Presentation is loading. Please wait.

Presentation is loading. Please wait.

”Complexity Theory and Innovation Management” Dr. Harri Jalonen Principal lecturer Turku University of Applied Sciences, Finland

Similar presentations

Presentation on theme: "”Complexity Theory and Innovation Management” Dr. Harri Jalonen Principal lecturer Turku University of Applied Sciences, Finland"— Presentation transcript:

1 ”Complexity Theory and Innovation Management” Dr. Harri Jalonen Principal lecturer Turku University of Applied Sciences, Finland


3 Nowadays private and public organizations have to face new challenges. Complexity, uncertainty, crisis, change, and turbulence are common for all kind of organizations. This also questions traditional approaches for innovation management. More theoretical and practical knowledge is needed for the understanding of the approaches, models and tools for supporting the renew and the development of new business models. Adapting complexity theories, this lecture provides a new perspective on innovation management in complex organizations."

4 “One has to make up his mind whether he wants simple answers to his questions – or useful ones… ….you cannot have both.” (Joseph Schumpeter, in 1930)

5 ‘creative destruction’ ”The question is not how capitalism administers existing structures, but how it creates and destroys them, causing continuous progress and improved standards of living for everyone” (Joseph Schumpeter in 1930s)

6 Knowledge/information is the basis for development of new products, production processes, the opening of new markets, adoption of new raw materials, and reorganizing of economic sectors. (Joseph Schumpeter in 1930s)

7 Agenda 1) 10 Starting points 2) What is an organization? 3) What is an innovation? 4) A short introduction to complexity theory 5) Case: ”Managing innovations in complex welfare service systems”

8 1) 10 Starting points


10 a) Data -not yet intrepreted symbols -simple observations -unstructured facts -text that does not answer questions to a particular problem STARTING POINTS (#1)

11 b) Information -”in form”, ”informare” -a flow of meaningful messages or data with meaning/structured data with relevance and purpose -includes all the documents and verbal messages that make sense or can be interpreted by organizational members -transferred or shared among people -involves actions of sensing, collecting, organizing, processing, communicating, and using expressions and representations of own or others’ knowledge -text that answers the questions who, when, what or where STARTING POINTS (#1)

12 c) Knowledge -justified true belief (Platon) -the capacity to act (Sveiby) -experience, values, insights and contextual information -obtained from experts based on actual experience -originates and is applied in minds of “knowers” -personal -involves understanding, using, applying, interpreting: the “knowers” know STARTING POINTS (#1)

13 EXAMPLE Data  exam results Information Extract from a study register A course codeA course mark Knowledge Course marks are exceptional  it´s worthwhile to consider postgraduate STARTING POINTS (#1)

14 VALUE OF INFORMATION/KNOWLEDGE Increase the capacity to act. ”Train leaves from London to Edinburgh” ”Train to Edinburgh leaves 22nd of November 10:15 a.m. from the King’s Cross” STARTING POINTS (#1)

15 Two types of Knowledge (Nonaka & Takeuchi 1995 and Polanyi 1967) TACIT KNOWLEDGE (Subjective) Knowledge of experience (body) Simultaneous knowledge (here and now) Analog knowledge (practice) e.g., Intuitions Unarticulated mental models Embodied technical skills Personal, context -specific EXPLICIT KNOWLEDGE (Objective) Knowledge of rationality (mind) Sequential knowledge (there and then) Digital knowledge (theory) e.g., Meaningful set of information articulated in clear language incl. numbers or diagrams Formal, objective, codifiable STARTING POINTS (#2)


17 Test your tacit knowledge. STARTING POINTS (#2) Karl-Erik Sveiby

18 INFORMATION SEEKING IS COSTLY The optimal amount of information is reached when further efforts are not worth their cost. STARTING POINTS (#3)

19 ”The difference between the information available and the information required for an optimal decision.” (Galbraith, 1973) ”Information can have a positive or negative value depending on whether it is a source of pain or pleasure. People and organizations often do not want more information.” (Weick & Ashford, 2001) STARTING POINTS (#3)

20 STARTING POINTS (#3) Information stickiness (von Hippel, 1994) Information stickiness is a result of costs related to acquire, transfer, and use of information compared to the value or benefit of the information sought Due the stickiness information seekers and information providers do not encounter each other in a way that they are able come to new insights that were not available based on information from one source.

