Building trust through world class digital identity services
Key tasks
- Digital Identity transformation
- Revolutionize Digital Identity and Customer Data services to stand out as the most preferred choice for customers.
- Data-centric and AI approach
- Use the power of data and AI and an innovative approach to make data security, privacy, and data ownership a central theme of BT’s services.
- User comfort and building trust
- Build a solution that can make our customers feel at ease when storing and sharing information linked to their digital identity.
Constraints
Use cases
Here are examples of use cases that are already being adopted. These are just examples. Use innovation to disrupt existing use cases and build better solutions that can have a bigger impact.
- Customer onboarding
- Proof of age
- Authentication
- Secure login
- Right to work and rent
- Digital credentials
More details here: https://www.digitalidconnect.com/digital-id-for-business/
Tech stack
While the teck stack remains open to all stacks, here are some suggestions to help you choose a direction:
- You could use Java or NodeJs to create APIs, React/Angular/Flutter or any other JS framework for a great UI experience
- A SQL or NoSQL DB e.g. Postgres, MySQL, MongoDB, DynamoDB, etc. can also be used.
- To create a caching layer, you could use Redis, memcache or any equivalent.
Resources
Evaluation criteria
- EE’s right to play in this space, and the idea as a unique differentiator in the competitive landscape
- Validated problem-solution and product market fit (desirable, feasible, viable)
- Novelty and invention of the solution overall
- To what extent data and AI is considered in the solution
AI-powered marketplace with the EE app
Key tasks
Use the latest marketplace capabilities and the power of data and AI unique to EE to build a solution for this problem statement. Think about personalizing the shopping experience for BT’s customers. Focus on strategies that can improve the performance of both merchandising and trading while expanding offerings.
Also, think about how bundled offerings (connectivity + additional products in new categories) and one-time purchases be catered to through a simple and easy digital shopping experience?
In your solution, also add how we might use our distribution channels: app, web, call centre, retail stores, and other platforms such as social media (e.g. TikTok, Instagram, etc.) to meet the shopping needs of different segments. Can new delivery channels/devices, such as VR/AR, be used to deliver more immersive experiences?
Add a focus on opportunities for cost optimization through innovative solutions. Also, think of solutions about how to onboard partners onto our marketplace platform quickly so that they are able to offer their products and services to customers immediately.
Using standard third party product description content, how might we optimised the PDP (product descriptions page) and make it more unique to EE's marketplace at scale?
Constraints
Tech stack
While the teck stack remains open to all stacks, here are some suggestions to help you choose a direction:
- You could use Java or NodeJs to create APIs, React/Angular/Flutter or any other JS framework for a great UI experience
- A SQL or NoSQL DB e.g. Postgres, MySQL, MongoDB, DynamoDB, etc. can also be used.
- To create a caching layer, you could use Redis, memcache or any equivalent.
Resources
- Example marketplace/ecommerce platforms include:
- Retailers such as Amazon, Currys, Argos, ASOS, John Lewis, Debenhams, Zalando, Wayfair, Next, Marks & Spencer.
- Supermarkets such as Ocado, Tesco, Sainsbury.
- International Telcos: Jio, Airtel or Singtel who have ventured into new categories outside connectivity.
Evaluation criteria
- EE’s right to play in this space, and the idea as a unique differentiator in the competitive landscape
- Validated problem-solution and product market fit (desirable, feasible, viable)
- Novelty and invention of the solution overall
- To what extent data and AI is considered in the solution
Revolutionizing delivery methods with AI
Key Tasks
- AI-first ways of working and tooling
- Using a data/AI first approach, how might we enhance or adapt the end to end product management or software development lifecycle to deliver better outcomes to business and users.
- How might we use established design patterns/systems or code libraries to accelerate building/scaling/optimise experiences?
- How might we reduce labour intensive tasks without compromising on product/code quality.
- How might we use AI to continually improve our products, services and experiences?
Use cases
AI can have an impact on almost anything. For this specific brief, we are looking at how AI can improve,
- Delivery of our products, services and experiences.
- Focus on how we improve our ways of working.
- From ideation, concepting, design, build, test, deploy, operations, optimisation, where do you see the biggest impact that AI has?
Constraints
Tech stack
While the teck stack remains open to all stacks, here are some suggestions to help you choose a direction:
- You could use Java or NodeJs to create APIs, React/Angular/Flutter or any other JS framework for a great UI experience
- A SQL or NoSQL DB e.g. Postgres, MySQL, MongoDB, DynamoDB, etc. can also be used.
- To create a caching layer, you could use Redis, memcache or any equivalent.
Resources
Evaluation criteria
- EE’s right to play in this space, and the idea as a unique differentiator in the competitive landscape
- Validated problem-solution and product market fit (desirable, feasible, viable)
- Novelty and invention of the solution overall
- To what extent data and AI is considered in the solution