For our first Learning and Development Day of 2023, we offered the team the opportunity to get involved in our very own “Hack Day”.
This Hack Day allowed our staff to collaborate with colleagues and departments they wouldn’t ordinarily work with, and tackle briefs requiring them to solve real world problems in a short amount of time. Read on below to see how our 5 teams tackled 4 briefs within 6 hours.
Brief 1: How can we reduce loneliness and isolation in an ageing population, using service design or systems thinking to identify opportunities?
Team 1: Reducing loneliness through shared community activities
A system map showing the key touchpoints which aim to create purpose through mentorship, build connections, find purpose and fulfilment, and overall reduce loneliness.
Key touchpoints are based on our persona, Jefferey:
Team 2: Companionship (find like-minded friends)
Research
- Found loneliness to be a global problem with 1 in 3 older people being lonely
- Identified pain points and grouped them into financial, geographical, accessibility, motivation and ageing issues.
Ideation
- Initial focus on current solutions and an exploration of “what brings joy” to the elderly population
- Brainstorming opportunity areas to link with the identified pain points as a starting point (i.e. accessibility, motivation, etc).
Looking at products / services / solutions for 4 core topics using “How might we” questions
- Companionship (finding like-minded people)
- Engagement (leading a more active life)
- Digital accessibility / engagement
- Reducing societal and/or geographic distance
Brief 2: How can we use data visualisation tools and modelling to help clients evaluate the sustainability of their material choices in product design?
Research and exploration
The team explored a range of third-party calculators available and compared these to the type of output we might create in our own work.
Based on this research, the team explored the key types of data and common visualisations available from each tool and down-selected the most useful data and formats to create a concept for a custom tool to make the analysis of bespoke data smoother.
Output
The team created a clickable visual prototype in Adobe XD to show how bespoke data could be included in the visualisation and an interactive coded prototype using a feed of sample data to demonstrate how the data could be interpreted through the interface.
Brief 3: How might AI provide new ways to diagnose or monitor a medical condition?
Research process
Research
The team focused their research on the Fem-Tech space to narrow down the number of conditions to explore. They were able to find reports that showed clear areas of opportunity for digital tools in relation to the menopause.
Ideation
With a clear focus on the problem area, the team were able to map a hypothetical journey and look at how AI tools could be leveraged to improve this.
Diagnosing menopause, gestational diabetes and other female-specific health concerns
As part of their exploration, the team looked at an existing menopause support community and explore how image recognition ML and a natural language model could be deployed to ask and respond to questions centred on the conditions associated with the menopause.
Brief 4: How could we create a cheap smart device that allows people with long-term conditions to collect biometric data to aid with medical research into treatment and therapy?
Research process
Research
As a starting point, the team split their effort between landscape research into the spectrum of chronic conditions, innovations in biomarker detection and the impact of these conditions on society.
Ideation
During ideation, the team narrowed down the list of conditions looking for those with a large impact on society and little to no therapies.
Exploration
The team focused their efforts on Rheumatoid Arthritis and explored the current and potential future landscape for data collection in trials for therapies for this condition.
Clinical trial journey to collect data and identify therapies for the treatment of Rheumatoid Arthritis
The problem
Rheumatoid Arthritis is currently difficult to monitor long-term which is essential for understanding a degenerative disease. Patients suffer flare-ups at irregular intervals, making it hard for clinicians and researchers to be able to understand the causes. Further to this, the cause of the condition is currently understood to be approximately 50% genetic and 50% environmental factors. To be able to understand how these factors influence the progression of the disease, monitoring of the participant’s behaviours and lifestyle choices could give further insights into how the disease originates and develops. Current blockers including routine blood testing accessibility, concerns with digital data collection, and dexterity problems inherent with the condition.
Intermediate steps
The blood markers which will provide the most useful data with a targeted monitoring device are currently unknown. We propose that the five blood tests are performed regularly in initial trials in an intermediate step to determine where future innovation work is best focused. Users within this trial may include those who have genetic markers showing predisposition to RA and those which have previously been diagnosed with the condition.
Hopeful outcome
With the ability to associate blood marker data with objective physical data and questionnaire style information, analysis by medical research teams may be able to draw further conclusions to assist in treatment and therapy.
Markers may include:
+Heart rate & variability
+Activity levels
+SpO2
+Body-fat percentage
If you’re also working in these areas and interested in collaborating on your very own Hack Day for your business, contact our Head of Digital, Tim Banks, to find out how KD can support you.
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