ID: Past, Present and Future Kevin McCullagh
Future
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Headline 30pt Product strategy consultancy
We help companies to navigate the early stages of innovation
Market foresight
Opportunity discovery
Proposition development
Experience strategy
Capability building
ID: Past, Present and Future
ID was a cult
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Past Big themes of the past few decades Present Future
Past
Global design A new business environment – Global markets – Global competition – Global supply chains – Global teams – Global talent
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Past
Experience design A new philosophy – Customer journeys – Touch-points – Signature moments – Storytelling – Joined up thinking – Seamless and end-to-end
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Past
Service/UX design A new design discipline – Huge job growth – More integrated with other business functions – Familiarised more functions with ID methods
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Past
Design thinking Opened the door to the C-suite Further spread ID methods such as user research and iterative development
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Past
Business design Design meets the MBAs – Value propositions – Business model canvas
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Past
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Lean/Agile methods Design meets the start-up thinking – Hypotheses – Prototyping – Iterative testing – Validation
EARLY
MVP
ALPHA
BETA
TEST MARKET
LAUNCH MARKET
Experiment Measure Learn
MVP
Experiment Measure Learn
MVP
Experiment Measure Learn
MVP
Experiment Measure Learn
MVP
Experiment Measure Learn
TIME
Past
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Growing integration with business
Global design
Experience design
Service/ux design
Design thinking
Business Design
Lean/Agile methods
Past
Present Issues of the moment Future
Present
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Remote collaboration Covid’s forced experiment Global teams got closer Concerns of long-term productivity, innovation and erosion of team cultures Hybrid working is the next challenge
Present
Design for D2C Rise of e-retail Brands looking to break reliance on Amazon Rethinking value propositions and business models
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Present
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Systematic Foresight Pro tip #1
Ensure viewpoint diversity
Pro tip #3
Take the long view
Frame the trends Selection criteria
Influence
Move from ad hoc trends studies to systematic foresight
Pro tip #2
Building a foresight capability
Long term Fads
Time
‘Hold strong opinions weakly…If you must forecast then forecast often – and be the first to prove yourself wrong.’ Paul Saffo
Pro tip #4
Get under the surface
Pro tip #5
Play out alternative scenarios
Now
Future
Pro tip #6
Build a point of view
Present
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Delivering on sustainability commitments Driven by regulation, consumer and retailers Many Design teams have been tasked with implementation planning of corporate commitments
Present
Diversity Design with diversity Designing for diversity Which dimensions of diversity? How to set the benchmark to aim for Get the data, rather than assume bias
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Present
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Covid accelerated
Remote collaboration
Design for D2C
Systematic Foresight
Delivering on sustainability commitments
Diversity
Past Present
Future Directions
Future
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Data aware design
Data aware design
Using data to understand the market landscape
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Data aware design
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Using data to understand the market landscape; identify, size and illuminate opportunities
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Data aware design
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Using data to understand the market landscape; identify, size and illuminate opportunities; and measure performance
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Data aware design
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Data Driven
‘Designing with Data’, Rochelle King and Elizabeth F Churchill, 2017
Quantitative data determines design decisions, focused on performance optimization, in a well understood areas.
Data aware design
‘Designing with Data’, Rochelle King and Elizabeth F Churchill, 2017
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Data Informed
Other factors are considered alongside quantitative data. Suited to problems with nuance, but well established KPIs.
Data Driven
Quantitative data determines design decisions, focused on performance optimization, in a well understood areas.
Data aware design
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Data Aware
‘Designing with Data’, Rochelle King and Elizabeth F Churchill, 2017
A wide range of data types are considered in the design process. Well suited to framing phase.
Data Informed
Other factors are considered alongside quantitative data. Suited to problems with nuance, but well established KPIs.
Data Driven
Quantitative data determines design decisions, focused on performance optimization, in a well understood areas.