21 ”The VALUE of knowledge is a function of TIME” Business event Data ready for analysis Information delivered Action taken VALUE LOST BUSINESS VALUE TIME ACTION TIME DATA LATENCY ANALYSIS LATENCY DECISION LATENCY (Hackathorn 2004) STARTING POINTS (#4)

22 ”All men by nature desire to know” Aristoteles (384 BC – 322 BC) ”Ignorance is bliss.” (Gray, 1765) STARTING POINTS (#5)

23 The hidden side of the knowledge behavior = information avoidance (Jalonen 2010) Cognitive Social Technological Cultural Economic INFORMATION FILTERS STARTING POINTS (#5)

24 ”ingrained pattern seeking” ”confirmation bias” Nassim Nicholas Taleb (2007) The Black Swan. The Impact of the Highly Improbable. STARTING POINTS (#5)

25 STARTING POINTS (#5) (Taleb 2007)

26 All swans are white – are they? STARTING POINTS (#5)

27 1) Joey seemed happily married. He killed his wife. 2) Joey seemed happily married. He killed his wife to get her inheritance. (Taleb 2007) STARTING POINTS (#5) The second statement seems more likely… However, it is a pure mistake of logic, since the first, being broader, can accommodate more causes, such as he killed his wife because he went mad, because she cheated him with the postman, because he entered a state of delusion and mistook her for a financial forecaster……..

28 Facts Explicit knowledge Hierarchy Boundaries Decision-Making  choices Problem-Solving Measurement Ideas, intuitions Tacit knowledge Interpretation Autonomy, empowerment Interaction Decision-Making  alternatives Problem-Finding Dialogue, communication Knowledge exploitation exploration Logic of convergence Logic of divergence STARTING POINTS (#6) AMBIDEXTROUS ORGANIZATION?


30 (Eppler & Mengis 2004) STARTING POINTS (#7)

31 -too much information -too little information  Information anxiety Uncertainty = absence of information Equivocality, Ambiquity = existence of multiple and conflicting interpretations and lack of understanding (Daft & Lengel 1986, Weick 1995) STARTING POINTS (#7)

32 INFORMATION REDUNDANCY PROBLEM AND INEVITABLE CONDITION …is annoying and time consuming to the user, since the user may need to read the same information multiple times in multiple different documents. Once the user finds a particular piece of information in one document, time should not be wasted reviewing the same information in many other documents (Brill & Dumais 2006). …is an enabling for knowledge creation which is defined as the exitence of information that goes beoynd the immediate operational requirements of organizational members (Nonaka &Takeuchi 1995). STARTING POINTS (#8)

33 Innovation is a world of uncertainty and equivocality! But at the same time uncertainty is a basis for new knowledge! (Moensted 2006) STARTING POINTS (#9)

34 (Moensted 2006) STARTING POINTS (#10) A normal problem for managers is to decide on potential innovation growth projects at an early stages of development. They often face a pressure both to avoid failures of investments in ’false positives’ and also projects later proven successful in other contexts, i.e. ’false negatives’.

35 "Failure is only the opportunity to begin again, only this time more wisely." Henry Ford "Success is the ability to go from failure to failure without losing your enthusiasm." Sir Winston Churchill Clear tendency to fail 56 Reasons Why Most Corporate Innovation Initiatives Fail STARTING POINTS (#10)

36 ”Trying is the first step to failure” Homer Simpson Data-Information-Knowledge Explicit-Tacit Knowledge Uncertainty & Ambiguity Information overload Information redundancy Time Knowledge explotion & exploration Value Information filters Divergence & Convergence Confirmation bias & pattern seeking

37 PROPOSITION #1 Knowledge cannot be managed – only enabled. This is done through a process of interaction, in which people interpret information and make judgements on the basis of it.”

