Created in partnership with designer and developer Digital Liberties, Innovate! aims to improve how policymakers work together, strategise and incorporate the views of key stakeholders to address large-scale issues, such as air pollution, data ethics or inequality.

When we launched it in August 2018 we were plunging into unknown waters: the first board game we had produced and the first time Digital Liberties had developed a game with this purpose. Following rigorous testing and numerous iterations we created a product with a positive message: by bringing the right people together we can find solutions to complex societal challenges.

The process taught us a lot about developing games and simulation, and we are continuing to explore this method as a tool to support innovation in policymaking.

If you have feedback on the game, or if you develop games in this field or train people using a similar tool, we’d like to hear from you. Please contact [email protected]

Groups of four to six players take on the role of innovation policymakers, aiming to understand which policy proposals are popular across five stakeholder groups: academia, technology, industry, entrepreneurship and community.

Players need to work together to uncover evidence for their policy ideas, use their budget efficiently, share networks, launch surveys and organise round tables. Event cards represent disrupting events, such as economic booms or recessions for example, which force players to adapt their strategy or rationalise their resources regularly throughout the game.

We had the following three objectives in mind when designing the game, driven by the core challenges of innovation policy.

• Get players to understand the need for collaboration and the challenges for communicating effectively when working in silos.
• Demystify failure, encouraging players to experiment with different strategies and learn from their mistakes in the process.
• Highlight the necessity to bring in perspectives of different stakeholders to understand the needs of the beneficiaries of policies they are putting in place.

While we could bring content expertise and an understanding of how innovation policy processes could be simulated into the boundaries of a game, we needed help from Digital Liberties, a cooperative of game makers, designers and policy analysts, who we commissioned to develop the concept, rules and design identity.

We were inspired to develop the game by board games like Datopolis, ₹ubbish! and IMPACT, and by cohorts of policymakers taking part in our flagship capacity-building programme, the Global Innovation Policy Accelerator, who showed interest in testing it.

We worked with the following groups to test prototypes at different stages of maturity and used their feedback to develop the game during July and August 2018.

• April 2018: Policymakers from South East Asia taking part in Nesta’s Global Innovation Policy Accelerator programme.
• June 2018: Innovation policy experts and practitioners taking part in Nesta’s Innovation Growth Lab Global Conference in Boston.

This stems from two main issues.

• Innovation policymakers are increasingly tasked with solving ever greater, more complex challenges, like climate change or the future of jobs. They involve many different stakeholders and have the potential to directly impact future generations.
• Simultaneously, it is difficult for policymakers to adjust to unpredictable events with their current instruments. Examples include the election of Donald Trump in the US, the Brexit referendum in the UK or the fall of the traditional leftist party after the French presidential elections. And while it has never been possible to accurately predict the future, new socio-economic and political movements bring even more questions and doubt into the process.

The value of simulation

For the purpose of our research and this report, we have roughly defined simulation as ‘the imitation of a real world process, system or actor’. In the way we are describing them here, then, games are a form of simulation. We are using the game primarily to experiment with raising awareness of the main issues and trade-offs policymakers have to deal with when facing complex choices in increasingly unpredictable environments.

Games are experiential by nature and include rules that simulate facets of a complex world we are trying to explore. By designing a game, with its interactive and experiential elements, we are moving beyond merely telling people that innovation policy trade-offs are hard, allowing them to experience aspects of those challenges directly. The player can look at a subject from many different angles and learn something new about the complex whole each time. It is important to stress that we are not simulating ‘the world’, but representing an experience within it – that of innovation policymaking.

Below are some key benefits that we believe games are bringing to policy training and practice tools, illustrated with examples gathered from the world of policymaking.

Illustrate trade-offs

Games can illustrate trade-offs that are inherent to any decision-making process and they can elicit choices from players, helping them to understand the consequences of those choices.

