The Floriculture Industry
Corresponding author Faculty, School of Management and Leadership
Tel: (020) 2361160/ 2361161 Official email: [email protected] Abstract
This is a concept paper based on literature review on complex adaptive systems and the research findings on the floriculture industry in Kenya. A wide range of issues on complex adaptive systems are discussed. These issues include: definition of complexity; the meaning
systems; the level of complexity of the floriculture industry in Kenya and managing complex adaptive systems. Preliminary research findings on the supply networks optimisation under complexi
apparent that there is a need for further developments in all these areas. As such, the issues provide a basis for a research agenda in complex adaptive systems.
Key words: Complex adaptive system, Complex adaptive environmen 1.0 Introduction
Complex adaptive systems as a field of study began in the mid
distinguished by extensive use of computer simulation as a research tool, and emphasis on systems, such as markets or ecologies, which are less integrated or “organised” than the ones studied by the older tradition ( e.g. organisms, machines and companies) ( Chan, 2001).
The paper aims to outline the key issues in complex adaptive systems. Based on a review of current liter ture in the field a series of issues are identified. The aim is not to address the issues here. The hope is that in identifying the issues and the extent to which they have (or have not) been identified a research agenda for co plex adaptive systems in the floriculture industry in Kenya might emerge. The issues are discussed under the following headings: i) definition of complexity; ii) the meaning of complex adaptive systems; iii) characteristics of complex adaptive systems; iv) the level of complexity of the
adaptive systems.
Floricultural exports are Kenya’s biggest export earning, surpassing tourism as of the year 2008. The value of the exports rose from Ksh. 1 billion in 1990 to a record over Ksh. 43 billion in
sector has averaged over 10% for the past five years and is projected to continue. Hence, the economic stability of the country is dependent on the continued success of the industry (HCDA, 2008). Floriculture in particular is estimated to employ over 100,000 people directly, while indirect employees in transport, packaging, inputs etc are approximately 1.2 million people who derive a livelihood from the export industry. The fact that these e ployments are in the rural areas is ve
to poverty alleviation, a major focus of the government (Kenya Economic Survey, 2009). 2.0 The meaning of complex adaptive systems
Concepts that deal with complex adaptive syste
environment (CAE) have many names: chaos theory (Tetenbaum, 1998), complexity theory (Smith, 2005), co plex science (Kelly and Allison, 1999; Stacey, 2003) and systems thinking (Senge, 1990). Com
from the inter-relationships, inter-action and interconnectivity of elements within a system and between a system and its environment (Chan, 2001). The meaning of complexity is traced to the word
entwined, from which is derived complexus, meaning braided together (Gell
complex is derived from latin. Complex adaptive systems (CAS) on the other hand results in a complex adaptive environments.
Complex adaptive systems are dynamic systems able to adapt in and evolve with a changing environment. It is important to realise that there is no separation between a system and its environment in the idea that a sy tem always adapts to a changing environment. Rath
linked with all other related systems making up an ecosystem. Within such a context, change needs to be seen in terms of co-evolution with all other related systems, rather than as adaptation to a
ment (Chan, 2001). In reality change, especially large scale changes, defies logical rules and simple management
The Floriculture Industry in Kenya: A Complex Adaptive
Environment
Corresponding author , Emmanuel Awuor
Faculty, School of Management and Leadership, The Management University of Africa
PO BOX 29677-00100， NAIROBI
Tel: (020) 2361160/ 2361161, Personal mobile: 254(0)720405692 [email protected], Personal email: [email protected]
cept paper based on literature review on complex adaptive systems and the research findings on the floriculture industry in Kenya. A wide range of issues on complex adaptive systems are discussed. These issues include: definition of complexity; the meaning of complex adaptive systems; characteristics of complex adaptive systems; the level of complexity of the floriculture industry in Kenya and managing complex adaptive systems. Preliminary research findings on the supply networks optimisation under complexity are also highlighted. It is apparent that there is a need for further developments in all these areas. As such, the issues provide a basis for a research agenda in complex adaptive systems.
Key words: Complex adaptive system, Complex adaptive environment.
Complex adaptive systems as a field of study began in the mid-1980 at the Santa Fe Institute in Mexico. It is distinguished by extensive use of computer simulation as a research tool, and emphasis on systems, such as es, which are less integrated or “organised” than the ones studied by the older tradition ( e.g. organisms, machines and companies) ( Chan, 2001).
The paper aims to outline the key issues in complex adaptive systems. Based on a review of current liter in the field a series of issues are identified. The aim is not to address the issues here. The hope is that in identifying the issues and the extent to which they have (or have not) been identified a research agenda for co
riculture industry in Kenya might emerge. The issues are discussed under the following headings: i) definition of complexity; ii) the meaning of complex adaptive systems; iii) characteristics of complex adaptive systems; iv) the level of complexity of the floriculture industry and; v) managing complex Floricultural exports are Kenya’s biggest export earning, surpassing tourism as of the year 2008. The value of the exports rose from Ksh. 1 billion in 1990 to a record over Ksh. 43 billion in 2008. Annual growth in the sector has averaged over 10% for the past five years and is projected to continue. Hence, the economic stability of the country is dependent on the continued success of the industry (HCDA, 2008). Floriculture in particular is timated to employ over 100,000 people directly, while indirect employees in transport, packaging, inputs etc are approximately 1.2 million people who derive a livelihood from the export industry. The fact that these e ployments are in the rural areas is very important, as it not only stems rural urban migration but also contributes to poverty alleviation, a major focus of the government (Kenya Economic Survey, 2009).
