Build and jointly assess scenarios: Difference between revisions

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{{SumpStep/top|step=4|phase=2|title=Build and jointly assess scenarios}}<div class="sump-intro">
{{SumpStep/top|step=4|phase=2|title=Build and jointly assess scenarios}}<div class="sump-intro">
With a clear baseline from Step 3, the plan turns from diagnosis to direction. Step 4 is where alternative futures are sketched and weighed: not a single finished proposal handed down for comment, but several plausible directions the area could take, each tested for what it would actually deliver and for whom. Assessing those options openly, and with the stakeholders who will live with the result, is what makes the strategy that follows both evidenced and supported. A scenario quietly chosen behind closed doors rarely survives contact with the people it affects.
Now the plan turns from diagnosis to direction. Alternative futures are sketched and weighed, not a single finished proposal handed down for comment, but several plausible directions the area could take, each tested for what it would actually deliver and for whom. Assessing those options openly, and with the stakeholders who will live with the result, is what makes the strategy that follows both evidenced and supported. A scenario quietly chosen behind closed doors rarely survives contact with the people it affects.
</div>
 
<div class="sump-prereq">
<div class="sump-prereq__title">Before you start this step you should already have</div>
<div class="sump-prereq__list">
<div class="sump-prereq__item"><div class="sump-prereq__box"></div><div class="sump-prereq__text">A dated [[Analyse the mobility situation|accessibility baseline]] for the area as it stands, measured both against a normative standard and against what residents said they need.</div></div>
<div class="sump-prereq__item"><div class="sump-prereq__box"></div><div class="sump-prereq__text">The groups your diagnosis found least well served, because a scenario aimed at the area average will not close the gap that matters.</div></div>
<div class="sump-prereq__item"><div class="sump-prereq__box"></div><div class="sump-prereq__text">Every body that holds a lever [[Set up working structures|at the table and willing to weigh options together]], since no single authority in a periphery can impose a preferred future.</div></div>
</div>
</div>
</div>


== Why scenarios matter more in the outskirts ==
== Why scenarios matter more in the outskirts ==


In a dense core, the menu of mobility measures is broad and familiar, and the argument is usually about priorities among well-understood options. In the periphery the situation is different. The interventions that close a 15-minute gap are often newer and less proven, a shared mobility service, a flexible activity hub, a demand-responsive line, and their success depends heavily on local conditions that vary from one outskirt to the next. That uncertainty is exactly why scenario work earns its place here. Rather than betting the plan on one untested idea, Step 4 lets a team lay several options side by side, see which closes the most of the perceived-accessibility gap, and understand the trade-offs before any money is committed.
In a dense core, the menu of mobility measures is broad and familiar, and the argument is usually about priorities among well-understood options. In the periphery the situation is different. The interventions that close a 15-minute gap are often newer and less proven, a shared mobility service, a flexible activity hub, a demand-responsive line, and their success depends heavily on local conditions that vary from one outskirt to the next. That uncertainty is exactly why scenario work earns its place here. Rather than betting the plan on one untested idea, scenario work lets a team lay several options side by side, see which closes the most of the perceived-accessibility gap, and understand the trade-offs before any money is committed.


The other reason is ownership. The DREAMS approach treats residents and local actors as co-authors of the scenarios, not an audience for them. Because the periphery's levers are shared across a core city, suburban municipalities and a regional transport tier, no single authority can simply impose a future. Building the options together is how a cross-boundary coalition comes to back the same direction.
The other reason is ownership. The DREAMS approach treats residents and local actors as co-authors of the scenarios, not an audience for them. Because the periphery's levers are shared across a core city, suburban municipalities and a regional transport tier, no single authority can simply impose a future. Building the options together is how a cross-boundary coalition comes to back the same direction.
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== How DREAMS structures the choice ==
== How DREAMS structures the choice ==


DREAMS frames the whole decision through a single layered model. The first two layers are the baseline you established in Step 3: a normative, calculated view of accessibility and a perceived view that reflects what residents actually need and will accept. The three higher layers are built for scenario work, and they map almost exactly onto the questions a planning team has to answer in this step.
DREAMS builds the answer in layers, each one adding a constraint the layer below it leaves out. The lower two describe the neighbourhood as it stands today, first against a textbook standard and then against what residents themselves need and will accept. The three above them take a proposed scenario and put it through the three tests a planning team has to pass before committing to anything.


