Strategic Management for Systems Archetypes in the Piggery Industry of Ghana—A Systems Thinking Perspective

Approximately sixty percent of rural households in developing countries are partially or fully dependent on livestock for their livelihoods [1]. Livestock rearing provides the household with a wide range of benefits, such as cash income, food, manure, draft power and hauling services, savings and insurance, and social status [2]. The livestock farming sector, including piggery remains critically important for millions of people in developing countries including Ghana and developments within this sector are most important in terms of attaining the sustainable development goals (SDGs), goals of no poverty [3,4].

In Ghana, the Agriculture sector growth rates declined from 4.6 percent in 2014 to 0.0 percent in 2015. Of all the agriculture activities the livestock subsector recorded the highest growth of 9.3 percent in 2015 [5]. The piggery sector which contributes to household income, is one of the fast growing sectors of the livestock industry because of increase in pork consumption [6,7]. Pork production rose from 11,173 MT in 1999 to 17,512 MT in 2009 with pork production index ranging from 98 to 154 within the same period. Pork import in Ghana rose from 358.1 MT in 2000 to its peak of 13,290.5MT in 2006 and dropped to 3150.2 MT in 2009 [8]. Piggery represents a form of cash security of the livelihood strategies of many farmers and plays a central role in their socio-economic and cultural identity, and is a source of food, employment, food security and also assets for store or trade [6]. Livestock and crop production contribute 66.8% to agricultural GDP in Ghana [8]. The multiple roles of pig rearing and other indigenous livestock breeds are significantly acknowledged in different farming systems of Ghana including the intensive, semi-intensive and free range systems. The growth of Ghana’s domestic piggery industry has been impeded by several constraints such as lack of improved breeding stock, the balance between the limitations and availability of land and water, rapid urbanisation processes, pollution and lack of managerial skills [7,9]. The industry is also affected by diseases caused by the PRRS virus, PCVD virus, Classical Swine Fever (CSF) Viral diarrhoea in piglets, Aujeszky’s Disease virus or pseudorabies, Foot-and-Mouth Disease (FMD) virus, and of secondary importance, bacterial diseases [10–12]. As a result, pig production in Ghana is reflected in numerous research and development (R&D) projects, a vast number of grants, research projects and other activities developed by the government to support the piggery industry [13–15]. Their contribution to household food security and income as well as their social roles is well known; however,  improvement of their productivity through crossbreeding, improved health and nutritional management are also concerns of many livestock development plans through national and international programmes [16–18]. Pig production, therefore is an integral part of Ghana’s agri-business activities and a major source of livelihood for many entrepreneurs seeking an alternative source of profitable business ventures [6,7,16]. However, most Ghanaian entrepreneurs enter this business based on a survival driven motive without adequate knowledge and a business plan leading to subsequent business failure.

Apart from the question of competition for human staples, pigs are generally more efficient than ruminants as converters of food into flesh. A high proportion of Ghana’s pork, up to 95%, is raised by farmers in small-scale (20–100 pigs) commercial operations and backyard outfits involving a handful (1–20) of pigs [6,19]. Large-scale private pig enterprises involve several hundreds of pigs with varieties of breeding stocks but with the Danish large white dominating. These farmers are acutely sensitive to the movements in price that determine their profit or loss margins. The two most important variables: the price of pork (the output) to the price of corn (the input) ratio of 6:1 is enough for pig farmers to break even [6,20]. Within the food industry, pork prices are particularly volatile [21–23]. In March 2009, the increase in pig population rose by 35% from 332,000 in 1999, with the pig population index rising from 96 to 150 within the same period [8,24]. During peak prices, farmers take advantage by slaughtering sows out of the breeding herd for the meat which in the short term results in unintended consequences of pork shortage and higher prices [24]. 

