAN MARKLUND DEPUTY DIRECTOR GENERAL

Strategic Intelligence revisited GÖRAN MARKLUND DEPUTY DIRECTOR GENERAL

Imagine a Small Country.

Global Societal Challenges Win Win Win Source: Rockström, J. and Sukhdev, P. new way of viewing the Sustainable Development Goals. Illustration: Azote Images for Stockholm Resilience Centre

Public Innovation Governance Industrial Policy Labour Market Policy Regional Policy Tax Policy Finance Policy Monetary Policy Foreign Policy Trade Policy Migration Policy Research Policy Education Policy Integration Policy Environment Policy Energy Policy Social Policy Infrastructure Policy IT Policy Housing Policy

Innovation Policy for System Innovation Health Life Science Industry 4.0 Sustainable Cities Circular Economy Smart Mobility Research and Innovation Public Innovation Processes Smart Regulation Projects, Programs, Clusters Governance, Production, Procurement Laws, Supervision, Control

Policy Rationales Strategic shift 1945-1990- 2010- Market Failures (Neoclassical perspective) Structural System Failures (Innovation system perspective) Transformative System Failures (System innovation perspective) 1) Limited experimental economy* Weak incentives, information assymetries and capability deficincies limit ideation and experimentation 1) Infrastructural failures Under investments in infrastructures due to big uncertainties, high risk, big scale and long time-horizons 1) Directionality failures Weak incentives, lack of common visions and weak actor mobilization stop system transformation 2) Under investments in R&D and Innovation Genuine uncertainty about results and apprpriability make cost-benefit-calculus impossible 2) Institutional failures Laws, property rights, regultations, trust, values, normes and attidudes could generate negative incentives 2) Demand articulation failures Weakly articulated user and societal needs and weak demand articulation capablilities limit system renewal 3) Negative externalities Societally negative effects if private actors do not have incentives to include such costs in their calcultations 3) Network failures Weak cooperation limit knowledge exchanges, learning and empowerment too strong clusters could lead to lock-ins 3) Policy coordination failures Under developed processes for multi-level policy and horizontal policy coordination limit system renewal 4) Overexploitation of socitetal commons Societal commons land, water, environment tend to be overexploited if they are not priced 4) Capability failures Lack of key competences, leadrership and organizational capabilities limit absorption of new knowledge and innovation 4) Reflexivity failures Under developed systems and renewal perspectives in policy, evaluation and policy learning limit system renewal Source: Based on Weber and Rohracher Research Policy 41 (2012), p.1037-1047 (*Marklund)

System Renewal Societal Challenges System Innovation Sustainability System Landscape Mega trends Technological Demographical Political Wicked Problems Socio-Technical Paradigm Silo Organization Power Structures Trust Norms Routines Culture Incentives Regulations Path Dependent Research & Development Innovative Experiments Note: Based on Geels FW. Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study. Research Policy 2002;31(8/9):1257 74. Value Generation

Example: Mobility System Source: Geels, F.W, Technological transitions as evolutionary reconfiguration processes: A multi-level perspective and a case-study, p.3, Paper presented at Nelson and Winter Conference, June 12-15, 2001, Aalborg, Denmark, organised by DRUID (Danish Research Unit for Industrial Dynamics), Research Policy and Corporate and Industrial Change.

Evolutionary Processes Learning Formative Impact Evaluation Impact Evaluation Directionality, Empowerment, Reflexivity Evolutionary Summative Impact Evaluation Impact Evaluation Directionality, Empowerment, Reflexivity Amplify Impact Evaluation Directionality, Empowerment, Reflexivity Select Experiment

System Renewal Societal Challenges System Innovation Sustainability System Landscape Mega trends Technological Demographical Political EU Wicked Problems Socio-Technical Paradigm Silo Organization Power Policy Structures Labs Trust Norms Routines Culture Incentives Regulations Path Dependent Research & Development Testbeds Mission Driven Intiatives Small Business Experiments Challenge Driven Initiatives Innovative Experiments Value Generation Note: Based on Geels FW. Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study. Research Policy 2002;31(8/9):1257 74.

Domains for Strategic Intelligence Source: Grin, J., Rotmans, J. and Schot, J., p.154, Transitions to Sustainable Development New Directions in the Study of Long Term Transformative Change. In collaboration with Frank Geels and Derk Loorbach. Routledge Studies in Sustainability Transitions.

Strategic Intelligence

Strategic intelligence revisited for a new R&I Policy A policy maker perspective Societal challenges are generated and sustained by highly complex and strongly path dependent relationships between behaviors, actors, value chains, institutions, infrastructures etc. To efficiently address such challenges, system transformation would be required. However, R&I policy is generally based on industry, sector or technological perspectives and often tend to focus on different R&I-programs or schemes. And, R&I-policy is mostly generated and evaluated within the frameworks of only one or a few ministries, which tend to generate silo perspectives. However, system transformation to address societal challenges could not be generated successfully by R&I-programs alone. Innovation policy aiming at successfully address societal challenges would need to orchestrate all policy areas of importance for structures and developments that are generating and sustaining the challenges. This would require a strategic intelligence based on a much deeper and broader systemic understanding than what is generally characterizing analysis, reviews or evaluations used in policy strategies. As system transformation is genuinely uncertain, with strong wicked problem features, innovation policy need to take an evolutionary perspective and be based on evolutionary principles. This implies, among other things, that reflexivity through evaluation need to be deeply integrated into the processes to generate continuous learning rather than being limited to summative evaluations ex post, which is the dominant practice.

Thank you! Vinnova.se Vinnova @Vinnovase fb.com/vinnovase