Designer in the enterprise world by SAP

Marion and Heike from SAP shared their experiences with us on implementing SD in the corporation world. Being a service designer in an enterprise requires expertise in a multitude of areas and teamwork with internal stakeholders that have divergent motivations. In large projects it is crucial to have moments of synchronization to stay aligned. Service designer has to learn to sell the approach, learn the language of business and teams and adapt the vocabulary of “what is design” to get the message through. It is useful to know how to measure impacts, to use the power of data and metrics to convince others. Peers should be made to experience the process, but not by pushing by force.

They introduced an interesting illustration on different work styles and productiveness vs. time, see below. The value of service designer’s work is constituted in the late phases of the project whereas regarding engineering skills the case is the opposite. They also pointed out that the development team members tend to develop empathy for the team whereas it is in the service designer’s role to develop the empathy for the end customer.

Data Canvas

My second bar camp was held by Katrin Mathis, who is currently graduating from Laurea. Katrin has developed a new tool called Data Canvas to help out to consider the role of data when developing services and to understand quickly what data exists for the client organization.

The dimensions used in the canvas are whether the data is internal or external and whether the frequency of update is low or high. Internal data has a higher usage potential as it is under full control. With external data there is the risk of discontinuance and lack of uniqueness if competitors can access the same data.

The canvas can be worked on for example from angles such as what data has the highest potential, who benefits, how to tune the business model to take into account existing data. The business canvas elements can help in structuring the data canvas. The process requires engaging diverse experts. The additional variables are the trustworthiness of data source (expressed with red-orange-green colors of post-it notes) and the structure level of data (expressed with forms square-triangle-round of post-it notes). More on Katrin’s work on her pages.