The major and biggest challenges for entrepreneur farmers in Ghana is the attitude that they must have hands-on control of all aspects of their business; from management, accounting systems, sales and decisions making; leading to business failure in both short or long run [25]. Delegation or outsourcing a particular task in the livestock sector is vital for effective production; however, this can sometimes be a major challenge for pig farm owners who take delight in having control of all aspects of the business. These owners are more concerned about giving up control at a cost than incurring the cost of training or building up the capacity of low standard employees. Nevertheless most pig owners, according to the survey results, lack the technical know-how in pig management (feed formulation, heat detection, identifying and curing poor and sick animals, pricing, marketing, and drug administration). Employing qualified or trained staff is essential to economic progress because it allows specialized people to deliver in their capacity. This specialization makes workers more efficient and effectively reduces the total cost of producing the pigs. The basic infrastructure required for pig farming including water source, proper feed formulation and ration, proper supervision and market access, with appropriately qualified staff is sometimes lacking [26,27]. Also, common arrangement found in pig farms are unskilled labourers who clean and water the animals, with the rest of the activities which do not require physical strength, managed by the owner. Thus, productivity and profit are highly influenced by poor infrastructure and lack of technical skills leading to unsustainable business. Because of the complexity of many agri-business issues, where numerous interacting variables need to be accounted for and multiple interventions and groups bring different values and concerns to bear, it is not uncommon for people to call for a holistic Systems Thinking approach.

The piggery sector, and the role that animals play in the household economy in Ghana, are anticipated to change rapidly in the coming decades. Consumers are increasingly demanding high-value agricultural products including pork products. In this fast-changing context, good-quality livestock data are needed for designing and implementing policies and investments that promote the sector’s social and sustainable development [28]. Available livestock data, and the derived statistics or indicators, however, are largely considered inadequate for effective decision making. Ruling governments, agriculture advocates and livestock stakeholders including farmers have neither adequate facts nor the essential tools essential to analyse the performance and investment decisions affecting the agricultural sectors [29]. Governments and research scientists are under increasing pressure to implement the right management decisions in the face of a dynamic political and socioeconomic landscape. The domestic and worldwide challenges currently fronting the livestock sector in Africa (including Ghana) are highly complex in nature [29,30]

This research gap regarding inadequate information is likely to continue for these several reasons: inadequate support for research, high inflation, administrative complacency,  and the use of the traditional approach to addressing livestock challenges often undermine the success of its sustainability. History suggests that these problems cannot be solved with the traditional approach in isolation and with single-dimensional mindsets and tools. Livestock sustainability may benefit from a systemic approach to interventions and capacity-building based on systems thinking and complexity management to address challenges holistically in order to deliver the desired sustainable outcomes.

Many factors affect pork production and price in Ghana; however, these factors are related [31]. There have been many initiatives to address and modernize the agriculture sector, including the pig industry in Ghana by the Government but with limited success [3,6,29,32]. It is clear from the earlier discussion that the challenges in Ghana’s piggery industry are complex [3]. To help address these, there is the need to equip policy makers, researchers and all relevant stakeholders with a new way of ‘thinking’ beyond the traditional ‘linear’ approach to solving problems, to a holistic systems approach that focuses on the root causes and provide a holistic view between various components of an industry [3]. Thus, this research explored these issues using systems thinking to reveal how these components affect each other and to recommend the way forward. This paper explores the application of system archetypes to serve as effective tools for gaining insights into patterns of behavior of the piggery industry of Ghana and how it interacts to affect the survival of this industry. These models can be used to assess many dimensions of the piggery industry, from pig production dynamics to economic policies designed to support the production venture. Identifying and understanding the various system archetype in the piggery industry is crucial to building a robust and integrated production activity that can be managed under different production scenarios [30,33].

The trend of increasing piggery productivity in tropical and subtropical regions and increasing pressure on tropical and subtropical livestock systems to produce food, to feed livestock, and to produce energy crops warrants the development of systemic models to address issues such as the economic importance of piggery.