A great example of this is the Uber Game, developed in 2017 by the Financial Times, which is based on interviews with, and research on, Uber drivers in the San Francisco Bay Area. It is an online, multiple-choice game that positions the player as an Uber driver, with the goal of earning enough money in seven days to be able to make payments on a typical $1,000-a-month mortgage. The player navigates the game by making choices, such as working late or coming home early to help a child with homework. These choices are aggregated and impact the outcome of the game, forcing the player to reflect on trade-offs around aspects such as income, work hours, incentives and location, and what may have been different if they had made other choices. The game also helps to bring data to life and started a conversation that could lead to real changes in practice.

Enable better visualisation

A benefit of using games to illustrate policymaking processes is that they can present data, ideas, concepts or trends in new and interesting ways, which might be more intuitive than traditional methods or mediums like reports, policy papers or legislation. They adopt a certain level of simplification, which helps to make them fun and engaging. Consequently, they are a powerful medium to carry a set of lessons or a message.

Datopolis, a serious game about data policy, was developed by the Open Data Institute between 2015 and 2016. The game aims to change the way the public thinks about open data and data-related issues. With well-thought-out game mechanics (the basic rules of the game being individual mission cards; trading and tile placement in this case) and a healthy dose of competition, the game helps players to develop a better understanding of the complexity of data policy. Players learn about the dangers of working in silos and the value of sharing information effectively among other things.

Understand different perspectives

Games are also good at helping players develop an understanding of, and empathy with, different perspectives because they can integrate elements of role playing, or can require players to guess or analyse the strategy of their opponents or team members.

The European Commission’s Scenario Exploration System, developed in collaboration with the Hawaii Research Center for Futures Studies, is a board game that aims to engage players in building scenario and exploring future-thinking concepts. Each player takes on the role of a stakeholder (entrepreneur, academic, citizen, for example) with a specific long-term objective. The player has to build scenarios at various times in the future (five, ten or even twenty years from now), from the perspective of that stakeholder. By trying to achieve objectives from a position that is different from their own, players can gain insight into the motivations, incentives and perspectives of others.

Highlight the power of collaboration

Games are a powerful way to showcase opportunities for collaboration and how that might be achieved. This is central to many games as alliances can make resources and strategies more efficient.

Games studio Free Ice Cream, specialising in real-world games, developed the multi-platform experience 2030 Hive Mind for a UN conference in early 2017. More than 450 conference participants played the role of government ministers in fictional low-income countries, with an allocated portfolio of policies, a fixed budget and the objective to achieve a specific sustainable development goal.

Participants initially started playing the game ‘online’, through the dedicated application. But as they realised other players had similar goals and resources that could be combined to improve efficiency, they quickly started to collaborate ‘offline’, in the physical realm of the conference.

Provide a space for experimentation

Because games often simulate a real world system or process, they naturally provide a form of distance from reality. That distance allows players to experiment with different strategies, in real time, at a relatively low cost of failure compared to real-world trials or experiments.

The Indian not-for-profit organisation Fields of View are experts in developing policy simulations. They developed the board game ₹ubbish, to try and solve the waste management crisis affecting the city of Bangalore. Through collaboration with MediaLAB Amsterdam, the team realised the game would be an appropriate tool to get policymakers, citizens and waste collection managers together to discuss what was not working with the city’s waste management policy and in the system more generally. The game allowed these conversations to happen by giving stakeholders distance from reality and their day jobs, and a safe space to discuss potential solutions.

Games are a form of simulation, often imitating a real-world process, system or actor within a scenario. As with any model of a process or situation, users of that model need to be aware of the assumptions built into it, because they are subjective and can be biased. Games also run the risk of oversimplifying, or failing to simplify enough, the systems they represent. This could mean they are less effective in achieving their objectives.

The key to maximising the value of games lies in the clarity of their goals and the honesty and transparency around what they can or cannot achieve. See our Five rules for designing a policymaking game for more advice in this area.

Central to this project was our desire to be experimental and try something new. We want to be as open and transparent about what we learned to support others developing similar games.

