This working paper describes the results of a survey done on soil data availability and use in the agricultural sector in Kenya. The survey was commissioned by the National Environment Research Council (NERC) to assess the potential value of NERC digital tools such as the MySoil app, to decision makers in the region. The objectives of the survey were therefore to highlight the decision needs related to sustainable agricultural intensification that would be met through greater accessibility to soil information, identify the critical uncertainties surrounding those decisions and identify the potential information that could be provided by a digital app such as the MySoil app for Africa. Those surveyed were selected from research and academia, government, private sector, agricultural extension, community work and farmer groups. The survey was conducted through an online questionnaire on SurveyMonkey. The results showed that the greatest information need that could be met through a digital application was site- and crop-specific input recommendations while the biggest consideration when developing such a tool needs to be given to figuring out how to communicate effectively with end users. The report also recommends a horizontal approach to the development of the app. This would allow for contributions based on farmers’ indigenous knowledge.
Tag: Decision-making
Stakeholder Approach to Risk Informed and Evidence Based Decision Making (SHARED) for Resilience
Decision-makers from the household to state level frequently have to make decisions within a context of risks, uncertainties, multiple possible outcomes and stakeholder groups with varied interests. It is therefore reasonable for them to be concerned about the risk that an investment or intervention could fail to achieve its objectives. This happens because the uncertainties surrounding the impacts of a proposed development intervention during project assessment are usually not addressed. These uncertainties can be high where information on the parameters of interest and how they will evolve under future change is scarce. For instance, there is a severe lack of data on the ecological, socioeconomic, cultural and political parameters that would influence the complex dynamics of environmental systems.Decision analysis aims to assist decision-makers in making rational decisions in situations where they are faced with imperfect information. It is concerned with identifying the most promising course of action, while recognizing risks and uncertainties. Initially, analyses are based on the current state of knowledge about particular variables of interest, before any measurements are taken. This knowledge is used for probabilistic simulations of the full range of plausible system outcomes of particular interventions, which aid in prioritizing decision options based on their likely outcomes or impacts. This is achieved by including decision-makers, various stakeholders and end-users in conducting ex-ante impact assessments using quantitative impact pathways and probabilistic estimates of all relevant benefits, costs, risks and uncertain variables. Business decision analysis methods offer a promising way forward, because they have been designed for aiding businesses in making decisions on risky projects with limited research budgets. To achieve this, a key objective of decision analysis is capturing the current state of uncertainty.
Kenya Decision Dashboard
This information brief describes the on-going development of a decision dashboard for the Upper Tana region to assist decision makers in using data and evidence for planning, implementation and monitoring. The dashboards support the work of three IFAD funded projects (KCEP-CRAL, UTNWF and UTNRMP) within the region and 14 partnering Counties where the projects are active.
Developing a national system for land health monitoring using decision dashboard
This information note describes the proposed dynamic system to monitor and track land degradation, land health status and agroforestry systems to allow for evidence based planning and decision making.
Enabling Decision-Making for Agricultural Interventions
Agricultural systems are influenced by a range of environmental, economic and socio-‐cultural factors. Due to this complexity, policymakers in agricultural development need science-‐based guidance to make decisions. Classical research approaches, using data-‐driven models, often fail to inform intervention decisions due to insufficient and low quality data. Given their multifaceted and complex nature, agricultural issues require the integration of knowledge and systems thinking from beyond the discipline-‐specific approaches that are often used.
A novel decision analysis and risk assessment framework for improving agro-ecosystem interventions
Designing and implementing agro-ecosystem intervention decisions is a complex undertaking, outcomes are uncertain and risk of project failure and cost overruns are large.
The need for an Intervention Decision Model
The Consultative Group on International Agricultural Research (CGIAR) needs to develop a comprehensive, quantitative model to assess the value of intervention decisions. The Intervention Decision Model (IDM) will be the basis for prioritizing interventions, determining how to measure the impact of interventions on development outcomes, and calculating the value of the research itself.
Guidelines for identifying and designing planned comparisons
Planned comparisons help us to assess the relative effectiveness (possibly including cost-effectiveness) of options in addressing development challenges. Often, the suitability of options will vary by context, so different options suit different people and places. Planned comparisons help us to compare different options, so that we can better understand what works where and for whom. They provide us with evidence to guide investment decisions and to target interventions to where they are most likely to be effective. They can also generate more basic understanding to support the further design or modification of those options being considered, and—at the same time—contribute scientifically sound knowledge to the global knowledge base.
Survey data of intra-household decision making and smallholder agricultural production in Northern Uganda and Southern Tanzania
This article provides a description of intra-household survey data that were collected in Uganda and Tanzania in 2014 and 2015, respectively. The surveys were implemented using a structured questionnaire administered among 585 households in Uganda and 608 in Tanzania. Information on decision making processes in agricultural production was collected from the principal adult male and female decision-makers in each household. The survey consisted of two parts. Firstly, the decision-makers, both male and female of each household were jointly interviewed. Secondly, individual interviews were carried out, questioning the decision-makers separately. The datasets include both household and individual level data containing numeric, categorical and string variables. The datasets have been shared publicly on the Harvard dataverse.
Capacity development manual and training workshop report
The SHARED is a comprehensive framework tailored to specific decision needs, which brings together processes, evidence and tools to assist in shifting the decision paradigm towards more inclusive, inter-sectoral and inter-institutional integration.