- Sustainable landscape initiatives should be based on reliable data.
- Different types of analysis are useful for evaluating proposed interventions against different criteria: environmental, social, financial and cross-cutting criteria.
- These analyses can help a sustainable landscape initiative define an investment portfolio.
- Cash flow analyses and financial risk analyses are a necessary step for investors. These analyses can also help producers understand possible net income from taking part in the scheme.
These analyses build on the BAU and SEM scenarios constructed for each intervention, whether they are in productive supply chains, conservation activities or projects supporting sustainable livelihoods. Building on these scenarios, it is possible to carry out several key assessments:
Before implementation, this process is useful for comparing different interventions and selecting which would be best to finance, and which should be discarded. During implementation, the criteria used in these analyses are also useful for measuring progress.
However, it should be noted that some things are not directly comparable in all assessments. Conservation and sustainable livelihood interventions are unlikely to generate revenue, so financial criteria should not be used to compare them with interventions in productive supply chains. However, these interventions bring significant environmental and social benefits so should still be considered.
1. Socio-economic impact assessment
This assessment aims to ensure the interventions contribute to local social priorities, bringing benefits for local people including employment, income and education. Moreover, they should not promote activities with negative effects. For example, some interventions may have a negative effect on traditional production methods. In other cases, interventions on disputed lands could restrict indigenous peoples’ access to natural resources.
Important stages in socio-economic impact assessment:
Define a set of ‘no go criteria’ for interventions.
Discard interventions failing the ‘no go criteria’.
Define important benefits for the local area. These may include health, education, land rights, income, cultural heritage and so on.
Narrow the benefits down to the most relevant according to regional priorities.
Define one or more specific and relevant indicators per benefit. These indicators may be qualitative or quantitative.
Assess the interventions according to the indicators.
Criteria based on quantitative indicators, such as jobs created or the number of farmers trained, are easier to measure accurately. In contrast, some qualitative indicators such as producer satisfaction are harder to measure. A combination of qualitative and quantitative indicators should be used.
Existing guidance frameworks can help, providing suggestions for indicators and assessment methods. Useful reference documents in this process include the performance standards for international investments developed by the International Finance Corporation (IFC) and the project level standards by the REDD+ Social & Environmental Standards Initiative.
Once indicators have been selected, it is important to draw up a guidance document explaining how they should be used.
When there is a significant risk of a negative impact on working conditions, it may be possible to mitigate this by designing effective Codes of Conduct for producers.
2. Environmental impact assessment
What are the possible environmental risks and benefits associated with interventions? For example, is increased efficiency likely to lead to an expanded area of agriculture, potentially consuming forest or other important landscapes?
It is crucial to understand how interventions may impact the landscape. In this area, it may be necessary to consult environmental experts or carry out questionnaire research with producers and other stakeholders. The results of such an assessment also form the basis for possible mitigation strategies to avoid unintended negative impacts.
Define a set of ‘no go criteria’ for interventions.
Discard interventions when ‘no go criteria’ is applicable.
Define which environmental benefits are important. For example, these may include greenhouse gas emissions reductions, improvements in water quality or a reduction in deforestation.
Draw up a series of indicators to measure these benefits. They may be qualitative or quantitative.
Assess the interventions according to the chosen indicators.
As with the socio-economic impact assessment above, existing guidance frameworks can provide suggestions for indicators and assessment methods.
The Unlocking Forest Finance projects used the impact assessment questionnaire template below:
In general, selection criteria should be chosen according to the priorities of the project. In some cases, criteria may be prioritised which are more interesting to investors or donors. For example, philanthropic funds or donor governments may value environmental impact well above financial impact. These kinds of investors will need a significant level of information regarding the impact their investment will make.
3. Financial viability assessment
When assessing the financial viability of interventions, there should ideally be two main types of analysis: Cash flow analysis and financial risk analysis. These analyses may also incorporate risks from future climate change as this may significantly affect the financial viability of the intervention.
Climate change risk assessment
The climate is certainly changing. But climate change will affect the agriculture sector very differently in different regions. Agriculture is particularly sensitive to extreme climate events such as droughts and floods. Increases in temperature might render some crops more productive while reducing output of others.
More significantly, specific interventions such as agroforestry systems and better water management, might give sustainable agriculture the edge, not only in environmental terms but also in financial terms when climate change is considered. For these reasons, climate change should be incorporated into assessments of future agricultural output, such as the cash flow analysis or risk analysis.
Cash flow analysis
The aim of cash flow analysis is to project the most likely financial outcome of the interventions over several years. This is done on a basic metric (such as per hectare) for the whole proposed transition in a particular activity. This analysis is a basic requirement for most investors.