In this research, systems archetypes are developed to provide an understanding of the dynamics, interconnectedness and relationships present within the piggery industry. The research is conducted using a systems thinking approach and tools such as causal loop diagrams (CLDs) to demonstrate its application in effectively addressing complex sustainability issues affecting the agriculture sector. This research seeks to address the agricultural system’s complexity by gathering the ‘mental models’ of various stakeholders involved in the piggery sector in Ghana. The results and approach will help livestock farmers, decision makers, scientists, and managers to anticipate the long-term consequences of their decisions and actions, as well as significant unintended consequences of decisions and strategies, and avoid the danger of ‘silo mentality’ and ‘organisational myopia’. The process aims to provide a common language for diverse stakeholders, such as pig farmers, labourers, policymakers, and researchers, for deep dialogue and consensus building. This will help build research capacity in areas needed to improve and modernize peri urban pig production and make it more efficient and profitable with a view to eradicating poverty and promoting the health and welfare of the people and the animals. Using a case study approach, data were collected from El-Capitano Piggery Farm at Agona-Duakwa in the Central Region of Ghana,  Ketu Pig Farmers association (involving 60 smallholder typical pig farmers) in the Volta Region and the Biotechnology and Nuclear Agriculture Research Institute (BNARI) Farm Complex at Kwabenya in the Greater Accra Region.

The systems thinking approach is a transdisciplinary ‘framework’ that addresses the root causes of challenges by viewing ‘problems’ as parts of an overall system [29]. Currently, it is unusual to go through a single day without hearing the words “sustainability” or “green” applied to anything from Apple products to Zinfandels [34]. Resolving today’s challenges requires moving from a “linear” way of thinking to a “systems” perspective that brings thought and behaviour in line with the natural laws of sustainability [29,35]. Systems thinking is a trans-disciplinary “framework for seeing interrelationships rather than things, for seeing patterns of change rather than static snapshots” [36]. Systems thinking helps one develop new ways of thinking and enables one to grasp and manage situations of complexity and uncertainty in which there are no simple answers. It is a way of ‘learning your way towards effective action’ by looking at connected wholes rather than individual component parts [37]. The piggery industry and its sustainability may benefit from a systems thinking approach to interventions and capacity building, to address challenges holistically and deliver the desirable sustainable outcomes. This is in contrast to the linear approach of identifying ‘quick fixes’ to specific parts which leads to the danger of ‘silo mentality’ in which a fix ‘here’ simply shifts the problem to ‘there’ and ‘organizational myopia’ in which a fix ‘now’ gives rise to a much bigger problem to fix ‘later’ [29,38,39]. The application of systems thinking to manage complexities has generated a broad array of tools including system archetypes and causal loop modelling. 

An archetype is a well-defined structure, which exhibits distinct behavior over time, and has well-defined strategies for dealing with the underlying structure of the system being studied [40]. The system archetypes do not describe anyone problem specifically. They describe a spiral of problems generically [40]. Their value comes from the insights that they offer into the dynamic interaction of complex systems. This approach illustrates one’s understanding of a particular system’s structure and behaviour, which foster communication and identification of high leverage interventions for problematic complex system behaviour. The system archetypes exposed insights into the livestock system structure that already exist to anticipate potential problems and the problem symptoms. As part of a suite of tools, they are extremely valuable in developing broad understandings about the livestock industries and their environments and contribute to more effectively understanding the root cause of challenges rather than a fix ‘now’ giving rise to a much bigger problem to fix ‘later’ [38].

A causal loop diagram (CLD) is the first-step practical approach to modelling and simply converting the complex components into a simple easily understandable structure [30]. CLDs are variables connected by key causal relationships to represent reality used to display the behavior of cause and effect from a system standpoint [41]. The model is a framework for seeing interrelationships between components in livestock systems and sustainability rather than isolated features that impact the productivity of the livestock sector. The word ‘causal’ refers to causes-and-effects relationships, and ‘loop’ allies with closed chain of causality that link back to each variable [42]. CLDs are variables connected by key causal relationships to represent reality used to display the behavior of cause and effect from a system standpoint [41]. Causal loop diagram is simply a diagram of ‘words and arrows’ in which the ‘words’ represent variables (factors) in the systems and the ‘arrows’ show causal connections between the variables [43]. A variable can be a condition, a situation, an action or a decision which can influence and also be influenced by others variable (factors) [44]. Variables can be quantitative or qualitative. Quantitative variables are the factors that can be measured such as the value of average air temperature, levels of rainfall, cost of feed sources and animal population; while qualitative variables refer to soft factors, for example, traditional culture, belief, moral and reputation [42].