2.0 The meaning of complex adaptive systems
Concepts that deal with complex adaptive systems (CAS), hence facilitating operation in a complex adaptive environment (CAE) have many names: chaos theory (Tetenbaum, 1998), complexity theory (Smith, 2005), co plex science (Kelly and Allison, 1999; Stacey, 2003) and systems thinking (Senge, 1990). Com
action and interconnectivity of elements within a system and between a system and its environment (Chan, 2001). The meaning of complexity is traced to the word plexus
entwined, from which is derived complexus, meaning braided together (Gell-Mann, 1996). Hence, the word complex is derived from latin. Complex adaptive systems (CAS) on the other hand results in a complex adaptive daptive systems are dynamic systems able to adapt in and evolve with a changing environment. It is important to realise that there is no separation between a system and its environment in the idea that a sy tem always adapts to a changing environment. Rather, the concept to be examined is that of a system closely linked with all other related systems making up an ecosystem. Within such a context, change needs to be seen in
evolution with all other related systems, rather than as adaptation to a separate and distinct enviro ment (Chan, 2001). In reality change, especially large scale changes, defies logical rules and simple management
Kenya: A Complex Adaptive
The Management University of Africa
cept paper based on literature review on complex adaptive systems and the research findings on the floriculture industry in Kenya. A wide range of issues on complex adaptive systems are discussed. These issues of complex adaptive systems; characteristics of complex adaptive systems; the level of complexity of the floriculture industry in Kenya and managing complex adaptive systems. ty are also highlighted. It is apparent that there is a need for further developments in all these areas. As such, the issues provide a basis for a
1980 at the Santa Fe Institute in Mexico. It is distinguished by extensive use of computer simulation as a research tool, and emphasis on systems, such as es, which are less integrated or “organised” than the ones studied by the older tradition ( e.g. The paper aims to outline the key issues in complex adaptive systems. Based on a review of current litera-in the field a series of issues are identified. The aim is not to address the issues here. The hope is that litera-in identifying the issues and the extent to which they have (or have not) been identified a research agenda for
com-riculture industry in Kenya might emerge. The issues are discussed under the following headings: i) definition of complexity; ii) the meaning of complex adaptive systems; iii) characteristics floriculture industry and; v) managing complex Floricultural exports are Kenya’s biggest export earning, surpassing tourism as of the year 2008. The value 2008. Annual growth in the sector has averaged over 10% for the past five years and is projected to continue. Hence, the economic stability of the country is dependent on the continued success of the industry (HCDA, 2008). Floriculture in particular is timated to employ over 100,000 people directly, while indirect employees in transport, packaging, inputs etc are approximately 1.2 million people who derive a livelihood from the export industry. The fact that these
em-ry important, as it not only stems rural urban migration but also contributes
ms (CAS), hence facilitating operation in a complex adaptive environment (CAE) have many names: chaos theory (Tetenbaum, 1998), complexity theory (Smith, 2005), com-plex science (Kelly and Allison, 1999; Stacey, 2003) and systems thinking (Senge, 1990). Comcom-plexity results
action and interconnectivity of elements within a system and between a system plexus meaning braided or Mann, 1996). Hence, the word complex is derived from latin. Complex adaptive systems (CAS) on the other hand results in a complex adaptive daptive systems are dynamic systems able to adapt in and evolve with a changing environment. It is important to realise that there is no separation between a system and its environment in the idea that a
sys-er, the concept to be examined is that of a system closely linked with all other related systems making up an ecosystem. Within such a context, change needs to be seen in separate and distinct environ-ment (Chan, 2001). In reality change, especially large scale changes, defies logical rules and simple manageenviron-ment
actions (Stacey, 2003). Complex theory and a view of organisations as “complex adaptive systems”, attempts to consider some of those realities and arguably provides a better model for change when considering the floricu ture industry in Kenya.
2.1 Characteristics of complex adaptive systems
According to Gisogon (2006), a system is considered to be complex when: i) Ca
worked – i.e. simple cause –effect relationships does not apply. There are many contributing causes and infl ences to any one outcome; ii) The number of plausible options is vast
of finding the one best solution in a reasonable amount of time; iii) Systems behavior is coherent curring patterns and trends, but; iv) The system is not fixed
seem to keep changing. Something that “worked” yesterday may not do so tomorrow and; v) Predictability is reduced – for a given action option it is not possible to accurately predict all its consequences, or for a desired set of outcomes it is not possible to determine precisely whic
According to Stacey (1996): “Most textbooks focus heavily on techniques and procedures for long planning, on the needs for visions and missions, on the importance and the means of securing strongly shared values, on the equation of success with consensus, consistency, uniformity and order. However, in complex e vironments the real management task is that of coping with and even using unpredictability, clashing and cou ter-cultures, disensus, contention, conflict and inconsist
managers has to do with instability, irregularity, difference and disorder”.