<div class="sump-phases">
<div class="sump-phases">
<div class="sump-phases__item">
<div class="sump-phases__item sump-phases__item--fig">
<div class="sump-phases__fig">[[File:DREAMS-scenario-what-residents-want.svg|frameless|180px|link=]]</div>
<div class="sump-phases__title">What residents want</div>
<div class="sump-phases__title">What residents want</div>
<div class="sump-phases__desc">User-optimised scenarios, co-created with residents, that reflect the changes they want in activities, services and everyday access. This is the desirable future, defined by the people who live there.</div>
<div class="sump-phases__desc">Take a scenario as residents and local actors co-created it, with the changes they asked for in services, activities and everyday access, and measure how much of the accessibility gap it closes. Nothing is filtered for cost yet. This settles whether the scenario is worth having.</div>
</div>
</div>
<div class="sump-phases__item">
<div class="sump-phases__item sump-phases__item--fig">
<div class="sump-phases__fig">[[File:DREAMS-scenario-what-is-realistic.svg|frameless|180px|link=]]</div>
<div class="sump-phases__title">What is realistic</div>
<div class="sump-phases__title">What is realistic</div>
<div class="sump-phases__desc">The same scenarios filtered through real constraints: budgets, available infrastructure, governance, and viable business models for new services, mobility hubs and activity hubs. This is the achievable future.</div>
<div class="sump-phases__desc">Now run the same scenario against the constraints, the budget, the infrastructure already on the ground, who holds the authority to act, and whether a new service or hub can run at a cost someone will cover. Scenarios usually shrink here. This settles what could actually be delivered.</div>
</div>
</div>
<div class="sump-phases__item">
<div class="sump-phases__item sump-phases__item--fig">
<div class="sump-phases__fig">[[File:DREAMS-scenario-what-it-delivers.svg|frameless|180px|link=]]</div>
<div class="sump-phases__title">What it delivers</div>
<div class="sump-phases__title">What it delivers</div>
<div class="sump-phases__desc">The estimated effect of each scenario on the strategic objectives and societal impacts that matter locally, from accessibility and emissions to health and equity. This is the future worth choosing.</div>
<div class="sump-phases__desc">Score what survives against the outcomes the area says it cares about, from accessibility and emissions to health and equity. A scenario that is wanted and deliverable is not automatically the best one. This settles which option does the most good.</div>
</div>
</div>
</div>
</div>


Because the same accessibility model underlies both the baseline and the scenarios, a team can test a concrete change, a new mobility hub at a particular junction, a demand-responsive service across a low-density fringe, a relocated or added amenity, and read off how much of the perceived-accessibility gap it closes, and for which groups. The five intervention families DREAMS works with across the living labs give a ready vocabulary for these tests: '''mobility hubs''', '''flexible activity hubs''', '''demand-responsive transport''', '''car-sharing and car-pooling''', and '''shared micromobility'''. Most can be combined, and the point of the exercise is to find the package that performs, not to crown a single measure.
Because the same accessibility model underlies both the baseline and the scenarios, a team can test a concrete change, a new mobility hub at a particular junction, a demand-responsive service across a low-density fringe, a relocated or added amenity, and read off how much of the perceived-accessibility gap it closes, and for which groups. The five intervention families DREAMS works with across the living labs give a ready vocabulary for these tests. They are '''mobility hubs''', '''flexible activity hubs''', '''demand-responsive transport''', '''car-sharing and car-pooling''', and '''shared micromobility'''. Most can be combined, and the point of the exercise is to find the package that performs, not to crown a single measure.