38 2) What is an ORGANIZATION?


40 Some features of organization -it is about people (their needs, ambitions, fears…) -it is about interaction between people (within the same organizational level and between different organizational levels) -it is about other resources (factor of production: capital, machinery…) -it is about goal (setting and achievement) -it is about boundaries (in and out) -it is about management and leadership  It´s more or less messy! WHAT IS AN ORGANIZATION?

41 Organization as a Jigsaw Puzzle There are boundaries (straight edged pieces) Each piece plays a specific role Pieces are highly interconnected Each piece is unique in its nature The solution may be fragile (breaks) The whole is more than the sum of its parts Central and peripheral pieces There are ‘natural groupings’ (colour) Pieces need someone to connect them Speed of solution relies on the ability to ‘see’ the whole picture (Paraskevas 2007) WHAT IS AN ORGANIZATION?


43 ”It´s not the strongest of the species that survive nor the most intelligent, but the one most responsive to change” ( Charles Darwin) In what ways can it be paralleled to an organization? WHAT IS AN ORGANIZATION?

44 Is it ”a machine” or ”machine-like OR Is it ”an organism like dynamic living system”? WHAT IS AN ORGANIZATION?

45 ORGANIZATION as a SYSTEM A system is any set of mutually interdependent elements that co-exist with a purpose. The mutual interdependence of a system means that changes introduced into one part of the system will bring about changes elsewhere. (Paraskevas 2007) WHAT IS AN ORGANIZATION?

46 (Paraskevas 2007) WHAT IS AN ORGANIZATION?

47 WHAT IS AN ORGANIZATION? As the ontology shifts, epistemological and methodological consequences are explicit…

48 48 The Two Cultures of Management* a nature of problems a nature of solutions complexity uncertainty unpredictability Old and routine problems Only old ideas are needed Skills and knowledge are at use Risks can be calculated Best fit can be found New and changing problems New and novel ideas are needed New skills and knowledge are needed Uncertainty not turned into risk Create knowledge to meet an evolving world * Charles Percy Snow, The Two Culture and Scientific Revolution WHAT IS AN ORGANIZATION?

49 49 Traditional Management It means simply this: Make an analysis of your environment, design your strategies, make everybody align with them, and act It means simply this: Make an analysis of your environment, design your strategies, make everybody align with them, and act Plan, act, evaluate, and correct (Harisalo 2009) WHAT IS AN ORGANIZATION?

50 50 Assumptions of Traditional Management Knowledge is a product – its only problem is how to find it Knowledge helps to recognize strong trends Strong trends helps to decide what the organization will do and provide to its customers These decisions – strategic of their nature – require biggest possible consensus – unanimity – in the organization Aligning the organization requires hierarchy in division of labor Strategic purposes legitimize the organization’s existence (Harisalo 2009) WHAT IS AN ORGANIZATION?

51 51 Interaction as a Strategic Way to Create Value It means simply this: Value is created together with service professionals and clients It means simply this: Value is created together with service professionals and clients Designing, experimenting, implementing, and correcting are reciprocal processes (Harisalo 2009) WHAT IS AN ORGANIZATION?

52 52 Assumptions of Reciprocal Management Its true nature is research and development: –from implementing to meeting new challenges in work Novel ideas and knowledge are created in interaction: –from knowledge management to managing ignorance in work –from executing plans to discovering possibilities Divergent thinking, different thinking, paradoxes, and constructive opposites are needed to speed up interaction: –the job of managers is to pave way to these things which in traditional management were barriers of efficiency and effectiveness Experiments in small scale must be allowed and managerial responsibilities must be decentralized (Harisalo 2009) WHAT IS AN ORGANIZATION?