The following propositions by Stacey (1996) as a basis for complex theory and applicable to the floricu ture industry in Kenya also needs to be considered: i) All organisations are webs of non
connected to other people and organisations by webs of non are capable of operating in states of stable and
far from equilibrium, in bounded instability at the edges of chao, .iii) All organisations are paradoxes. They are pulled towards stability by forces of integration, maintenance control
and adaptation to the environment on the one hand. They are also pulled towards the opposite extreme of unst ble equilibrium by the forces of division and decentralisation, human desires for excitement and innova isolation from the environment, iv) If the organisation gives in to the pull of stability and it fails because it b comes ossified and cannot change easily. If it gives in to the pull of instability it disintegrates. Success lies in sustaining an organisation at the border between stability and instability. This is a state of chaos and difficult to maintain dissipative structures.
It is further affirmed by Stacey ( 1996) that: i) the dynamics of the successful organization are therefore those of irregular cycles and discontinuous trends, falling within the quantitative patterns, fuzzy but recognisable categories taking the form of archetypes and templates; ii) because of its own internal dynamic, a successful o ganisation faces completely unknowabl
long-term future, nor can they install specific frameworks to make it successful nor can they apply step analytical reasoning or planning or ideological controls to long
only do these things in relation to the short term; iv) Long term development is a spontaneous self process from which new strategic directions may emerge. Spontaneous self organization is political
and learning groups. Managers have to pursue reasoning by analogy; v) in this way managers create and discover the environments and the long-term futures of the organisation.
The general approach to complex adaptive environments can be visuali certainty matrix (Stacey, 2003):
actions (Stacey, 2003). Complex theory and a view of organisations as “complex adaptive systems”, attempts to ider some of those realities and arguably provides a better model for change when considering the floricu 2.1 Characteristics of complex adaptive systems
According to Gisogon (2006), a system is considered to be complex when: i) Causality is complex and ne effect relationships does not apply. There are many contributing causes and infl ences to any one outcome; ii) The number of plausible options is vast – it is not possible to optimise (in the sense
inding the one best solution in a reasonable amount of time; iii) Systems behavior is coherent
curring patterns and trends, but; iv) The system is not fixed – the patterns and trends vary, for example, the “rules” hing that “worked” yesterday may not do so tomorrow and; v) Predictability is for a given action option it is not possible to accurately predict all its consequences, or for a desired set of outcomes it is not possible to determine precisely which actions will produce it.
According to Stacey (1996): “Most textbooks focus heavily on techniques and procedures for long planning, on the needs for visions and missions, on the importance and the means of securing strongly shared
tion of success with consensus, consistency, uniformity and order. However, in complex e vironments the real management task is that of coping with and even using unpredictability, clashing and cou
cultures, disensus, contention, conflict and inconsistency. In short the tasks that justifies the existence of all managers has to do with instability, irregularity, difference and disorder”.
The following propositions by Stacey (1996) as a basis for complex theory and applicable to the floricu in Kenya also needs to be considered: i) All organisations are webs of non
connected to other people and organisations by webs of non-linear feedback loops, ii) Such non
are capable of operating in states of stable and unstable equilibrium, or in the borders between these states, that is far from equilibrium, in bounded instability at the edges of chao, .iii) All organisations are paradoxes. They are pulled towards stability by forces of integration, maintenance controls, human desires for security and certainty and adaptation to the environment on the one hand. They are also pulled towards the opposite extreme of unst ble equilibrium by the forces of division and decentralisation, human desires for excitement and innova isolation from the environment, iv) If the organisation gives in to the pull of stability and it fails because it b comes ossified and cannot change easily. If it gives in to the pull of instability it disintegrates. Success lies in
organisation at the border between stability and instability. This is a state of chaos and difficult to It is further affirmed by Stacey ( 1996) that: i) the dynamics of the successful organization are therefore rregular cycles and discontinuous trends, falling within the quantitative patterns, fuzzy but recognisable categories taking the form of archetypes and templates; ii) because of its own internal dynamic, a successful o ganisation faces completely unknowable specific futures, iii) agents within the system cannot be in control of its
term future, nor can they install specific frameworks to make it successful nor can they apply step
analytical reasoning or planning or ideological controls to long term development. Agents within the system can only do these things in relation to the short term; iv) Long term development is a spontaneous self
process from which new strategic directions may emerge. Spontaneous self organization is political
and learning groups. Managers have to pursue reasoning by analogy; v) in this way managers create and discover term futures of the organisation.
