Together with our project partner “Oldenburgisch-Ostfriesischer Wasserverband (OOWV)” (“Oldenburg-East Frisia Water Board”), a major user of SAP software, we are exploring innovative frameworks for information management and data warehousing. Furthermore, Oldenburg University’s Very Large Business Applications (VLBA) department – again joining forces with OOWV – develops and tests leading-edge methods to select best-practice SAP and non-SAP solutions and configurations supporting the digitalization  of business processes in the public utilities industry.

OOWV’s planned migration from SAP ECC 6.0/BW 7.5 to their SAP HANA-based equivalents provides the breeding ground for cutting-edge research and offers our students the chance to put their own scientific insights to the test by implementing prototypes as a part of their final (Bachelor or Master) theses.

Data warehouses (DWHs) are IT’s work horse when it comes to supporting management control systems (MCSs). Classically, DWHs underpin diagnostic control systems (Simons 1995). But newer analytical tools (like artificial intelligence), new methods to automatically detect causal relationships, or revolutionary and unconventional approaches to modelling human behavior enable DWHs to provide a much wider range of services. Nowadays, data warehouses can also play a role with interactive controls or contribute to a better understanding of belief systems and the impact of such belief systems on human behavior. And thanks to new insights with behavioral economics (Kahnemann 2011, Bruza, Wang and Busemeyer 2015, Busemeyer 2012, Busemeyer and Wang 2015, Lord, Dinh and Hoffman 2015, Yearsley and Busemeyer 2016) and to the implementation of algorithms supporting the detection of causal relationships (Kalisch 2012, Pearl and Mackenzie 2018, Shpitser and Pearl 2006, Shpitser 2007, Tian and Shpitser 2010, Tikka 2017), potential applications of data warehouses for decision support can even go beyond the boundaries of both, classic probability theory and mere correlations.

At the same time - and in the face of disruptive events such as the 2008 financial crisis (Köhn 2017) or the COVID-19 pandemic - Knight’s idea of separating risk and uncertainty (Knight 1964) is experiencing a comeback in management theory (Alvarez 2020). In our VUCA  world, agility has become the key competitive advantage. At the same time, true agility under Knightian uncertainty is no longer based on the one-off implementation of static management control systems but instead on installing processes that produce and implement a never-ending stream of ever better MCSs in ever shorter time. The assumption that the capability to rouse “8,000 workers” and compensate them with “a biscuit and a cup of tea” (Teece, Peteraf and Leih 2016, 23) generates the organizational agility needed today seems naive. Nowadays, organizational agility as a dynamic capability (Teece et al. 2016) also calls for new architectural paradigms that can – for example – deal with event streams (Bruns and Dunkel 2010) or support the automatic generation of entities and transformation steps in data warehouses (Linstedt and Olschimke 2016).

With our common MigHANA research project, OOWV and Oldenburg University’s Very Large Business Applications (VLBA) department are porting such new paradigms into management practice.
 

2021 – 2023

Oldenburgisch-Ostfriesischen Wasserverband (OOWV)
www.oowv.de

• Prof. Dr-Ing. Jorge Marx Gómez
• Michael Mattern

mighana.vlba.net/