53 PROPOSITION #2 Organizations are organic, living systems. People in complex organizations hardly even accomplish their joint actions and goals following entirely the designed systems and processes. Pre-designed systems simply cannot encompass every event in complex environments. However, coherent efficient action can (and should) take place also in complex environments.

54 3) What is an INNOVATION?

55 Innovation is the generation, acceptance and implementation of new ideas, processes, products or services which have (economic) value (Rogers 1983) Radical innovation The creation of something entirely new Incremental innovation Primarily adaption of an existing product or process WHAT IS AN INNOVATION?

56 “Seeing things in a new way” & “Doing things differently” (Joseph Schumpeter, 1934) Novelty in action (Altshuler & Zegans 1997) WHAT IS AN INNOVATION?

57 Every idea has been an innovation sometimes. Any list of innovations must change with the times. (Rogers & Shoemaker, 1971) Novelty is context-dependent! WHAT IS AN INNOVATION?

58 “Innovation is work rather than play: Everything always comes from work, including the free gift of the idea that arrives.” (Meier 2007) “Chance favours only the prepared minds.” (Pasteur ) WHAT IS AN INNOVATION?

59 “Innovation is a ’moment of danger’ because you loose control.” (Meier 2007) WHAT IS AN INNOVATION? Innovation is not good nor bad!




63 Dilemmas in management of innovations EquilibriumDynamic StabilityChange Fit to modelCreating model AnalysisIntuition Exploiting opportunitiesExploring opportunities KnownNot yet known ManagementEntrepreneurship ClosenessOppeness WHAT IS AN INNOVATION? AMBIDEXTROUS ORGANIZATION?

64 PROPOSITION #3 What is needed is not ‘good design’ for innovation per se, but creation of the conditions that allow the emergence of innovation.

65 4) A short introduction to complexity theory

66 Complexity - a situation or a problem that is difficult to understand or complicated to handle English word ”complex” is derived from the Latin Complex behaviour arises from the intricate inter-twining or inter- connectivity of elements within a system and between a system and its environment (Mittleton-Kelly 2003) COMPLEXITY THEORY

67 Complexity – a basic property of a system Complexity enriches traditional systems theory by amplifying additional characteristics of complex systems and by stressing their inter-relationship and interdependence (Mittleton-Kelly 2003) Complexity does not comprise a single, unified theory but rather a family of theories, arising from the fields of biology, physics, chemistry, computer simulation, evolution and mathematics (Mittleton-Kelly 2003). COMPLEXITY THEORY

68 Entropy is important factor of the process of self-organization. Self-organization consisting of phases such as production of entropy, disequilibrium and chaos, reduction of entropy and finally new organization. 1) SELF-ORGANIZATION Self-organization is a more or less spontaneous process without externally applied coercion or control. (Ståhle 2004) COMPLEXITY THEORY

69 In case of social systems, entropy can be understood as a capability to produce and reduce information. Entropy forms the basic dynamics of social systems. An increasing of information may have various consequences. When considered in the context of social system, increasing of information opens up new possibilities, but it also means exclusion of others. Information can be understood simultaneously both as a potential as well as a significant source of threat. COMPLEXITY THEORY

70 The whole is something that cannot be foreseen from what is known of the component parts. (Lewin 1993) 2) EMERGENCE Emergence means complex organizational structure growing out of simple rules. COMPLEXITY THEORY

71 What is important is that systems may have a great diversity of components but relatively simple relations between parts such as most machines and technical systems. In other words, it is not just the great number of interactions but the quality of those interactions. Complex behaviour of the system emerges from the connectivity and interdependence its parts (Mitleton-Kelly 2003). COMPLEXITY THEORY

