Tci2014 cluster complexity_mesopartner
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This presentation was hold by Dr. Ulrich Harmes-Liedtke at the panel on "The evolution of clusters" at the TCI conference in Monterrey Mexico, 2014, November 12th
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Tci2014 cluster complexity_mesopartner
- 1. IS CLUSTER PROMOTION AN OBVIOUS OR COMPLEX ENDEAVOR? ULRICH HARMES-LIEDTKE
- 2. NEW PERCEPTION CLUSTERS ARE COMPLEX SYSTEMS 17 TH TCI GLOBAL CONFERENCE | CREATING SHARED VALUE THROUGH CLUSTERS FOR A SUSTAINABLE FUTURE 1
- 3. CLUSTERS ARE COMPLEX SYSTEMS Source: MATTA, A. 2012
- 4. Cluster emerge, evolve and increase complexity The cluster community recognizes more and more evolutionary character clusters. Source: Cluster policy Whitebook,Andersson, Schwaag-Serger et al. 2004
- 5. CHARACTERISTICS OF COMPLEX SYSTEMS Source: ANDRUS, D.C. 2005
- 6. Simple Complicated Complex Baking a cake Sending a rocket to the moon Raising a child Right recipe is essential Gives the same result every time Formulas needed Experience built over time and can be repeated with success No right recipes or protocols Outside factors influence Experience helps, but does not guarantee success DIFFERENT TYPES OF PROBLEMS In cluster management we treat problems mostly as simple or complicated
- 7. WHY COMPLEXITY IS INCREASING? Move from the industrial era of mass production to the knowledge society Globalization of people and trade New challenges in context of climate change, epidemics and wars In general: increased uncertainty and vulnerability
- 8. SENSE MAKING DEALING WITH CLUSTER COMPLEXITY 17 TH TCI GLOBAL CONFERENCE | CREATING SHARED VALUE THROUGH CLUSTERS FOR A SUSTAINABLE FUTURE 2
- 9. NOT EVERYTHING IS COMPLEX Source: Dave Snowden/ Cognitive Edge
- 11. RECIPES AND CHEFS In complexity the Cluster Manager need to act as a chef
- 12. BEYOND STRATEGIC PLANNING CLUSTER POLICY IMPLICATIONS 17 TH TCI GLOBAL CONFERENCE | CREATING SHARED VALUE THROUGH CLUSTERS FOR A SUSTAINABLE FUTURE 3
- 13. Conceptualization of Cluster evolution Resilience refers to the capacity of firms to respond flexibly to shocks internal and external to a cluster Resource accumulation refers to increase productive, knowledge and institutional capital over time Connectedness refers to the extend of traded and untraded interdependencies between cluster firms Source: MARTIN, R. & SUNLEY, P. 2011
- 14. SERENDIPITY OR THE "PLEASANT SURPRISE" Finding something without looking for it. The Three Princes of Serendip were always making discoveries, by accidents and sagacity, of things they were not in quest of. Alexander Fleming, discovered by accident penicillin (1928) Source: Robert K. Merton & Elinor Barber, 2006
- 15. CLUSTERS, INNOVATION AND POLICY Clusters have a higher rate of innovation, because knowledge and skills come from localized social networks Clusters increase probability of accidental discoveries and recombinant innovations Interventionist policies negate conditions that facilitate the occurrence of serendipitous events Source: karostech.fi An alternative is to favor experimentation and provide a favorable environment where emerging clusters can operate successfully
- 16. CONCLUSIONS A NEW PARADIGM? 17 TH TCI GLOBAL CONFERENCE | CREATING SHARED VALUE THROUGH CLUSTERS FOR A SUSTAINABLE FUTURE 4
- 17. ARE WE FACING A NEW PARADIGM?
