Sustainability Indicators (SIs) represent elements or processes of real world systems and have specific (typically numerical) values that have a special meaning. The numerical value is a key feature of the SIs. “Indicators arise from values (we measure what we care about), and they create values (we care what we measure)” (Meadows, 1998). Other main features of SIs are their capacity to summarise, focus and compress the vast complexity of our dynamic environment to a manageable quantity of important information (Singh et al., 2012; Warhurst, 2002). Numerical SIs can be calculated in many different ways such as per time period, or per area, per total population, per capita, etc. and allow one to assess the progress of a project, process, region, city or country towards a specific goal. The values of the indicators can have different forms:
Nominal scale: consists of two binary values yes or no. It can be meaningless in terms of quantitative information, however in controversial cases it is often used to agree on a solution.
Ordinal scale: based on a hierarchy of qualitative states, such as the quality of training provided for the employees. The hierarchy has to be unambiguous with different defined classes for these scales to work correctly.
Cardinal scale: provides quantitative information. In sustainability goals are linked to targets, hence the progress can be measured. Quantified targets have to be agreed on before deriving the scale (Mulder, 2006).
By simplifying complex phenomena, SIs may help politicians, industry leaders and other stakeholders to define specific targets, linking them to understandable objectives and real life projects. Scipioni et al. (2008) argue that the core function of the indicator is to represent the analysed problems in a way that maintains the informative content of the evaluation. Donnelly et al. (2007) argue that the main function of a sustainability indicator is to reduce the volume and complexity of
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information which is required by decision makers. For example, water or air quality indices are the most common environmental quality indicators. However, these indices are calculated using a lot of data based on the concentration of chemicals and pollutants in water and air. Decision makers and other stakeholders do not have to know all the details behind these calculations; it is the purpose of the indicator to communicate this complex information in an accurate and understandable way to influence a decision making process (Donnelly et al., 2007).
The main purposes of sustainability indicators are summarised in figure 2.1.
Figure 2.1. The main roles of sustainability indicators. Adapted from Pastille, 2002b.
PURPOSES OF
SUSTAINABILITY
INDICATOR USE
Involving Stakeholders Participation and involvement Communication Initiation of discussion and awareness raising Solving Conflict Coordination and liaison Mediation Discussion about different values Supporting Decisions Definition ofobjectives and goals
Identification of actions required Benchmarking Understanding Sustainability Identification of relevant issues
Current state and future trends
Education and provision of information Direction Monitoring and evaluation Assessing performance Interpretation Guiding/controlling
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Sustainability indicators must satisfy a certain number of criteria. The summary of main criteria is provided in figure 2.2.
Not all indicators, however, can satisfy all the above criteria. In some cases, the accurate data cannot be obtained, thus some assumptions have to be made. In other cases, particularly in regards to the social aspects, the indicators cannot be measured
MEASURABLE
- Be easily measured; - Use existing and
available data; - Be reliable and
consistent over time and space;
- Be scientifically robust and credible; - Be verifiable and
replicable;
- Have a target level, baseline or threshold against which to measure them; - Be cost effective to
measure.
CRITERIA FOR SUSTAINABILITY INDICATORS
CLEAR - Be accurate and bias free; - Unambiguous, easy to understand and interpret; - Transparent and accountable; - Be simple- the number of indicators should be limited and the way of calculating them transparent;
- Can detect changes at the appropriate temporal and spatial scale; - Be easily accessible to decision-makers; - Be based on well- understood and generally accepted conceptual models of the system to which they are applied. RELEVANT - Measure what is important for stakeholders; - Be linked to practical action; - Be policy relevant
for all stakeholders, including the least powerful;
- Be directionally clear – they have to specify objectives and trends noticeably relevant in terms of significance for sustainability, therefore be able to indicate the progress or the lack of it; - Predict changes that
can be averted by management actions.
Figure 2.2. Criteria of sustainability indicators (Reed et al., 2006, Ugwu et al., 2006, Valentin and Spangenberg, 2000, Meadows, 1998, UNCCD, 1994, Braat, 1991, Zhen and Routray, 2003, Dale
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in quantifying terms. In many circumstances, aggregated indicators can be unclear, ambiguous and difficult to interpret due to a large number of data hidden behind the final value. Identifying a core set of sustainability indicators for the evaluation of a specific project or process is a prerequisite for any sustainability assessment. However there are a number of pitfalls in SIs development and use. The most common of these are the following:
The indicators cannot explain all the complexities of the ecosystems and economic systems; thus, often they cannot provide the exact answer and could only be used as a guideline.
Not presenting sufficient numbers of indicators for each component in the framework may lead to misleading interpretation. Indicators that are only presented as percentage deviations from a baseline or, the ones that use a comparison without presenting the absolute values may not give the whole story.
The existing data is often used instead of collecting new data, which leads to measuring what is easier and not what is important to measure.
Aggregated indicators (indices) can lead to a misrepresentation of the correlations between the component parts.
The indicators could be easily intentionally misrepresented to support a predetermined particular result rather than letting the indicator illustrate a neutral story (Olewiler, 2006).