72 3) FAR-FROM-EQUILIBRIUM, SPACE OF POSSIBILITIES, BIFURCATION and PATH-DEPENDENCY Far-from-equilibrium means that the complex system is continually changing. To ensure its survival, the system has to be able to produce and reduce entropy. Bifurcation point is a choice between two or more possibilities which are constrained by earlier choices (path-dependency). Space of possibilities implies that it is impossible to explore all possibilities. Path-dependency means that every choice of individual is the result of a individuals selection among a finite set of perceived choices as well as the past choices made that have shaped that individuals life path. COMPLEXITY THEORY

73 (Mitleton-Kelly 2003, Nicolis & Prigogine 1989) COMPLEXITY THEORY

74 The complexity theory sees conflicts and opposite interests as triggers which create tensions and multiply interactions of the system Conflicts and opposite interests can be seen as imperative nodes that forces system to make choices. In complexity theory, these nodes are called bifurcation points. They are some kind of the moment of truth in which the system has different options. When a social entity is faced with a bifurcation point, it endows the entity space of possibilities (Mitleton-Kelly 2003). Therefore, the bifurcation can be seen as a source of innovation. The alternatives at the bifurcation point “are sources of innovation and diversification, since the opening up of possibilities endows the individual and the system with new solutions” (Mitleton-Kelly 2003) COMPLEXITY THEORY

75 4) DIVERSITY Diversity is the state or quality of being different. Increasing the diversity of the system means more observation capabilities and fewer blind spots. (Jalonen 2007) COMPLEXITY THEORY An actor of the system ”World” that the system can observe

76 Ashby´s law of requisite variety (1957): a system has to have enough resources at its disposal to be able to cope with the complexity of its environment. In other words, the principle of requisite variety implies that the complexity of environment can be met by the complexity of system. (Clippinger 1999) COMPLEXITY THEORY


78 5) CONNECTIVITY and INTERDEPENDENCE Connectivity and interdependence points that actions by any individual may affect (constrain or enable) related individuals and systems. Because of limited information capacity of individual actors, to solve highly interconnected and multidimensional (i.e. wicked) problems or to realize promising policies and generating innovations, there is the need to for interactions between a wide variety of actors (Kooiman 1993; Castells 1996, Sotarauta 1997). Such interaction may generate not only a larger information and knowledge base than an individual, but also a better one on which to base decisions. COMPLEXITY THEORY

79 (Jalonen 2007) COMPLEXITY THEORY

80 6) FEEDBACK and NON-LINEARITY Without feedback there is no emergence or self-organization. Positive feedback enhances and stimulates systems capability, whereas effects of negative feedback are opposite (detracting, inhibiting). Non-linearity implies that behavior of the system may not depend on the values of the initial conditions. In complex systems, dynamical interactions are non-linear, i.e. small causes can have large results, and vice versa. A system is dynamical when it changes over time. “The flap of a butterfly´s wings in Brazil set off a tornado in Texas” (Lorenz, 1963 COMPLEXITY THEORY

81 (Jalonen 2007) Circular interdependence COMPLEXITY THEORY

82 7) CO-EVOLUTION Connectivity applies not only to components within a system but also to related systems. It can be said that a system and its environment “co- evolves”, with each adapting to the other. Interactions and interdependencies between system and its environment. Co-evolution means “that the evolution of one domain or entity is partially dependent on the evolution of other related domains or entities, and that one domain or entity changes the context of the other(s)” (Mitleton-Kelly 2003). Adaptation & Selection COMPLEXITY THEORY


84 Adapted Sotarauta & Srinivas 2005 COMPLEXITY THEORY

85 PROPOSITION #4 Organisations as complex systems: i) do not ‘behave’ in a straightforward predictable way, ii) consist of a huge number of diverse interrelated elements, iii) trivial causes can have massive effects (no linear relation between cause and effect), iv) control over the system is virtually impossible and v) dapt to environmental changes and evolve together with their environment.


