Shaping Strategic Direction for Data & Analytics
Client
Government
Deliverables
Data Archetypes, Value Proposition Canvas, Data Lifecycle Map
Year
2024
Role
Experience Designer
During a broader transformation, the organisation recognised the need to better understand how data was used, shared and valued. Yet, there was little clarity on what specifically needed to be addressed. We were engaged to lead discovery research, mapping the current data and analytics landscape to inform future strategy. The outcome was three key artefacts — Data Consumption Archetypes, a Business Value Map, and a Data Lifecycle Map — which helped stakeholders see not just the pain points, but also the opportunities for strategic uplift.
During a broader transformation, the organisation recognised the need to better understand how data was used, shared and valued. Yet, there was little clarity on what specifically needed to be addressed. We were engaged to lead discovery research, mapping the current data and analytics landscape to inform future strategy. The outcome was three key artefacts — Data Consumption Archetypes, a Business Value Map, and a Data Lifecycle Map — which helped stakeholders see not just the pain points, but also the opportunities for strategic uplift.
During a broader transformation, the organisation recognised the need to better understand how data was used, shared and valued. Yet, there was little clarity on what specifically needed to be addressed. We were engaged to lead discovery research, mapping the current data and analytics landscape to inform future strategy. The outcome was three key artefacts — Data Consumption Archetypes, a Business Value Map, and a Data Lifecycle Map — which helped stakeholders see not just the pain points, but also the opportunities for strategic uplift.
(01)
UX Research, Discovery & Synthesis
( research & insight synthesis )
To explore how data is managed and used, we interviewed 70 stakeholders across 33 teams
To explore how data is managed and used, we interviewed 70 stakeholders across 33 teams
We reviewed existing data inputs, conducted 1:1 research interviews and facilitated group workshops.
We reviewed existing data inputs, conducted 1:1 research interviews and facilitated group workshops.
Design Activities
Stakeholder Identification & Recruitment
Review of Existing Data Outputs
Workshop Facilitation
Research Plan
Moderation Guides Development
Research Framework Creation
Synthesis & Insight Generation
Stakeholder Identification & Recruitment
Review of Existing Data Outputs
Workshop Facilitation
Research Plan
Moderation Guides Development
Research Framework Creation
Synthesis & Insight Generation
Stakeholder Identification & Recruitment
Review of Existing Data Outputs
Workshop Facilitation
Research Plan
Moderation Guides Development
Research Framework Creation
Synthesis & Insight Generation
Key Insights
It became clear that the organisation was split between the ‘Data Team’ and the ‘Business.’ Misalignment and misunderstandings had created growing rifts — making this work especially timely in showing how early efforts could start bridging those gaps.
Outcomes
Shifted from personas to archetypes to better capture the diversity of stakeholders and their behaviours, ensuring insights reflected groups across the organisation rather than individual “user types.”
Recognised a significant need to map pain points across the data lifecycle to clearly visualise challenges along the journey and highlight where targeted, strategic improvements could be made.
Understanding our the use and management of data allows for targeted improvements to the organisation's people, processes and products, ensuring our efforts are intentional, data-driven and yield tangible benefits.
( 02 )
Deliverable
( data consumption archetypes )
We identified 5 dynamic archetypes based on data usage: Consultant, Curator, Storyteller, Changemaker and Regulator.
We identified 5 dynamic archetypes based on data usage: Consultant, Curator, Storyteller, Changemaker and Regulator.
Many individuals align with multiple archetypes, highlighting a key challenge — teams are often stretched as they try to manage all these roles simultaneously.
Many individuals align with multiple archetypes, highlighting a key challenge — teams are often stretched as they try to manage all these roles simultaneously.
Design Activities
Synthesis of Data into Archetypes
Validation & Alignment Workshops
Development of Data Consumption Archetypes
Synthesis of Data into Archetypes
Validation & Alignment Workshops
Development of Data Consumption Archetypes
Synthesis of Data into Archetypes
Validation & Alignment Workshops
Development of Data Consumption Archetypes
Key Insights
Due to poor communication between both systems and teams, a single individual is often required to juggle multiple roles, experiencing responsibilities and challenges that span all five archetypes.
Large volumes of unmanaged data left stakeholders feeling overwhelmed in an environment of fragmented systems, inconsistent processes, and unclear data ownership. These archetypes illustrate this landscape affects their daily activities.
Due to poor communication between both systems and teams, a single individual is often required to juggle multiple roles, experiencing responsibilities and challenges that span all five archetypes.
Large volumes of unmanaged data left stakeholders feeling overwhelmed in an environment of fragmented systems, inconsistent processes, and unclear data ownership. These archetypes illustrate this landscape affects their daily activities.
Due to poor communication between both systems and teams, a single individual is often required to juggle multiple roles, experiencing responsibilities and challenges that span all five archetypes.
