DIGITAL CONCEPTS
WITH GREATER VALUE.

DIGITAL CONCEPTS WITH GREATER VALUE.

Data-Need Fit

The constantly increasing amounts of available data create new opportunities in all areas of the business world. Few visionary companies already leverage their data for new services and business models. But for most organizations, that is still in out in the future with little guidance available on how to create new business models from data

 

This post introduces a process for a way to create new business models starting from data. For a value proposition to be attractive, data must relate to relevant user needs – there must be a Data-Need Fit.

Limits of existing approaches

For the most part, business model innovation processes start with a vision. With that, tested methods such as Lean Startup can validate and realize these visions in the marketplace. For businesses, even so, the question remains of how to systematically envision new business models.

 

Processes for finding new ideas, such as Design Thinking, focus strongly on the user. But as long as neither the target group nor the value proposition is defined, it will remain unclear to whom which questions should be directed. Businesses are faced with the dilemma of how to initiate and carry out targeted user research.

Data and Partners as a starting point for business model innovation

Instead of proceeding in this manner and starting with the vision, it can be worthwhile to have a look at what means are available in the organization and to experiment with the possibilities that arise in that way – an entrepreneurial thought process known as effectuation. Means are, above all, the company’s resources and existing partnerships, but also strategies and values:

  • What data and what knowledge is available within the company?
  • Which partners are able to supply additional data or other support?
  • How can the data be used in line with the corporate value set?

 

For analysis of partnerships, there is a tool in Service Design called the Stakeholder Map. Actors with whom a company has a relationship are placed in one of three circles. Their relevance decreases with the distance from the center point. Arrows represent the connections and value streams between the actors.

 

A similar tool for the discovery of data could not been found. It is because of this that the Data Canvas was developed, as a plugin for the well-known Business Model Canvas that visualizes business models on a single page. The Data Canvas helps representatives from different departments create an overview of what data is available in the organization.

Targeted user research for a Data-Need Fit

The Stakeholder Map and Data Canvas narrow the scope for user research, defining the boundaries of the target groups and the themes. Objective of the user research is to identify relevant jobs which can be supported with the available data. Depending on the context, different research methods can be used, such as interviews, observations, or user diaries.

 

Insights from user research can, for example, be captured in a Value Proposition Canvas. With the customer placed on the right side and the data in the left area of the canvas, it will quickly become apparent where data and user needs fit. A Data-Need Fit is found when one or more available data sources are able support relevant customer jobs, solve customer problems or create valuable gains for customers.

From Data-Need Fit to a functioning business model

A Data-Need Fit is an important prerequisite for an attractive value proposition. It constitutes the heart of a business model and determines which products and services, in the context of user tasks, can be usefully supported by which data, and where the data can be used to create value.

 

Data-driven business model innovation process model

A second Value Proposition Canvas can be used to design products and services to be developed around that Data-Need Fit. When this value proposition solves relevant user problems, a Problem-Solution Fit has been found. Other elements of the Business Model Canvas such as customer relationship and channels result partly from the value proposition; others such as the pricing model may be experimented with.

 

Because the Business Model Canvas is initially based on assumptions, those assumptions must, as soon as possible, be validated with potential customers to minimize the risk of failure. Established processes, such as the Lean Startup approach, offer a systematic procedure with which to test the most critical assumptions through interactions of users with a Minimum Viable Product (MVP).

 

 

I developed this process model together with the Munich-based marketing consultancy firm FELD M for my MBA thesis in Service Innovation & Design. It was used for the first time in the BMWi research project ExCELL: Real-time analysis and crowdsourcing for a self-organized city logistic. The Data Canvas can be downloaded under a Creative Commons license. I am always happy to get feedback on the Data Canvas and the process. As a consultant, I will work with you on how to use data for new business models and I am available to lead workshops in this field.


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Katrin Mathis, UX Konzepterin und Service Designerin aus Freiburg

Katrin Mathis
MBA in Service Innovation & Design und BSc in OnlineMedien berät seit über 10 Jahren Unternehmen, die digitale Transformation zum Nutzen ihrer Kunden einzusetzen.

 

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