87 5) Case: ”Managing innovations in complex welfare service systems” by Harri Jalonen & Pekka Juntunen A paper presented at ICEG 2010 in Cape Town, South Africa. The paper is currently in review process to be published in Baltic Journal of Management

88 A Starting Point (1/2) A growing number of welfare services are being provided through co-operation between the public and private sectors. i) Co-operation = fertile ground for innovations in welfare services. ii) Co-operation = creates complicated organisational interlacing, which, in turn, may lead to a situation where this innovation potential remains unrealised.  It is these public-private partnerships that are seen to produce complex welfare service systems that cannot be understood on the basis of what is known about the individual components of these systems. CASE

89 A Starting Point (2/2) Innovation = novelty in action Innovation = “seeing things in a new way” and “doing things differently” Experimentation and high tolerance of risk-taking and fail as success mechanisms for innovation. It is argued that the public sector suffers from a lack of success mechanisms. The public sector has ‘asymmetric incentives’ for innovations. The incentives are asymmetric because successful innovations are not rewarded, while unsuccessful innovations may have grave consequences. However, innovations are needed, partly due to an increasing pressure to respond to the demands from the customers and partly due to diminishing resources for supplying services. CASE

90 Aim and research question The main aim of this paper is to develop a framework that deepens our understanding of managing innovations in a welfare service system. What kinds of management practices can be used in supporting innovative actions in complex welfare systems? The paper concentrates on the interaction processes within the welfare service system and between the welfare system and the surrounding environment. CASE

91 Research design Qualitative methods  purpose is to gain an understanding of how practitioners “define the situation”. The empirical data was collected by conducting semi-structured interviews with leading office holders and representatives [n=50] of welfare service providers in the Helsinki region of Finland. All of the interviewees hold a manager or director position in their organization. Based on the interviewees’ experience, it is reasonable to expect that they have “something to say on the topic”. The topics for the interviews were determined by issues identified in the relevant innovation and complexity literature. The empirical material collected in these interviews was analyzed using Yin’s (2003) pattern matching logic. In our paper, pattern matching refers to a method whereby the interview material was interpreted with the concepts of complexity theories. CASE

92 Research site The value network of social services in the City of Helsinki (Finland). The City of Helsinki is a large municipal organization with around 40,000 employees and an annual expenditure of around 3,000 million Euros. -highly fragmented and difficult to perceive  the value network has been launched as a strategic concept for describing the complex operating environment. The Social Services Department has five responsibilities: Child Day Care Services, Services for Families with Children, Adult Services, Elderly Services and Management and Development Centre. The department produces welfare services in about 700 units. Services are also bought from about 600 external producers. The amount of outsourced services has steadily increased and in 2008 the department was buying services with about 220 million Euros. The value network of Social Services Department has formed during a long historical continuum and today, it forms a multi-layer network of very diverse agreements and relationships. This particular service system provides an interesting field for the development of system- level innovation thinking due its societal importance and its highly intangible outputs and outcomes. CASE COMPLEX SYSTEM

93 Complexity as Theoretical Framework (1/3) Complexity refers to the feature of the system. A system can be defined as a complex system if it exhibits an emergence phenomenon occurring due to the connectivity and diversity of its parts. ‘Emergence’ refers to the “coming-into-being of novel, ‘higher’ level structures, patterns, processes, properties, dynamics and laws, and how this more complex order arises out of the interactions among components that make up the system itself”. While the complex system is aggregated from its parts, the interplay between these parts produces emergent patterns that cannot be analytically reducible to the constituent parts. In practice emergence results from the process whereby each welfare service provider continually decides which other organizations it will engage with, and what information and other resources it will exchange with them. CASE

94 Complexity arises from the nature of the issues in the welfare domain. Public policy problems can be characterized as ‘malignant’, ‘vicious’ and ‘tricky’. Such problems, especially in the welfare domain, are “wicked problems” in the sense that they have no definitive formulation; solutions are not true or false; there is no test for a solution; every solution has a consequence; they do not have simple causes; and they have numerous possible explanations, which, in turn, frame different policy responses. In health care, for instance, a good example of a wicked problem is the goal of increasing equality in the service delivery while simultaneously trying to decrease the costs of the care. Complexity as Theoretical Framework (2/3) CASE

