We developed a new revenue making venture for a financial services client

A new data science business

We’re currently designing and building a new data-science business for a blue-chip financial services client—specifying products, formatting billable activities and building capacity.

This kind of work represents a shift in our focus at After the flood from product design, to a consultancy innovation model: we solve business problems and identify new businesses or revenues for our clients, where the digital product is part of a much bigger venture.

It’s still unusual for most sectors and businesses, but particularly the financial sector, to take a design-led approach to prototyping and modelling new products and revenue models. Our client has found this approach unique in terms of its potential to identify opportunities for customers, and to offer a better understanding of data as a material.

The project has three distinct phases:

1. Diagnostics

  • Surveying the current client business, users, tech and data capacities.
  • Interrogating and contrasting the aspirations for a new service, with the data and capabilities the business currently has.
  • Auditing internal capacity and the brand, to expose untapped equity.
  • Sector research to identify where best the client can compete.
  • ‘Shopper’ interviews with senior buyers across target sectors.

This points the way forward, identifying where the business needs to gather new data or use AI to enrich its current data set. And it dispenses with some expensive assumptions early on.

2. Prototyping

A prototyping-led approach departs from standard consultancy models by making concepts tangible in the form of products and services. We then test and validate the concepts, refining and/or replacing these as we move forward. Standard financial specification instruments and consulting tools (e.g. a go-to-market plan with sector sizing, a sales pipeline, and revenue models) also form part of this phase. When combined with design-thinking, validation, and visualisation techniques the process provides more relevant results faster.

3. Launch

Using a ‘launch and learn’ attitude means the modular structure of engagements can rapidly iterate in-project. We’re sampling different sectors to launch the client’s prototype engagements into, and learning from early engagements in the pipeline. As this begins to form a coherent, validated set of plans, we can then build capacity with human resources and leadership with the client business, to prepare for and implement launch.

Our clients are all grappling with data, in some shape or form, and designing it is the tip of the iceberg: the real value is in helping them make sense of how central and powerful their use of data can be for their businesses and the future of their businesses. But data can’t just be theorised, or speculated about—these opportunities and new models can only take shape through a hands-on, informed approach that allows organisations to see what they have, and might have, to learn, and to adapt.

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