Such long-term projections of the future are complicated. This is particularly true when these projections are based on regional government plans and projections, which often look forward no more than 3-5 years. In contrast, sustainable landscape initiatives may consider 10, 15 or even 30 year horizons. Moreover, external factors such as technology changes, weather events or drastic changes in supply and demand can be impossible to predict.
Nonetheless, more detailed information will probably lead to more accurate projections. This includes data on the specific situation in the region where the initiative will take place.
To complete a cash flow analysis for the proposed transition, it will be necessary to have the following information.
Area cultivated: For projections of future agriculture, it is first necessary to define how much land is currently used by supply chains, and how much will be used under the business as usual scenario, without the sustainable landscape initiative.
Costs: It is important to understand the costs involved in various supply chains. This includes the costs of pesticides, seeds, machinery and so on. For calculations of labour costs, it is necessary to understand the hours of work needed for each process and average wages. The costs are defined on a basic unit (such as per hectare). Information is needed on specific costs in both scenarios (BAU and SEM). This may include information on the types or amounts of fertiliser, number or quality of seeds, and so on. More detail is generally better.
Prices: In most cases, price data can be gathered from international trade statistics. When commodities have not been traded internationally, it may be necessary to gather information by interviewing farmers, cooperatives or processors. In some cases ’official’ information might not be available. In this case it will be necessary to work with other local stakeholders to validate available data to increase reliability.
Productivity: In most agricultural interventions, one of the key objectives is to significantly increase productivity. To assess potential productivity and subsequent financial gains, it is necessary to know both current productivity levels, and potential productivity after interventions. For current levels, this data may be available from the regional or national government. If not, it may be necessary to interview farmers or representatives of producer organisations. For potential future productivity, after interventions, this information comes from looking at the real-life productivity levels of other farmers already using these methods.
A template spreadsheet for carrying out cash flow analysis is included below.
A note on using proxy data
If there is little data available on a particular supply chain in a particular region, there may be a temptation to use proxy data – for example, using data on the same supply chain but based in a different region.
The Unlocking Forest Finance project avoided using proxy data because it is unlikely to provide a complete picture. For example, there may be little data available for a remote region deep in the forest. More populated, better connected areas will usually have better data – but for the same reasons, costs, prices and productivity are likely to be different, as these factors are strongly influenced by transport distances, population and so on.
Financial risk analysis
The aim of risk analysis is to estimate, with 95% confidence:
the probability of a supply chain incurring a loss
and the maximum extent of a loss in a worst case scenario.
Cash flow analysis looks at the expected general business case for investment, including projected costs and prices over time. They represent the ‘central case’ or best estimate of future revenues and costs (and therefore profits).
However, projecting far into the future is a difficult task given the inherent uncertainty involved. It is almost inevitable that future estimates will be impacted by unforeseeable events. Risk analysis allows us to account for the possibility that cash flows may not follow the ‘central case’ based on these estimates.
Importantly, adverse outcomes can result in financial mechanisms yielding lower than expected returns or even a loss. It is thus a key consideration for investors. For instance, there may be an agreement to pay a certain price for a kilo of coffee produced in a certain region. In reality, however, returns might be above or below the ’central case’ estimated. This is particularly likely given the long planning horizon involved in the transition.
Risk analysis is therefore important for investors, as uncertainty surrounding data and the extent of risk can influence the design of the financial mechanism or even the overall viability of the investment.
Risk analysis uses similar sources the cash flow analysis to estimate data inputs: historical data, research into key literature and interviews with local experts.
However, there is a key difference: cash flow analysis uses point estimates for prices, costs and productivity, while risk analysis is based on ranges around these point estimates. At a minimum, data should cover fluctuations in these factors over the last five years.
More on risk analysis is available in the document below:
4. Overall viability of interventions
Beyond individual assessments of environmental, social and financial impacts, it is necessary to consider interventions in terms of their overall viability. Project partners will need to discuss a number of different questions. For example:
Are there investors interested in funding these supply chains? Supply chains which will not attract investors should be removed from this round of investment.
Are there enough technical specialists available to train producers? If there are not enough, is it feasible to attract the necessary professionals to the region?
Are there existing credit lines funding this supply chain?
Are there reliable organisations to help disburse finance working in this area?
Could this intervention be scaled up to address more producers?
Once these questions have been answered, it should be possible to eliminate supply chains which may be too complicated or problematic. The remaining list can make up a definitive portfolio of supply chains for investment.