Data aware design
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Types of problems
Knowledge Funnel
Mystery
Heuristic
Algorithm Roger Martin, ‘The Design of business: Why design thinking is the next competitive advantage’, 2009
Unexplained problem
Rule of thumb
Replicable success formula
Data aware design
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Wide range of data types Quantitative – What’s happening Market data
Sales data
Customer data
Usage data
Sentiment data
– Socio-demograhic – Industry sector trends – Competitor intelligence – Online customer behaviour
– Sales and trends – Market shares
– Context – Attitudes – Behaviours – Preferences – Brand equity measurements – Product satisfaction
– Session duration – Frequency – Task completion rate
– Category mentions – Brand and competitor mentions – Keyword mentions
User data
User testing data
– Transcripts – Interview notes – Videos and photos – Personas – Reports
– Blink test perceptions – Desirability and associations – Feature comprehension and usability score – Comparison with competitor or adjacent products – Perceptions and value of overall experience – Customer reviews
Qualitative – Why it’s happening Trend data – Social – Economic – Technological – Lifestyle – Design
User feedback – Contact forms – Instant feedback pop ups
Data aware design
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Data skills
Data
Information
Knowledge
Decision
Data + structure
Information + meaning
Knowledge + Recommendation
Data sourcing
Data analysis
Data visualisation
How to specify actionable data and gain access to it
How to work with data analytics and interpret the results
How to communicate with data
Change
Data aware design
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Shopify
Shopify’s philosophy for every design sprint is to be data informed and not data driven. To make product briefs, they leverage both qualitative and quantitative data to try paint a clear picture of the problem they’re trying to solve. Framing the core problem using data helps the team move fast and build the right thing.
Future
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Human-machine interlace
Human-machine interlace
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Job Destruction
Job Re-design
Humans vs machines as rivals
Humans + machines as allies
Human-machine interlace
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Most jobs are best tackled with a mix of ... Low data situations
High data situations
Human strengths
Machine strengths
Judgement Empathy Creativity Improvisation Leadership Mode shifting
Following rules Analysis Speed Accuracy Repetition Always on
Human-machine interlace
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New
Human + Machine capabilities
Human strengths Judgement Empathy Creativity Improvisation Leadership Mode shifting
Facilitating automation
– Training – Explaining – Sustaining
Human augmentation
– Amplifying – Interacting – Embodying
Machine strengths Following rules Analysis Speed Accuracy Repetition Always on
Human-machine interlace
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AI enhances the effectiveness of human activities and decision making
Human augmentation
Amplifying
Activities – Automate repetitive and low-level tasks – Prioritise options – Identify anomalies and trends
Human-machine interlace
10 ways AI can amplify design
1
Discover AI identifies new data patterns and connections
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Human-machine interlace
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10 ways AI can amplify design
1
2
AI identifies new data patterns and connections
AI uncovers new insights from existing consumer or user insight data
Discover
Empathise
Human-machine interlace
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10 ways AI can amplify design
1
2
3
AI identifies new data patterns and connections
AI uncovers new insights from existing consumer or user insight data
AI created design options within predefined constraints
Discover
Empathise
Generate
Human-machine interlace
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10 ways AI can amplify design
1
2
3
4
AI identifies new data patterns and connections
AI uncovers new insights from existing consumer or user insight data
AI created design options within predefined constraints
AI accelerates and democratises prototyping
Discover
Empathise
Generate
Prototype
Human-machine interlace
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10 ways AI can amplify design
1
2
3
4
5
AI identifies new data patterns and connections
AI uncovers new insights from existing consumer or user insight data
AI created design options within predefined constraints
AI accelerates and democratises prototyping
AI accelerates iteration and unlocks new creative possibilities
Discover
Empathise
Generate
Prototype
Refine
Human-machine interlace
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10 ways AI can amplify design
1
2
3
4
5
AI identifies new data patterns and connections
AI uncovers new insights from existing consumer or user insight data
AI created design options within predefined constraints
AI accelerates and democratises prototyping
AI accelerates iteration and unlocks new creative possibilities
Discover
6
Test
Level of sophistication AI lowers the analysis load