In this paper, the piggery industry’s past behavior has been analyzed using a systems thinking approach, and the structure of the piggery industry in the form of a system archetype has been developed, which explains the behavior of the industry. The system archetype developed here is generic enough to explain any productivity decline and business rivalry behavior of an agribusiness industry. The proposed archetype can also help the farm managers and producers to make various decisions.

In the following sections, the four levels of thinking model framework were used to explain the past behavior of the piggery industry and the development of the underlying structure causing the behaviour, to generate a list of sustainable management strategies for the industry. The industry’s problems were pooled together, and key factors whose behavior over time caused problems were identified. Thereafter, we explain the past behavior of the industry by developing various individual two-loop system archetypes. Later, the individual variables affecting the industry were consolidated to obtain a causal loop structure and a behavior-over-time graph of the piggery industry.

The model which starts at the ‘first level of thinking’, involves a series of literature reviews and interviews with experts in the field. Data on stakeholder opinions and perceptions of how the livestock system works, the barriers to success, the system drivers and the possible strategies (solutions) to overcome these problems were obtained through focus group discussions with a group of agricultural experts (e.g., agricultural scientists and extension officers and pig farmers) to obtain their mental models of the piggery sector under deliberation. A 2-day workshop organized in “Ketu” (Volta Region) and “Agona Duakwa” (Central Region) helped identify the core issues and high leverage interventions for problematic complex system behaviour in the piggery system. Several key variables in the livestock sector were identified through the focus group (65 smallholders; 5 research scientist, 4 extension officers, 3 large scale farmers, 3 Ministry of Food and Agriculture agents, 5 input dealers) discussions and an in-depth review of literature. All farmers were males ranging from 32 to 73 years in age. Key leaders of heads of departments and some of the staff of these respondents were also interviewed. These variables are processed into loops using CLD modelling approach with the VENSIM Software program (Ventana Systems UK) for the development of the CLD of the issues under consideration. A researcher of BNARI, who has a rich experience and knowledge of the livestock industry in Ghana, provided the context and issues related to piggery to participants of the workshop. Some of the 85 workshop participants also had prior experience working in several piggery projects in Ghana. Researchers used key variables identified and integrated the different mental models into the causal-loop model using Vensim software. The outcomes of the actions and decisions that have been implemented by policymakers were also reflected upon to determine their effect and identify significant unintended consequences and new barriers generated. The research adopted an approach ‘teaching to transfer’ the art of interconnected thinking with stakeholders during the workshop, and these respondents are also involved in policy revision and formulation in Ghana. These 85 stakeholders were familiarised with and educated about the art of interconnected thinking. Research scientists and extension agents were also present. It is believed that these groups will be the facilitators of the art of interconnected thinking in policy formulations including some of the authors in Ghana who are also stakeholder of policy formulation at governmental level.

Once the unintended consequences and new barriers have been identified, the ‘second level of thinking’ is used to interpret and explore patterns and their interconnected components, and to analyse the kind of feedback loops, reinforcing loops and balancing loops that were generated.

This is followed by step three, which is the ‘third level of thinking’, in which the literature review was used to identify what pre-existing system archetypes were influencing the piggery industry. System archetypes are used to develop an understanding of interdependency and analyse the implemented strategies and/or policies that led to the intervention effect. The Vensim software program (Ventana Systems UK) was used for the development of the systems archetypes of the issues under consideration. A CLD is the first step to modelling and simply converting the complex elements into a simple, easy-to-understand structure. CLDs are variables that are connected by key causal relationships to represent the reality used to display the behaviour of cause and effect from the system’s standpoint [41].

Finally, the ‘fourth level of thinking’ highlights the strategies needed to overcome the issues and challenges facing the entire complex agricultural system. Archetypes are useful for gaining insights into the ‘nature’ of the underlying problem and for offering a basic structure or foundation upon which a model can be further developed and constructed. Thus, Systems theory provides a framework for taming complexity, in other words, providing systems concepts and tools to unravel the complexity of any system under consideration [29].