Our general approach: iterative and evidence-informed

Because we were working on a high level of abstraction (designing a board game that emulates the innovation policymaking process), a large part of the work we carried out involved researching and understanding what innovation policymakers do on a day-to-day basis, and identifying how we could transform this into an engaging set of basic rules – what games designers call ‘game mechanics’. However, there were a few challenges with this approach.

Although a literal interpretation of policymaking processes helped us to develop the game’s theme and narrative, this approach affected our ability to turn this into engaging game mechanics. After the first few design iterations we decided to take a more flexible approach, creating prototypes that presented the policymaking process as a playful system. We used game mechanics that were more engaging to a general audience, such as collaborative problem solving, which aligned with parts of the policy-making process. This allowed us to swap between game mechanics based on users' responses.

Choosing the right level for our simulation

One of the first issues we encountered when approaching the game is that policymakers are dealing with increasingly complex issues in increasingly unpredictable environments. This means that there is no clear mechanism that guarantees the policies have the impact policymakers predict.

The world is a complex and open-ended system, so even a highly-credible simulation is full of assumptions and simplifications. This particularly becomes a problem when trying to turn the world into a game. One of the most important aspects in a game is how it communicates why and how a player’s action causes a certain reaction (the 'feedback mediation'). This mechanism is crucial for the player's experience of the game, allowing them to plan and do better the next time they play, or in other words, to learn while playing.

The real world tends to provide us with ‘fuzzy’ feedback that is unclear or even contradictory. So, giving policymakers a simulation that tells them precisely how their selected policies have contributed to, for example, a measurable effect in a broad phenomenon such as reducing air pollution, would not be realistic. As a result, we decided against modelling a simulation at the societal level and instead focused on exploring certain aspects of the innovation policymaking process.

How the game evolved

Because the game was developed following an iterative design approach, several prototypes and versions of the game were created over six months. It was hugely helpful to test them with a range of stakeholders so that we could make the following important improvements to the game’s design.

Adding skill

In one of the first versions of the game, the player had to collect four of the same policy proposal cards to present a policy. Each subsequent card in a stack got more expensive – that is, you had to use an even larger number of game tokens representing currency or research budget. As a result, the last policy proposal card in the stack was very expensive.

Our original idea was to show that, at times, policymakers need to use a lot of resources to reach stakeholders who might have good ideas, but are hard to reach. The problem with this system was that it made the game more about luck than skill. Based on how the cards were shuffled, a player’s fourth card might end up at the bottom of the pile, which makes it hard to ‘prove’ which policy option is the most effective. This meant that in ‘play tests’ some teams who did very well on the first round did badly on the second because of the pricing ‘ratchet’, potentially sending the wrong message to players about the benefits of collaboration and reaching out to other stakeholders within the game mechanism.

We addressed this problem by introducing 'network' cards, which allowed us to vary the ‘price’ of the policy proposal cards more convincingly. The price fluctuated based on how many network cards a player had, so they could now use their skills to collect the right amount of network cards to make ‘buying’ policy proposal cards cheaper. This changed the game to base it more on skill than luck.

Making it engaging

After building network cards into the game, we needed a mechanism that would provide an engaging core to the game while still being rooted in skill. We turned to a number of potential mathematical problems and puzzles to help us.

The two best mathematical problems we found to achieve this were ‘set packing’ and ‘maximum cover’. Set packing is the act of making a particular combination with given pieces, such as cards, while maximum cover is the act of trying to cover maximum ground with the least amount of pieces possible.

By distributing network cards among themselves, the players had to work together to get the right combination of cards to get maximum value.

Not only did this encourage more conversation and interaction, it also gave the game a strong problem to solve at its centre: to juggle contacts and resources to get as much evidence out of the world as possible, played out through mathematical-type puzzles. During play testing this system worked well because players understood the game better each time they played, which improved their performance overall.

Playing with the ‘rhetoric'

We used what game designers call ‘rhetorics’ to develop the game’s design, based on underlying mechanics rather than the theme itself. Rhetorics is a way of persuading players of the game’s narrative through rule-based representations and interactions. We looked at potential mechanical changes; what these expressed about the innovation policymaking process and whether they were relevant.