Empathise
Generate
Prototype
Refine
Human-machine interlace
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10 ways AI can amplify design
1
2
3
4
5
AI identifies new data patterns and connections
AI uncovers new insights from existing consumer or user insight data
AI created design options within predefined constraints
AI accelerates and democratises prototyping
AI accelerates iteration and unlocks new creative possibilities
6
7
AI lowers the analysis load
AI optimises parameters
Discover
Test
Level of sophistication
Empathise
Optimise
Generate
Prototype
Refine
Human-machine interlace
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10 ways AI can amplify design
1
2
3
4
5
AI identifies new data patterns and connections
AI uncovers new insights from existing consumer or user insight data
AI created design options within predefined constraints
AI accelerates and democratises prototyping
AI accelerates iteration and unlocks new creative possibilities
6
7
8
AI lowers the analysis load
AI optimises parameters
AI enables new levels of personalisation
Discover
Test
Level of sophistication
Empathise
Optimise
Generate
Customise
Prototype
Refine
Human-machine interlace
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10 ways AI can amplify design
1
2
3
4
5
AI identifies new data patterns and connections
AI uncovers new insights from existing consumer or user insight data
AI created design options within predefined constraints
AI accelerates and democratises prototyping
AI accelerates iteration and unlocks new creative possibilities
6
7
8
9
AI lowers the analysis load
AI optimises parameters
AI enables new levels of personalisation
AI facilitates more effective collaboration
Discover
Test
Level of sophistication
Empathise
Optimise
Generate
Customise
Prototype
Collaborate
Refine
Human-machine interlace
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10 ways AI can amplify design
1
2
3
4
5
AI identifies new data patterns and connections
AI uncovers new insights from existing consumer or user insight data
AI created design options within predefined constraints
AI accelerates and democratises prototyping
AI accelerates iteration and unlocks new creative possibilities
6
7
8
9
10
AI lowers the analysis load
AI optimises parameters
AI enables new levels of personalisation
AI facilitates more effective collaboration
AI streamlines hiring process
Discover
Test
Level of sophistication
Empathise
Optimise
Generate
Customise
Prototype
Collaborate
Refine
Hire
Human-machine interlace
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10 ways AI can amplify design
1
2
3
4
5
AI identifies new data patterns and connections
AI uncovers new insights from existing consumer or user insight data
AI created design options within predefined constraints
AI accelerates and democratises prototyping
AI accelerates iteration and unlocks new creative possibilities
6
7
8
9
10
AI lowers the analysis load
AI optimises parameters
AI enables new levels of personalisation
AI facilitates more effective collaboration
AI streamlines hiring process
Discover
Test
Level of sophistication
Empathise
Optimise
Generate
Customise
Prototype
Collaborate
Refine
Hire
Future
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Design and research ops
Design and research ops
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The orchestration and optimisation
Design and research ops
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The orchestration and optimisation of teams, processes and tools
Design and research ops
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The orchestration and optimisation of teams, processes and tools to amplify design’s value and impact at scale.
Design and research ops
Evolution
Dev Ops – Oversee code releases – Optimise processes – Design IT infrastructure – Evaluate systems
2008 Emerged from a discussion between system administrators Patrick Debois and Andrew Clay. Inspired by Lean Manufacturing’s ‘Continuous improvement’ is the mantra, they looked to introduce quality control into Agile software development.
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Design and research ops
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Evolution
Dev Ops – Oversee code releases – Optimise processes – Design IT infrastructure – Evaluate systems
2008 Emerged from a discussion between system administrators Patrick Debois and Andrew Clay. Inspired by Lean Manufacturing’s ‘Continuous improvement’ is the mantra, they looked to introduce quality control into Agile software development.
(UX) Design Ops – Hire the right people – Grow design teams – Create efficient workflows through asset libraries, design systems, etc. – Improve output quality
2014 After being immersed in the world of agile software development, Interaction Designer Dave Malouf developed Design Ops. Working with likeminded peers, he set up the DesignOps Summit.
Design and research ops
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Evolution
Dev Ops – Oversee code releases – Optimise processes – Design IT infrastructure – Evaluate systems
2008 Emerged from a discussion between system administrators Patrick Debois and Andrew Clay. Inspired by Lean Manufacturing’s ‘Continuous improvement’ is the mantra, they looked to introduce quality control into Agile software development.
