Data ‘Doers’ not ‘Sayers’

In this post we explore different methods of increasing the use of our data tools by users. This blog unpacks our experience of working with stakeholders on data projects and discusses some key learnings that are found along the way.

Our lesson, your learning

As those who work with open data have painstakingly learnt, it is not always easy to get stakeholders to incorporate this information into their workplace. Therefore, it is imperative that we allow for innovation and creativity in our methodology, project design and approach to implementation. The first step to becoming data ‘Doers’ and not ‘Sayers’ is practising what we propose.

Users, users, users

Through our work, we understand the undeniable value of involving stakeholders from the very beginning. A fundamental part of innovative product development is recognising and documenting the needs of stakeholders (such as our Codebridge Youth groups, CBOs, NGOs, and community journalists) before we design tools to best suit their needs. But why stop the innovation there? Can the egg come before the chicken? Can stakeholder engagement come before the project? These are questions we constantly ask ourselves.

Beautiful Packaging

Experience has taught us that users won't ‘trip and fall’ into one of our data visualisations, but rather they (our data viz) should be housed where the target audience or stakeholders are most likely to find them and then packaged and wrapped in an easy-to-understand “added value” proposition.

Good old desktop Research

Don’t forget desktop research, as more often than not, these kinds of spaces may already exist, and so the game of leveraging resources begins, and be prepared because from this point it never stops.

Without meaningful quality data it will be pointless to spend the time building out dynamic visualisations, as even the best designed tools will lose interest when its purpose is not clearly defined to be targeted to users. And yes, it will require scrupulous data protocols and quality assessments, but trust us, this process saves projects from perverse product designs.

Become the environment experts

When working with stakeholders and domain experts it is essential to understand the various contexts that individuals come from and where they would like to go. With data visualisations there should be no such thing as one bird, one stone, as it is the iterative nature of data and its ability to be seamlessly interoperable — and that makes data such an important resource that can be used across fields and sectors.

With data visualisations there should be no such thing as one bird, one stone, as it is the iterative nature of data and its ability to be seamlessly interoperable.

Endless need for training

One of our most surprising lessons to date is the endless need for training interventions. Without users having the appropriate knowledge and skills to access, visualise, and action the data its relevance comes into question and the use of a tool may begin to decrease.

Working in the training space, we find our role as not only one that involves teaching people how to use a particular tool, but rather collaborating with stakeholders to understand their data training needs, and how to leverage civic action and data in their respective civic and social circumstances.  

When reviewing our product design methodology, it is clear that becoming a data 'doer' is not a singular action or an exclusive task that can be completed but it is a culmination of well designed and planned interventions that lead us to a particular goal.

To find out more about how we become data doers please visit the OpenUp project page

Data doer (n): A person who understands the value of data, and is also empowered to use it proficiently as a resource within their workplace.
Data sayer (n): A person who understands the value of data, but does not often access it, uses it as a resource to create action.
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In this post we explore different methods of increasing the use of our data tools by users. This blog unpacks our experience of working with stakeholders on data projects and discusses some key learnings that are found along the way.

Our lesson, your learning

As those who work with open data have painstakingly learnt, it is not always easy to get stakeholders to incorporate this information into their workplace. Therefore, it is imperative that we allow for innovation and creativity in our methodology, project design and approach to implementation. The first step to becoming data ‘Doers’ and not ‘Sayers’ is practising what we propose.

Users, users, users

Through our work, we understand the undeniable value of involving stakeholders from the very beginning. A fundamental part of innovative product development is recognising and documenting the needs of stakeholders (such as our Codebridge Youth groups, CBOs, NGOs, and community journalists) before we design tools to best suit their needs. But why stop the innovation there? Can the egg come before the chicken? Can stakeholder engagement come before the project? These are questions we constantly ask ourselves.

Beautiful Packaging

Experience has taught us that users won't ‘trip and fall’ into one of our data visualisations, but rather they (our data viz) should be housed where the target audience or stakeholders are most likely to find them and then packaged and wrapped in an easy-to-understand “added value” proposition.

Good old desktop Research

Don’t forget desktop research, as more often than not, these kinds of spaces may already exist, and so the game of leveraging resources begins, and be prepared because from this point it never stops.

Without meaningful quality data it will be pointless to spend the time building out dynamic visualisations, as even the best designed tools will lose interest when its purpose is not clearly defined to be targeted to users. And yes, it will require scrupulous data protocols and quality assessments, but trust us, this process saves projects from perverse product designs.

Become the environment experts

When working with stakeholders and domain experts it is essential to understand the various contexts that individuals come from and where they would like to go. With data visualisations there should be no such thing as one bird, one stone, as it is the iterative nature of data and its ability to be seamlessly interoperable — and that makes data such an important resource that can be used across fields and sectors.

With data visualisations there should be no such thing as one bird, one stone, as it is the iterative nature of data and its ability to be seamlessly interoperable.

Endless need for training

One of our most surprising lessons to date is the endless need for training interventions. Without users having the appropriate knowledge and skills to access, visualise, and action the data its relevance comes into question and the use of a tool may begin to decrease.

Working in the training space, we find our role as not only one that involves teaching people how to use a particular tool, but rather collaborating with stakeholders to understand their data training needs, and how to leverage civic action and data in their respective civic and social circumstances.  

When reviewing our product design methodology, it is clear that becoming a data 'doer' is not a singular action or an exclusive task that can be completed but it is a culmination of well designed and planned interventions that lead us to a particular goal.

To find out more about how we become data doers please visit the OpenUp project page

Data doer (n): A person who understands the value of data, and is also empowered to use it proficiently as a resource within their workplace.
Data sayer (n): A person who understands the value of data, but does not often access it, uses it as a resource to create action.