The first design had no set solution. We cannot safely say there is a predetermined solution for each societal challenge, such as air pollution or congested public health systems, which could act as the game’s goal or objective. However, we know that the best policymakers collect enough high-quality evidence to help them lean towards one solution rather than another.

We also wanted to push against the idea that ‘policymakers know best’. To do this, we introduced a mechanism that allowed there to be an achievable solution each time the game is played. However, the ‘correct’ solution is redefined with each play and not dictated by any of the players.

We achieved this through the mechanism of a ‘shuffling algorithm’: every time the game is played, the cards are reshuffled and reordered so that there is a ‘set’ policy solution to the challenge. But there can be a different solution every time the game is played. By using their skills and collaborating, players can uncover the pattern of cards that is created by the algorithm for that specific play of the game.

In one of the later play tests, a player suggested having private and public goals to balance their policymaking priorities (country, organisation or department for instance). Framing the game mechanics like this would allow individual players to win at the expense of the wider system, discouraging collaboration, and detract players from having a clear sense of public good at the heart of their objectives. The game is ultimately about teamwork: teams can win only through good communication and collective planning.

These rules are not an exhaustive list of guidelines but a series of prompts, informed by Nesta and Digital Liberties’ experience developing Innovate!

Be clear on your goals

From the outset it is crucial to think about what the game will achieve. ‘Goals’, in this context, means learning objectives rather than game's objectives. (which might be to accomplish a quest for instance).

Key questions you could ask yourself at this stage could include:

• What will the game try to achieve? Will it be a training, research, or analysis tool? Will it be used to test a specific hypothesis?
• How will the game serve that purpose?
• What will the game simulate?

Creating a game for the sake of creating one will not have the same impact as one with a clear purpose and set of objectives.

Choose the right mechanics

Only once learning objectives are really clear can you start thinking about game objectives and game play, or game mechanics. A useful way to think about this is to think about the kind of mechanics that would align with and serve the learning goals. In doing so, there is no point reinventing the wheel and other games can (and should) be great sources of inspiration.

Classic game mechanics might include (but are not limited to):

• Randomised movement on a board actioned by throwing dice (eg The Game of Life)
• Resource management, where players need to increase, spend or exchange various resources (eg Monopoly)
• Role-playing, where players act out the role of a fictional or non-fictional character (eg Werewolf)
• Getting players to solve a problem to win the game (eg Cluedo)

It is worth remembering at this stage that simple game mechanics can be as effective as more elaborate ones. The mechanics should be tailored to the primary audience and how you anticipate that they will engage with them and the game.

Have a defined and consistent narrative

The narrative of a game is the story that connects actions, choices and events. A good and coherent narrative is central to its success in engaging players. It should not be tokenistic, but properly thought through and consistent. This can help players to:

• Relate to the narrative or theme, making it more likely that they will be emotionally invested in the outcome and that they return to play again.
• Understand the rules of the game (very abstract games can be harder to play).

When developing Innovate!, we had to strike the right balance between presenting an accurate reflection of how the innovation policymaking process works, without over-simplifying the process and patronising players with experience in the field, or over-complicating it for players with no knowledge of innovation policy.

Give players meaningful choices

A game that players play just once is likely to be unsuccessful, but keeping players interested so that they play it repeatedly is a real challenge. One way to achieve this is to give players plenty of meaningful choices throughout the game, so that they do not feel like they are missing out by making a particular choice. Choices affect the game by bringing new challenges that could impact the outcome.

Meaningful choices also help players to learn from their mistakes and improve their strategy. Choices are particularly powerful and pivotal in education game design.

Take your players on a journey

Finally, keep in mind that playing a game is like taking a journey. The game is not and should not need to necessarily be an end in itself. Rather, it can be the means to achieve something else, or to start a conversation, for all the reasons highlighted in Why we created it.

As a result, framing the game is very important, especially if it is designed to teach something or pass on a message. This includes making sure that you: are open about what the game can achieve and how; clearly explain the rules; and take some time after the game is over to debrief with players on the experience and what lessons they have learned.