(UX) Design Ops – Hire the right people – Grow design teams – Create efficient workflows through asset libraries, design systems, etc. – Improve output quality
2014 After being immersed in the world of agile software development, Interaction Designer Dave Malouf developed Design Ops. Working with likeminded peers, he set up the DesignOps Summit.
Research Ops – Ensure research is consistent, repeatable, reliable and high quality – Democratises research within an org so cross-functional teams can participate – Makes research insights accessible to an organisation
2018 Kate Towsey, Research Ops Manager at Atlassian, tweeted that she was starting a Research Ops channel on Slack. Worldwide workshops were then set up to ideate on research ops.
Design and research ops
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Evolution
Dev Ops – Oversee code releases – Optimise processes – Design IT infrastructure – Evaluate systems
2008 Emerged from a discussion between system administrators Patrick Debois and Andrew Clay. Inspired by Lean Manufacturing’s ‘Continuous improvement’ is the mantra, they looked to introduce quality control into Agile software development.
(UX) Design Ops – Hire the right people – Grow design teams – Create efficient workflows through asset libraries, design systems, etc. – Improve output quality
2014 After being immersed in the world of agile software development, Interaction Designer Dave Malouf developed Design Ops. Working with likeminded peers, he set up the DesignOps Summit.
Research Ops – Ensure research is consistent, repeatable, reliable and high quality – Democratises research within an org so cross-functional teams can participate – Makes research insights accessible to an organisation
2018 Kate Towsey, Research Ops Manager at Atlassian, tweeted that she was starting a Research Ops channel on Slack. Worldwide workshops were then set up to ideate on research ops.
ID Ops? – Attract, hire, grow and retain talent – Put trends, insights and data at designers’ fingertips – Streamline workflows with honed processes and tools – Cultivate cultural growth – Measure and evaluate progress
Design and research ops
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DesignOps landscape
How teams work together
Organise
Collaborate
Humanise
– Organisational structure – Team composition – Role definition
–R ituals and meetings – Environment – Communities of practice
– Hiring and onboarding – Career development – People operations
Nielsen Norman Group
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Design and research ops
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DesignOps landscape
How teams work together
How work gets done
Organise
Collaborate
Humanise
Standardise
– Organisational structure – Team composition – Role definition
–R ituals and meetings – Environment – Communities of practice
– Hiring and onboarding – Career development – People operations
– Guiding – Design systems – Balancing principles – Research hubs workflow – Design process – Asset – Estimation – Consistent management – Allocation toolsets
Nielsen Norman Group
Harmonise
Prioritise
Design and research ops
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DesignOps landscape
How teams work together
How work gets done
Organise
Collaborate
Humanise
Standardise
– Organisational structure – Team composition – Role definition
–R ituals and meetings – Environment – Communities of practice
– Hiring and onboarding – Career development – People operations
– Guiding – Design systems – Balancing principles – Research hubs workflow – Design process – Asset – Estimation – Consistent management – Allocation toolsets
Nielsen Norman Group
Harmonise
How work creates impact
Prioritise
Measure
Socialise
Enable
– Design standards – Design metrics – Defining good and done
– Success stories – Skills training – Reward and – Playbooks recognition – Education – Value definition
Design and research ops
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Airbnb
Before After Airbnb scaled from a small team on the same floor to a large team on different sites information and best practices became harder to share
After A DesignOps team was formed to integrate and orchestrate an effective design organisation through centralised tools, systems and services that enhance speed and quality of execution.
Future
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Design as change agent
Designwe’re as change Where goingagent
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Headline 30pt
How can I increase the impact of Design in my organisation?
Design as change agent
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Design teams deliver value to different stakeholders within an organisation Design
CEO
Corporate strategy
Product management
Customer insights
HR & Development
R&D
Engineering
Voice of customer/user
Customer / user
Finance
Production & Quality
Marketing
Sales
Customer service
Future as change agent Design
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Headline 30pt
Product/service strategy
Product/service design
The purpose of this document... dolor sit amet, consectetur Identifying market Delivering high-quality adipiscing elit. In pellentesque nisi opportunities product experiences sit amet ipsum volutpat id nulla turpis.