The research method used focuses on the application of the Evolutionary Learning Laboratory (ELLab) and CLDs as knowledge integration tools in sustainable agricultural management and decision-making [39]. The ELLab is designed to equip policy makers, researchers and all relevant stakeholders with a new way of ‘thinking’ beyond the traditional ‘linear’ approach of solving problems, to a holistic systems approach that focuses on dealing with the root causes and interconnectedness between various components of the agricultural system. The process involves setting management objectives, abstract modelling to explore the effect of decisions on these objectives, identifying preferred management interventions and monitoring to track the success of implemented management intervention.

The purpose of this approach is for decision support, policy assessment and prioritisation of management interventions.

‘Systems thinking’ approach highlights and addresses complex problems using integrated approaches and demonstrates how to translate complex ideas into potent management tools for change [45]. The systems analysis is guided by different levels of thinking. Generally, researchers do analysis based on the symptoms and patterns; however, this research focuses on the systemic structures that underlie the patterns of behaviour over time to anticipate the problem in the piggery industry and accommodate them [46–48]. This allows altering the source of the problem rather than just dealing with the symptoms.

The underlining systemic structures were shown using systems archetypes identified from the Causal Loop Diagram (CLD) to unravel the complexity of the piggery industry, where greatest leverage lies in solving problems. The CLDs have proven to be effective to unravel complexity and dynamics within a system [3,39,49]. Systems thinking approach also offers an opportunity for creating informal learning spaces for managing complex issues [39].

Systems archetypes and CLD modelling are key processes of using a systems approach to understanding the systems and identifying systemic intervention. The basic elements of any causal loop model or diagram are variables (factors) and links [29,46,50]. A “variable” is a condition, situation, action or decision that can influence and can be influenced by other variables. A variable can be quantitative (measurable) such as profit, productivity, or it can be qualitative (soft data) such as motivation, trust, morale, burnout and reputation. Qualitative variables do not generally lend themselves to direct measurement. One of the strengths of causal loop methodology is its ability to incorporate qualitative variables into the systems thinking approach [48]. System archetypes provide a systemic structure and storyline that can be used to diagnose or make sense of a situation [51]. The relationships between these variables, represented by arrows can be labelled as positive or negative. A link indicates a causal association between two variables or a change in the state of these variables of which “S” indicates a change in the same direction and an “O” indicates a change in an opposite direction [49]. Variables and links can form loops indicating feedbacks, either reinforce (R) or balance (B). Reinforcing feedback is when changes in elements of the system are fed back and result in an amplification of the change. Balancing feedback is when changes in elements of the system are fed back opposing the original change resulting in a counteracting effect [3]. The delay mark (+) on the causal arrows indicate that it will take time before the effect starts to play out.

The combination of loops can form systems archetypes which are generic systems models that represent a wide range of situations [47,52].  Systems archetypes can provide valuable indications of potential systemic interventions, normally referred to as leverages, which means actions or interventions that can have lasting impacts on the system in terms of reversing a trend or breaking a vicious cycle [51].

The increasingly complex nature of the Ghana piggery industry and other agribusiness has necessitated the use of a systemic research approach in solving operational problems. This assumes a significant role in the formulation of economic policy for both governments and businesses. The piggery industry sustainability may benefit from a systemic approach to interventions and capacity building, based on systems thinking and complexity management to address challenges holistically and deliver the desirable sustainable outcomes.

Eighty five respondents participated in the focus group discussions and all participants own or are involved in piggery businesses, from farmers, processors, wholesalers to retailers. Focus group discussion participants were asked to give their views about the problems of the piggery industry and their impact on economics in their livelihood. The mental models of participants, which included past observations and experience, were then analysed by the research team using the “four levels of thinking” model.

The research used focus study to gather the mental models of stakeholders. Given the growing complexity dynamism and instability of the pork markets, all businesses and economic factors that might influence the piggery industry were considered.