== Backcasting: start from the future you want ==
== Backcasting starts from the future you want ==


Forecasting asks what happens if current trends continue. '''Backcasting''' asks the more useful question for a 15-minute plan: if this is the neighbourhood we want in ten years, what has to happen to get there? DREAMS built its scenario work around participatory backcasting workshops in the living labs, bringing together government, business and civil society to define a desired 15-minute state and then work backwards to the interventions, business models and governance changes that would reach it. The method suits the outskirts particularly well, because it forces the cross-boundary conversation about who funds and who delivers each step early, while the vision is still being shaped, rather than after a plan is fixed.
Forecasting asks what happens if current trends continue. '''Backcasting''' asks the more useful question for a 15-minute plan. If this is the neighbourhood we want in ten years, what has to happen to get there? DREAMS built its scenario work around participatory backcasting workshops in the living labs, bringing together government, business and civil society to define a desired 15-minute state and then work backwards to the interventions, business models and governance changes that would reach it. The method suits the outskirts particularly well, because it forces the cross-boundary conversation about who funds and who delivers each step early, while the vision is still being shaped, rather than after a plan is fixed.


The living labs show the raw material of these scenarios in practice. In [[Living_Labs/1|Vienna's Liesing district]], a flexible activity hub reactivating an underused space, paired with a light bike-sharing station, was co-designed with residents rather than specified in advance. In the Paris T12 corridor, the scenario centred on new shared-mobility stations feeding the tramway, tested directly against whether they shortened last-mile trips and pulled people out of cars. Reading how a comparable lab framed its options is a fast way to populate your own scenario set with interventions that have already been tried.
The living labs show the raw material of these scenarios in practice. In [[Living_Labs/1|Vienna's Liesing district]], a flexible activity hub reactivating an underused space, paired with a light bike-sharing station, was co-designed with residents rather than specified in advance. In the Paris T12 corridor, the scenario centred on new shared-mobility stations feeding the tramway, tested directly against whether they shortened last-mile trips and pulled people out of cars. Reading how a comparable lab framed its options is a fast way to populate your own scenario set with interventions that have already been tried.
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== Building and assessing your own scenarios ==
== Building and assessing your own scenarios ==


The sequence holds whether you use the DREAMS tools or your own modelling. Start from the baseline and the population groups your Step 3 diagnosis singled out, and define two or three contrasting scenarios rather than one, each a coherent package of measures aimed at the gaps that matter most. Co-create them with residents and local actors, so the options reflect real needs, not just what is easy to build. Then assess each one consistently: how much of the perceived-accessibility gap it closes, for which groups, at what cost, and against the strategic objectives the area cares about. Bring the assessed options back to stakeholders as the basis for an open choice, and record both the chosen direction and the reasoning, because the scenarios you reject are part of the evidence trail too. Resist the urge to model a dozen variants; a few well-drawn, genuinely different futures will serve the decision far better than an exhaustive set no one can compare.
The sequence holds whether you use the DREAMS tools or your own modelling. Start from the baseline and the population groups your diagnosis singled out, and define two or three contrasting scenarios rather than one, each a coherent package of measures aimed at the gaps that matter most. Co-create them with residents and local actors, so the options reflect real needs, not just what is easy to build. Then assess each one consistently, against how much of the perceived-accessibility gap it closes, for which groups, at what cost, and how it performs on the strategic objectives the area cares about. Bring the assessed options back to stakeholders as the basis for an open choice, and record both the chosen direction and the reasoning, because the scenarios you reject are part of the evidence trail too. Resist the urge to model a dozen variants when a few well-drawn, genuinely different futures will serve the decision far better than an exhaustive set no one can compare.


