If you did not know that knowledge has a life cycle you are not alone. However, that should not be a consolation. Effectively managing knowledge begins with realizing that knowledge has a life cycle. Just as each valuable commodity has a life cycle, knowledge has a life cycle especially in the current knowledge economy. To the extent that knowledge changes form as it diffuses through a community or an ecosystem such as an agricultural market, it has several life cycles. Value chain actors who understand the dynamics of knowledge life cycles are better able to determine their knowledge needs and develop the right methods or tools to manage such knowledge.
Making sense of knowledge life cycles in African agriculture
While African agriculture and local socio-economic development is anchored on knowledge, skills and ability to apply (practical wisdom), trust and relationships remain fundamental in acquiring and applying knowledge. Farmers can have knowledge but lack skills to convert it into practical outcomes like crops, meat, milk and honey. The ability to mobilize resources, methods and navigate environmental challenges may be lacking due to poor understanding of existing knowledge life cycles.
On the other hand, instead of starting with knowledge, most development interventions start at the skills level. This is revealed through excessive emphasis on skills training which does not adequately consider farmers’ ability to apply what they learn from outsiders. Emphasis on outputs by development interventions also tend to ignore the application of knowledge, skills and abilities to produce better outcomes such as improved livelihoods, income, better decision making processes, wealth creation and employment creation, among others. Agricultural markets are mainly interested in the outcome of combining knowledge, skills and abilities, expressed through volumes of commodities, profit, growth-orientation, etc.,.
Knowledge life cycles drive project life cycles
Behind every project that has a life cycle is a knowledge cycle that functions as a mental software for the project. The knowledge life cycle can be surfaced through identifying knowledge gaps, mobilizing relevant knowledge, storing and classifying the knowledge appropriately. Most local knowledge in developing country communities is fragmented due to lack of storage systems where it can layered according to commodity orientation, farmer-level orientation, consumer-orientation and origin, among other parameters. This calls for the need to pay particular attention to developing knowledge life cycles.
Commoditizing through utilization
When they understand knowledge life cycles in their community and sector, farmers should be able to determine for which customers to convert skills into knowledge and commodities that satisfy market niches. This is where revenue generation starts through sharing, exchanging and filtering knowledge into different contexts. As local people and farming communities utilize knowledge they commoditize it in ways that continuously generate knew knowledge. Tangible value can be seen through commodities in the market.
Storing knowledge means using it over time and when it reaches its peak it becomes common knowledge or common sense. For instance knowledge required to produce staple crops like maize, small grains and vegetables has become common sense and stagnant. It can now either be enriched, updated or discarded completely, depending on different users. When hunting ceased to be an economic activity, related knowledge also disappeared. Some pesticides have reached their sell-by date and can no longer kill insects. It means new pesticides come with new knowledge that replaces old knowledge that was associated with pesticides that have moved out of circulation. The more users the more knowledge becomes common. When it reaches its peak, its competitiveness goes down. For instance, tomato production competitiveness has almost gone down. The market can tell you the point at which you should start considering export markets and related knowledge.
Managing climate change requires new knowledge life cycles
Many African communities, policy makers and development agencies realize the absence of new knowledge life cycles that can manage a changing climate. A decrease in crop yields and quality has caught most knowledge workers off-guard. There is urgent need to accurately identify knowledge gaps and arrange such knowledge appropriately before utilizing it. Continuous updating can enable knowledge curves to stay up until they reach a common sense level. This effort can start as upgrading the same commodities through value addition. For instance, producing new varieties or new products. Consumers can assist in identifying, sharing, classifying and utilizing knowledge related to different commodities.
Where do we start when identifying and building a knowledge life cycle?
A sensible starting point is data gathering. Such data has to be contextualized and converted into information which answers questions like who, what, where and when? Answering such questions generates usable knowledge (how and why?). Some of the insights can show why agricultural commodities behave the way they do on the market. When this awareness reaches its peak, it becomes wisdom and actors can either go back to start looking for more knowledge elements.
It is also important to figure out the source of building a knowledge cycle. If it’s about the consumer, the process boils down to creating awareness and knowledge about commodities. This is where it becomes critical to classify knowledge by consumer class and niche markets. The next step is satisfying knowledge needs embedded in commodities such as crop varieties, fruit type & quality, etc.. Ultimately this translates into customer loyalty or specific niche markets. Given that consumer tastes and preferences continue to change, they can signal the need for new knowledge life cycles based on new tastes, preferences, levels of income, etc. As a result, the need to develop new knowledge cycles become apparent. It means carefully monitoring the changing consumer needs and consumption patterns.
Mapping knowledge life cycles along agricultural value chains such as production, marketing, processing and consumption is very important. This will avoid cases where knowledge life cycles at production level get to their peak level while consumption level knowledge life cycles are still very low and unstructured. In such situations, you don’t just remove a crop variety out of circulation without consulting consumers or the market. On the other hand, processors can end up having their own variety which has nothing to do with knowledge existing at production levels. The prevalence of different knowledge life cycles compels farmers, informal markets, formal markets and processors to work together in order to harmonize their different knowledge life cycles.
Helping people, communities and organizations to identify and build knowledge life cycles
eMKambo has started rolling out master-classes whose themes include helping farmers, communities and organizations to identify and create their knowledge life cycles. For a long time, eMKambo has observed that most enterprises in developing countries focus on the production life cycle (revenue and volumes traded) yet behind the production life cycle is the knowledge life cycle that should be updated continuously. What happens on the consumer side signals competitiveness and shows the extent to which knowledge is now common sense and no longer unique. That influences the production life cycle.
The capacity to identify key elements of an effective knowledge-management strategy can no longer be over-emphasized. Most blue chip enterprises are collapsing because their knowledge cycles have reached their ceiling and cannot adjust to the new agile knowledge economy. Too many copy-cats are increasing competition. Likewise, extension models have reached their ceiling. Farmers need new knowledge life cycles. In the African education field, the curriculum has remained the same for decades. Attempts to tweak it are not adequately informed by the principles of effective knowledge generation, management and development of meaningful knowledge life cycles. Too much repetition of the same content with nothing really new to be considered value addition is the main reason why many ordinary level students can now achieve 20As at ordinary level. But this does not make the students practically knowledgeable.
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