The general approach to complex adaptive environments can be visualised using the Stacey agreement vs. actions (Stacey, 2003). Complex theory and a view of organisations as “complex adaptive systems”, attempts to ider some of those realities and arguably provides a better model for change when considering the
floricul-usality is complex and net-effect relationships does not apply. There are many contributing causes and influ-it is not possible to optimise (in the sense inding the one best solution in a reasonable amount of time; iii) Systems behavior is coherent – there are
re-the patterns and trends vary, for example, re-the “rules” hing that “worked” yesterday may not do so tomorrow and; v) Predictability is for a given action option it is not possible to accurately predict all its consequences, or for a desired set According to Stacey (1996): “Most textbooks focus heavily on techniques and procedures for long-term planning, on the needs for visions and missions, on the importance and the means of securing strongly shared tion of success with consensus, consistency, uniformity and order. However, in complex en-vironments the real management task is that of coping with and even using unpredictability, clashing and coun-ency. In short the tasks that justifies the existence of all The following propositions by Stacey (1996) as a basis for complex theory and applicable to the
floricul-in Kenya also needs to be considered: i) All organisations are webs of non–lfloricul-inear feedback loops linear feedback loops, ii) Such non-linear systems unstable equilibrium, or in the borders between these states, that is far from equilibrium, in bounded instability at the edges of chao, .iii) All organisations are paradoxes. They are s, human desires for security and certainty and adaptation to the environment on the one hand. They are also pulled towards the opposite extreme of unsta-ble equilibrium by the forces of division and decentralisation, human desires for excitement and innovation and isolation from the environment, iv) If the organisation gives in to the pull of stability and it fails because it be-comes ossified and cannot change easily. If it gives in to the pull of instability it disintegrates. Success lies in
organisation at the border between stability and instability. This is a state of chaos and difficult to It is further affirmed by Stacey ( 1996) that: i) the dynamics of the successful organization are therefore rregular cycles and discontinuous trends, falling within the quantitative patterns, fuzzy but recognisable categories taking the form of archetypes and templates; ii) because of its own internal dynamic, a successful
or-e spor-ecific futuror-es, iii) agor-ents within thor-e systor-em cannot bor-e in control of its term future, nor can they install specific frameworks to make it successful nor can they apply step-by-step term development. Agents within the system can only do these things in relation to the short term; iv) Long term development is a spontaneous self-organising process from which new strategic directions may emerge. Spontaneous self organization is political interaction and learning groups. Managers have to pursue reasoning by analogy; v) in this way managers create and discover sed using the Stacey agreement vs.
Fig 1.1: Stacey’s agreement vs. certainty matrix Adapted from: (Stacey, 2003)
It is emphasised by Stacey that traditional decision making applies in the rational area of the matrix at left. The chaos area is the area to be avoided
sion-making takes place in the area of complexity where there are many alternatives with differing degrees of predictability ( and little certainty).Operation in this area requires a high level of interaction amongst organis tional agents – those involved in implementing change. Change in this case cannot be driven but must be fo tered and supported (Stacey, 2003).
When analysed, CAS are not
However, it is still possible to find inherent order in the complex systems (Palmberg, 2009). It has been asserted that: “The art of systems thinking lies in seeing through compl
change” (Senge, 1990:290).
Fig. 1.2: An overview of the properties of CAS Adapted form: (Palmberg, 2009:485)
Complex adaptive systems are seen as adaptable, which means that they have the ability to learn from Fig 1.1: Stacey’s agreement vs. certainty matrix
It is emphasised by Stacey that traditional decision making applies in the rational area of the matrix at
left. The chaos area is the area to be avoided – the area of guess work and randomness. However, much dec making takes place in the area of complexity where there are many alternatives with differing degrees of
ertainty).Operation in this area requires a high level of interaction amongst organis those involved in implementing change. Change in this case cannot be driven but must be fo
predictable in detail, because of their interdependencies and non
However, it is still possible to find inherent order in the complex systems (Palmberg, 2009). It has been asserted that: “The art of systems thinking lies in seeing through complexity to the underlying structures generating
Fig. 1.2: An overview of the properties of CAS Adapted form: (Palmberg, 2009:485)
Complex adaptive systems are seen as adaptable, which means that they have the ability to learn from
It is emphasised by Stacey that traditional decision making applies in the rational area of the matrix at the bottom the area of guess work and randomness. However, much deci-making takes place in the area of complexity where there are many alternatives with differing degrees of
ertainty).Operation in this area requires a high level of interaction amongst organisa-those involved in implementing change. Change in this case cannot be driven but must be fos-predictable in detail, because of their interdependencies and non-linearity. However, it is still possible to find inherent order in the complex systems (Palmberg, 2009). It has been asserted exity to the underlying structures generating
experience and adapt to new, unexpected conditions (Zimmerman
fines the autonomy of each agent as the local memory of the agent and the ability to learn from his or her exp rience and to generate new response.
2.2 The level of complexity of the floriculture industry in Kenya.
The floriculture industry in Kenya is composed of active 412 flower exporters (HCDA, 2009). The analysis this data revealed that there are only five international players in this i
local firms which are mainly small scale and most operating as free agents, see table 1.1 below. Table 1.1: Stratification of the Floriculture Industry in Kenya.
INTERNATIONAL LARGE
SME TOTAL
(Source: HCDA, 2009)
Some of the players in the industry especially the international firms operate in a well embedded supply chains whereas the small scale firms and the free agents are unempeded. Hence, the
characteristic of non –linearity and uncertainty. Pellissier (2009) assets that:
non-linearity of outcomes. For example, even small differences between stakeholders or changes during exec tion, can lead to differing solutions and outcomes. Non
at the design (call them ‘unknown unknowns’).
