Value based selling framework for prescriptive analytics : Explorative case study: Finnish banking sector - Rissanen, Helga (My University, 2022)
Data analytics has become the engine for business today. Companies are using, for example, big data to analyze their business processes, formulate future business strategies and, extensively, employ it for decision making. Prescriptive analytics is the most advanced sort of data analytics, and it can provide the greatest value and intelligence to businesses. Its goal is to suggest (prescribe) the best decision options in order to take advantage of the predicted future based on massive amounts of data. This research discovers the current state of the analytics used in the banking sector and how a value based selling (VBS) framework suits for selling prescriptive analytics. The theoretical part illustrates the development of analytics in general and having a deeper focus on prescriptive analytics. The empirical part explores what types of analytics are used in banking sector and what are the future prospects. The primary data for the study is gathered by extensive case study representing the seven major banks in Finnish banking sector. Banking sector was chosen as a case sector because prescriptive analytics have been utilized successfully already in logistics sector, but financial sector have not applied prescriptive analytics that widely yet. The results reveal that the VBS framework can be applied in the context of selling prescriptive analytics. Key elements are cocreation, communication and cooperation among the vendor and buyer. Also different models of responsibility sharing is an advantage. For example model where realized opportunities and emergent risks are shared between the vendor and buyer.
Keywords: Prescriptive analytics, Value based selling, Optimization, Data analytics