Large volumes of unmanaged data left stakeholders feeling overwhelmed in an environment of fragmented systems, inconsistent processes, and unclear data ownership. These archetypes illustrate this landscape affects their daily activities.
Outcomes
Our Data Consumption Archetypes represent a collection of frustrations, stories and experiences, offering a deeper, more realistic perspective into stakeholder sentiments and experiences regarding data and analytics. They reveal opportunities for the organisation to strengthen support, clarify roles, modernise technologies and design cohesive data experiences.
Our Data Consumption Archetypes represent a collection of frustrations, stories and experiences, offering a deeper, more realistic perspective into stakeholder sentiments and experiences regarding data and analytics. They reveal opportunities for the organisation to strengthen support, clarify roles, modernise technologies and design cohesive data experiences.
Our Data Consumption Archetypes represent a collection of frustrations, stories and experiences, offering a deeper, more realistic perspective into stakeholder sentiments and experiences regarding data and analytics. They reveal opportunities for the organisation to strengthen support, clarify roles, modernise technologies and design cohesive data experiences.
( 03 )
Artefact
( value proposition canvas )
Jobs, pains and needs were mapped to the Stakeholder Profile within the Value Proposition Canvas and then, ranked by priority.
Jobs, pains and needs were mapped to the Stakeholder Profile within the Value Proposition Canvas and then, ranked by priority.
This mapping shows all archetypes share similar responsibilities and common frustrations.
This mapping shows all archetypes share similar responsibilities and common frustrations.
Design Activities
Synthesis of Information
Method: Jobs, Pains & Gains
Validation Workshop
Synthesis of Information
Method: Jobs, Pains & Gains
Validation Workshop
Synthesis of Information
Method: Jobs, Pains & Gains
Validation Workshop
Key Insights
Interviews and workshops revealed the organisation lacked a clear way to evaluate future data products, leading to inconsistent decisions and misaligned priorities.
Interviews and workshops revealed the organisation lacked a clear way to evaluate future data products, leading to inconsistent decisions and misaligned priorities.
Interviews and workshops revealed the organisation lacked a clear way to evaluate future data products, leading to inconsistent decisions and misaligned priorities.
Outcomes
This dual-sided product development tool aims to help the Data & Analytics Team stay aligned with stakeholder needs and guide how to best meet their needs, ensuring new value offerings foster strategic alignment and business satisfaction.
This dual-sided product development tool aims to help the Data & Analytics Team stay aligned with stakeholder needs and guide how to best meet their needs, ensuring new value offerings foster strategic alignment and business satisfaction.
This dual-sided product development tool aims to help the Data & Analytics Team stay aligned with stakeholder needs and guide how to best meet their needs, ensuring new value offerings foster strategic alignment and business satisfaction.
( 04 )
Artefact
( data lifecycle map )
The data collection, storage, access and archival processes were mapped to a 6-stage lifecycle map.
The data collection, storage, access and archival processes were mapped to a 6-stage lifecycle map.
This visual representation reveals extensive use of storage spaces, leading to a fragmented landscape of data storage and retrieval. This hampers data discovery and visibility.
This visual representation reveals extensive use of storage spaces, leading to a fragmented landscape of data storage and retrieval. This hampers data discovery and visibility.
Design Activities
Desktop Research
Synthesis of Information into Map
Validation Workshop
Desktop Research
Synthesis of Information into Map
Validation Workshop
Desktop Research
Synthesis of Information into Map
Validation Workshop
Key Insights
Across the data lifecycle, the loudest frustration was simple access. Many stakeholders struggled to get the data they needed, forcing them to track information in multiple spreadsheets and attempt their own analysis — often without the skills or confidence to do so.”
Across the data lifecycle, the loudest frustration was simple access. Many stakeholders struggled to get the data they needed, forcing them to track information in multiple spreadsheets and attempt their own analysis — often without the skills or confidence to do so.”
Across the data lifecycle, the loudest frustration was simple access. Many stakeholders struggled to get the data they needed, forcing them to track information in multiple spreadsheets and attempt their own analysis — often without the skills or confidence to do so.”
Outcomes
The Data Lifecycle Map is a design artefact that details the current methods of data collection, storage, access, analysis, use and archiving. This visual representation offers a high-level current state snapshot of data management process and serves as a tool for identifying areas for improvement.
The Data Lifecycle Map is a design artefact that details the current methods of data collection, storage, access, analysis, use and archiving. This visual representation offers a high-level current state snapshot of data management process and serves as a tool for identifying areas for improvement.
The Data Lifecycle Map is a design artefact that details the current methods of data collection, storage, access, analysis, use and archiving. This visual representation offers a high-level current state snapshot of data management process and serves as a tool for identifying areas for improvement.