- 18. THERE IS NO NEED TO START FROM SCRATCH, BUT… We need to o be more aware of complexity o be able to identify complex situation o don’t seek for early consensus o find simple ways to understand and communicate complex situations
- 19. MOVING IN COMPLEXITY SHOULDN'T BE COMPLICATED Source: @gapingvoid
Notas del editor
- Complexity is one of the most popular buzz word today. In 2010, IBM published a study called “Capitalizing on Complexity” based on conversations with more than 1500 CEOs worldwide. While 79% of them expected a high degree of complexity over the next years, only 49% felt prepared for it. This so called “complexity gap” is also relevant for the cluster community. Many of us cluster practitioner sense instinctively increasing complexity, but we have no clear understanding, what it really means and how to address it.
- I like to start my presentation with some conceptual explanations of so called “complex adaptive systems” (CAS) and relate to clusters. I built here on a broad research on complexity and especially on publications with evolutionary perspective on clusters. I have to confess, that I am still in the beginning of study and understand clusters as a complex phenomenon. The scientific jargon and several of the main concepts are still new for me as a cluster practitioner.
- This graph is part of a Social Network Analysis of Electronics and Software Cluster for the city of Córdoba (Argentina). It visualizes the linkages between the firms of the cluster. The arrows represent the flow of strategic information between firms of different sizes within the cluster. The number of cooperative relationships increases with the firm size until you get to a sort of "roof" which begins to fall. The smaller firms have marginal positions, meanwhile the role of the midsize firms is more prominent. A special place in the information flow do have the firms comprising the executive committee of the cluster trade associations (red color). Source: MATTA, A. 2012. Aportes del Análisis de Redes Sociales a la Gestión de Estrategias de Cooperación Empresarial. REDES- Revista hispana para el análisis de redes sociales, Vol.23 5 146-177.
- The complexity of clusters evolves overtime. The graphs describes the typical development of a cluster according to the live cycle model: The point of departure or necessary condition for cluster building is the agglomeration of firms with similar competences in a given region. The cluster emerges when the actors in the agglomeration start to cooperate around a core activity, and realize common opportunities through their linkages. New actors in the same or related activities emerge or are attracted to the region, new linkages develop between all these actors. A mature cluster has reached a certain critical mass of actors. As time goes by, markets, technologies, and processes change, as do clusters. In order for a cluster to survive, be sustainable and avoid stagnation and decay, it has to innovate and adapt to these changes. This can take the form of transformation into one or several new clusters that focus around other activities or simply a change in the ways that products and services are delivered. The complexity of the cluster can be measured by the number and form of linkages. In the early phases complexity increases and after reaching its peak in the mature phase decreases.
- The next pictures put the linkages between the cluster member firms in the context of a CAS. Starting point are the simple self-organized relationships between the components of the system. At the same time, the system receives information from changes in the external environment. Contradicting amplifying and dampening feedback effects shape the system. The result is the typical complex adaptive behavior of a cluster which makes it difficult to foresight its development. Source: ANDRUS, D.C. 2005. The wiki and the blog: Toward a complex adaptive intelligence community. Studies in Intelligence, 49 3. In comparison with biological systems a human system like a cluster is even more complex.
- GLOUBERMAN, S. & ZIMMERMAN, B. 2002. Complicated and complex systems: what would successful reform of Medicare look like? In Care, C.O.T.F.O.H.Manuscript. Discussion Paper No. 8. Toronto/ Canada. The metaphor that Glouberman and Zimmerman use for complex systems is like raising a child. Every child is unique and must be understood as an individual. A number of interventions can be expected to fail as a matter of course. Uncertainty of the outcome remains. You cannot separate the parts from the whole. The most useful solutions to problems usually emerge from within the family and involve values.
- The traditional approach to cluster management follows the linear logic of strategic planning. This planning and expert-driven approach is suitable when facing simple and complicated problems. Unfortunately, in many situation we face in cluster promotions are complex and will require a different approach.
- As the environment of clusters is more and more characterized by uncertainty, complexity sensitive-approaches gain increasingly relevance.
- After having described clusters as increasingly complex systems, we can ask, how to make sense and deal with complexity.
- A practical tool to make sense of different problems a cluster initiative is facing is the Cynefin framework. The term was created by the knowledge management expert Dave Snowden, and means in his native Welsh languages “place of multiple belongings”. Broadly we can differentiate between ordered and unordered situations. In ordered systems the cause and effect relationship is know (simple domain) or at least knowable (complicated domain). Meanwhile in the unordered area causality is only knowable in retrospective (complex domain) or even completely incoherent (chaotic domain). For some situations it is difficult to decide where they belong. Those once will remain in the central field of disorder.