The specific challenges exhibited by the floriculture industry which further compound its complexity d mension are as outlined below ( Awuor, 2012): i) extremely short shelf life; ii)very specific demand cycles with extreme peaks; iii) changes in consumer trends; iv) mixing characteristics of service and product dimensions; v) operating part of ‘first world’ suppl
tional, local, embedded, unimpeded and free agents operating in the industry; vii) simultaneous optimisation of supply networks, both vertically and horizontally in an effort to rea
ronmental and social).
Supply networks fully embedded S U P P L I E R
1.3: supply networks in the floriculture industry in Kenya. Source: (Awuor, 2012)
Figure 1.3 is a diagrammatic representation of the supply
both fully embedded and non–embedded supply networks. It also constitutes the supply networks of first world economies operational in a developing economy. This further compound the complex nature of t
industry in Kenya.
The industry uses many chemicals
experience and adapt to new, unexpected conditions (Zimmerman et al. 1998). Further, Richardson (2008) d fines the autonomy of each agent as the local memory of the agent and the ability to learn from his or her exp
sponse.
2.2 The level of complexity of the floriculture industry in Kenya.
The floriculture industry in Kenya is composed of active 412 flower exporters (HCDA, 2009). The analysis this data revealed that there are only five international players in this industry (Awuor, 2012). The vast majority are local firms which are mainly small scale and most operating as free agents, see table 1.1 below.
Table 1.1: Stratification of the Floriculture Industry in Kenya.
INTERNATIONAL NATIONAL FREE
05 42 07
358
Some of the players in the industry especially the international firms operate in a well embedded supply chains whereas the small scale firms and the free agents are unempeded. Hence, the complex adaptive systems linearity and uncertainty. Pellissier (2009) assets that: “in a complex project there is linearity of outcomes. For example, even small differences between stakeholders or changes during exec
ad to differing solutions and outcomes. Non-linearity occurs when these changes cannot be predicted at the design (call them ‘unknown unknowns’).
The specific challenges exhibited by the floriculture industry which further compound its complexity d are as outlined below ( Awuor, 2012): i) extremely short shelf life; ii)very specific demand cycles with extreme peaks; iii) changes in consumer trends; iv) mixing characteristics of service and product dimensions; v) operating part of ‘first world’ supply network in developing country; vi) a composition of large, small, intern tional, local, embedded, unimpeded and free agents operating in the industry; vii) simultaneous optimisation of supply networks, both vertically and horizontally in an effort to realise country specific benefits (financial, env
Supply networks not embedded
COUNTRY BENEFITS( TBL) Information flow
Product / service flow Reciprocal flow
1.3: supply networks in the floriculture industry in Kenya.
Figure 1.3 is a diagrammatic representation of the supply networks in the floriculture industry, constituted of embedded supply networks. It also constitutes the supply networks of first world economies operational in a developing economy. This further compound the complex nature of t
The industry uses many chemicals – fertilizers, insecticides, fungicides, nematocides etc. Some of these 1998). Further, Richardson (2008) de-fines the autonomy of each agent as the local memory of the agent and the ability to learn from his or her
expe-The floriculture industry in Kenya is composed of active 412 flower exporters (HCDA, 2009). expe-The analysis this ndustry (Awuor, 2012). The vast majority are local firms which are mainly small scale and most operating as free agents, see table 1.1 below.
FREE TOTAL
54
358 358
412
Some of the players in the industry especially the international firms operate in a well embedded supply complex adaptive systems “in a complex project there is linearity of outcomes. For example, even small differences between stakeholders or changes during
execu-linearity occurs when these changes cannot be predicted The specific challenges exhibited by the floriculture industry which further compound its complexity
di-are as outlined below ( Awuor, 2012): i) extremely short shelf life; ii)very specific demand cycles with extreme peaks; iii) changes in consumer trends; iv) mixing characteristics of service and product dimensions; v) y network in developing country; vi) a composition of large, small, interna-tional, local, embedded, unimpeded and free agents operating in the industry; vii) simultaneous optimisation of
lise country specific benefits (financial,
envi-Supply networks not C U S T O M E R Fig.
networks in the floriculture industry, constituted of embedded supply networks. It also constitutes the supply networks of first world economies operational in a developing economy. This further compound the complex nature of the floriculture fertilizers, insecticides, fungicides, nematocides etc. Some of these
chemicals have potential for serious harm to the ecosystem and human health. Studies / statistics on pesticides use and pesticide related health effects in the floriculture industry in Kenya are very rare and scanty (Fedha, 2009). Most of the flower farms are situated around Lake Naivasha. Lake Naivasha is a Ramsar site, implying that it is a protected wetland under the
a site from ecological damages. However, Pesticides and the degradation products find their way into the lake. This has had serious consequences on pollution of the lake.
Hence, some questions of concern in the floriculture industry in Kenya are: a) who benefits from the indu try? Is the industry fighting poverty among the Kenya poor?; b) What are the long term effect on the enviro ment?; c) What are the long term effects of the indu
health?; d) Where do the elderly workers go, and what health effects may manifest later; and e) what are the i pacts of urbanisation with poor planning which is a social problem. This further emph
the industry and the need to deal with it as a complex adaptive environment. 2.3 Managing complex adaptive systems.
A number of authors strongly agree that CAS cannot be controlled (Cillers, 2000). However, according to Tapscott and Williams (2006), even though a CAS cannot be controlled, as is assumed in the approach of the traditional management of hierarchical organisations, a CAS can be managed. It is asserted by Deming (1994) that: “A system must be managed, and that it is the
nents towards the goals of the system”.
