What is Targeted Scenario Analysis
Targeted Scenario Analysis (TSA) is an innovative analytical approach that captures and presents the value of ecosystem services within decision-making to help make the business case for sustainable policy and investment choices. It was developed by UNDP in 2013.
Using TSA, practitioners working with governments and the private sector can produce balanced evidence for a decision-maker. This weighs up the pros and cons of continuing with business as usual (BAU), or following a sustainable development path in which ecosystems are more effectively managed. This alternate path is termed sustainable ecosystem management (SEM). Presenting data in this way to decision-makers increases the likelihood that it will be used to make policy and management decisions that result in effective and sustainable management of ecosystems and ecosystem services.
How TSA works
TSA builds on and combines traditional cost benefit analysis and economic valuation methods, broadening the type of information captured. It differs from these traditional approaches in that it takes a sector-specific approach to valuation, to reflect the perspective and remit of policy makers and companies. Rather than determining the general value of a particular resource or ecosystem service, TSA looks at ecosystem services from a stakeholder point of view. For example, rather than coming up with a single number that estimates the overall value of a coral reef, TSA will find the value of preserving the health of that reef from a fisheries perspective or from a tourism perspective (i.e. from the perspective of those influencing the management of the coral reef).
This makes the approach demand driven, rather than supply driven, asking: What information do decision-makers need in order to judge the importance of a particular ecosystem service and the benefits of enacting a particular policy or management option that maintains it?
TSA differs from traditional methods in that it provides information on the results of specific decisions and management practices as a continuous, long-term analysis, showing relative change over time of key monetary and non-monetary indicators, rather than as a static single value. This is key for decision making, as decisions are rarely made based on absolute numbers in isolation, but rather by comparing at least two options over time.