<div class="dreams-handoff">
<div class="dreams-resource-cards">
<div class="dreams-handoff__label">Tools for this step</div>
<div class="dreams-resource-card dreams-resource-card--access">
The [[Dreams Accessibility Tool|DREAMS Accessibility Tool (DAT)]] carries the map-based accessibility layers used here, letting you test how a proposed intervention shifts accessibility against the baseline from Step 3. For the qualitative side of weighing options with stakeholders, the [[Stakeholder-based Impact Scoring|stakeholder-based impact scoring]] approach helps structure how different actors rate the trade-offs between scenarios.
<div class="dreams-resource-card__title">DREAMS Accessibility Tool</div>
<div class="dreams-resource-card__text">Carries the map-based accessibility layers used here. Test how a proposed intervention shifts accessibility against your current baseline and read off which groups gain and which do not.</div>
<div class="dreams-resource-card__action">[[Dreams Accessibility Tool|Open the tool →]]</div>
</div>
</div>
</div>


<div class="sump-sources">Sources and further information: EU SUMP Guidelines, Second Edition (Rupprecht Consult, 2019), Step 4 "Build and jointly assess scenarios"; DREAMS Deliverable 3.1 (the DDST layer architecture and the DREAMS Accessibility Tool); DREAMS Deliverable 6.1 (intervention scenarios and impact areas across the living labs); the participatory backcasting approach set out in the DREAMS project design (WP3 and WP4).</div>{{SumpStep/bottom|step=4}}
<div class="sump-sources">
<div class="sump-sources__title">Sources and further information</div>
<div class="sump-sources__item"><span class="sump-sources__ref">EU SUMP Guidelines, Second Edition</span> (Rupprecht Consult, 2019), Step 4, Build and jointly assess scenarios.</div>
<div class="sump-sources__item"><span class="sump-sources__ref">[[Publications/7|DREAMS Deliverable 3.1]]</span>: the decision support tool layer architecture and the DREAMS Accessibility Tool.</div>
<div class="sump-sources__item"><span class="sump-sources__ref">[[Publications/6|DREAMS Deliverable 6.1]]</span>: intervention scenarios and impact areas across the living labs.</div>
</div>
{{SumpStep/bottom|step=4}}

Latest revision as of 12:44, 31 August 2026

Step 4 of 12 Strategy Development

Now the plan turns from diagnosis to direction. Alternative futures are sketched and weighed, not a single finished proposal handed down for comment, but several plausible directions the area could take, each tested for what it would actually deliver and for whom. Assessing those options openly, and with the stakeholders who will live with the result, is what makes the strategy that follows both evidenced and supported. A scenario quietly chosen behind closed doors rarely survives contact with the people it affects.

Before you start this step you should already have
A dated accessibility baseline for the area as it stands, measured both against a normative standard and against what residents said they need.
The groups your diagnosis found least well served, because a scenario aimed at the area average will not close the gap that matters.
Every body that holds a lever at the table and willing to weigh options together, since no single authority in a periphery can impose a preferred future.

Why scenarios matter more in the outskirts

In a dense core, the menu of mobility measures is broad and familiar, and the argument is usually about priorities among well-understood options. In the periphery the situation is different. The interventions that close a 15-minute gap are often newer and less proven, a shared mobility service, a flexible activity hub, a demand-responsive line, and their success depends heavily on local conditions that vary from one outskirt to the next. That uncertainty is exactly why scenario work earns its place here. Rather than betting the plan on one untested idea, scenario work lets a team lay several options side by side, see which closes the most of the perceived-accessibility gap, and understand the trade-offs before any money is committed.

The other reason is ownership. The DREAMS approach treats residents and local actors as co-authors of the scenarios, not an audience for them. Because the periphery's levers are shared across a core city, suburban municipalities and a regional transport tier, no single authority can simply impose a future. Building the options together is how a cross-boundary coalition comes to back the same direction.

How DREAMS structures the choice

DREAMS builds the answer in layers, each one adding a constraint the layer below it leaves out. The lower two describe the neighbourhood as it stands today, first against a textbook standard and then against what residents themselves need and will accept. The three above them take a proposed scenario and put it through the three tests a planning team has to pass before committing to anything.