According to Palmberg (2009) the one idea that has inspired organisations is the capacity to hold a shared picture of the future we seek to create
2007). According to Sandberg and Targama (2007), there is no such a thing as resistance To change something, all one has to do is create stronger attractors tha
leave behind the principle of managing through detailed instructions, which decreases the freedom of individual agents, and, instead, to lead by making people embrace visions, creating attractors and stimulating
agents and organisations to use their inherent abilities.
Though simplicity is advocated for by Palmberg in managing CAS, it does not mean that everything should be simplified indeed just the opposite is required. Traditionally, in industrial e
among organisations. Today, with the pressure to remain innovative and flexible, managers instead need to create an environment of tension and instability. However, challenge is to keep the tension level where it generate namic imagination without exceeding people’s ability to handle the stress generated (Tetenbaum, 1998).One a proach to creating tension is to ensure that the organisation is diverse (Zimmerman
The vision of the agriculture sector in Kenya
farming methods (Ngige, 2010). Hence, the floriculture industry needs to be styled up to this. According to Muia (2010), the achievement of this vision will require:
i) Reforming institutions by transfo
high-performing entities that facilitate growth in the sector; ii) Increasing productivity through provision of widely iii) Transforming land use to ensure
iv) Developing arid and semi-
An interesting feature of the floriculture industry in Kenya is the tendency towards concentrated acti defined and limited geographical locations. Which may have been informed by climatic conditions and logistics considerations. The Kenyan government is trying to address these issues through the development of infrastru ture with respect to energy from geothermal, wind, solar, coal and nuclear power. The Ksh. 34 Billion that was allocated to energy in the 2010/11 budget speaks to this (Muia, 2010). In addition, recent development of roads and investment in water will also significantly reduce the cos
for horticulture (Ngige, 2010).
Since the launch of the vision 2030 in June 2008 (GOK, 2008), the focus is on implementation of its first 5-year phase that is guided by the medium term plan (MTP) covering t
of Kenya Vision 2030 relies heavily on the direct and indirect involvement of the private sector, the business community as well as civil society organisations. One of the flagship projects identified in the MTP 2008 2012 was fertiliser cost reduction programme (GOK, 2008). In 2009, bulk procurement of fertilizer commenced and was injected into the market through National Cereals and Produce Board (NCPB), resulting in the reduction of fertiliser prices.
Available information indicates that most of the exports of Kenya’s floriculture have been to a limited range of export markets resulting in a concentration that expose the industry to systemic market risk (Muia, 2010). Whilst there is need for pro-active efforts to
diversify into other markets especially those that have significant growth potential and whose economies are not closely correlated with those of the traditional Kenyan markets. Besides in
velopment would greatly enhance Kenya’s bargaining power in the global agricultural markets.
chemicals have potential for serious harm to the ecosystem and human health. Studies / statistics on pesticides and pesticide related health effects in the floriculture industry in Kenya are very rare and scanty (Fedha, 2009). Most of the flower farms are situated around Lake Naivasha. Lake Naivasha is a Ramsar site, implying that it is a protected wetland under the Ramsar convention. Kenya has the international obligation to protect such a site from ecological damages. However, Pesticides and the degradation products find their way into the lake. This has had serious consequences on pollution of the lake.
e questions of concern in the floriculture industry in Kenya are: a) who benefits from the indu try? Is the industry fighting poverty among the Kenya poor?; b) What are the long term effect on the enviro ment?; c) What are the long term effects of the industry on reproductive health, cancer related diseases, child health?; d) Where do the elderly workers go, and what health effects may manifest later; and e) what are the i pacts of urbanisation with poor planning which is a social problem. This further emphasises the complexity of the industry and the need to deal with it as a complex adaptive environment.
2.3 Managing complex adaptive systems.
A number of authors strongly agree that CAS cannot be controlled (Cillers, 2000). However, according to nd Williams (2006), even though a CAS cannot be controlled, as is assumed in the approach of the traditional management of hierarchical organisations, a CAS can be managed. It is asserted by Deming (1994)
system must be managed, and that it is the job of the management to direct the efforts of all the comp nents towards the goals of the system”.
According to Palmberg (2009) the one idea that has inspired organisations is the capacity to hold a shared picture of the future we seek to create – visioning. Another suggested approach is to use attractors (Gharajedaghi, 2007). According to Sandberg and Targama (2007), there is no such a thing as resistance –
To change something, all one has to do is create stronger attractors than the ones in place. The basic idea is to leave behind the principle of managing through detailed instructions, which decreases the freedom of individual agents, and, instead, to lead by making people embrace visions, creating attractors and stimulating
agents and organisations to use their inherent abilities.
Though simplicity is advocated for by Palmberg in managing CAS, it does not mean that everything should be simplified indeed just the opposite is required. Traditionally, in industrial era, stability was a success factor among organisations. Today, with the pressure to remain innovative and flexible, managers instead need to create an environment of tension and instability. However, challenge is to keep the tension level where it generate namic imagination without exceeding people’s ability to handle the stress generated (Tetenbaum, 1998).One a proach to creating tension is to ensure that the organisation is diverse (Zimmerman et al. 1998).