In this structure, a problem symptom gets bad enough that it captures attention: for example, a slump in pig or pork sales leads to the implementation of a quick fix (a marketing promotion) that makes the symptoms go away (pig sales improved). However, that action triggers unintended consequences that make the original symptom reappear after some delay—often worse than before—thus limiting business development and growth. The systems thinking approach is a transdisciplinary ‘framework’ that addresses the root causes of challenges by viewing ‘problems’   as part of an overall system, in contrast to the linear approach of identifying ‘quick fixes’ to specific parts. ‘Quick Fixes’ lead to the danger of ‘silo mentality’ in which a fix ‘here’ simply shifts the problem to ‘there’ and ‘organizational myopia’ in which a fix ‘now’ gives rise to a much bigger problem to fix ‘later’ [38]. Therefore, a systems thinker frames a problem in terms of seeing the whole forest, instead of focusing on a particular part. They see beyond the details to the context of relationships in which they are embedded. Today, it is widely used by academics and practitioners alike to address sustainability challenges.

A “fixes that fail” structure is often part of a more elaborate structure in which the fixes that fail structure simply represents dealing with the symptoms rather than the root cause underlying the real problem. A “fixes that fail” structure often results in becoming dependent on the fix, thus applying it over and over.

The most effective strategy for dealing with this structure is advance planning. Since one can never do just one thing, as everything affects everything else, before taking action to change the current state, one has to think about what else that action is apt to affect and what the impact will be. Sometimes the unexpected consequences may be several effects away, so one does not have to stop at just one. Essentially what one seeks to do is to identify the unexpected, which means it is no longer unexpected.

However, sustained investment leads to ‘Project A”s success. The key here is that, if the investment is sustained in ‘Project A’ beyond a critical point, ‘Project A’ begins to generate positive returns. Beyond this critical threshold of positive returns, ‘Project A’s success is likely to be self-sustaining because continued investment brings ongoing positive net returns. In the case of ‘piggery’, we start by making the same initial investments as for ‘Project A’ but, for whatever reasons (inadequate knowledge, poor timing, external forces, lack of a business plan, etc.) ‘piggery’ takes longer than ‘Project A’ to become successful. In many cases, the reason for ‘Project A’ comparative success is that it had a head start in and is already beyond the critical threshold of positive returns. Thus, ‘piggery’s net returns stay low or negative longer than ‘Project A’, and ‘piggery’ begins to look less attractive as an alternative. Thus, less and less is invested in ‘piggery’, which delays ‘piggery’ achievement of success even further. At a certain point, resources, such as people, equipment, etc. is even taken away from ‘piggery’ because we do not want to waste resources on a “lost cause”. In turn, ‘piggery’s performance only declines further. Finally, ‘piggery’ will be considered a failed project and abandoned.

One warning signal that the “Success to the Successful” archetype is at work is if you hear yourself validating decisions by saying,  “Project A is a good way to go,  because it is clear by the progress  to date that it outshines the piggery alternatives.” The Project A system has become entrenched because of the “Success to the Successful” loops and is difficult to dislodge because of the “competency trap” phenomena.

Competency traps lock us into a way of doing things simply because we are already skilled at doing it that way. Suppose, for example, you are good at managing Project A skillfully and profitably. When a new alternative business such as the piggery emerges, everyone raves and says it is superior to the first. However, you think, “I already know how to manage this one, so I’m just going to keep using it.” Each time you use it, you invest more of your time and resources to get to know it better, without gaining any skills in the alternative piggery business. Over time, your competency “traps” you into continuing to manage Project A.

Such competency traps can turn your business into a corporate dinosaur, because they disconnect you from the current progress of piggery alternatives and engender the belief that you have the way, the best way, or the only way. Even if your favored method is currently superior, once you get caught in the “Success to the Successful” loops, you will not realize it when progress passes you by

The measurement systems you use can perpetuate your competency traps by making current Project A successes look good and Piggery alternatives appear less favorable than they actually are. Is your current system weighing too heavily the costs that have already been invested? Does it overly discount the opportunity costs of not switching or not scanning for other possibilities? If you think your system may be skewed in one direction, you may need to question the assumptions behind your current measurement systems and perhaps change them if necessary.

When you are successful in a market for a long time, you often begin to believe that your internal view of success is the same as the market’s view. The internal success loop can thus blind you to shifts in the competitive environment that are obvious to less successful players. Mapping your internal view of success will make the operating assumptions explicit and clear.

To complete the picture, you need to obtain external views of market success. This usually requires getting an assessment from a true “outsider” to the industry. Internal attempts to map the external view run the danger of looking too similar to the internal view.

