We are in era of digital economy, where data can be used to leverage functionality of anything from governmental institutions, private sector to healthcare. Many companies perceive data infrastructure as cost center, but now with all possibilities of advanced analytics and Big Data analytics, data centers should become profit centers. In order to make this happen, companies should start treating their data as any other asset.
By combining internal and external data, companies have great opportunity to discover new products and services. The more we become digital the more opinions on our services and suggestions for changes are available online, almost everything can be tested, evaluated and improved. Having an overview about total revenue, profit and cost is simply not enough, knowing which KPI influences those outcomes and other business goals is the todays business must, only from these insights you are able to improve your business.
This research project theme is “Data-driven Business Models in Healthcare and its Regulations Limits”. This research project to be divided into three thematic sections as follows: complex overview of Big Data opportunities and challenges in healthcare, overview of existing data-driven business models and its respective identified regulation/legal limits, which need to be addressed by companies, that are active in digital economy market.
However, there is a lot of buzz about Big Data, there is not much actually happening in this area for various reasons, predominantly it is linked to the structure of data, respectively unstructured data and lack of interoperability across the data collectors. In the respective sections dedicated to the business models we will discuss several possibilities how to use data in businesses and how data can help to derive value for the customer, there are more possibilities and new approaches in field of data-driven business models to be discovered. Business models section to encompass Business Model Canvas that is applicable to new businesses/products creation as well as it is applicable on companies trying to figure out its next business models, innovation whether product or process innovation and potential synergies. Key regulation/legal limits analysis related to data-driven business model to be discussed in detail.
This research project is conducted by MIPLM graduate Nora Reháková and supervised by Prof. Dr. Alexander Wurzer and Prof. Dr. Céline Meyrueis both CEIPI.
Nora is born in Prague, Czechia. She graduated from Czech Management Institute Prague (Czech branch of the ESMA Barcelona University) in 2012, two years long MBA program. She studied International Institute of Enterprise and Law and obtained master degree in law in 2014. In 2017, she graduated from University of Strasbourg, master program on Intellectual Property Law and Management and obtained LL.M. degree. In last 2 years she was working as “Senior Strategy Outreach Business Analyst” in an IT Innovation Center of Merck pharmaceutical company (known outside of US and Canada as MSD). She was serving as the vocal point for MSD – EU Programs, particularly for IMI (Innovative Medicines Initiative) and HORIZON 2020, responsible for identification and establishment of partnerships with external parties, including but not limited to the EU academic scene, SME parties and startup companies, incubators and other parties. She was coordinating MSD Strategic Partnerships projects with United Nations Global Compact and LES (Licensing Executives Society). She has experience from business development in different fields (from real estate industry, event management, etc.), she was running several startups in various areas as well as she gained experience from NGO sector (Missing Children Czech Republic co-founder and board member 2011 – 2017).
Here you can find a presentation on the research project: Data-driven Business Models and its regulations limits.
Author: Prof. Dr. Alexander Wurzer