The vision of the agriculture sector in Kenya is to be “innovative, commercially
farming methods (Ngige, 2010). Hence, the floriculture industry needs to be styled up to this. According to Muia (2010), the achievement of this vision will require:
Reforming institutions by transforming key organisations such as cooperatives into contemporary and performing entities that facilitate growth in the sector;
Increasing productivity through provision of widely-accessible inputs and service to farmers; Transforming land use to ensure better utilization of high and medium potential lands and;
arid areas, (which accounts for 80% of Kenya’s land mass) for crops. An interesting feature of the floriculture industry in Kenya is the tendency towards concentrated acti defined and limited geographical locations. Which may have been informed by climatic conditions and logistics considerations. The Kenyan government is trying to address these issues through the development of infrastru
rom geothermal, wind, solar, coal and nuclear power. The Ksh. 34 Billion that was allocated to energy in the 2010/11 budget speaks to this (Muia, 2010). In addition, recent development of roads and investment in water will also significantly reduce the cost of transportation and perhaps open up new areas Since the launch of the vision 2030 in June 2008 (GOK, 2008), the focus is on implementation of its first year phase that is guided by the medium term plan (MTP) covering the period 2008 to 2012. Implementation of Kenya Vision 2030 relies heavily on the direct and indirect involvement of the private sector, the business community as well as civil society organisations. One of the flagship projects identified in the MTP 2008 2012 was fertiliser cost reduction programme (GOK, 2008). In 2009, bulk procurement of fertilizer commenced and was injected into the market through National Cereals and Produce Board (NCPB), resulting in the reduction nformation indicates that most of the exports of Kenya’s floriculture have been to a limited range of export markets resulting in a concentration that expose the industry to systemic market risk (Muia, 2010). active efforts to maintain and defend existing markets there is also a clear need to diversify into other markets especially those that have significant growth potential and whose economies are not closely correlated with those of the traditional Kenyan markets. Besides increasing the volume of sales, this d velopment would greatly enhance Kenya’s bargaining power in the global agricultural markets.
chemicals have potential for serious harm to the ecosystem and human health. Studies / statistics on pesticides and pesticide related health effects in the floriculture industry in Kenya are very rare and scanty (Fedha, 2009). Most of the flower farms are situated around Lake Naivasha. Lake Naivasha is a Ramsar site, implying Ramsar convention. Kenya has the international obligation to protect such a site from ecological damages. However, Pesticides and the degradation products find their way into the lake. e questions of concern in the floriculture industry in Kenya are: a) who benefits from the indus-try? Is the industry fighting poverty among the Kenya poor?; b) What are the long term effect on the environ-stry on reproductive health, cancer related diseases, child health?; d) Where do the elderly workers go, and what health effects may manifest later; and e) what are the
im-asises the complexity of
A number of authors strongly agree that CAS cannot be controlled (Cillers, 2000). However, according to nd Williams (2006), even though a CAS cannot be controlled, as is assumed in the approach of the traditional management of hierarchical organisations, a CAS can be managed. It is asserted by Deming (1994) job of the management to direct the efforts of all the compo-According to Palmberg (2009) the one idea that has inspired organisations is the capacity to hold a shared
ing. Another suggested approach is to use attractors (Gharajedaghi, – there is only attraction. n the ones in place. The basic idea is to leave behind the principle of managing through detailed instructions, which decreases the freedom of individual agents, and, instead, to lead by making people embrace visions, creating attractors and stimulating individual Though simplicity is advocated for by Palmberg in managing CAS, it does not mean that everything should ra, stability was a success factor among organisations. Today, with the pressure to remain innovative and flexible, managers instead need to create an environment of tension and instability. However, challenge is to keep the tension level where it generates dy-namic imagination without exceeding people’s ability to handle the stress generated (Tetenbaum, 1998).One
ap-1998).
is to be “innovative, commercially- oriented use modern farming methods (Ngige, 2010). Hence, the floriculture industry needs to be styled up to this. According to rming key organisations such as cooperatives into contemporary and
accessible inputs and service to farmers; better utilization of high and medium potential lands and; arid areas, (which accounts for 80% of Kenya’s land mass) for crops. An interesting feature of the floriculture industry in Kenya is the tendency towards concentrated activity in defined and limited geographical locations. Which may have been informed by climatic conditions and logistics considerations. The Kenyan government is trying to address these issues through the development of
infrastruc-rom geothermal, wind, solar, coal and nuclear power. The Ksh. 34 Billion that was allocated to energy in the 2010/11 budget speaks to this (Muia, 2010). In addition, recent development of roads t of transportation and perhaps open up new areas Since the launch of the vision 2030 in June 2008 (GOK, 2008), the focus is on implementation of its first he period 2008 to 2012. Implementation of Kenya Vision 2030 relies heavily on the direct and indirect involvement of the private sector, the business community as well as civil society organisations. One of the flagship projects identified in the MTP 2008 to 2012 was fertiliser cost reduction programme (GOK, 2008). In 2009, bulk procurement of fertilizer commenced and was injected into the market through National Cereals and Produce Board (NCPB), resulting in the reduction nformation indicates that most of the exports of Kenya’s floriculture have been to a limited range of export markets resulting in a concentration that expose the industry to systemic market risk (Muia, 2010). maintain and defend existing markets there is also a clear need to diversify into other markets especially those that have significant growth potential and whose economies are not creasing the volume of sales, this de-velopment would greatly enhance Kenya’s bargaining power in the global agricultural markets.
