Product Validation
We identified two key assumptions critical to our product’s effectiveness, particularly in determining whether hotels would adopt our platform, with method diagrams for each:
Delivering soft-skill training through our platform leads to measurable improvements in users' soft skills.
Employees take ownership of their soft-skill development and are motivated to progress.
Validating these assumptions required MVP development, with insights from testing informing both initial design decisions and future iterations. For further details, see the Works-Like MVP Prototype section.
Assumption 4
Delivering soft-skill training through our platform leads to measurable improvements in users' soft skills.
Experiment 4
Part I: Utilise existing frameworks and novel literature for module delivery
Part II: Interview L+D Professionals to identify key LMS aspects
Part III: Semi-Structured Centre Manager Interview
Part IV: Quantitative Skills Profiling Data
Motivations
We want to ensure our system effectively improves employees' soft skills by linking the Skills Builder Framework with our learning platform, particularly through skills profiling and up-skilling modules.
Method
We combined a literature review, expert interviews, and quantitative analysis to define our Works-Like MVP’s design requirements and assess its effectiveness in improving employees' soft skills.
Part I: Literature Review
Part II: L&D Professionals Interviews
Part III: Centre Manager Interview
Part IV: Quantitative Skills Deltas
Key Insights
Our platform is likely to lead to measurable improvements in users’ soft skills*
*The study's limitations include potential bias in skill assessments, the absence of a control group, and a short two-week timeframe, making it difficult to attribute skill improvements solely to the upskilling intervention.
Quantitative skill-level data showed slight skill level progression, from 9.3-10. Conducting a paired t-test, we can reject the null hypothesis and conclude that the up-skilling intervention had a statistically significant impact on skill improvement.
Next Steps
We identified the necessary next steps to further validate whether the platform enables measurable skill-level improvements:
1. Validate assessment metrics
Speak to behavioural science academics to validate method of assessment and overall study
2. Create Platform Prototype
Implement WhatsApp MVP into platform prototype, ready for platform study
3. Perform 1-Year study
Collaborate with hotel to gather qualitative employee/manager feedback and quantitative skills delta metrics
Assumption 5
Employees will take ownership over their soft skill development and are motivated to progress
Experiment 5
Part I: Employee Co-Design Focus Group
Part II: Semi-Structured Employee Interviews
Part III: Quantitative Engagement Data
Motivations
We aim to ensure employees take ownership of their soft-skill development by analysing platform engagement and identifying key factors—like reminders and content format—that drive sustained participation.
Method
We used a mixed-method approach, combining engagement metrics and employee interviews, to assess motivation, identify participation trends, and inform design improvements like personalised reminders and interactive learning.
Part I: Employee Co-Design Focus Group
Part II: Semi-Structured Employee Interviews
Part III: Quantitative Engagement Data
Key Insights
Workers initially demonstrated responsibility for their soft-skill growth, though ongoing enthusiasm needed constant reminders, progress monitoring, and interactive components, suggesting areas for enhancement.
"I know soft skills are important, but without reminders or a clear routine, I’d probably forget to use the platform." "Having a structure helps—I wouldn’t seek this out on my own, but when it’s there, I engage with it."
- Ali Dawson, Senior Duty Manager
Ownership Key Insights: Employees valued structured learning but required external nudges to stay engaged.
"Some days I just didn’t have time, and the reminders felt a bit generic." "I’d engage more if the reminders were more personalised—like a nudge based on what I last did."
- Jon White, Duty Manager
Engagement Drivers Key Insights: Personalisation of reminders - through AI (LLM integration for full scope) and bite-sized content preferred
"I liked that the lessons were short—it felt doable even on a busy shift." "Seeing my progress made me want to keep going, like ticking off a checklist."
- David Zhang, Duty Manager
Barriers Key Insights: Time constraints and platform reminders needed refining.
“If only the platform could provide more tailored responses for my queries rather than A/B/C/D...”
- Tom Crossland, Team Member
Next Steps Key Insights:
Iterate from binary response to more tailored response using LLM built up over a longer pilot period
Co-Design Post-Its
From the Co-Design workshop above, employees engaged best with short, interactive, workplace-relevant learning, driven by scenario-based training, progress tracking, and adaptive reminders, highlighting the need for goal-setting and real-world application to sustain motivation.
Employees’ engagement increased (messages per day: 3.0 → 3.5), with slightly shorter messages, suggesting active participation, though further validation is needed to distinguish intrinsic motivation from external factors.
Next Steps
We identified the next steps to further validate whether employees are motivated and take ownership of their soft-skill development over a prolonged period of time:
1. Enhance Features for MVP
Refine reminders and nudges to be more context-aware and personalised. Combine works-like prototype with looks-like.
2. Optimise Engagement Mechanics
Test interactive learning elements and gamification features to encourage consistent participation.
3. Strengthen Data-Driven Validation
Compare engagement metrics between intrinsically vs. extrinsically motivated employees to tailor future interventions.
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