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Skills application

Instruction and application
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MVP vs full-scale solution exercise​

How will these skills help you and your business?

Did you know…​

  • A Gartner study found that only 53% of AI projects progress from prototype to production.
  • According to a 2023 McKinsey study, only 15% of ML initiatives achieve a successful deployment. Forbes (2023)

Activity instructions​

You have 25 minutes to complete the three tasks below.

Choose one case study​

Choose one of the two case studies below to work with throughout this skills application task.

FinServe Solutions PLC

FinServe Solutions PLC, a global leader in financial services, is developing an ML-powered chatbot to enhance efficiency and accuracy in answering compliance-related questions for employees. The company must deliver an MVP within three months while working within a limited budget of £50,000 and constrained IT resources due to other ongoing projects.

The chatbot will be trained using existing compliance policy documents, an FAQ database and historical support tickets from the last two years.

Business intelligenceTo determine which compliance-related challenges the chatbot should focus on, consider the following:

  • Number of compliance queries per month: 12,000.

  • Average time taken to resolve compliance queries (current): 10 minutes per query.

  • Percentage of queries that are repetitive: 80%.

  • Most common compliance topics (% of total queries):

  • Anti-money laundering (AML) – 30%.

  • Data privacy (GDPR, PCI DSS) – 25%.

  • Employee conduct and ethics – 20%.

  • Fraud prevention – 15%.

  • Other – 10%.

  • Current compliance support cost per year: £2 million.

  • Employee satisfaction score (current): 62% (due to slow response times).

  • Query escalation rate (when answer is unclear): 40%.

  • IT resources available for project: Limited, with only two engineers allocated part-time. ConstraintsThe MVP chatbot needs to deliver impact within three months, but there are constraints to consider:

  • Budget: £50,000.

  • Time frame: Three months.

  • IT support is limited due to ongoing projects.

  • The chatbot can only be trained on existing policy documents, FAQs and support tickets (no external data). Future visionThe company envisions a full-scale chatbot capable of:

  • Handling complex compliance queries beyond FAQs.

  • Providing role-specific guidance based on the employee’s department.

  • Integrating with HR, training platforms and risk management systems.

  • Continuously learning and improving based on user feedback. ShopeWise Retail Limited

ShopeWise Retail, a national online retail chain, aims to improve conversion rates by implementing an ML-powered recommendation system that suggests products based on user browsing history. The system must be deployed within a limited budget of £50,000 and a strict three-month deadline to support an upcoming marketing campaign.

Business intelligenceTo determine which challenges the recommendation system should address, consider the following:

  • Monthly website traffic: 1.2 million visitors.

  • Average conversion rate (current): 2.1%.

  • Targeted conversion rate improvement: Increase by at least 20%.

  • Most viewed product categories (% of total browsing activity):Fashion – 35%.

  • Electronics – 25%.

  • Home and kitchen – 20%.

  • Beauty and personal care – 10%.

  • Other – 10%.

  • Average basket abandonment rate: 65%.

  • Historical data available:Browsing history and purchase data from the past year.

  • Product descriptions, pricing and stock availability.

  • Customer reviews and ratings. ConstraintsThe recommendation system must be operational within three months, but the project has constraints to consider:

  • Budget: £50,000.

  • Time frame: Three months.

  • IT resources: Limited to one ML engineer and two software developers.

  • Data availability: Only historical browsing and purchase data (no real-time tracking at MVP stage).

  • Integration restrictions: MVP must function within the existing ShopeWise Retail e-commerce platform without major infrastructure changes. Future visionThe company envisions a full-scale ML-powered recommendation engine capable of:

  • Real-time product recommendations based on current user behaviour.

  • Multi-lingual personalisation for a diverse customer base.

  • Cross-selling and upselling capabilities based on customer preferences.

  • Integration with loyalty programmes to provide personalised discount offers.

  • AI-driven continuous learning to improve recommendations over time.

Process templates

To help you with the task, you can download a worked example for your chosen case study and a blank template to make notes throughout the tasks.

MVP Proposal and Roadmap Template.pdf / MVP Proposal and Roadmap Process Template]The MVP Proposal & Roadmap Process streamlines product development by identifying key business needs, defining essentialfeatures, and planning phased implementation. It ensures efficient resource use, mitigates risks, and measures success to guidefuture improvements.Step 1 Business Needs AnalysisObjective: Define the main goals and pain points the MVP aims to address.Key Business Needs: List and prioritize based on how critical to the business each are]Summary of requirements: Summarize findings]Challenges and opportunities: Highlight critical challenges and opportunities]© Multiverse 2024 1Step 2 Propose an MVP SolutionObjective: Define the core features for MVP to meet critical needs first.Core MVP features: Summarize core MVP features here detailing how they meet critical needs first]Technical considerations: Detail any technical factors that need to be considered, detailing the potential risks oropportunities]Summary of MVP Summarize core MVP features here detailing how they meet critical needs first]2Step 3 Roadmap: Phase 1 MVP Launch 03 Months)Objective: Define the initial MVP release schedule.Phase 1 Summarize the launch plan for initial MVP, detailing rationale]Key deliverables: List the key deliverables]Risks and mitigation: List potential risks and how youʼd mitigate them]3Step 4 Roadmap: Phase 2 Optimization & Expansion 36 Months)Objective: Define the optimization and expansion plan.Phase 2 enhancements: List and prioritize enhancements]Key deliverables: Summarize phase 2 enhancements, detailing rationale]4Step 5 Roadmap: Phase 3 Scaling & Personalization 6 Months)Objective: Define the scaling and personalization plan.Long term goals: Summarize long term goals]Key deliverables: Summarize approach to ongoing scaling, detailing rationale]5Step 6 Roadmap: Success Metrics & EvaluationObjective: Define how success will be measured and evaluated.Key metrics: Detail key success metrics]Iteration strategy: Summarize iteration plan]Key deliverables: Summarize success measuring and evaluation plan]6

Optional: Download a copy of the workshop slides​

Optional: Download a copy of the workshop slides​

Create a proposal for an MVP solution​

Create a proposal for an MVP solution that addresses the most critical needs first.

Create a development road map​

Create a road map that shows how you’d iterate and scale the solution to meet other business needs over time.

Group presentations​

The final task is to present back to the wider group.

Each group will have one to two minutes to share:

  • How you prioritised MVP features against business needs and constraints.
  • Your proposal for the MVP solution.
  • Your road map for future iterations with key milestones.

Key takeaways​

  • Scoping solutions and prioritising requirements ensures alignment with business needs.
  • Phased deployments tackle critical priorities first, while strategic trade-offs between MVPs and full-scale solutions maximise impact and efficiency.