Workshop Data-Driven Business Model Innovation

data-driven business

09/04/2018

In the past years, data and analytics have become increasingly important on management agenda’s. With the increasing digitalization of work and organizing, it becomes vital to understand the (im)possibilities, chances, and consequences of data and analytics.

Frans Feldberg KINOn the 5th of April, we organized the interactive professional workshop Data-driven business model innovation. In this workshop, professor Frans Feldberg discussed the “Why, What, and How” of big data and data-driven business model innovation. How did the world, in terms of data, change in the past years? Why are big data and analytics an important digital innovation that is listed high on many management agenda’s? Why are organizations investing so much in big data and data science? How can organizations create value with data by improving existing business models, as well as by developing new data-driven business models? These and other questions were addressed during this workshop. By using a variety of examples, and combining them findings from top-tier academic research, this workshop showed how and why big data is a “disruptive innovation” that can have big consequences for many organizations. In the workshop participants also gained hands on experience with the Business Model Canvas to see where potential chances and opportunities lie, to create value with data and analytics.

One of the core learning points of this workshop was to learn the special skills in storytelling with data and analytics. You can find the original information page here.

Data is everywhere

In the first part of the workshop, professor Frans Feldberg talked about the ways in which data have become the new oil, and how proper analytics is key to actually create profitable value propositions with data. Thanks to the vast technological developments in the past years, more and more data is being gathered. And while the field of “big data” exists for quite some time now, the actual implications for organizations are still very much developing. Consider for example the images that are taken in MRI scanners. Doctors use the images to determine the conditions of a patient. What if we could bring together all images of all MRI machines from all over the world, and then let an algorithm detect whether there are anomalies? This could potentially bring enormous benefits in the accuracy of diagnostics. There are of course very serious privacy-concerns that would need to be dealt with first, but this thought experiment helps us understand that there are many opportunities with data that reach further than most people realize. The example also shows that the emergence of data and analytics has unintended consequences, as data & analytics may also affect the role of the hospital. Who owns the data? The hospital, the MRI manufacturer, the patient?

This is merely one of the examples that was used to spur debate and get the participants thinking about the ways that the collection and analysis of data may change their current role and/or organization.

Business Model Innovation

What became clear in the first part is that organizations need to know how to deal with data, to either improve their current business model or come up with new business models to survive. So how do you develop new business models? Emphasizing that there of course are different approaches to business model innovation, Frans Feldberg focused on the Business Model Canvas. Participants gained hands on experience with understanding and using the different parts of the Business Model Canvas. By focusing on the importance of elements such as the value proposition, customer segments, and key resources, participants experienced the complexity of designing new business models.

workshop data-driven business 

Data-driven Business Model Innovation

In second half of this full day workshop, participants were first fueled with a variety of both theories on innovation and cases to show how the use of data can radically change any organization. For example by digitizing existing assets, or by combining data within and across industries. After the participants were fully charged with ideas for innovative data-driven business models, they continued to work in teams. In groups of four people the participants picked an organization and started to think and develop the business model canvas. To spur additional interaction, the teams were asked to present their ideas at the end of the day. During these presentations a lot of discussions emerged both on the feasibility and refinements of original ideas.

Participants of this workshop on Data-Driven Business Model Innovation not only learned the ins-and-outs of data & analytics, but also gained thorough hands-on experience on what it means to really think about the possibilities and challenges of data & analytics for their organization.