Competency traps and inaccurate views of the marketplace indicate how the “Success to the Successful” archetype can erode the innovative spirit of the organization. This trap is characterized by the old management adage, “If it ain’t broke, don’t fix it.” Instead of allowing one successful way to predominate, use the archetype to question how you think and perceive. The challenge here is to always entertain alternatives in a highly innovative spirit.

By nurturing an innovative spirit and continually scanning for new alternatives, you can become your own best competitor. With this mindset, you become the most critical of your own success, continually looking for gaps and areas for improvement. For example, Proctor & Gamble’s approach of having multiple brands compete with each other helped the company become and remain the industry leader in many markets. By viewing your successes as if you were another company, you can find ways to create a competing product or service that may be better or more successful.

“Success to the Successful” is one of the toughest structures an organization has to overcome because many choices are often made subconsciously, influenced by the momentum of past actions. It is easy to become trapped in your success by continuing to learn how to do the same thing better.

The commons in the case of the piggery and vegetable production in Ghana is a resource (people, materials, space, tools, etc.) that is simultaneously made available to multiple people and/or teams. The initial rationale for creating the commons is typically economies of scale. As each person or team claims their “share” of the commons, within the context of the goals and objectives that they have set for themselves, they regard the commons as being uniquely available for their own purposes. Initially using the resource contributes to each reinforcing loops results. After some time the total activity of the reinforcing structures exceeds the capacity of the resource which results in a reduction of the growing action for each of the reinforcing structures. As the Total Activity approaches the Resource Limit it begins to limit the Gain Per Individual essentially limiting the gain of both reinforcing structures. In the case of commons such as people, tools, materials or space, there is no conscious awareness of increased demand, but the concrete, physical limitations have no elasticity, and the satisfaction of people or teams placing demands on the commons erodes [60]. As aggregate performance of the commons slides, several consequences can be felt in the agribusiness. Individual or team performance declines as the erosion of the commons affects their ability to meet individual goals and objectives which in turn erodes agribusiness goals and performance. It is assumed that if the total usage of a common resource becomes too great for the system to support, the commons will become overloaded or depleted and everyone will experience diminished benefits. As long as the total activities or total draw on the resource from all players stay within the carrying capacity or limits of the commons, everything is fine. The Tragedy never gets triggered, and the players keep doing what they are doing. When consumption begins to exceed the resource’s ability to replenish itself; however, gains per individual effort will start to decline. When this happens, participants often respond by redoubling their efforts (B2 and B1). They may try to get the commons faster, initiate more request for the commons, or just outright grab more of the commons before others get to it. Of course, these kinds of tactics are quickly copied by everyone else, which further accelerates the depletion of the commons. Left unmanaged, these kinds of actions will eventually bring on the collapse of the commons. In this case, there will be no more gains for the participants, so their activities will finally cease or be greatly curtailed

This structure repeatedly appears in organizational contexts where a service organization supports the success of multiple departments who fail to support the service organization in return. There are two strategies for dealing with this structure, one being more effective than the other.

Death loss of growing pigs averaged about 50 pigs per week (at Agona Duakwa). Among these, preweaning mortality contributed about 60% which is attributed to lack of iron, hunger and thirst (as a result of lactating sow starvation), poor hygienic pens, and poor supervision. Other possible causes of preweaning death were small piglets’ susceptibility to cold, making them lie more closely to the dam to avoid hypothermia and resulting in them dying as a result of crushing. Unlike many mammals, piglets do not possess brown adipose tissue, a type of fat that enables newborn animals to generate a great deal of heat to maintain body temperature [61]. Wean-to-finish mortality was mainly due to starvation, thirst and unhygienic pen and environment.

Figure 11 shows the conceptual model, which was developed at the workshop to broadly describe the current situation in the piggery. The model explains the sources of complexity that has given rise to pig productivity predicament. From the model, it is apparent that the relationships between the key variables are far from simple or linear [62]. An inspection of this model revealed that the current adverse outcomes (pressure on management, high mortality rate and poor pen maintenance) could be traced back to the lack of integrated planning or decision making which affects productivity and in turn leads to business failure [63]. Ad-hoc cleaning of the pen by staff without taking charge or ownership of a block contributed mostly to these challenges as shown in Figure 11. This, in turn, increases the mortality rate and affects productivity, increasing workload and pressure on management.