Change management
Facilitating organisational change
Market analysis
Concept development
Instigating change
Market foresight
Design for scale
Capability building
Proposition development
Product/portfolio differentiation
Culture modelling
Envisioning futures
Experience/system design
Customer engagement
Future as change agent Design
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Headline 30pt
Product/service strategy
Product/service design
The purpose of this document... dolor sit amet, consectetur Identifying market Delivering high-quality adipiscing elit. In pellentesque nisi opportunities product experiences sit amet ipsum volutpat id nulla turpis.
Change management
Facilitating organisational change
Market analysis
Concept development
Instigating change
Market foresight
Design for scale
Capability building
Proposition development
Product/portfolio differentiation
Culture modelling
Envisioning futures
Experience/system design
Customer engagement
Future as change agent Design
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Headline 30pt
Product/service strategy
Product/service design
The purpose of this document... dolor sit amet, consectetur Identifying market Delivering high-quality adipiscing elit. In pellentesque nisi opportunities product experiences sit amet ipsum volutpat id nulla turpis.
Change management
Facilitating organisational change
Market analysis
Concept development
Instigating change
Market foresight
Design for scale
Capability building
Proposition development
Product/portfolio differentiation
Culture modelling
Envisioning futures
Experience/system design
Customer engagement
Designwe’re as change Where goingagent
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Headline 30pt
Instigating change
The purpose of this document... dolor sit amet, consectetur Provokingelit. debate and adipiscing In pellentesque nisi introducing thinking sit amet ipsumnew volutpat id nulla turpis. – Scanning for new thinking – Experimenting – Engaging other functions
CEO
HR & Development
Designwe’re as change Where goingagent
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Headline 30pt
Capability building Strengthening the organisation’s expertise, tools and processes – Identifying areas for improvement – Tool and process development – Innovation training
CEO
HR & Development
Designwe’re as change Where goingagent
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Headline 30pt
Culture modelling Role modelling new behaviours and ways of working – Championing and demonstrating innovative ways of working – Identifying and removing friction points
CEO
HR & Development
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Designwe’re as change Where goingagent
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Headline 30pt
Customer engagement Making the customers’ sales journey more compelling – Generating sales and marketing content and assets – Participating in B2B sales meetings – Scoping opportunities with customers
Marketing
Sales
Future
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More Tech and organisational literacy
Data aware design
Human-machine interlace
Design and research ops
Design as change agent
Where’s ID going?
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Summary
Past
Present
Future
Themes of the past few decades
Issues of the moment
Directions
Global design
Experience design
Service design
Remote collaboration
Design for D2C
Design thinking
Business design
Lean/Agile methods
Delivering on sustainability commitments
Diversity
Systematic Foresight
Data aware design
Design as change agent
Humanmachine interlace
Design and research ops
We joinyou Thank the dots plan.london/subscribe kevin@plan.london www.plan.london
Future
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Quantitative & qualitative data
– Quantitative data shows what is happening with a product – Qualitative data shows the reasoning for what is happening – Using a combination of quantiative and qualitative methods gives a wider picture
Future
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Data collection methods
Qualitative
Quantitative
Purpose
– Exploratory research – Understand motivations, attitudes and perceptions
– Quantify data – Measure or predict behaviour
Sample
– Small and narrow
– Large and broad
Methodology
– Focus groups, in-depth interviews, ethnographies, shadowing, etc. – Can be in-person or online
– Data analysis platforms – Surveys
Data collection
– Semi-structured using discussion guides – Can evolve over course of study
– Data analysis platforms – Highly structured questionnaires
Data analysis
– Non-statistical, generally non-numeric – Insight drawn from observation / patterns
– Numeric and statistical
Reporting outcome
– Directional in nature – Not projectable to the total target audience
– Graphical reports – Guidance for business decisions