95 Complexity as Theoretical Framework (3/3) Complexity of objectives and values in the public sector. Compared to the private sector, the public sector fulfils various values and pursues multiple goals. Efficiency = reduction in the cost of operation and in the generation of profits AND procedural adherence to the rule of law, due process and obedience to legislative mandates. The public sector suffers ‘innovation deficit’, which can be explained by the detrimental side- effects of pursuing efficiency. Innovation is difficult in the public sector because the goal of efficiency is inconsistent with the goal of innovation. Paradoxically, ‘good values’, such as efficiency, accountability and transparency, may lead to the emergence of higher level [a]dynamics, which can ossify the structures of welfare provision. An emergence, in this sense, manifests itself as an inability of the welfare service system to change and grow through experimental endeavour in order to meet new environmental threats and opportunities. CASE

96 ”Trying is the first step to failure” Homer Simpson A story of successful innovation is actually that ‘form follows failure’. “When fear of failure replaces a capacity to experiment and create trial and error learning, the result is unlikely to be an artefact that actually works” (Potts, 2009) The real issue is how, on the one hand, to facilitate the processes of “seeing things in a new way”, and, on the other hand, how to ensure that “things are done differently”. CASE

97 Innovation supportive conditions (1/4) TRUST “ ideas are often generated when someone discovers the problem. If you can trust that you are not in trouble when you tell problems, it could encourage more innovation”. “...service providers do not always bring out the problems involved service provision because they fear that it worsens their position in the negotiations with the Social Services is this uncertainty or lack of confidence that pull the rug from under the development of new ways of action” CASE

98 Innovation supportive conditions (1/4) Creating trust Trust helps to build up space for creativity innovation, and encourages people to ’see things differently’. It enables playing with ideas. Personal and system trust  new ideas are given every chance to succeed. Important is that personal and system trust not only reduces complexity and makes up for obscurity caused by imperfect knowledge but also increases certainty, because certainty does not call for correct and certain knowledge but rather the fact that the actors can predict each other’s behaviour. Trust increases the welfare service system´s ability to take risks and withstand failures. An atmosphere of trust lowers the mental threshold that suppresses thinking that differs from the conventional. CASE

99 Innovation supportive conditions (2/4) RESPONSIVENESS “…if you want real partnership, I mean not just rhetoric of partnership, the service delivery should be considered in open and dialogic conversations between service providers and the Social Services Department... dictate do not lead to best outcomes”. “The cruel fact is that we [private sector service providers] compete to get the contract with the Social Services Department.” “it is not reasonable to regard other service providers just as rivals......sometimes the most valuable innovation impulses come from them......therefore it is important to seek informal settings where you can meet and exchange thoughts with colleagues from outside your own organization.” CASE

100 Innovation supportive conditions (2/4) Increasing communication responsiveness Responsiveness refers to reciprocal communication processes where the actors of the system co-create relationships that “evoke potential in a trusting environment”. Responsive communication processes create trust, which, in turn, can increase the welfare service system’s capacity to renew itself and generate new services. Innovations are rooted in the interplay between the cooperative–competition intentions of the actors. Instead of imposing innovation from the ‘centre of the welfare service system’, innovation should be allowed to emerge from the ‘periphery of the welfare service system’. Therefore, the task of innovation management is not to control the actors but to facilitate responsive processes, which, in the words of Schön (1973), include “detecting significant shifts at the periphery, paying explicit attention to the emergence of ideas in good currency, and deriving themes of policy by induction”. CASE

