Environmental organisations need to rank projects that they could potentially invest in. Often it is done poorly. This post starts a series on how to do it better.

The funding available for environmental projects and policies is a small percentage of the money we would need to deal comprehensively with all environmental problems. As a result, whether we like it or not, we have to choose what we do and don’t protect. Even programs that don’t explicitly prioritise their environmental investments do so implicitly – they just do it in a non-transparent, and usually very poor, way.

In my experience, the difference in potential environmental outcomes between poor prioritisation processes and good ones is enormous.

Doing a good job of ranking the investment options is not that hard if you are aware of a few principles, but it seems to me that most people who are responsible for deciding how environmental funds get allocated are not aware of these principles. Indeed, some of the most commonly used approaches to ranking environmental projects are guaranteed to result in very poor rankings. As a result, we miss easy opportunities to deliver much greater environmental outcomes.

My aim in this series of posts is to outline a set of relevant principles and insights that will help environmental decision makers choose the best projects. My focus is on collecting and analysing the information needed to provide high-quality project rankings. There is another set of issues about how the rules of the program are designed to provide incentives for its participants to behave appropriately (e.g. Pannell and Roberts 2010), but I won’t be covering those here. I’ll be talking about information, calculations and clear thinking – stuff that is easy to get right if you know what you are doing.

My aim is to help with practical decision making. As a result, I’ll be talking about the possibility of cutting corners by simplifying aspects of the process. You’ll see that I’m not averse to well-considered simplifications, but very wary of the risk that some simplifications will sabotage the whole process. For a practical system, simplifications are essential, but bad simplifications are disastrous.

Throughout, I will be assuming that the aim is to provide the most valuable environmental outcomes for the available resources.

What is being ranked?

The first requirement is to be clear about what is being ranked. Sometimes programs set out to rank a set of projects that they might invest in. The projects should define what would be done, to which environmental assets, where, and by whom.

At other times, programs seek to rank a set of environmental assets, with no explicit project activities defined. (I’ll use the term “environmental asset” to refer to any identifiable feature, entity, place, or species that might become a target for investment.) There is a risk here – if you don’t define the project activities for an environmental asset, you cannot rank them on the basis of providing the most valuable outcomes.

The problem is that the environmental value for money depends on the answers to questions like, “what is the technical feasibility of protecting the asset?”, “to what extent would the community cooperate?” and “what would it cost to protect the asset?” However, those questions can only be answered for a particular set of actions or interventions.

To further illustrate the point, various different projects could be defined for the same environmental asset. One potential project might have very ambitious goals, aiming to return the asset to pristine condition, while another might aim for a moderate improvement in its condition. Some of these different projects for the same asset may offer relatively good value for money while others don’t (e.g. Roberts et al. 2012). So you cannot conclude that investing in any particular asset is good or bad without being clear about the project actions that will be undertaken.

If the analysis is limited to environmental assets, not projects, then it is important to be aware of what can and cannot be done with the results. What you can reasonably do is filter the assets to identify ones where it is relatively likely that a well-designed project would deliver worthwhile benefits. This could be done using variables such as:

• the value or significance of the assets,
• the levels of degradation they have already suffered or are likely to suffer in future, and
• the feasibility of managing them (in a loose general sense that doesn’t require specification of particular management actions).

You should not be making final decisions about which assets received funding, because that does require the specification of projects. Rather, you would be concluding that some assets are probably not worth considering further, and so not worth developing projects for.

Even this is not without risks. Because you are not looking at all of the relevant information, there is a chance of excluding some assets that would actually be worth investing in. For example, you might exclude investment in a particular asset because it seems likely to provide only modest benefits, but if the cost of the project is low enough, it could still be worth doing. With this process of filtering assets, you would miss out on cases like that.

However, it still might be worth filtering assets as part of a more comprehensive process. Indeed that is exactly what we do in Step 1 of INFFER (the Investment Framework for Environmental Resources) (Pannell et al. 2012). This is a simplification we use to reduce the cost of the system. If we can knock out some potential investments based on partial information, it takes less work to properly evaluate and rank a reduced set of potential projects.

If you must make final investment decisions based on assets, not projects, you need to imagine a notional project for each asset. Even a rough-and-ready notional project definition would be better than nothing.

Further reading

Pannell, D.J. and Roberts, A.M. (2010). The National Action Plan for Salinity and Water Quality: A retrospective assessment, Australian Journal of Agricultural and Resource Economics54(4): 437-456. Journal web site here ♦ IDEAS page for this paper

Pannell, D.J., Roberts, A.M., Park, G., Alexander, J., Curatolo, A. and Marsh, S. (2012). Integrated assessment of public investment in land-use change to protect environmental assets in Australia, Land Use Policy 29(2): 377-387. Journal web site here ♦ IDEAS page for this paper

Roberts, A.M. Pannell, D.J. Doole, G. and Vigiak, O. (2012). Agricultural land management strategies to reduce phosphorus loads in the Gippsland Lakes, Australia, Agricultural Systems 106(1), 11-22. Journal web site here ♦ IDEAS page for this paper