Towards the development of a situation-driven approach for the

of indicators

Following on from what was said in section 3.1, this section discusses how different decision making situations may be categorised further and explores the possible implications on the use of indicators. It is suggested that indicators’

selection may, at least in parts, be situation driven, and that a range of variables may constitute to a specific decision making situation. In order to demonstrate that different decision making situations may require different kinds of indicators, requirements along the strategic – tactical – operational dimensions of decision making are discussed and exemplified.

Niemeijer (2002) called the use of criteria for selecting indicators the theory-driven approach. He contrasted this with a data-theory-driven approach, which applies when the selection of indicators is based on data availability. A third approach was described by Lehtonen (2009; see also section 3.1) who suggested that there is also a politically-driven approach wherein indicator selection is motivated by politics and legal requirements.

In this section, a fourth approach is developed, following on from what was discussed in the previous section. This may be called ‘the situation-driven approach’ which is based on the hypothesis that indicators are used (or not used), depending upon the nature of the decision-making situation. If this was true, a decision maker could take advantage of the knowledge about a situation for selecting indicators. For example, if the situation was a bike path or transport

corridor plan situation, the decision-maker would potentially be able to select indicators, or narrow down the set of choices, based on this simple situational information. Therefore, the situation-driven approach says that indicator selection criteria are a function of the decision making situation.

Figure 9. Some dimensions characterising decision making situations

A number of variables characterising the differences in decision making situations have been discussed in the previous two sections. Some of them are included in Figure 9, depicting seven overall groups of variables that may influence the choice and formulate criteria of situation specific indicators. The seven groups include (1) the decision tier (i.e. whether it is a policy / strategic decision, a plan / tactical decision, programme or project / both operational decisions that is being prepared). Furthermore, and related to this, they include (2) the stage in the policy cycle, i.e. whether the policy agenda is set, the policy is formulated, concrete decisions are made and implemented or post decision evaluation is conducted. Also, (3) the transport modes to be considered, the administrative and functional geographical boundaries as well as the (4) spatial scale of impacts (from local to international) may play a role. (5) The type of formal requirements, as well as (6) the affected users / stakeholders and (7) the timescale of the policy, plan programme or project that is being prepared may influence the choice of situation specific indicators.

There are other related variables which could also be used to describe a decision making situation, including e.g. the legal framework within which a decision is made, whether objectives are agreed, whether knowledge exists, whether the decision rules are fuzzy or crisp, whether the problem is simple or complex, or whether uncertainties are large or small (see previous sections).

Due to the budget and time limits of this research project, trying to describe decision making situations so that all variables constituting the context of concrete decision making situations are fully considered is not possible, even though it may be desirable. In this chapter, instead, an attempt is made to characterise certain differences in indicator requirements related to the specific decision making situation along the strategic – tactical – operational dimensions. This is not randomly selected, as a number of decision making systems are organised along these dimensions, e.g. land use and planning acts are often organised in this way (national guidelines, municipal land use plans, zoning plans). The same could also be said about sector plans (National transport plan, regional transport planning, local transport plans). Furthermore, these tiers are related to what has been described as the ‘structuredness’ of different types or transport PPPP making and associated acting strategies in section 3.1.

Decisions made at the strategic level are long-term decisions about what to do in order to achieve something. This could be generic decisions about how to e.g. reduce GHG emissions from transport, or more specific decisions about how to solve a traffic and environment problems, like congestion on major roads or health problems caused by transport at the municipal level. Tactical decisions are of a more medium term nature and consider how to achieve what is decided on at the strategic level, including decisions on alternatives. Operational decision making, finally, is more short term and concerns the actual implementation in ways that maximize the positive outcomes and that minimize and mitigate negative effects and impacts (see also the policy, plan and programme examples provided in section 3.1).

Decision relevance is a criterion common for the selection of indicators.

Decision relevance revolves around the question what the decision is relevant

for. For example, climate change is an important environmental issue for which various indicators have been proposed (e.g. “Global Warming Potential” (GWP) or CO2 emission: see section 5.6.1). Yet the relevance of climate change depends on the decision-situation. If the decision concerns whether or not to build a new road (strategic), then climate change may be considered as being extremely relevant and associated indicators should be used in the decision-making. However, if the decision to build the road has already been made and if the situation revolves around the alignment of the road (i.e. whether tactical or operational), then climate change can be expected to be less relevant and other issues, such as noise pollution and habitat fragmentation, may be of greater importance. This does not mean that the global warming potential can not be reduced further, by e.g. choosing a different alignment. However, compared with other impacts, this is likely to be less significant and would probably be more appropriately covered under the heading reduction and mitigation of impacts. This point is discussed further in section 6.1.1.2. In a similar manner, other criteria may be a function of the situation, such as “Representativity” and

“Data availability” (for the discussion of criteria for indicator selection see Chapter 4).