101 Innovation supportive conditions (3/4) Connectivity and interdependencies “We don´t operate very well in the system level. There is a lot of administrative hurdles between the social services and the health care services... especially in elderly care......These hurdles hinder developing customer-oriented services......sometimes we forget that the customers’ problems don´t follow the logic of administration.” “ is not easy to talk about new seems that they [the Social Service Department] just politely listen what we tell them......too often ideas remain ideas......don´t proceed to the implementation stage......there is some kind of cultural stickiness.” “Sometimes we ask service providers to introduce new ideas of how to meet the changing needs of citizens. I think it is reasonable to expect that service providers with the best experience in the field could think services from the new perspectives and develop new kind of services......However, we have found that there are service providers that are not very seems like they miss old good days and don't want to see the reality of what happened.” CASE

102 Innovation supportive conditions (3/4) Utilising connectivity and interdependencies Connectivity and interdependency are essential for the system´s evolution. It is the degree of connectivity which determines the network of relationships and the transfer of information and knowledge. ‘Strong’ and ‘weak’ ties (Granovetter, 1973). Weak ties improve the welfare service systems´ ability to see things “in a new light”, whereas strong ties support the conversion of seeing into “doing differently”. Weak and strong ties increase information redundancy in the welfare service system. Information redundancy is important for innovation because it means the use of more elements than necessary to maintain the performance of the system in the event of failure of one or more of the elements. In other words, information redundancy reduces the fear of failure, which, is one of the main obstacles to innovation. CASE

103 Innovation supportive conditions (4/4) Diversity “Diversity is important because the needs of clients are varied… …it is not possible to develop new services without understanding of various needs, and getting understanding requires knowledge that is dispersed different actors.” CASE

104 Innovation supportive conditions (4/4) Pursuing diversity Most people take risks on the basis of known rather than unknown probabilities. ‘Playing safe’ may be disastrous in the decision domains around innovation, because the usefulness of innovation cannot be known a priori may induce public organizations to play safe and stay away from uncertainty and experimentation. ’Boundary spanning’ = a combination of the different functions, processes and roles that are used by the actors who try to guide their interaction in a direction that produces results. ‘Boundary spanners’ = information filters & knowledge interpreters  regulate the flows of information that both come into the system from the environment and go out of the system, and change information into forms others can understand. They ensure that the welfare service system not only has clearly expressed rules and guidelines but also openness to new ideas and influences, and a willingness to change old patterns. CASE

105 Conclusions While adapting the complexity-based interpretation that the innovation is emergent in its nature, we do not claim that an emergence is the result of a process of pure self- organization. Instead of claiming that innovations “simply happen” or “bubble up”, we believe that a new order, i.e. innovation, is more appropriately constructed rather than self-organized as such (cf. Hazy et al 2007, Goldstein 2003). Adapting Hazy et al (2007), we think that innovation requires constant support and resources. The ‘success’ of an innovation much depends on the attention the actors bring to the innovation process. We argue that by paying attention to trust, responsive communication processes, connectivity, interdependencies and diversity, it is possible to create favourable conditions for innovations in complex welfare systems. CASE

106 Enables INNOVATION as a COMPLEX PROCESS TRUST INTERACTION Communication in strong & weak ties Builds DYNAMIC CREATIVE ABRASION Diversity of ideas Information redundancy Power conflicts Controversial interests Emerges POSITIVE FEEDBACK NEGATIVE FEEDBACK Strengthen Crumbling Equivocality Ambiquity INNOVATION DEADLOCK ‘CREATIVE DESTRUCTION’

107 See more.... Aasen, T. M. B. (2009) Innovation as social processes. A participative study of the Statoil R & D program Subsea Increased Oil Recovery (SIOR), Norwegian University of Science and Technology. Fonseca, J. (2002) Complexity and innovation in organizations. New York: Routledege. Jalonen, H. & Juntunen, P. (2011?) “A Framework for Enabling Innovation in Complex Welfare Service Systems”, Baltic Journal of Management

Download ppt "”Complexity Theory and Innovation Management” Dr. Harri Jalonen Principal lecturer Turku University of Applied Sciences, Finland"

Similar presentations

Ads by Google