DREAMS-scenario-what-residents-want.svg
What residents want
Take a scenario as residents and local actors co-created it, with the changes they asked for in services, activities and everyday access, and measure how much of the accessibility gap it closes. Nothing is filtered for cost yet. This settles whether the scenario is worth having.
DREAMS-scenario-what-is-realistic.svg
What is realistic
Now run the same scenario against the constraints, the budget, the infrastructure already on the ground, who holds the authority to act, and whether a new service or hub can run at a cost someone will cover. Scenarios usually shrink here. This settles what could actually be delivered.
DREAMS-scenario-what-it-delivers.svg
What it delivers
Score what survives against the outcomes the area says it cares about, from accessibility and emissions to health and equity. A scenario that is wanted and deliverable is not automatically the best one. This settles which option does the most good.

Because the same accessibility model underlies both the baseline and the scenarios, a team can test a concrete change, a new mobility hub at a particular junction, a demand-responsive service across a low-density fringe, a relocated or added amenity, and read off how much of the perceived-accessibility gap it closes, and for which groups. The five intervention families DREAMS works with across the living labs give a ready vocabulary for these tests. They are mobility hubs, flexible activity hubs, demand-responsive transport, car-sharing and car-pooling, and shared micromobility. Most can be combined, and the point of the exercise is to find the package that performs, not to crown a single measure.

Backcasting starts from the future you want

Forecasting asks what happens if current trends continue. Backcasting asks the more useful question for a 15-minute plan. If this is the neighbourhood we want in ten years, what has to happen to get there? DREAMS built its scenario work around participatory backcasting workshops in the living labs, bringing together government, business and civil society to define a desired 15-minute state and then work backwards to the interventions, business models and governance changes that would reach it. The method suits the outskirts particularly well, because it forces the cross-boundary conversation about who funds and who delivers each step early, while the vision is still being shaped, rather than after a plan is fixed.

The living labs show the raw material of these scenarios in practice. In Vienna's Liesing district, a flexible activity hub reactivating an underused space, paired with a light bike-sharing station, was co-designed with residents rather than specified in advance. In the Paris T12 corridor, the scenario centred on new shared-mobility stations feeding the tramway, tested directly against whether they shortened last-mile trips and pulled people out of cars. Reading how a comparable lab framed its options is a fast way to populate your own scenario set with interventions that have already been tried.

Assess together, not after

The value of this step is lost if scenarios are modelled in private and only the winner is shown. Put the alternatives in front of stakeholders while they are still genuinely open, with their accessibility and impact figures attached, so the choice is made on shared evidence. A scenario the coalition helped weigh is one it will help deliver.

Building and assessing your own scenarios

The sequence holds whether you use the DREAMS tools or your own modelling. Start from the baseline and the population groups your diagnosis singled out, and define two or three contrasting scenarios rather than one, each a coherent package of measures aimed at the gaps that matter most. Co-create them with residents and local actors, so the options reflect real needs, not just what is easy to build. Then assess each one consistently, against how much of the perceived-accessibility gap it closes, for which groups, at what cost, and how it performs on the strategic objectives the area cares about. Bring the assessed options back to stakeholders as the basis for an open choice, and record both the chosen direction and the reasoning, because the scenarios you reject are part of the evidence trail too. Resist the urge to model a dozen variants when a few well-drawn, genuinely different futures will serve the decision far better than an exhaustive set no one can compare.

DREAMS Accessibility Tool
Carries the map-based accessibility layers used here. Test how a proposed intervention shifts accessibility against your current baseline and read off which groups gain and which do not.
Sources and further information
EU SUMP Guidelines, Second Edition (Rupprecht Consult, 2019), Step 4, Build and jointly assess scenarios.
DREAMS Deliverable 3.1: the decision support tool layer architecture and the DREAMS Accessibility Tool.
DREAMS Deliverable 6.1: intervention scenarios and impact areas across the living labs.