There are also some generic differences between decision making situations. In strategic decision making, the aim is often to select few indicators, which represent main differences between strategic choices related to main objectives and main thresholds. In operational decision making, on the other hand, frequently the aim is to seek to develop a comprehensive knowledge about the impacts of the action to be implemented, and to bring in indicators representing most types of impacts.

There will be differences in the knowledge of the details of future situations.

Strategic decisions are often made without detailed knowledge, for example when dealing with the question whether to improve public transport services or building a new road. Operational decision making often happens on the basis of detailed information about the future situation, e.g. what will be built or done.

This also means that the certainty of impacts and of indicators representing these impacts will differ between strategic (i.e. policy), tactic (i.e. plan) and operational (i.e. programme and project) decision making situations. Taken together, the differences in detail and certainty about what will happen in the future represent a main difference between criteria for indicators to be used. It could be argued that the more strategic a decision making situation is, the more robust the indicators should be. Robustness here refers to the ability to represent differences in impacts related to the main objectives and thresholds.

Robustness also often relates to the existence of general knowledge about the interrelations between the decision and its implementation and how this will affect what is understood as the most important variables in each case.

Frequently, this means that the precision of the knowledge is not very good, even if there is certainty about roughly what the main impacts of different decisions are. The more operational a decision making situations becomes, on the other hand, the more comprehensive and detailed it is and appropriate indicators are needed. Among the main differences of indicator requirements for different decision making situations along the strategic – tactic – operational

dimensions could thus be said to be representativeness (few) versus comprehensiveness (many), and robustness versus certainty and precision.

This is illustrated here through a few virtual examples. If a city or a region has a problem with growing traffic volumes, causing increasing GHG-emissions, local pollution, health problems, traffic accidents, congestions and delays, a number of strategies may be chosen in order to improve the situation. At the strategic level, detailed planning of the different alternatives will often not be carried out. Instead, main variables to consider will be defined, based on their importance and on whether they are decision relevant (such as GHG-emissions, number of people affected by noise and local pollution, costs, accidents). Based on general knowledge about how implementation of the different strategies will affect these variables and about informed assumptions about possible solutions, knowledge will be produced (often as rough predictions) about what will happen in the future if each of the strategies is carried out, and how this will affect the most important variables. Indicators may be selected, representing the impacts on these variables.

At the tactical level, a decision may have been made to improve the situation by increasing road capacity or to build new roads. This can be done in several ways. Existing roads could be considered, new roads could be built, or tunnels be constructed. How and where this is done may have very different impacts. If it is supposed to be built in an environmentally sensitive area, then the impacts ensuing would make certain indicators particularly useful (vulnerability of nature, species etc., landscape aesthetics, effects on biodiversity etc.). If it was built in a populated area, it would have other impacts and a need for other indicators (number of people affected by noise and pollution, barriers etc.). What impacts we are talking about depends on the context and on the road (its size, speed limits, traffic load etc.). When it comes to decision making at the tactical level, the different alternatives would be defined in more detail (e.g. route alignment), which improves the possibilities to know what may happen in the future (what may be built) and what concrete impacts could be expected. This means that the knowledge needed in a specific decision making situation is defined by the context. Since there are a number of alternatives to consider, the focus will often be on trying to find the most important impacts. The number of variables, and thus the number of indicators, increases. At the same time, knowledge becomes more detailed and certain. Cost-benefit analyses are often used in programme situations to aggregate the positive and negative impacts of various alternatives into an index that is supposed to tell which is the “best” alternative, or what proposed projects should be given priority for investment (see a presentation of economic approaches in section 6.2.5).

When a decision is made about how and where to build a road, very detailed plans must be made. Detailed knowledge about the environment in which the road is to be built will be gathered. Together, this can provide decision makers with some good knowledge about what will be built and what consequences this will have on nature, society and economy. In this phase, an important task will often be to try adjusting the project, in order to maximize the positive effects and to minimise the negative effects. Severe negative impacts should always be mitigated.

3.4. An investigation into indicator selection