The strategic management which curbs these deaths were assigning staff to take charge of the block, assigning new experienced manager and introduce new feed formulation to overcome malnutrition. The most important action implemented to decrease preweaning mortality was to install a manager during farrowing. Concern and vigilance during this time ensure that struggling piglets find the udder and can consume adequate colostrum. In addition, piglets that would be crushed can be placed in a safe spot until they can maneuver well and compete for a teat. However, the required tools (Measuring cups, shovels, wheelbarrows, cleaning brushes and brooms) to enable effectiveness were unavailable. Other challenges were workers not paid on time (sometimes almost 3 weeks over scheduled date), leading to disrespect to management instruction and putting more pressure on managers affecting the quality of work desired as shown in Figure 11.

 

 

Other challenges encountered leading to rising death rate within the period of November were re-allocation and mixing of weaned piglets to different pens as a result of counter instruction by the farm owner leading to fighting to death among piglets. However, the overall achievement in the face of all these challenges was enormous as within a period of 3 months, 70 sows were crossed and 220 weaned piglets castrated.

Accurate heat detection is essential for the correct timing of crossing [64]. Poor heat detection leads to higher production cost and reduced herd size as shown in the limit to growth archetype (Figure 14). This affects pork production and profit. Sows and gilts are non-seasonal and polyoestrous, with the oestrous cycle lasting 18–24 (average 21) days [65]. Sows are behaviourally anoestrous during pregnancy. Ovulatory oestrus usually is not seen during lactation except under conditions of group rearing, high feed levels, or boar contact. Partial weaning or gonadotropin treatment can induce oestrus during lactation, but the results are inconsistent and not economical [66]. Normal uterine physiology is re-established by 20–25 days postpartum. Most sows exhibit oestrus 3–7 days after weaning [67]. Oestrus lasts ~36–48 h in gilts and ≥48–72 h in sows [68]. Time to oestrus after weaning and duration of oestrus in sows can be influenced by the length of lactation, nutrition, body condition, genetics, and other management practices. Oestrus is characterized by behavioural (e.g., mounting, fence walking, vocalizing, tilted ears, kyphosis) and sometimes physical (e.g., vulvar swelling, vaginal discharge) changes. Ovulation generally occurs in mid to late oestrus. During ovulation, 15–24 ova are released over a 1 to 4-h period. Ovulation rate increases over the first four parities, so that the fourth to sixth litters tend to be the largest in number. Ovulation rate can decrease when gilts or sows are undernourished. Most gilts are on full feed, thereby averting the adverse effects of undernourishment on early reproductive performance. In circumstances in which gilts are not routinely provided with a full feed, increasing energy intake for 10 days before oestrus (i.e., “flushing”) is performed. This has optimized ovulation rate under these circumstances. To prevent undernourishment in recently weaned sows, an energy-dense diet should be fed until after oestrus and breeding.

Author Contributions: K.E.B. made contributions to the conception, design, and acquisition of data, analysis and interpretation of data. Led in drafting the article and revising it critically for important intellectual content; and gave final approval of the version to be submitted and any revised version; N.C.N. made contribution to methodology and editing, S.D. provided software support, help in original draft of manuscript and support in funding acquisition; D.K.A. helps in validation and editing; S.S.K. helps in data collection and validation, I.A. help in farm management and data collection and J.L. helps in formal analysis and focus group survey.

Funding: The contribution of Dr. Daowei Sun to this research was funded by the National Nature Science Foundation of China (71473282).

Acknowledgments: First and foremost, I would like to thank God Almighty for giving me the strength, knowledge, ability and opportunity to undertake this research study and to persevere and complete it satisfactorily. Without his blessings, this achievement would not have been possible. The authors would like to express great gratitude to all the livestock stakeholders of Ghana and BNARI for their time, willingness and contributions to this study.

Conflicts of Interest: The authors declare no conflict of interest.