It is critical to look at the range of products that are offered in the Kenya Floriculture industry. The flor culture industry need to devote time to increase its product depth and width. The following questions are further posed:
i) Is there scope to grow scented plants in large scale?
ii) How about trying new varieties of fruits, vegetables and flowers that have never been grown bef Cactus for breakfast vegetable and perfumes?
iii) How about trying Olives in Kerio Valley and Semi Arid parts of Kenya?
The government is keen on adopting a cluster strategy in dealing with these issues. This involves employing the triple helix concept which brings together government, private sector and researchers. The complexity of the floriculture industry is revealed by Awuor ( 2012) in a study that found the following factors to be important for the performance of the industry: i) financin
transport, research and development as positively influencing the performance of the floriculture industry in Kenya. The conceptual model is as illustrated in figure 1.4.
Fig 1.4: Conceptual model for managing the floriculture industry in Kenya Source: (Awuor, 2012)
In his study, Awuor (2012) concludes that for simultaneous optimisation of the floriculture industry and given its existence in a complex adaptive environment then it is vital that emphasis
key success factors; factor 2 – financing; factor 3 velopment and; factor 5 – country specific benefits. 3.0 Conclusion: A research agenda?
The discussion above identifies a set of issues that need to be seriously investigated in trying to understand and subsequently improve the performance of the floriculture industry in Kenya. The issues include; i) developing consensus over the definition of a complex adaptive system and a complex adaptive environment with regard to
KEY SUCCESS FACTORS FINANCING INFORMATION INTE-GRATION TRANSPORT, RESAERCH &
DEVEL-OPMENT
COUNTRY SPECIFC BENEFITS
It is critical to look at the range of products that are offered in the Kenya Floriculture industry. The flor y need to devote time to increase its product depth and width. The following questions are further Is there scope to grow scented plants in large scale?
How about trying new varieties of fruits, vegetables and flowers that have never been grown bef Cactus for breakfast vegetable and perfumes?
How about trying Olives in Kerio Valley and Semi Arid parts of Kenya?
The government is keen on adopting a cluster strategy in dealing with these issues. This involves employing concept which brings together government, private sector and researchers. The complexity of the floriculture industry is revealed by Awuor ( 2012) in a study that found the following factors to be important for the performance of the industry: i) financing; ii) key success factor; iii) country specific benefits; and iv) transport, research and development as positively influencing the performance of the floriculture industry in Kenya. The conceptual model is as illustrated in figure 1.4.
managing the floriculture industry in Kenya
In his study, Awuor (2012) concludes that for simultaneous optimisation of the floriculture industry and given its existence in a complex adaptive environment then it is vital that emphasis is put on four main factors: factor1
financing; factor 3- information integration; factor 4- transport, research and d country specific benefits.
3.0 Conclusion: A research agenda?
The discussion above identifies a set of issues that need to be seriously investigated in trying to understand and subsequently improve the performance of the floriculture industry in Kenya. The issues include; i) developing f a complex adaptive system and a complex adaptive environment with regard to
SIMULTANEOUS OPTIMI-SATION
PERFORMANCE OF THE FLORICULTURE
INDUSTRY
It is critical to look at the range of products that are offered in the Kenya Floriculture industry. The flori-y need to devote time to increase its product depth and width. The following questions are further
How about trying new varieties of fruits, vegetables and flowers that have never been grown before e.g.
The government is keen on adopting a cluster strategy in dealing with these issues. This involves employing concept which brings together government, private sector and researchers. The complexity of the floriculture industry is revealed by Awuor ( 2012) in a study that found the following factors to be important g; ii) key success factor; iii) country specific benefits; and iv) transport, research and development as positively influencing the performance of the floriculture industry in
In his study, Awuor (2012) concludes that for simultaneous optimisation of the floriculture industry and given its is put on four main factors: factor1 – transport, research and
de-The discussion above identifies a set of issues that need to be seriously investigated in trying to understand and subsequently improve the performance of the floriculture industry in Kenya. The issues include; i) developing f a complex adaptive system and a complex adaptive environment with regard to
PERFORMANCE OF THE FLORICULTURE
the floriculture industry in Kenya; ii) identifying the characteristics of a complex adaptive system with regard to the floriculture industry in Kenya; iii) determining the level
iv) establishing methods of managing complex adaptive systems with reference to the floriculture industry. A befitting conclusive remark for this article from Grisogono (2006) asserts that: clearly ther
work to be done to operationalise our growing understanding of CAS and to increase our ability to effectively exploit it. There are also some difficult implementation issues arising from traditional ways of thinking and d ing things, and from the inherent nature of human cognition and the history and structure of our organisations. However the overall take-away lesson from this discussion should be an optimistic one, if we make proper use of adaptability we do not need to know all the answer
the first time. We just need, as nature has ever done to start with a straw man and know how to grow it to a better one.
4.0 References
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