- The complex domain is the area of the unknown unknowns. The cause and effect relationship is only visible in retrospective and do not repeat. In this area the patterns reveal by probing the system. The practice emerges during experimentation. The situation can move from complex to complicated (but also in the opposite direction, to chaotic).
- How do we now that we are facing a complex situation in cluster management?
- This slide is hidden and can be used during the Q&A session.
- byhttp://www. auralab.co.uk http://whatsthepont.com/tag/innovation/ A complex system has no repeating relationships between cause and effect, is highly sensitive to small interventions and cannot be determined by outcome based targets, hence the need for experimentation; hence when dealing with complex systems there is the need for experimentation. Safe-fail Probes are small-scale experiments that approach issues from different angles, in small and safe-to-fail ways, the intent of which is to approach issues in small, contained ways to allow emergent possibilities to become more visible. The emphasis, then, is not on ensuring success or avoiding failure, but in allowing ideas that are not useful to fail in small, contained and tolerable ways. The ideas that do produce observable benefits can then be adopted and amplified when the complex system has shown the appropriate response to its stimulus. Where systems and the environments in which they exist become increasingly complex, what is known and what can be planned for becomes less certain - introducing and increasing organisational tolerance for failure is more crucial than ever. - See more at: http://cognitive-edge.com/library/methods/safe-to-fail-probes/#sthash.2WtJU0Iv.dpuf
- The metaphor is used to illustrate the difference between theory-informed and merely repetitive practice. When the recipe book user cooks a meal then they get out their best practice document, copy out the list of ingredients and go shopping. As they prepare to cook said ingredients are all neatly weighed out and arranged in small bowls on the work top. The recipe book is open on a stand and its instructions are followed step by step. If they are guest in the kitchen, they may want to have it fully re-engineered before they can even start to cook, especially if they were trained in one of the larger management consultancies cooking schools. If anything goes wrong disaster ensues and you will end up with a take away, possibly flavored by the residual traces of carbon from the earlier catastrophe. In contrast the chef turns up and produces a brilliant meal from whatever you happen to have available in your kitchen and garden. Its a key difference; the chef understands the principles of cooking, taste, etc. As a result they can adapt to the present and evolving future, they are not constrained by best practice, they are liberated by true knowledge. Source: http://cognitive-edge.com/blog/entry/3179/the-chef-the-recipe-book-user
- The characterization of clusters as CAS has implications also for cluster policy.
- The cluster life cycle concept has limits as a characterization how clusters evolve over time. Especially the intrinsic idea of biological ageing cannot be applied fully to industrial clusters. MARTIN, R. & SUNLEY, P. 2011. Conceptualizing Cluster Evolution: Beyond the Life Cycle Model? Regional Studies, Vol. 45 (10) pp. 1299-1318.
- Cluster adaptability
- Serendipity refers to the unplanned appears of radical innovations.
- Recommendations based on: ANDRIANI, P. 2005. The Cluster Effect. University of Birmingham, and ANDRIANI, P. & SIEDLOK, F. 2006. The collapse and regeneration of complex clusters: some evolutionary considerations. Working Paper, Durham Business School, University of Durham. Picture Source: Harnessing serendipity” event in Helsinki on 18th of June, Sebastian Olma & Ilkka Kakko http://karostech.fi
- Are we facing a new paradigm in cluster management and policy?
- cognitive-edge.com/blog/entry/4576/jumping-the-s-curve/ Dave Snowden see Complexity Sense-Making as the new paradigm in Management. This hypothesis can possibly applied also to cluster management and policy.
- Following the same save-to-fail principle recommended by complexity theory, we should not throw the baby out with the bathwater, will say, we do not have say goodbye to all the proven cluster management and policy practices. But we need to be more complexity sensitive and react accordingly.
- The mayor challenge which hinders us to fully embrace complexity is possibly our entrenched cause and effect thinking.